Some new data is in, and it’s pretty clear: The financial institutions spending more on AI are the ones seeing the biggest gains.

This week, I cover:

• ELGA Credit Union drives $5.7M in new auto loans with AI targeting in 30 days

• American Banker’s 2026 AI Talent Shift Survey reveals where Credit Unions stand

• Texas Tech FCU cuts response times 50% with voice AI

Read time: 9 minutes

Top Stories

The biggest news this week…

1) ELGA Credit Union drives $5.7M in new auto loans with AI targeting in 30 days

Mass media outreach, like billboards and radio ads, builds awareness, but it can’t tell you which members are actually ready to borrow.

That was the challenge ELGA Credit Union faced in Fall 2025. The Michigan-based Credit Union, which serves 100,000+ members and manages over $1.6B in assets, launched a “90 Day No Pay” direct auto-loan promotion backed by a full mass-media push including billboards, radio, Spotify ads, and in-branch signage. The awareness was there. But the team knew broad advertising alone was sending general messaging into what they called a “black hole.”

To fix that, ELGA CU layered Vertice AI’s predictive modeling on top of its existing campaign. The platform analyzed member data and identified 13,890 members with middle-to-high propensity scores, stronger engagement histories, and relevant life-stage indicators like Young Adult/Family or Retired Household. Only those members received personalized email outreach tied to the promotion. The broader community saw the billboards and radio ads, while the identified members received a message tailored to them. The team was able to build and manage the targeted campaign without needing a data team or manual extraction, identifying the audience in minutes compared to a longer traditional timeline.

The results came within 30 days. The targeted group generated 226 loan applications, $5,772,149 in total balance added, and an average auto-loan balance of $26,847 per member. That average balance was 48.5% higher than the non-targeted group. Overall, the targeted campaign outperformed non-targeted efforts by 167%. The targeted group also opened more than twice as many additional products as members exposed only to mass-media advertising. (link)

2) American Banker’s 2026 AI Talent Shift Survey reveals where Credit Unions stand

A new survey of 206 banking professionals from American Banker reveals a financial services industry that is accelerating into AI faster than most Credit Union leaders may realize. And the gap between those investing heavily and those moving cautiously is already showing up in real operational results.

Credit Unions are lagging on AI prioritization compared to the rest of the industry. Only 23% of Credit Union leaders rank AI as a top organizational priority, versus 63% of national banks and 44% of regional banks. At the same time, 44% of Credit Union respondents said AI is a moderate to low priority — the highest share of any institution type in the survey. Yet when asked why they are investing in AI at all, 73% of Credit Union executives cited productivity improvement as their top rationale, tied with automating key tasks and workflows. So the intent is there, but the urgency appears to be lagging. (link)

The data is clear on what happens when institutions do commit. Among organizations that increased AI spending by 25% or more in the last 12 months, roughly 60% reported moderate to significant productivity gains. That number drops to 40% for those who increased spending by 10% to 24%, and falls further to 16% for those who increased spending by less than 10%. Departments that expanded AI investment also expanded their capabilities. About 75% of respondents who upped AI spending by 25% or more said their department’s capabilities grew over the past year. AI integration was cited as the number one driver of improved productivity by 41% of respondents, ahead of internal efficiencies (34%), new technology (25%), and task automation (23%). (link)

The short-term job outlook looks stable, but the longer-term signals are harder to ignore. Today, only 3% of banking professionals say AI has led to workforce reductions at their institutions, with 28% reporting efficiency gains and 12% citing role augmentations. But 33% of national bank executives and 30% of regional bank executives expect significant headcount reductions at their organizations within the next 12 months. Surjit Chana, a board member of Beneficial State Bank and Harvard fellow, warned that clerical and administrative roles face the highest displacement risk, and that institutions have a responsibility to invest in reskilling before the transition happens faster than they can manage. Clearview FCU’s CIO Raymond George put it plainly to his own staff: “AI may not take your job, but somebody who knows AI will.” (link)

3) Texas Tech FCU cuts response times 50% with voice AI

Handling routine member calls one at a time is a drain on any Credit Union. Agents stuck answering balance inquiries can’t focus on the complex conversations that actually build relationships.

At Texas Tech Federal Credit Union, that problem was compounded by a legacy contact center platform that siloed voice from digital channels entirely. When a chat interaction escalated to a phone call, members had to repeat themselves. Managers had no unified view of agent performance. And with no reliable data, strategic decisions felt, in Consumer Banking Director Tyler Young’s words, “unfocused.”

Texas Tech FCU had already deployed Glia’s digital platform for chat. When it became clear the voice channel needed the same upgrade, the Credit Union turned to Glia again, this time for voice AI.

Before launching, Glia conducted an Impact Study — a deep analysis of Texas Tech FCU’s call traffic to identify which high-volume, routine inquiries could be automated. The study gave leadership hard data to bring to their board. “We now understand why members are calling into the service center, and we can make better decisions based on that data,” Young said.

The Credit Union deployed Glia Banker, naming its voice AI agent “Scarlet.” Glia’s library of 1,000+ pre-built banking-specific inquiry responses allowed the team to launch quickly without building journeys from scratch. “I honestly cannot imagine how long the writing process would have taken without these AI tools,” said Member Services Manager Jessica Pharr.

Scarlet now fully handles 25% of all incoming calls, with the containment rate expected to reach 50% once authenticated actions like account transfers go live. When calls do escalate, Glia’s AI Transfer Summary gives agents full context before they even say hello, so members never have to repeat themselves. Average speed of answer improved by 50%. Agent onboarding time dropped from six weeks to four, a 33% reduction, thanks to consolidating on a single platform. The team saves 81 hours of agent work per month, equivalent to one part-time staff member. Managers reclaimed 14 hours per month through automated quality assurance, allowing coaching to shift from monthly to weekly. Digital engagement also climbed 8.6% over the last year as members moved more seamlessly between channels. (link)

Tips & Use Cases

Learn to apply AI…

Altra FCU uses AI across its entire marketing engine: CMO Cheryl Dutton says AI-powered audience targeting through Google Performance Max and a social media analytics platform helped drive over 200,000 member engagements against an industry benchmark of 54,000, while Synthesia cuts video production time for their in-house team. Altra also runs ACE, a 24/7 virtual assistant handling roughly 1,000 member questions per month, and deployed Microsoft Copilot internally for content generation. (link)

AI cuts financial counseling prep from days to minutes: Shirley Senn, Chief Community Development & Impact Officer at New Orleans Firemen’s FCU, says AI can compress cash flow analysis and budget prep from two days down to five minutes, freeing counselors to spend that time on the member conversation that actually matters. (link)

Stanwood Area FCU CEO says AI should free staff to connect: Charles Frederickson says AI should handle account opening paperwork and applications so staff can spend more time understanding what members actually need. His Credit Union’s goal isn’t just better finances for members, it’s a better quality of life. (link)

Marine Credit Union automates mortgage document classification with Ocrolus: Business Systems Administrator Heather Olson says the platform automatically sorts and places incoming loan documents into the correct locations, eliminating inconsistent manual filing across underwriters. Early results point to faster income analysis, more consistent debt-to-income calculations, and a more streamlined borrower experience. (link)

AI is how Credit Unions win back member loyalty: Mark Sievewright, Chief Strategy Officer at Sievewright & Associates, an SRM company, says the concept of a primary financial institution is dead as members now spread relationships across seven to thirteen providers. He argues Credit Unions that become data-driven and AI-enabled can free up loan officers and member service reps to focus on the relationship work fintechs can never replicate. (link)

AI underwriting cuts loan decisions from days to 30 minutes: Lenders using AI underwriting report 80% faster decisions and 75% improvement in operational efficiency, while 43% of applicants abandon applications if they wait more than 24 hours for feedback. Credit Unions still in pilot mode risk falling behind as AI already automates up to 95% of manual underwriting decisions at institutions that have fully deployed it. (link)

TD Bank report finds 83% of workers now use AI on the job: TD Bank’s second annual AI Insights Report found workplace AI adoption jumped 20 percentage points YoY, with 71% of users saying it gives them a competitive edge over peers. Despite the surge, only 18% would trust AI to make financial recommendations entirely on its own. (link)

How Credit Unions can use AI to close language gaps: With nearly 75M Americans speaking a language other than English at home, AI translation tools can help Credit Unions serve non-English-speaking members across marketing, financial education, and contact centers without replacing bilingual staff. Starting small, like translating existing blogs or adding language options to contact center menus, lets teams build familiarity before scaling. (link)

Big banks signal AI will shrink workforces through attrition: JPMorgan Chase has deployed a large language model used by roughly 150,000 employees weekly, Block cut 40% of its workforce citing AI, and Goldman Sachs has already moved to constrain headcount growth. Credit Union leaders watching these trends should start conversations now about how AI will reshape roles before staff anxiety gets ahead of the plan. (link)

Scienaptic AI joins DCUC to expand credit access for military members: Scienaptic AI’s iCUE platform uses agentic AI to help Credit Unions assess borrowers on a fuller financial picture, addressing data gaps caused by frequent military relocations and deployments. The partnership gives Credit Unions serving DCUC’s 143M members access to faster, more transparent lending decisions built for complex lending environments. (link)

DailyPay cuts AML analyst workload 50% with agentic AI: DailyPay deployed ComplyAdvantage’s agentic AI to research flagged transactions and deliver summaries to human analysts, cutting their workload in half while keeping humans in charge of final decisions. (link)

Visa survey finds businesses embrace AI agents, but consumers want guardrails: Visa surveyed 2,000 Americans and 500 businesses and found 53% of businesses will let AI agents negotiate directly with other AI agents, but only 27% of consumers are comfortable letting AI spend money without limits. Trust jumps when financial institutions are involved, with 36% trusting bank-backed AI systems versus 28% trusting independent AI agents. (link)

Why banks should keep hiring junior tech staff despite AI: A study in Communications of the ACM found programming and database roles face up to 80% AI disruption exposure by 2032, but banks that stop hiring juniors today risk a supervision crisis by 2030 with no pipeline of staff who can audit AI outputs, catch errors, or understand why systems were built the way they were. (link)

Funding Spotlight

Where the money is flowing for innovation…

Capital One closes $5B acquisition of Brex to expand agentic AI: The deal adds Brex’s 35,000 business banking clients and a suite of agentic AI tools, including expense, review, auditing, and accounting agents that automate back-office financial workflows. Capital One plans to spend nearly $1B over three years to integrate Brex into its broader payments strategy. (link)

AccuQuant raises $20M to build AI-driven financial decision infrastructure: The fintech platform will use the funding to advance machine learning, automated execution, and risk control systems designed to support data-driven decision-making across digital financial applications. (link)

DepthFirst raises $80M Series B to secure AI software infrastructure: The applied AI security lab, which raised $40M just 90 days earlier, will use the funds to train additional security models and accelerate enterprise adoption of its platform that identifies vulnerabilities and delivers fixes directly inside developer workflows. Its first in-house model outperformed frontier models at 10 to 30 times lower cost in early testing. (link)

Variance raises $21.5M Series A to deploy AI compliance agents: Variance’s AI agents handle KYC, KYB, AML, transaction monitoring, and fraud detection by reasoning across fragmented data sources and returning fully auditable decisions in minutes instead of days. Variance processes more than 70M context signals daily and carries out around 300,000 automated enforcement actions across customer environments. (link)

Cara raises $8M seed to automate insurance brokerage workflows: The AI platform cuts processes that traditionally take 90 minutes down to roughly two minutes by automating coverage comparisons, proposal generation, ACORD form completion, and customer service requests via voice and email. (link)

Keeping up with Tech

The latest in fintech and tools…

Visa, Mastercard, and Microsoft race to deploy AI shopping agents: Visa piloted its Intelligent Commerce platform with DBS Bank and Banco Santander. Mastercard completed Europe’s first live end-to-end AI agent payment. And Microsoft launched Copilot Checkout in the US in January, letting consumers complete purchases without visiting external sites. (link)

Visa rolling out 6 AI-powered dispute resolution tools for issuers and merchants: The suite includes a GenAI representment tool with win prediction scoring for merchants and a Dispute Intelligence tool that uses predictive AI to help issuer agents make more informed case-by-case decisions. Visa processed a record 106M disputes globally in 2025, a 35% increase since 2019. (link)

Visa and Ramp deploy AI agents to automate corporate bill payments: Using Visa’s Intelligent Commerce and Trusted Agent Protocol, the partnership replaces manual payment workflows with AI automation and real-time spending controls for Ramp’s 50,000 corporate clients. The platform combines corporate cards, expense management, bill payments, procurement, travel booking, and automated bookkeeping into a single AI-managed system. (link)

FactSet launches AI workflow automation ecosystem for banking: Built with Finster AI, the platform uses trigger-based agents to automate deal processes like pitch materials, company profiles, and buyer analysis across the full investment banking lifecycle through natural language prompts. The system integrates with Microsoft Office and supports private cloud deployments designed for regulated financial environments. (link)

Google releases Gemma 4 open AI models for agentic workflows: The new model family supports function-calling, structured output, and multi-step reasoning natively, making it easier for developers to build autonomous agents without proprietary model restrictions. (link)

OpenAI cuts ChatGPT Business pricing and adds pay-as-you-go Codex seats: ChatGPT Business drops from $25 to $20 per seat annually, and teams can now add Codex-only seats with token-based billing and no rate limits, making it easier to run focused AI coding pilots without committing to full seat licenses. (link)

Anthropic secures multi-gigawatt TPU deal with Google and Broadcom: The compute expansion, expected online starting in 2027, will support Anthropic’s Claude models as run-rate revenue surpassed $30B in 2026, up from $9B at the end of 2025. The number of business customers spending over $1M annually doubled to 1,000 in less than two months. (link)

FinBox adds MCP support to Sentinel AI for agent-driven lending: The update allows AI agents and internal copilots to trigger credit decisions, fraud checks, and policy-governed approvals directly through natural language without duplicating underwriting logic or bypassing compliance controls. Loan officers can now simulate scenarios or move borrowers from inquiry to approval within a single AI interaction while all decisions remain centrally governed and auditable. (link)

Exabeam expands AI agent behavior monitoring for ChatGPT and Copilot: The updated Agent Behavior Analytics platform now tracks how employees use ChatGPT and Microsoft Copilot by baselining normal usage patterns and flagging anomalies like sudden spikes in API calls, unexpected privilege escalations, or prompt injection attempts. (link)

In Other News

Related news you can learn from…

• Responsible AI is the foundation for innovation in banking (link)

• Stablecoins and tokenization are reshaping banking, and waiting is the biggest risk (link)

• AI agents are exposing broken governance models in enterprises (link)

Community Corner

Memes and visuals…

@centralhub.ai

CentralHub AI | AI News & Insights on Instagram: "How it feels …

Thanks for reading!

Until next week,

— Credit Union AI Guy

Enjoying this newsletter? Forward it to a colleague who might appreciate practical AI insights.

Have a question or want to share your own AI experiment? Reply to this email or connect with us on LinkedIn. We’re building a community of curious Credit Union professionals. Come join the conversation!

Whether that’s faster loan decisions, personalized financial advice, or staff who always have the right answer.

This week, I cover:

• Mid Oregon Credit Union automates 70% of loan decisions

• How Credit Unions can go on offense to win Gen Z with AI + data

• Lake Trust Credit Union tackles internal AI fear

Read time: 9 minutes

Top Stories

The biggest news this week…

1) Mid Oregon Credit Union automates 70% of loan decisions

Kevin Cole, CEO of Mid Oregon Credit Union, says they deployed Zest AI to handle the majority of its loan decisioning. He describes the platform as a more advanced version of predictive AI, the same concept behind FICO scores that Credit Unions have used for years.

Cole describes the loan pool in three tiers: the bottom and top are easy decisions, and about half fall somewhere in the middle. Today, Zest AI is decisioning about 70% of Mid Oregon’s loan requests on a fully automated basis. The remaining 30% still go to human underwriters when marginal or complex enough to require judgment.

The result? Mid Oregon reassigned two employees from underwriting to other roles at the Credit Union rather than letting them go. The Credit Union has never laid off an employee in its history since 1957, and Cole says he has faith they’ll navigate this transition without abandoning that approach.

Beyond underwriting, Mid Oregon is using Eltropy Voice+ as one of its first conversational intelligence tools to serve members. Cole says the Credit Union has been learning with Eltropy through the process and making good progress.

At the same time, Mid Oregon has restricted staff access to ChatGPT and similar tools on its network for data security purposes. Cole says that restriction is only a limited time window, because eventually it will make the Credit Union less competitive than it wants to be. (link)

2) How Credit Unions can go on offense to win Gen Z with AI + member data

More than 6 in 10 Gen Z members are open to using AI for “what if” financial planning, according to Velera’s CU Growth Outlook 2025. Tools like ChatGPT and Gemini are already resetting what good financial service looks like for this generation. They expect their financial partners to anticipate needs, model scenarios, and deliver personalized guidance in real time. (link)

The problem, according to Lee Wetherington, Senior Director of Corporate Strategy at Jack Henry, is that most Credit Unions are missing the data to do it. Credit Unions typically hold only 20 to 25% of their average member’s financial data, limited to whatever accounts that member has at the Credit Union. Without a fuller picture, the most compelling AI use cases simply are not possible.

Wetherington says the Credit Unions best positioned to win are not waiting on regulators. They’re proactively asking members for permission to aggregate financial data from third-party relationships back to the Credit Union, so they actually know their members and can use that data to create new AI-driven products and services. The regulatory chaos around open banking, he says, is a window for aggressive Credit Unions to go on offense. (link)

3) Lake Trust Credit Union tackles internal AI fear

Krassi Kassabov, Chief Strategy Officer at Lake Trust Credit Union, dedicates a quarterly all-hands meeting to reviewing prior results and setting direction for the next quarter. Recently, he dedicated a full hour of that meeting to a single topic: AI. He posed three questions to his team:

• What excites you about AI?

• What scares you?

• What can we do together to get over that hurdle?

Several team members were vocal about believing AI would take their jobs. Kassabov’s response was to give it a try. He draws on his own experience immigrating from Bulgaria, moving 5,000 miles away without knowing anyone or the language, to make the point. The way he got over that fear was by showing up and discovering that different does not mean bad. He tells his team the same thing about AI.

His clearest example comes from marketing, where copywriters worried AI would take over message creation. Kassabov said he needs them even more now to make sure the branding and tone of voice are right. AI can draft the message, but the human still shapes it, and work that once took hours now takes minutes.

Lake Trust is already using Posh for conversational AI to handle basic member questions, so team members can focus on more complex conversations and building emotional connections with members. Kassabov said the Credit Union is also beginning to test AI in marketing and has introduced an internal knowledge system that helps get the right content to team members at the right time.

Kassabov is clear about what AI cannot do. It cannot build trust with members the way a human can, and it cannot supply the qualitative judgment that connects data to real member situations. (link)

Tips & Use Cases

Learn to apply AI…

Genesee Co-op Federal Credit Union bets on AI to build in-house: Dan Apfel, CEO of the Rochester-based CDFI Credit Union, believes AI could let a small team of engineers build what once required a hundred. He sees it as a path for small Credit Unions to develop their own tools instead of depending entirely on outside vendors. (link)

Firefighters First Credit Union uses AI to scale emotional member bonds: Jeffrey Staw, Chief Information and Innovation Officer, says AI helps the Credit Union determine when a human interaction is needed versus when automation serves members better. As the nationwide firefighter-only Credit Union grows, that distinction is key to preserving the personal connection members expect. (link)

Vantage Credit Union uses AI to coach collections staff in real time: Matt Stegall, AVP of Credit Resolution and Recovery, says the Credit Union is analyzing member phone calls with AI and generating information cards to help employees respond faster and more effectively. He sees AI as a productivity tool that frees staff to focus on the high-empathy situations machines can’t handle. (link)

Agentic commerce is headed for your disputes queue: As AI agents begin making purchases on behalf of members, Credit Unions face a new dispute challenge: not whether a transaction was authorized, but whether the member actually intended it. AI-assisted dispute platforms can cut resolution times from 30 days to as few as 10, but most CUs haven’t built the infrastructure to handle it yet. (link)

7 17 Credit Union plans to process loans in under two minutes: President and CEO John Demmler says the Ohio Credit Union expects 95% of transactions to be digital within two years. The goal is to use digital tools for routine transactions while freeing branch staff to focus on deeper member financial conversations. (link)

Solaris cuts 20% of staff in pivot to AI-native banking: The German fintech, which holds a full banking license, is eliminating 80 of its roughly 400 employees as new CEO Steffen Jentsch shifts the company toward an AI-native architecture. (link)

Microsoft says cloud migration is the foundation for AI in financial services: Laurent Verdier, Microsoft’s CTO for Worldwide Financial Services, argues that legacy systems are limiting what AI can do across lending, fraud, and compliance. Credit Unions still running on older infrastructure risk falling behind as AI-ready cloud platforms become the baseline for competitive operations. (link)

Posh offers a build-vs-buy framework for Credit Union AI strategy: Build what differentiates your Credit Union and buy what accelerates it. Focus internal resources on member experience while partnering for infrastructure, compliance guardrails, and model integration. Institutions that try to build everything risk spending more time on maintenance than innovation. (link)

Casap’s dispute automation cuts errors 63% in Filene pilot: Credit Unions participating in Filene’s 2025 FiLab evaluation of Casap’s automated fraud dispute platform also reported a 122% higher ease-of-use score compared to prior systems. Staff confidence in compliance improved and member complaints declined during the pilot period. (link)

NCUA updates examination approach as Credit Unions adopt AI: Acting Director of Examination and Insurance Amanda Parkhill told a House subcommittee the agency is integrating fintech expertise into its supervision process. Credit Unions are actively using AI for lending, fraud detection, and member services, and proposed legislation would create regulatory sandboxes for testing new products with advanced compliance assurance. (link)

AI-generated paystubs now appear in roughly 1 in 5 auto loan applications: Generative AI tools have made document fraud accessible to anyone, not just sophisticated criminal networks. Credit Unions using multilayered verification that combines metadata analysis, cross-document consistency checks, and shared fraud networks can catch fakes at application time rather than discovering losses months later. (link)

Only 11% of banks have deployed AI responsibly, SAS report finds: A global SAS and IDC survey of 2,375 IT and business leaders found nearly half of banks are either underusing reliable AI or over-relying on systems that haven’t been validated. Organizations that prioritized trustworthy AI were 60% more likely to report doubling their return on AI investments. (link)

UW Credit Union sponsors free 7-part AI literacy video series: Steph Harrill Kyle, Director of Financial Inclusion and Community Engagement, says the Credit Union partnered with the Universities of Wisconsin to launch ASAP, a free series teaching members how AI works and how to use it safely. (link)

Merrill Lynch rolls out AI meeting tools to 25,000 advisors: Bank of America integrated AI into Salesforce and Zoom to help advisors prepare for client meetings, summarize discussions, and handle follow-up tasks. Meeting prep that once took 45 minutes now takes a few minutes, freeing advisors to focus on client relationships instead of administrative work. (link)

CFO-led AI projects succeed at far higher rates, Fortune study finds: Only 2% of companies have their CFO driving AI value, but when they do, 76% achieve meaningful results. That rate outperforms every other C-suite role, including Chief AI Officers and CTOs. (link)

LHV Bank pilots agentic AI for email-based customer support: Interim CEO Kris Brewster says the bank is testing Gradient Labs’ agentic AI in a controlled environment to improve response quality and turnaround times on customer inquiries. The pilot emphasizes human oversight, explainability, and auditability throughout. (link)

AI drives measurable ROI across three areas in financial services: Personalized AI engagement improves cross-sell conversion rates up to 25% and reduces churn up to 20%. AI-assisted service operations cut average handle times 20-40% and reduce cost-per-contact 30-40%. In lending and onboarding, AI document processing can cut preparation time in half. (link)

i2c captures up to 40% of fraud while keeping friction at 0.5%: Matt Pearce, VP of Fraud Risk Management at i2c, says the platform embeds AI directly into the transaction authorization process rather than adding it as a bolt-on. Machine learning builds behavioral profiles within 60 to 90 days, and consortium intelligence draws on fraud patterns across i2c’s global platform to benefit smaller Credit Unions that lack dedicated fraud teams. (link)

Most financial institutions can’t reconstruct an AI decision for regulators: Experts across multiple firms say the gap isn’t the AI itself but the surrounding infrastructure. Credit Unions deploying AI in compliance workflows should ensure every decision has a traceable audit trail, a documented policy version, and a clear record of human oversight before a regulator ever asks for it. (link)

Agentic AI cuts compliance alerts by up to 82% and speeds onboarding: A ComplyAdvantage survey found 54% of firms linked agentic AI to improved efficiency in customer screening and case investigation, while 51% reported better member onboarding experiences. Nearly 80% of organizations still take more than five minutes to clear a single sanctions alert, a gap agentic AI is built to close. (link)

Citizens Bank targets 50% of call center calls answered by agentic AI: President Brendan Coughlin says the $226B bank is piloting agentic voice AI that can handle balance checks, fraud claims, address changes, and debit card replacements end-to-end without a human. The three-year, $300M “Reimagine the Bank” project targets $450M in earnings value creation by Q4 2028. (link)

Funding Spotlight

Where the money is flowing for innovation…

Spade raises $40M Series B to turn raw transaction data into AI-ready intelligence: The round will help Spade expand beyond transaction enrichment into a full payments intelligence platform. The company processes 1.9B transactions daily at 99.9% merchant coverage, helping financial institutions reduce disputes and power agentic AI workflows. (link)

Qodo raises $70M Series B to govern AI-generated code: Led by Qumra Capital, the round brings total funding to $120M and will help Qodo scale its code review and governance platform for enterprises. Platforms like Qodo address a growing concern: AI can write code fast, but without quality controls, it introduces risk into production systems. (link)

Grand raises $5M pre-seed to replace static credit reports with real-time risk signals: The round will fund Grand’s AI-powered trust network that monitors trade partner risk and stability continuously, rather than relying on data that is months out of date. The company targets B2B trade industries where outdated credit decisions contribute to thousands of insolvencies annually. (link)

Notch raises $30M Series A to automate end-to-end workflows in regulated industries: ARR grew 12x over the past year as insurers and financial institutions adopted the platform’s AI agents for claims intake, document processing, and policy servicing. (link)

Keeping up with Tech

The latest in fintech and tools…

UiPath rolls out AI agents for sanctions screening and loan origination: Valley National Bank automated 61% of sanction-hit reviews and now processes 14,000 alerts per month using UiPath’s transaction screening agent. Suncoast Credit Union is using the platform to ingest loan documents, compare them against systems of record, and surface quick insights for review teams. (link)

Flowdock launches AI back-office automation platform for financial workflows: The platform connects to bank accounts, email, and business tools to monitor invoices, contracts, and cash flow in real time, flagging supplier overcharges, missed renewals, and cash shortfalls before they become problems. It integrates with major EU banks via Open Banking APIs and tools like Stripe, HubSpot, and Slack. (link)

FinTech Studios opens its financial intelligence engine to self-serve users: The platform continuously monitors billions of global data sources across 100+ languages and delivers domain-specific insights without manual searching or prompting. Previously available only through six-figure enterprise contracts, it now offers free and tiered access for individual users and teams. (link)

ExeQution Analytics launches hallucination-resistant AI assistant for trading: Eolas converts natural language queries into API calls rather than generating free-form responses, preventing fabricated answers by limiting the tool to approved functions on approved data. Trading, quant, and IT teams can interrogate real-time and historical market data without pulling reports through intermediaries. (link)

CUBE integrates regulatory intelligence with Microsoft Azure for automated compliance: The partnership gives financial institutions an automated way to track and interpret thousands of regulatory updates monthly across multiple jurisdictions. CUBE’s platform is now available directly on the Microsoft Marketplace for faster deployment. (link)

Stripe processed $1.9T in volume and launches AI billing and stablecoin tools: The payments giant’s new AI billing tool tracks LLM usage costs in real time, while its x402 integration lets AI agents send and receive stablecoin payments autonomously. Reports also suggest Stripe is exploring a PayPal acquisition, which would add 439 million active accounts to its network. (link)

Ani Tech launches free AI cash flow modeling app for financial advisors: The app lets advisors build and compare financial scenarios using natural language, with an AI agent called Flo monitoring client goals in the background without manual prompts. Ani Tech says agentic AI can automate 75% of non-client-facing work, potentially cutting client onboarding costs from £800 to £200. (link)

Mastercard completes live agentic payment transactions across Latin America: AI agents executed real purchases across debit and credit cards on Mastercard’s existing network, covering groceries, books, and digital goods without requiring new payment rails. The company’s Verifiable Intent framework creates a tamper-resistant record of what a cardholder authorized, giving financial institutions a clear audit trail when AI initiates a transaction. (link)

Njordium adds self-learning AI fraud detection to its vendor management platform: The module extracts and validates invoices across PDFs, email attachments, and XML feeds, flagging phantom services, non-existent products, and prices deviating from market norms. High-confidence detections route automatically into AML and financial crime prevention workflows before funds leave the organization. (link)

Flanks debuts AI co-pilot for wealth advisors managing multi-custodian portfolios: The tool lets advisors query complex family structures, cross-border holdings, and private equity capital calls in plain language, drawing on data from 600+ financial institutions across 33 countries. All outputs are descriptive only, with no investment recommendations, keeping the platform within compliance guardrails. (link)

Microsoft 365 Copilot adds long-running agentic workflows with Cowork: Copilot Cowork lets users delegate multi-step work by describing an outcome, with the system creating a plan and carrying tasks forward across files and tools. The update also improves Researcher with a Critique feature that uses separate Anthropic and OpenAI models to draft and review outputs, scoring 13.8% higher on the DRACO deep research benchmark. (link)

Google releases Gemini 3.1 Flash Live for real-time voice AI applications: The updated model delivers lower latency and improved tonal understanding, adjusting responses based on user frustration or confusion in real time. Credit Union contact center developers can access it via the Gemini Live API, with enterprise deployment available through Gemini Enterprise for Customer Experience. (link)

In Other News

Related news you can learn from…

• Agentic AI payments and leadership moves dominate March (link)

• Perplexity shares lessons from building voice-first AI agents (link)

• AI cuts threat detection time 36% when kept in a support role (link)

• Australian financial institutions embed AI into AML compliance workflows to cut false positives (link)

Community Corner

Memes and visuals…

@algobrief

Algo Brief on Instagram: "Interesting fact:

Claude has been on…

Thanks for reading!

Until next week,

— Credit Union AI Guy

Enjoying this newsletter? Forward it to a colleague who might appreciate practical AI insights.

Have a question or want to share your own AI experiment? Reply to this email or connect with us on LinkedIn. We’re building a community of curious Credit Union professionals. Come join the conversation!

Done right, it means your members get better service, especially the ones who need it most.

This week, I cover:

• Statewide FCU put AI in every employee’s hands to serve members better

• Bay Federal CU unified its member data to power AI-driven growth

• The PenAir CIO’s strict vendor risk framework for an AI-era

Read time: 9 minutes

Top Stories

The biggest news this week…

1) Statewide FCU put AI in every employee’s hands to serve members better

For a Credit Union serving rural Mississippi communities where many members are low-income and underserved, trust is hard to earn and easy to lose. When staff don’t have instant access to accurate internal information, service quality can vary, and a single bad interaction can undo years of relationship-building.

Casey Bacon, CEO of Statewide Federal Credit Union, has spent 35 years working nearly every job in the building, from teller to IT director to the corner office. That background shapes how he thinks about AI. He sees it not as a replacement for people, but as a way to multiply what they can do.

Statewide’s AI Assist tool gives every employee instant access to accurate internal information at the moment they need it. Bacon describes it as the biggest thing the Credit Union has done so far with AI, because it enables consistent service to members across the whole organization.

Statewide serves rural communities where many members are getting their first shot at traditional credit and escaping predatory lending. By handling information retrieval and background work, AI frees staff to focus on what actually matters to members: showing up in person, earning trust face-to-face, and helping people understand tools that might seem intimidating. (link)

2) Bay Federal CU unified its member data to power AI-driven growth

Bay Federal Credit Union was preparing to expand into a new market and open a new branch, but its technology wasn’t ready for the growth. Member data lived in silos, the team lacked a true marketing automation platform, and they had no single view of member behaviors, preferences, and engagement. The $1.8B Credit Union needed a platform that could unify data, support personalization at scale, and let business teams move without relying solely on IT.

Trisha Bennett, VP of Enterprise Applications, and SVP/CTO Richard Roark led the search for a solution. They chose Creatio’s no-code, AI-native platform and partnered with Solutions Metrix for implementation. Before building anything, they formed cross-functional committees pulling in stakeholders from marketing, lending, operations, and IT to map requirements together.

The rollout followed an MVP approach, starting with referral management for mortgages and investments in select branches. The first phase gave the marketing team the ability to personalize campaigns, segment members more effectively, and launch journeys powered by real-time data from the connected data warehouse.

The future roadmap expands across sales and service. Referrals for mortgages and investments will be tracked directly in the platform, processes will be standardized, and SLAs managed through Creatio. Conversational AI tools will let staff ask the system about a member instead of searching through records, and predictive tools will flag changes in direct deposits and identify members at risk of falling behind before issues escalate. (link)

3) The PenAir CIO’s strict vendor risk framework for an AI-era

When a member opens the PenAir Credit Union app, that single interaction touches over 25 vendors working behind the scenes. For a smaller institution without an army of software developers, stitching all of that together seamlessly while keeping it secure is one of the hardest parts of the job.

After spending 26 years in IT and 11 years navigating the complexities of financial services, CIO Galen Counselman advises building your risk framework BEFORE you need it.

PenAir follows the NIST 800 framework for risk assessments on every vendor and every system change. Counselman recommends getting your board to formally agree on a written risk appetite statement. At PenAir, that appetite is low, and it drives every vendor decision. When a vendor assessment lands at medium risk, PenAir gives them two options: make the changes needed to bring it down to low, or the relationship does not move forward (except in some cases with board approval). Management and the board vote on risk acceptance quarterly, so no single person is carrying that weight alone.

Counselman exercises caution around one AI red line: if a vendor uses member data to train its models alongside other clients, that remains a medium risk unless the vendor gives guarantees they won’t. (link)

Tips & Use Cases

Learn to apply AI…

ICCU boosts loan approvals 34% with Zest AI underwriting: Idaho Central Credit Union automated 75% of loan decisioning using Zest AI, cutting staff touchpoints on routine applications while dropping delinquency rates an additional 0.3% below their already sub-1% baseline. (link)

InTouch CU CEO on why he chose to be an early AI adopter: Kent Lugrand says an $800M Credit Union competing against Chase and Wells Fargo cannot afford to wait for others to go first. He partnered with Eltropy to deploy agentic AI that handles member tasks like fee reversals and address changes 24/7, serving members across all 50 states without adding staff. (link)

Fintech leaders share what’s working and broken in AI banking: At the AFT Spring Summit, executives from Praxent, Stratyfy, and Vine Financial discussed the real impact of AI on financial software development, with Vine Financial’s David Eads reporting 286% more code written MoM with Claude Opus 4.6. Leaders also warned that AI hallucinations pose serious risks in regulated environments, and urged institutions to ensure any AI deployment can be explained step-by-step to a regulator on-site. (link)

Hudson Valley CU’s CIO shares how to build an AI-ready foundation: CIO John Fede explains how the $8B Credit Union is migrating to a cloud-based data warehouse, deploying RPA, and hiring a Chief AI Officer to lay the groundwork before scaling AI use cases across the organization. (link)

SavvyMoney’s CEO on using AI to close the credit education gap: JB Orecchia argues that financial institutions can use AI to build member financial profiles that adapt over time. The goal is moving beyond static credit snapshots to deliver personalized guidance on rates, cash flow, and long-term borrowing costs. (link)

How to build custom GPTs for your Credit Union workflows: Open ChatGPT, click Create GPT, add your instructions and any reference documents, and you have a reusable tool in under five minutes. Keep each GPT focused on one task, avoid overly complex instructions, and use it for anything you do repeatedly, like board reports, job postings, or NCUA minute-taking. (link)

69% of banks & Credit Unions prefer buying AI over building it: A Digital Banking Report study of 200+ financial institutions found the preference is driven by limited data science teams, compliance complexity, and faster deployment needs. Only 8% of institutions had internal teams actively working on generative AI solutions. (link)

How Credit Unions can combine AI and human review to fight fraud: AI fraud systems continuously analyze device behavior, synthetic identities, and account patterns in real time, flagging threats before they spread. Human staff still verify flagged transactions directly with members, and industry groups like SAPTA help Credit Unions share intelligence across institutions. (link)

Answer engine optimization is changing how Credit Unions get found online: AI tools like ChatGPT and Gemini now replace traditional search results with direct answers. Credit Unions need to restructure website content into clear, concise question-and-answer formats so AI systems can cite them rather than bypass them. (link)

Aliya CEO on why always-on lending beats point-in-time decisions: Most lending AI is just automated hindsight, built on top of manual workflows. The Aliya platform connects cash flow data, behavioral signals, and post-origination monitoring into a closed loop that manages risk and identifies opportunities every day, not just at application. (link)

Major banks cut thousands of jobs as AI replaces back-office roles: HSBC is considering cutting up to 20,000 positions, roughly 10% of its workforce, with layoffs focused on non-client-facing service center roles. Morgan Stanley, Citigroup, BlackRock, and Block Inc. have also announced cuts. (link)

Bank of Ireland trains entire workforce on AI and data literacy: The bank is rolling out AI-immersion learning to all staff in 2026, with 1,200-plus employees already enrolled in its AI Academy. The investment is already showing results: AI prevented €9.7 million in fraud across 1 billion card transactions in 2025 and reduced contact center call transfers by 40%. (link)

RBC expects AI to generate up to $1B CAD in revenue and savings by 2027: Canada’s largest bank has rolled out AI across investment banking, consumer banking, and call centers, with research analysts now covering 1,700 companies, up from 1,500 in 2023. RBC ranked third on the 2025 Evident AI Index behind JPMorganChase and Capital One. (link)

AI shopping bots are coming and Credit Unions need a plan: Agentic AI tools from Google, Visa, and Amazon will soon make purchases directly from members’ bank accounts, creating chargeback gaps and new fraud vectors that existing regulations don’t fully cover. CUs need updated vendor contracts, bot-detection controls, and clear policies on which AI agents they will and won’t allow. (link)

Why Credit Unions should slow down before signing the next AI contract: Jim Bouchard warns that FOMO is driving Credit Unions to adopt AI before clearly defining the problem they’re solving, with hidden costs like data cleanup and staff retraining often delaying expected returns. He argues the bigger long-term risk is automating entry-level roles that have historically been the training ground for future leaders. (link)

Propel CEO says AI cash flow models should replace FICO for near-prime borrowers: FICO scores fail borrowers in the 650-700 range by relying on years-old data. Propel’s FreshLine product uses machine learning to analyze thousands of real-time variables, including income timing and cash flow patterns, to align repayment schedules. (link)

How Credit Unions can turn member data into personalized financial guidance: AI-driven personalization uses transaction history, app behavior, and declared goals to anticipate member needs before they ask. Banks excelling at personalization generate 5-15% more revenue from targeted campaigns. (link)

Treasury launches AI roundtable series for financial institutions: The Financial Stability Oversight Council and Treasury Department are hosting four roundtables bringing together banks, tech firms, and regulators to identify high-value AI use cases in fraud detection, credit underwriting, and operational risk. (link)

Starling Bank launches UK’s first agentic AI assistant for personal banking: Built on Google Gemini after eight years of development, Starling Assistant lets customers manage money, set savings goals, and complete banking tasks. It works through voice and natural language prompts directly inside the app. (link)

Funding Spotlight

Where the money is flowing for innovation…

Steward raises $5M to automate AML/KYC onboarding for complex investor structures: Its AI-driven workflow combines document collection, risk screening, and periodic reviews into a single process. Same-day onboarding is achieved in 80% of cases for fund-of-funds, family offices, and offshore trusts that traditionally require weeks of manual review. (link)

Eclypsium raises $25M to secure AI hardware and supply chain infrastructure: Funding will expand platform coverage across NVIDIA GPU servers, network edge devices, and enterprise hardware. Financial services and government sectors are the primary targets as AI infrastructure security becomes a growing priority. (link)

Allure Security raises $17M Series B to fight AI-powered brand impersonation at scale: Its platform analyzes over 10 million digital assets daily and identified impersonation attacks targeting more than 700 financial institution brands in 2025 alone. VyStar Credit Union is among its current customers. (link)

Oasis Security raises $120M Series B to govern how AI agents access enterprise systems: Machine identities now outnumber human ones 82 to 1, and most lack task-specific permissions. Oasis addresses that gap by assigning scoped access to AI agents and machine identities. (link)

Manifold raises $8M Seed round to monitor what AI agents do: Real-time visibility into autonomous agent behavior covers shell commands, API calls, and system access across enterprise endpoints. First-generation AI security tools only monitored model outputs, leaving this layer unaddressed. (link)

Keeping up with Tech

The latest in fintech and tools…

Mastercard builds transaction AI model while Visa pilots agent-initiated payments: Mastercard is training a large tabular model on hundreds of billions of anonymized transactions to improve fraud detection and reduce false alerts. Visa is testing AI agents that complete purchases within pre-set spending limits across 21 European bank partners. (link)

Obin AI launches to run auditable AI workflows inside financial institutions: Founded by former JPMorgan and Google AI executives, the platform executes end-to-end financial workflows within a firm’s own governance boundaries. Institutions retain full ownership of their data and models while producing traceable outputs. (link)

Mastercard launches agentic AI platform to replace specialist staff for small businesses: The Virtual C-Suite integrates with existing accounting, banking, and business software to analyze performance, flag risks, and recommend actions. It covers finance, marketing, and cybersecurity for small business owners who lack dedicated teams. (link)

Mastercard builds a large tabular AI model trained on billions of payment transactions: The model already outperforms standard fraud detection on edge cases like infrequent high-value purchases. It could eventually replace thousands of separate market-specific AI models Mastercard currently maintains across its network. (link)

Coinbase launches wallet infrastructure letting AI agents transact autonomously: The Agentic Wallets platform gives AI systems the ability to hold funds, execute payments, and trade digital assets independently within programmable spending caps and compliance controls. (link)

Vivi Money partners with Pismo to build AI-driven banking accounts in Australia: The fintech’s AI assistant connects to users’ bank accounts, loans, and retirement savings to provide real-time cash flow analysis and proactive reallocation recommendations. (link)

Feedzai launches RiskFM, a foundation model built for financial crime detection: Trained on $9 trillion in annual payments across 120 billion events, RiskFM matches the performance of manually engineered fraud models on day one. It covers card fraud to AML without custom feature engineering and outperforms single-institution models when trained across multiple institutions. (link)

Constant AI launches Nia to automate skip-a-pay requests end-to-end for Credit Unions: Deployed at MSUFCU, Nia handles eligibility checks, approvals, and core system updates across voice, chat, and text in minutes. Nia replaces manual queues that previously took three to five days and risked members going delinquent before processing. (link)

ChatGPT launches visual shopping with AI agents completing purchases end-to-end: OpenAI expanded its Agentic Commerce Protocol to support product discovery, letting users browse visually, compare options, and move toward checkout inside ChatGPT. Partners include Shopify, Walmart, Target, and Nordstrom. (link)

In Other News

Related news you can learn from…

• Crypto.com cuts 12% of staff as AI replaces operational roles (link)

• White House proposes light-touch AI regulation to boost innovation (link)

• AI is shifting the competitive advantage from institutions to customers (link)

• Aveni launches industry council to establish agentic AI governance standards (link)

Community Corner

Memes and visuals…

@thefountaininstitute

The Fountain Institute on Instagram: "Original video by @valent…

Thanks for reading!

Until next week,

— Credit Union AI Guy

Enjoying this newsletter? Forward it to a colleague who might appreciate practical AI insights.

Have a question or want to share your own AI experiment? Reply to this email or connect with us on LinkedIn. We’re building a community of curious Credit Union professionals. Come join the conversation!

This week’s Credit Unions show how AI is making that easier (even during core conversions):

• Credit Union of America cut agent turnover from 90% to 24%

• First Heritage FCU fixes inconsistent, scattered knowledge

• APL Federal Credit Union took the chaos out of a core conversion

Read time: 9 minutes

Top Stories

The biggest news this week…

1) Credit Union of America cut agent turnover from 90% to 24%

Frontline staff at $1.5B Credit Union of America were losing time and confidence during member interactions because critical documentation was scattered across network drives, shared folders, and intranet pages. When employees couldn’t find answers quickly, it created friction for members and frustration for staff — contributing to a member support turnover rate that once reached 90%.

Credit Union of America launched interface.ai’s Employee AI in late 2023 to fix this. Austin Hamann, Employee Engagement Lead, worked with departments across the organization to identify common questions and gather the documentation needed to support them. The team began with an alpha test involving frontline staff, asking real questions to identify knowledge gaps and refine responses before expanding department by department. The Credit Union also launched a monthly incentive program rewarding employees who used the system and submitted feedback.

The AI assistant pulled from internal documentation to deliver accurate answers in seconds, replacing the need to search multiple systems or escalate to colleagues. Employees now ask an average of 15-25 questions per day through the platform. Member satisfaction reached 4.73 out of 5. And agent turnover in the member support department dropped from 90% to 24%. (link)

2) First Heritage FCU fixes inconsistent, scattered knowledge

When frontline staff can’t find answers quickly, they ask the person next to them. At First Heritage Federal Credit Union, that habit was producing a different answer depending on who you asked.

Zach Saunders, Director of Retail Operations and Training, played a key role in testing and refining the rollout of their AI solution, the Knowledge Assistant from Posh. Before going institution-wide, the team stress-tested the system with extensive questions, using the AI’s interpretations to identify gaps and improve how internal procedures were written. The tool launched first in the contact center, then expanded across departments. Staff can now find answers much faster, helping reduce hold times and transfers for members.

First Heritage also deployed Posh Answers on its public website, giving the marketing team analytics into what members are actually searching for — visibility they had never had before. New hires are now onboarded with Knowledge Assistant from day one, and that group has become the most engaged users, pulling more seasoned employees along with them. With strong early results, the CU is preparing to roll out Workshop Mode, a generative AI workspace, to over 150 staff members. (link)

3) APL Federal Credit Union took the chaos out of a core conversion

Core conversions are often treated as an all-hands emergency. Staff flood support lines, vendors send people on-site, and even simple questions like how to reverse a payment can slow down service.

$680M, 58-employee APL Federal Credit Union was planning to implement Eltropy’s Employee Assist after their conversion wrapped up. But a light bulb moment hit CEO David Woodruff: why wait? So the team loaded all their documentation into the platform before going live, giving staff a conversational tool to get instant answers during the transition. When the core vendor’s on-site support team arrived, they had almost nothing to do. APL’s staff were already getting answers through the AI assistant, in real time, without picking up the phone.

Woodruff sees this as the right model for AI in Credit Unions. Let the tech absorb the repetitive and procedural, so people can show up for the moments that actually require human judgment. He points to a $200 credit line extension for a single mom trying to get her daughter to Dover Air Force Base as the kind of decision that required human judgment and empathy. That’s where Credit Union staff need to be — not searching for a procedure in a folder somewhere. (link)

Tips & Use Cases

Learn to apply AI…

717 Credit Union uses AI decision engines to lend deeper: Dan Harp, Chief Lending Officer, says AI-powered decision engines now evaluate up to 2,000 variables per application, freeing underwriters from routine approvals to spend more time on complex, lower-credit-score borrowers who need a human review. The goal is fewer charge-offs through the engine, and more approvals through the human. (link)

FourLeaf CEO says tech is the biggest gap in member experience: Linda Armyn says the Credit Union is launching a new account opening system and evaluating a new loan origination system to close tech debt gaps and stay relevant with members. (link)

River Valley FCU taps Scienaptic AI for credit decisioning: The $60M South Arkansas Credit Union expects the platform to reduce manual processing, improve documentation consistency, and support responsible credit growth without adding complexity for members or staff. (link)

Vantage West CU builds AI-ready culture through experimentation: Rob Hoyle, Chief People & Technology Officer, says the CU is using AI across underwriting, member communications, and content creation, with an internal knowledge base in development. The goal is to serve 300,000 members with the same workforce that serves 210,000 today, by using AI to handle repetitive, recurring tasks. (link)

First New York FCU takes governance-first approach to AI adoption: CTO Justin Cresswell says they started their AI rollout by establishing governance and risk oversight before deploying any tools, using Microsoft Copilot as an early use case. The strategy focuses on identifying specific problems first, then bringing AI to the table rather than adopting tools and finding uses for them after. (link)

Survey finds FIs unprepared to manage vendor AI risk: A Ncontracts survey of 173 financial services professionals found that AI risk now ranks alongside cybersecurity as the top third-party concern. Yet 72% of respondents are only partially aware of which vendors are using AI. Nearly 63% of third-party risk programs run with just one or two staff members while overseeing 300 or more vendors. (link)

Santander and Visa complete agentic payments pilot in Latin America: The two companies completed a controlled pilot where AI agents autonomously purchased goods across Latin America using Visa Intelligent Commerce. The test validated consent capture, secure data handling, and cross-market interoperability. (link)

JPMorgan partners with Mirakl to enable agentic commerce: JPMorgan Payments is piloting a system where AI agents can browse merchant catalogs and complete purchases autonomously, combining JPMorgan’s payment infrastructure and fraud controls with Mirakl Nexus’s agentic commerce layer. A broader rollout is planned for later this year. (link)

PYMNTS report finds AI adoption plateauing at 49% of U.S. adults: Growth is now driven by existing users doing more rather than new users signing up, with power users averaging 27 AI-driven tasks per month across shopping, task management, and financial decisions. Over half of U.S. adults remain holdouts, including 72% of baby boomers. (link)

CU execs want AI use cases, not demos: Cornerstone Advisors reported that Credit Union executives at this year’s GAC described AI vendor pitches as “shiny object overload,” with leaders saying what they want most are practical use cases tied to specific business outcomes. Roughly 60% of CEOs are expected to retire within five years, adding urgency to AI strategy and succession planning simultaneously. (link)

AI agents accelerate processes but aren’t replacing jobs yet: Cornerstone Advisors argues that AI agents today are best understood as process accelerators that get work to the human faster, not replacements for human decision-making. Credit Unions against assuming “human-in-the-loop” means the agent does the work and a human approves it, that misunderstanding is leading institutions to underinvest in redesigning the underlying process. (link)

Goldman Sachs builds AI agents with Anthropic for back-office work: After embedding Anthropic engineers inside the firm for six months, Goldman Sachs deployed autonomous AI agents that compress week-long KYC compliance checks into automated document review and cut reconciliation from days to hours. Their CIO describes the result as a “digital coworker” for complex, process-intensive roles. (link)

Claude’s new visual reasoning tool aids financial decision-making: Anthropic’s Claude can now read uploaded financial statements and generate interactive visualizations, scenario models, and board-ready analysis within a single chat session. A CFO Office test showed Claude building three capital allocation scenarios from a P&L without being prompted to do so. (link)

Gemini in Google Sheets struggles with complex finance workflows: Google shipped a major Gemini update for Sheets in March, claiming 70% success on spreadsheet benchmarks. But real-world testing on a multi-file rolling forecast workflow showed the tool failing to reliably move data across Gmail, Drive, and Sheets in one flow, a capability Claude Cowork handled more reliably. (link)

Commerzbank deploys Hawk AI to boost AML detection accuracy: The bank layered Hawk’s AI-driven risk model on top of its existing rule-based compliance systems, reducing false positive alerts while detecting more novel money laundering cases. The solution integrates with legacy systems without requiring technology overhauls. (link)

AI ROI requires work redesign, not just tool deployment: Globant’s Financial Services AI Studio CEO argues that AI stalls when layered onto unchanged workflows without redefining accountability. The fix is explicitly separating what AI executes from what humans decide, then measuring results in cycle time and cost-to-serve rather than training completions. (link)

AI tools are pulling small businesses away from bank portals: More than 70% of small businesses now regularly use AI tools for cash flow forecasting, payment tracking, and financial reporting, often bypassing their bank’s platform entirely by exporting data into external AI tools. (link)

Funding Spotlight

Where the money is flowing for innovation…

Uptiq raises $25M Series B with investment from Curql: Curql, the investment fund backed by over 160 Credit Unions, participated in the round to scale Uptiq’s AI platform across lending, member servicing, compliance, and operational workflows. The funding will expand access to Qore, Uptiq’s AI orchestration platform for building and deploying financial workflows inside Credit Union core systems. (link)

Gangkhar raises $4.25M Seed to expand AI-native embedded protection platform: Gangkhar’s AI optimization engine uses real-time program data to improve segmentation, pricing, and underwriting across embedded protection products in multiple markets. The capital will fund product development and international expansion via its single-API infrastructure covering onboarding, pricing, underwriting, and claims. (link)

Onyx Security launches with $40M to govern AI agents in enterprise: The platform monitors AI agents in real time and can approve, modify, or block their actions before they execute, helping enterprises enforce governance policies as autonomous AI systems gain access to critical infrastructure. (link)

BrightPlan secures new funding to expand AI financial wellness platform: The platform serves 9.2M employees across 50+ countries, combining AI-driven guidance with live advisors, and posted 41% YoY recurring revenue growth. Funding will support global expansion and accelerated AI personalization across the platform. (link)

Armadin raises $189.9M to build autonomous AI cyber defense: The platform uses a network of AI agents that continuously probe an organization’s infrastructure for real-world exploit paths, moving at machine speed to outpace AI-driven attacks. (link)

Keeping up with Tech

The latest in fintech and tools…

Posh launches CoachQA to evaluate 100% of contact center interactions: Most Credit Union QA teams review less than 1% of calls, leaving compliance gaps, fraud signals, and coaching opportunities invisible. CoachQA automatically applies each institution’s SOPs to every interaction, with Citadel Credit Union and Chartway Credit Union among early adopters. (link)

Glia announces no hallucination guarantee for its banking AI platform: Glia’s proprietary approvals framework separates AI’s ability to interpret customer intent from the system that generates responses, preventing the AI from improvising answers in real time. The contractual guarantee covers hallucinations and prompt injection attacks across Glia’s platform. (link)

Napier AI launches Insights AI for AML investigations: The tool surfaces AI-driven explanations of customer behavior directly within transaction monitoring tasks, cutting manual analysis for compliance teams. It was developed using novel frequency-based algorithms tested in the FCA’s Supercharged Sandbox. (link)

Agora launches Orbit AI operating system for financial advisors: The platform runs continuously in the background, automating routine processes and surfacing only moments requiring advisor judgment or client engagement. (link)

OpenAI shifts AI checkout to third-party partners: Rather than embedding purchases directly in ChatGPT, OpenAI is routing transactions through third-party e-commerce partners to prove the agentic commerce model before the 2026 holiday retail freeze. (link)

Experian launches credit score tool inside ChatGPT: The app uses aggregated Experian data to show how credit scores compare by postcode and age group, with a direct route to check a personalized score. The move targets 18-34-year-olds, who make up more than half of ChatGPT’s user base but are among the least likely to have checked their credit score. (link)

Perplexity expands Computer platform with finance and enterprise tools: The platform now connects to brokerage accounts via Plaid for portfolio analytics, pulls live data from SEC filings, FactSet, S&P Global, and other sources, and can build Excel models and financial dashboards without additional licenses. An enterprise version integrates with Snowflake, Salesforce, and Slack for cross-platform financial analysis. (link)

Sutherland launches FinAI Hub for banking AI workflows: Modular AI agents cover KYC, AML, underwriting, fraud, disputes, and collections, designed to integrate with legacy systems in regulated environments. Early deployments reported up to 50% faster processing cycles and 40% reductions in operating costs. (link)

OpenAI equips Responses API with a computer environment for agents: Developers can now give AI agents a hosted container with a file system, database access, and controlled network access. A single prompt can trigger end-to-end workflows like fetching live data and generating a spreadsheet. (link)

In Other News

Related news you can learn from…

• No single solution can fully verify Deepfakes (link)

• AI is raising a new question: who should control powerful tech? (link)

• AI agents are facing a new wave of social engineering-style attacks (link)

• Bilt faces growing backlash as AI support and payments issues frustrate users (link)

Community Corner

Memes and visuals…

Thanks for reading!

Until next week,

— Credit Union AI Guy

Enjoying this newsletter? Forward it to a colleague who might appreciate practical AI insights.

Have a question or want to share your own AI experiment? Reply to this email or connect with us on LinkedIn. We’re building a community of curious Credit Union professionals. Come join the conversation!

But are you taking advantage of it?

This week, I cover:

• Texans CU uses Copilot to scale rapidly across Texas

• OceanAir FCU uses Q2 integrations to compete with larger institutions

• How a Credit Union tech exec escaped a legacy code crisis

Read time: 9 minutes

Top Stories

The biggest news this week…

1) Texans Credit Union uses Copilot to scale rapidly across Texas

Maintaining aging on-prem systems was consuming significant time and energy at Texans Credit Union, pulling focus away from innovation and automation. With Texans previously focused almost entirely on the Dallas-Fort Worth metroplex, its older infrastructure was not built to support the speed, scale, and digital experience modern members expect.

Backed by CEO David Frazier and the executive leadership team, VP of IT Systems Ian Beirnes helped lead Texans Credit Union’s move to Microsoft Azure and Microsoft 365. The team rolled out Microsoft Copilot with Microsoft Purview’s permissions and labeling controls as a key part of the security model. They blocked all other AI tools entirely so every data interaction would flow through Copilot’s controlled environment. Staff quickly found that tasks that took hours dropped to minutes, particularly for meeting notes, action items, and Excel-based financial analysis.

Texans is currently at about 130,000 members, growing ~10% YoY, and has expanded from the DFW metroplex to all 254 Texas counties. Beirnes used a crawl-walk-run approach to Copilot adoption, helping teams see how the tool applied to their specific jobs so they could become more engaged in the rollout. The Credit Union is targeting near-total cloud adoption by mid-2027. (link)

2) OceanAir FCU uses Q2 integrations to compete with larger institutions

In Q2’s 2026 Retail Banking Trends and Priorities research, 56% of Credit Unions listed digital transformation as a top priority, yet 60% remained in the early stages of implementation.

Members are not comparing their experience to the Credit Union down the street. They compare it to Amazon, Venmo, Chime, and Starbucks.

Jesus Garcia, Chief Experience Officer at OceanAir Federal Credit Union, built the entire digital experience around one operating principle: if a vendor does not already work well inside Q2’s ecosystem, OceanAir moves on. By choosing the right Q2-integrated partners, OceanAir’s department of one can move quickly without needing heavy IT lift.

OceanAir’s digital experience leader previously worked at the Credit Union, spent a couple of years at Q2, and then returned with deeper platform knowledge. Garcia’s team stacked Q2-integrated tools, including Eltropy for lobby appointments and loan status texts, Larky for push notifications, Origence for loan origination, and SavvyMoney for in-app FICO scores. Together, they create a closed loop where a member can check their score, apply for a loan, and get text updates without calling anyone.

On the AI side, OceanAir partnered with Eltropy on an employee assist AI program, loading their new card program and credit card rewards details into the tool so staff can get instant answers during member conversations. They also used data to spot a local advantage: OceanAir is the only financial institution in its county that’s a Visa shop, and Costco accepts only Visa, so the team increased rewards for Costco gas purchases to capitalize on that edge. Garcia also described using AI and member data to launch timely rewards, including refunding a month of Netflix for members paying for that subscription with the OceanAir card. (link)

3) How a Credit Union tech exec escaped a legacy code crisis

Legacy code written in a language with almost no available developers is a ticking clock, especially during a period of restructuring and mergers and acquisitions. If that code breaks, troubleshooting is brutal, and batch jobs that miss their midnight deadline can prevent a Credit Union from opening the next day.

Nupur Daruka, Sr. Director of Software Development at First Tech Federal Credit Union, used Claude and GitHub Copilot integrated directly into the team’s repos to convert legacy code at speed. Before broader adoption, the team created prompt templates, markdown files, and guardrails to reduce the risk of accidentally committing PII.

Adoption started with a small pilot group and expanded after the framework was proven. For AI-driven decisions, her team uses a tiered risk model: low-risk processes run fully automated, while high-risk decisions always keep a human in the loop for auditability. On fraud, her team replaced rule-based detection with a real-time AI vendor integration, replicating transactions to the vendor’s system the moment they occur so the fraud team can act before losses happen. (link)

Tips & Use Cases

Learn to apply AI…

Curql Collective backs AI fraud prevention initiative for Credit Unions: Charm Security and Curql Collective launched the National Member Protection Initiative with five Credit Unions, including InTouch, Lake Trust, and ORNL Federal, to test agentic AI that intervenes before scams cause financial harm. The effort comes as nearly 7 in 10 Americans were targeted by scams in 2025, resulting in an estimated $64B in losses. (link)

How Aliya Financial Technologies runs lending with 5 people instead of 50: The Aliya platform combines cash flow analysis trained on 1.2 trillion transactions, fraud detection, and portfolio optimization into one AI system, cutting loss rates to 2.5% compared to SoFi’s 7% on a lower average FICO score. (link)

How to roll out AI collections safely at your Credit Union: Start with a one to two week design phase covering one loan type and one delinquency segment, run internal simulations for opt-outs and hardship signals, then pilot with a limited member population for two to four weeks before expanding. This matters now as Credit Unions reported 95 basis points in total delinquency in Q3 2025. (link)

True North FCU adopts Scienaptic AI for lending decisions: The Juneau-based Credit Union is deploying Scienaptic AI’s credit decisioning platform to move beyond traditional credit scores and expand access to credit for Alaskan members. (link)

AI agents need the same governance controls as human employees: If a teller cannot approve their own override, neither should an AI agent. Financial institutions entering agentic AI should apply least-privilege access, audit logging, approval hierarchies, and separation of duties before any agent touches member data or initiates actions. (link)

Raddon’s chief economist says AI can close the scale gap: Bill Handel says 8 out of 10 Millennials and Gen Zers would choose a Big Five bank over a Credit Union as their primary institution. The gap is perception and positioning, not product quality, making AI-driven efficiency only half the solution. (link)

Sam Altman says slow AI adopters face a competitive disadvantage: The OpenAI CEO told Cisco’s AI Summit that companies not structured to adopt AI co-workers quickly will fall behind. Altman predicts the end state is “full AI companies” where AI actively participates in how work gets done rather than layered onto existing workflows. (link)

Port Washington State Bank uses GenAI to build campaign playbooks in minutes: Amy Kauper, VP of Retail Banking at Port Washington State Bank, uses GenAI to turn a completed marketing brief into talk tracks, FAQs, objection guides, and manager huddle plans in a single chat session. Starting at 80% instead of zero compresses campaign launch time from weeks to days and keeps frontline staff working from the same playbook. (link)

Joe Pine says AI can help banks shift from experience to transformation: In a Banking Transformed interview, author Joe Pine says AI excels at two things banks need most: building detailed customer profiles from transaction data to surface personalized goals, and coaching members between adviser appointments to keep them on track toward real financial outcomes. (link)

Anthropic research finds no AI unemployment spike yet, but hiring slows for young workers: The study found no measurable increase in unemployment for the most AI-exposed workers since late 2022, but hiring into those roles for workers aged 22 to 25 dropped 14% compared to pre-ChatGPT levels. Customer service representatives rank second-most exposed, at 70.1% task coverage, behind only computer programmers at 74.5%, with financial and investment analysts at 57.2%. (link)

Global illicit finance hit $4.4 trillion in 2025 as criminals weaponize AI: Nasdaq Verafin reports U.S. banks absorbed $179B in direct fraud losses while 63% of organizations faced business email compromise attacks, pushing 75% of anti-financial crime professionals to expand AI-driven detection over the next year. (link)

Credit Union tech IQ at highest level ever: SavvyMoney CEO JB Orecchia told the Fintech Hustle podcast that Gen Z is the platform’s most engaged user, obsessively tracking credit scores, but warned Credit Unions need to catch up on cash flow underwriting as Gen Z builds wealth through debit and buy-now-pay-later instead of traditional credit. (link)

SAS report finds only 11% of banks have trustworthy AI: A global IDC survey of 2,375 IT and business leaders found 47% of banks are either underusing reliable AI or over-relying on unvalidated systems, while 45% lack effective data governance and 42% face AI talent shortages. Banks using AI to improve member experience report $1.83 back for every dollar invested. (link)

96% of financial institutions are using or planning AI: A Finastra survey of 1,000+ leaders across 11 global markets found 43% cite AI as their top innovation lever. Another 54% are leaning on fintech partnerships to accelerate modernization, and institutions expect a 40% increase in security spending as AI scales. (link)

Verity Credit Union used Zest AI to boost loan approvals for members over 62 by 270%: An American Banker op-ed argues AI trained on historical data risks automating inequality. But Credit Unions using fair lending models like Verity’s partnership with Zest AI show purpose-driven AI can expand access with lower delinquencies rather than simply optimizing for profit. (link)

Accenture says “optimize my idle cash” should scare every Credit Union: Michael Abbott, Accenture’s global banking lead, warns that 65% of consumers are open to using a ChatGPT-type financial assistant. Credit Unions that don’t appear in AI-generated recommendations risk losing deposits and loans without ever knowing they lost the opportunity. (link)

How to get more out of GPT-5.4 for financial work: When prompting AI for multi-step finance tasks, define the exact output format upfront, tell the model to verify its own numbers before delivering results, and chain steps into explicit workflows so it knows what “done” looks like. (link)

Microsoft Foundry delivers 327% ROI over three years, Forrester finds: A study of five organizations found the biggest driver of returns was developer productivity, worth $15.7M over three years, as teams using Foundry reduced AI development time by 30% to 40% by building on shared knowledge bases instead of rebuilding pipelines from scratch. (link)

How to set up Claude Cowork as a CFO analyst in 15 minutes: Point Claude Cowork at a dedicated folder with three files: a workspace brief, a task list, and a memory file that stores decisions between sessions. It will ingest contracts, flag spend inconsistencies, and build reusable dashboards without writing a single line of code. (link)

Agentic AI governance starts at the logic layer, not the transaction layer: Once an AI agent initiates payments or routes funds without human approval, monitoring outcomes is already too late. Compliance advisor Natalia Taft says boards need plain-language answers on objective functions, hard limits, drift detection, and kill-switch procedures before any agent goes live. (link)

Funding Spotlight

Where the money is flowing for innovation…

Remitian raises $7M Seed round to automate tax payment and reconciliation workflows: The startup launched a Tax Payment API that lets accounting firms embed payment initiation, real-time tracking, and reconciliation across tax jurisdictions into their existing platforms, replacing manual government portal entries that create penalties and audit risk. (link)

RenoFi closes $22M Series B to scale renovation financing: RenoFi’s AI-powered platform combines credit underwriting with renovation-specific underwriting to unlock After Renovation Value financing, giving equity-light homeowners up to 11x more borrowing power. Credit Union partners include Ardent, Chartway, First Community, and USALLIANCE Financial. (link)

Pasito raises $21M Series A to automate benefits administration: Pasito’s agentic AI platform unifies group health, life, and retirement benefits workflows for carriers, brokers, and financial institutions, achieving 98% accuracy in plan construction vs. the 74% industry average. (link)

Denki raises $4.1M to automate SOX and BSA/AML compliance testing: Its three AI agents map internal controls, validate them in real time against HR and access data, and link general ledgers into a single audit trail that flags issues before they become findings and generates ready-to-share audit packs. (link)

Levitate raises $16M to scale AI relationship marketing: The platform helps finance, insurance, and other relationship-based businesses automate client outreach through email, text, social media, and more, now serving 8,000+ businesses with $71M raised to date. (link)

Vivox AI raises £1.3M to build auditable AI agents for compliance: The UK startup’s atomic AI agents handle AML, KYB, and KYC workflows for regulated financial institutions, with each agent responsible for a single defined task to maintain auditability and regulatory control. (link)

Keeping up with Tech

The latest in fintech and tools…

Upstart applies for national bank charter to expand AI lending: The move would let Upstart lend nationwide under a single regulatory framework and fund more loans with insured deposits, while continuing to sell roughly 95% of originated loans to Credit Union and bank partners. (link)

OpenAI releases GPT-5.4 with native computer use: The model matches or beats industry professionals on 83% of knowledge work tasks and operates desktop software and browsers natively. It uses 47% fewer tokens on complex tool workflows, making it more practical for document-heavy financial back-office work. (link)

OpenAI launches ChatGPT for Excel with financial data integrations: The add-in lets teams build, update, and analyze spreadsheet models in plain language directly inside Excel. Integrations for Moody’s, Dow Jones Factiva, MSCI, and others support workflows like credit memos, valuation, and due diligence. (link)

Apex FinTech and Wavvest partner on AI financial planning: The integration connects Wavvest’s AI planning engine to Apex’s custodial data infrastructure, generating financial plans, tax analyses, and portfolio recommendations in minutes instead of hours of manual entry. (link)

TransUnion launches AI agent to speed credit analytics: Built on Google’s Gemini models within the OneTru platform, the tool translates natural-language questions into governed, production-ready analytical workflows inside TransUnion’s TruIQ suite. It cuts credit analytics cycle times from weeks to hours, allowing financial institutions to run sophisticated analyses without direct data science support. (link)

Mastercard unveils trust layer for AI agent payments: The open-source Verifiable Intent layer creates a tamper-resistant record of what users authorized when AI agents act on their behalf, with Google, IBM, and Checkout.com among early backers. (link)

OpenAI launches Codex Security for AI-powered vulnerability detection: The application security agent builds context about a codebase to identify and patch complex vulnerabilities, cutting false positives by over 50% and reducing noise by up to 84%, giving development teams a faster path to secure code. (link)

Finastra and FraudAverse partner on real-time AI fraud detection: FraudAverse’s AI platform is now pre-integrated into Finastra’s Financial Messaging infrastructure, giving financial institutions real-time fraud monitoring across payment channels without extensive internal development. The companies claim the system can deter up to 99% of fraudulent transactions. (link)

Theta Lake patents AI detection of apps visible during screen shares: The system uses visual and textual fingerprinting to automatically identify software displayed during recorded meetings. Compliance teams at regulated financial institutions get an auditable way to flag accidental exposure of sensitive data. (link)

Rezolve.ai layers agentic AI on top of ServiceNow without replacing it: Credit Union IT teams can add an intelligence layer that handles voice, email, and chat support while reducing ticket volume within 60 days, with a conversational automation builder that constructs full workflows from a plain-language description. (link)

In Other News

Related news you can learn from…

• Consumer AI moves from tools to full digital ecosystems (link)

• AI productivity gap widens between executives and employees (link)

• Fintech founder shares lessons from building and selling an AI startup (link)

• AI value comes from sequencing the right business models, not running more pilots (link)

• PIMFA, Morningstar, and Finextra launch AI Tech Sprint for wealth management fintechs (link)

Community Corner

Memes and visuals…

@theintrovertedattorney

The Introverted Attorney on Instagram: "Less talk and more acti…

Thanks for reading!

Until next week,

— Credit Union AI Guy

Enjoying this newsletter? Forward it to a colleague who might appreciate practical AI insights.

Have a question or want to share your own AI experiment? Reply to this email or connect with us on LinkedIn. We’re building a community of curious Credit Union professionals. Come join the conversation!

If you couldn’t make it, CU leaders came with receipts on where the industry is already heading with AI.

And let’s not forget the fun: Zest AI brought the La-LuLu plushies, and Glia was making AI-generated portrait sketches for those who showed up to their booth. Well played.

This week, I cover:

• 3 Lessons GAC 2026 taught Credit Unions about AI

• Alltru Credit Union cuts delinquencies $10M in 90 days with texting AI

• PFCU ends knowledge chaos in 5 months

Read time: 9 minutes

Top Stories

The biggest news this week…

1) 3 Lessons GAC 2026 taught Credit Unions about AI

AI was one of the defining topics at GAC in Washington, D.C., this week. Here’s what the industry made clear:

AI has moved from pilots to daily operations.

SchoolsFirst Federal Credit Union, the largest Credit Union in California with 1.5M members and $35B in assets, is no longer testing AI. CEO Bill Cheney told GAC attendees that deploying AI across all consumer lending products tripled the rate of automated approvals, freeing loan officers to focus on complex cases. BECU CEO Beverly Anderson framed it simply: “There are things you do every day. That’s ‘no-joy’ work. How do we let AI help so you get more opportunities to serve members?” New York Fed President John Williams gave the macro context, telling Credit Union leaders that AI will increase productivity and create new opportunities, and that the biggest gains will come from workers who integrate it into daily work now. (link) (link)

Governance is lagging dangerously behind deployment.

Devon Lyon, President and CEO of Central One Federal Credit Union, put the governance problem plainly at GAC. “An overall lack of federal clarity is creating essentially different levels of impact across the markets in which you’re operating,” he said. “There are certain states right next to one another, your members live in both, and now you have to create two different sets of frameworks to service both.” Michael Berman, founder and CEO of Ncontracts, added that overlapping state AI and privacy laws make it critical that Credit Unions stop siloing AI and privacy compliance. The NCUA has not yet issued official AI guidance, though it does have internal guidance for how its own employees use AI. When the session moderator asked for a show of hands, most attendees admitted using AI tools at work. Very few had a formal internal AI data governance plan. “Your organization is using AI, whether it’s a strategic business decision or unregulated,” Lyon warned. “And that could come up in audits.” (link)

Purpose-built AI is outperforming general tools by a wide margin.

Glia’s 2026 Banking AI Benchmarks Report, released during GAC and built on data from 400 financial institutions, found that banking-specific AI achieves 92%+ intent understanding, handles 94.8% of balance checks without human intervention, and automates 90-98% of post-call wrap-up work. The numbers show up in individual Credit Union deployments, too. After deploying Casap’s AI dispute platform, the $3.2B Chartway Credit Union cut dispute costs 85%, dropped resolution time from 90 days to 12, reduced write-offs 72%, and saved $875,000 annually. Disputes that once hurt NPS now generate member thank-you emails. (link) (link)

Williams told GAC attendees that Credit Unions’ local community ties remain a competitive superpower. AI does not erase that advantage. But institutions treating AI as a future agenda item are already falling behind peers who acted. (link)

2) Alltru Credit Union cuts delinquencies $10M in 90 days with texting AI

Collections staff at most Credit Unions are stuck leaving voicemails that never get returned while delinquent accounts pile up.

At Alltru Credit Union, a $360M, 40,000-member institution in St. Louis, that problem was getting worse. “Delinquencies have risen since the pandemic stimulus lows,” says Katie Bendyk, Director of eServices & Payment Solutions. “We knew the phone call isn’t as effective as it used to be.” Operating in a market where there’s a bank on nearly every corner, Alltru couldn’t compete on products alone. “We pretty much have the same services as everyone else,” Bendyk says. “Our service and culture is what makes us stand out.”

Alltru deployed Eltropy’s texting platform for collections and marketing, replacing outbound phone calls with instant, personalized texts that members could respond to on their own time. The results came from January to March 2024, when delinquencies dropped $10M in 90 days. “When I saw the numbers, I almost couldn’t believe it,” Bendyk said. “It was mind-blowing.”

Efficiency gains followed. With eight disconnected systems previously required to serve a single member, call center reps were burning time toggling between platforms. Eltropy consolidated communication into one place, letting reps serve more members per day. Alltru has since integrated Eltropy with MeridianLink to help the lending team close loans faster, with plans to expand across every department. Bendyk is also eyeing Eltropy’s capabilities to reach underbanked and unbanked members through CDFI expansion. (link)

3) PFCU ends knowledge chaos in 5 months

Finding a policy at PFCU used to feel like a treasure hunt.

“It’s almost embarrassing to say out loud,” admits Theresa Burgess, Chief Member Experience Officer. Information was buried across shared drives, nested folders, and email threads. Subject matter experts were drowning in chat questions on top of their actual jobs. New hires felt overwhelmed, member surveys showed hesitation in employee conversations, and turnover was bleeding institutional knowledge out the door.

PFCU deployed Posh Knowledge Assistant in August 2025, connecting all internal procedures, policies, and documentation behind a single Google-style search. Before rollout, Burgess partnered with department leaders to audit and centralize scattered materials, letting Posh surface duplicates and contradictions in documentation the team didn’t know existed. A beta program in select branches built excitement before the full launch.

By January 2026, PFCU logged 10,000+ questions answered across nearly 200 users at a 95% success rate. New hires asked fewer repetitive questions and ramped faster. Member interactions became more confident. Turnover stabilized, with departures shifting from burnout to retirement and relocation. PFCU exported a full year of employee questions from Pedia, uploaded the spreadsheet into Workshop Mode, and used it to identify knowledge gaps. (link)

Tips & Use Cases

Learn to apply AI…

StagePoint Federal Credit Union turns policy docs into instant answers: Geoff Shimp, VP of Technology, connected over 600 docs to CurrentWave AI via SharePoint, giving employees a searchable tool. Staff get procedure answers in under 15 seconds instead of manually combing through files mid-member interaction. When AI can’t answer, it flags the gap to management. (link)

Clearview FCU CIO sets hard ROI standard for AI tools: Raymond George measures every AI license by one metric: hours saved versus cost. Clearview runs ChatGPT Enterprise, Microsoft Copilot, and Zest’s Lulu across HR, lending, and call center analysis, with trained AI champions driving adoption org-wide. (link)

GLCU’s AI voice bots drive $1M in community lending: Elizabeth Osborne reports that Interface AI bots “Olive” and “Oliver” handle all inbound calls and outbound outreach, driving a 5% NPS increase and 20% member awareness uplift. AI-guided outreach also helped lend $1M in underserved Philadelphia neighborhoods. (link)

Kemba CU CEO pledges no job cuts as AI handles routine work: Dan Sutton, CEO of Kemba Credit Union, rewrote an overly restrictive AI policy and now runs AI across contact center knowledge queries and outbound member calls for its 130,000 members. Sutton’s internal message: repetitive tasks shift to machines, no one loses their job, and any staff reduction happens through attrition only. (link)

OnPath FCU bets on AI to catch delinquencies before they start: Jared Freeman, CEO of OnPath Federal Credit Union, a $1.2B New Orleans Credit Union that grew 314% in five years, is beta testing Auvo’s delinquency prediction model to flag at-risk accounts early. Staff sends proactive outreach with payment resources before a payment is missed, replacing reactive collections notices after the fact. (link)

Generative AI adoption at banks tripled while Credit Union governance lags: Cornerstone Advisors reports bank generative AI adoption jumped from roughly 15% to 45-50% by function in 2025, but most institutions still lack autonomous decision policies, accountability structures, or ROI measures. Credit Union core replacements also dropped from 7% to 1% as AI investment crowds out legacy upgrades. (link)

BECU pilots AI financial advisor for paycheck-to-paycheck members: BECU is testing Becca, a purpose-built AI financial advisor, with 150 employee-members. The tool ingests budgets, credit scores, and open banking data to deliver personalized financial counseling to members who lack access to human advisors, with broad rollout targeted in 12-18 months and high-risk transactions kept under human control. (link)

AI is making Credit Union product differentiation obsolete: Allison Netzer of BrandThink argues that AI has eliminated product differentiation in financial services by making rate and feature comparisons instant. Her data from 75 banks and Credit Unions shows the institutions winning today lead with member pain, not product specs. (link)

Kobalt Labs CEO says start AI with vendor risk, not member-facing tools: Start AI adoption with third-party risk management because it requires no sensitive member data and keeps humans in the loop. Kobalt Labs automates vendor document review, flags fourth-party supply chain risks, and alerts Credit Unions to real-time vendor news without connecting to the core. (link)

Behavioral AI learns your workflows instead of replacing them: A third AI deployment model is emerging where agents observe real work patterns across an organization, surface shared inefficiencies, and build automation around how work actually gets done. Early results show 15-20 hours saved per week. (link)

Agentic Smart Collections AI resolves delinquency before relationships break: With Credit Union delinquency at 95 basis points in Q3 2025, agentic AI now runs coordinated voice, SMS, and email collections outreach within compliance guardrails, captures Promise-to-Pay commitments, and escalates to humans only when needed. (link)

US deposit growth slowed to 0.4% as acquisition costs hit $561 per account: AI is helping financial institutions stop the bleed by flagging at-risk members through behavioral signals like large withdrawals and dropping transaction frequency, then triggering personalized retention offers before members leave. (link)

CaixaBank deploys Salesforce Agentforce to guide in-app loan buyers: The Spanish bank’s new AI agent walks customers through pre-approved loan configurations, helping them define ideal terms and installments before handing off to a human specialist at signing. (link)

Motiv8AI adds behavioral science layer to cut loan defaults 50%: A digital bank in Brazil using Motiv8AI’s Relationship Intelligence Layer saw default rates drop over 50% and BNPL creditworthiness improve 35% by interpreting transaction data through a behavioral science lens. The platform also doubled response rates on member communications and boosted new credit card activation by over 40%. (link)

JPMorgan spends $2B on AI and saves roughly the same amount: Total headcount held flat at 318,512 while operations staff fell 4% and client-facing roles grew 4%, with operations employees handling 6% more accounts, fraud cost per unit down 11%, and software engineers 10% more productive. The bank is redeploying displaced workers into member-facing roles rather than cutting headcount. (link)

RBC creates dedicated AI Group to scale toward C$1B in value: Led by veteran tech executive Bruce Ross, the group will scale proprietary tools already in production, including the Atom credit adjudication model, RBC Assist used by 27,000 employees, and Aiden used by 8,000 Capital Markets staff across a workforce of 100,000 in 29 countries. (link)

Commonwealth Bank invests $90M to retrain 30,000 employees for AI: CEO Matt Comyn’s Future Workforce Program has already delivered AI training to 30,000 staff and includes a skills-based internal job portal to help employees move into higher-value roles. The bank is explicitly recruiting for judgment, critical thinking, and empathy alongside AI fluency. (link)

How one CFO built two board decks in an afternoon: Using ChatGPT, Claude, and Google NotebookLM, a CFO turned scattered notes into a 30-page transfer pricing policy covering five countries, then auto-generated executive presentations for the finance team and CEO. (link)

Funding Spotlight

Where the money is flowing for innovation…

Astelia raises $35M for agentic cybersecurity AI: The platform maps real network attack paths to identify genuinely exploitable vulnerabilities, filtering out noise. In some deployments, only 30 out of nearly 3 million flagged vulnerabilities created actual risk. (link)

Pluvo raises $5M Seed round to put agentic AI inside financial decision-making: The platform analyzes financial models, stress-tests forecasts, and captures the rationale behind past decisions to build institutional memory for CFO and FP&A teams. (link)

Thema raises $6.2M to replace static PE research with live AI analysis: Built with the University of Cambridge, Thema continuously maps how companies cluster into markets and where risk or adjacency sits across a portfolio, replacing one-time consulting reports with always-current intelligence. (link)

General Magic raises $7.2M Seed round to automate insurance workflows with AI agents: Early deployments cut time-to-quote from 30 minutes to under three minutes by running AI agents across pre-quote, post-quote, and claims coordination. (link)

Harper raises $47M Series A to automate commercial insurance brokerage: The platform reads applications, routes submissions, manages quotes, and liaises with underwriters automatically, delivering coverage in 24-48 hours. Harper has served 5,000 businesses across 165 underwriters in just 13 months. (link)

Rowspace launches with $50M Seed and Series A for finance AI: The platform connects structured and unstructured data across a firm’s entire history to help financial institutions make faster, fully informed decisions. Firms managing hundreds of billions in assets are already using it for portfolio monitoring, credit optimization, and deal analysis. (link)

Keeping up with Tech

The latest in fintech and tools…

Posh CoachQA brings full AI coverage to contact center QA: Most financial institutions review less than 1% of customer interactions, leaving compliance gaps, fraud signals, and missed revenue opportunities invisible until audit time. Posh CoachQA uses Retrieval-Augmented Evaluation to assess 100% of calls and chats against each institution’s own standards. (link)

Eleven Credit Unions launch AI Studio CUSO to share AI infrastructure: Founding members include Suncoast ($19.6B), Idaho Central ($14.7B), and MSUFCU ($8.3B), pooling resources to share vendor evaluation, readiness assessments, and fractional chief AI officer access. Solo AI adoption costs roughly $1.16M annually per institution, and AI Studio aims to deliver enterprise-grade capabilities at a fraction of that cost. (link)

Mastercard and Santander complete Europe’s first live AI agent payment: The transaction ran through Santander’s live payments infrastructure via Mastercard Agent Pay in a controlled pilot, marking the first end-to-end payment executed by an AI agent in Europe. Both institutions are now building the governance and technical frameworks needed to scale AI-initiated payments safely. (link)

Eltropy launches first agentic AI platform built for Credit Unions: Every agent action is logged, explainable, and constrained to approved SOPs across a single governance layer connecting institutions, fintechs, and core systems. Cobalt Credit Union reported 83% session containment on Eltropy AI Voice, and fintech Constant AI is already building a Skip-A-Pay agent on the platform. (link)

Microsoft rebuilds SharePoint as the knowledge backbone for Copilot: New custom AI skills let organizations package their own terminology, governance rules, and business logic so Copilot reasons against company-specific context rather than generic data. (link)

Klarna and Stripe embed BNPL into AI agent checkout flows: Stripe’s Shared Payment Tokens let AI agents initiate purchases using a customer’s preferred payment method without accessing actual card details. Klarna’s BNPL options now pass through the same permissioned layer with no additional integration required for existing Stripe merchants. (link)

OpenAI releases GPT-5.3 Instant with sharply reduced hallucinations: The update cuts hallucination rates by 22 to 27% compared to prior models while reducing unnecessary refusals and improving web synthesis. Available now to all ChatGPT users and via API, with GPT-5.2 Instant retiring June 3, 2026. (link)

Figma and OpenAI Codex connect design files to working code via MCP: Developers can now pull layout, style, and component context from Figma directly into Codex for code generation, then push live UI back onto the Figma canvas as fully editable frames. The integration eliminates manual recreation between design and development workflows. (link)

Mistral Document AI launches in Microsoft Foundry for enterprise document processing: The model combines OCR and intelligent document understanding to extract structured data from loan applications, KYC forms, contracts, and multilingual documents with 99%+ recognition accuracy. Financial institutions can deploy it via the open-source ARGUS pipeline without building document processing infrastructure from scratch. (link)

Visa leads payments industry in AI maturity as talent gap widens: Evident’s benchmark shows payments companies carry 30% more AI-focused workers than other financial institutions, with Visa, Mastercard, and Amex accounting for nearly half the industry’s total AI talent. (link)

In Other News

Related news you can learn from…

• Block cuts 40% of staff, citing AI productivity gains (link)

• AI won’t kill enterprise software, it will make the best of it bigger (link)

• Fed Governor Cook warns AI productivity boom could complicate rate policy (link)

• Anthropic and Pentagon resume talks after contract breakdown over surveillance concerns (link)

Community Corner

Memes and visuals…

@hardtoskip

HardToSkip on Instagram: "Me: waiting for him to leave"

Thanks for reading!

Until next week,

— Credit Union AI Guy

Enjoying this newsletter? Forward it to a colleague who might appreciate practical AI insights.

Have a question or want to share your own AI experiment? Reply to this email or connect with us on LinkedIn. We’re building a community of curious Credit Union professionals. Come join the conversation!

Meanwhile, back home, this week’s featured CUs are implementing AI that staff and members can trust.

This week, I cover:

• How Suncoast CU doubled automated loan decisions

• InTouch CU serves more members with 40% fewer staff

• SunWest FCU rebounds from an AI flop

Read time: 9 minutes

Top Stories

The biggest news this week…

1) Suncoast CU doubled automated loan decisions

Loan analysts buried in routine applications can’t focus on the members who need them most.

At Suncoast Credit Union, the nation’s largest CDFI with 1.3M members and $19.2B in assets, that bottleneck was real. Before Zest AI, staff were manually deciding on the majority of incoming loan applications. Only 30% of decisions were automated, leaving analysts stretched across 78 branches.

Five years ago, Suncoast engaged Zest AI to fix that. The results were significant. Automated decisions jumped from 30% to 60%, nearly doubling the share of applications decided without staff intervention. That shift unlocked 27,000 hours of staff time annually. It also made centralized underwriting possible across all 78 branches, creating consistency and freeing loan analysts for complex decisions that actually require human judgment.

The member impact was just as clear. Suncoast now consistently holds a 90% Net Promoter Score on consumer lending, one of the highest scores across the entire Credit Union. Joanna Bradley, Vice President of Consumer Loan Delivery, described a member who came in after a total vehicle loss, anxious about approval. With Zest AI in place, the member advocate delivered an instant yes and focused entirely on the member. “The member told us they felt like we were their partner,” Bradley said.

Suncoast is now expanding Zest AI into fraud detection and, through a new integration with Clutch, pre-qualifying members for loans before they even apply, so they can apply with confidence. (link)

2) InTouch CU serves more members with 40% fewer staff

What if you could serve more members than ever while cutting your headcount nearly in half?

Kent Lugrand, President and CEO of InTouch Credit Union, says that’s what leveraging new tech and AI allowed them to do. Five years ago, InTouch had 240 employees across 11 branches. Today it runs on 140, while serving more of its 70,000 members than before.

Lugrand calls himself an AI “tweener.” He knew opening the door too wide too fast was risky, describing AI internally as a Pandora’s box he didn’t want to crack without a plan. So InTouch moved deliberately. On the front office side, chatbots now handle routine member questions. In the back office, a partnership with Zest AI pushes lending decisions beyond the traditional four to six data points, forecasting member financial challenges and opportunities before they surface. Tasks that once consumed hours now clear in seconds, freeing staff for the relationship work no algorithm can replicate.

When employees raised concerns, Lugrand’s answer was never no. Instead, leadership brought staff into the AI conversation early, letting them shape how tools get used and where their human judgment still matters most. (link)

3) SunWest FCU rebounds from an AI flop

Imagine this: Your AI agent just went live… and members are absolutely repulsed.

That’s pretty much what happened to SunWest Federal Credit Union when it launched its AI assistant Sonny. Members pushed back hard because they wanted a real person, not a bot. Losing that trust with a relationship-first membership was a real risk.

Instead of defending the rollout, VP and Chief Experience Officer Katie DeFeo pulled Sonny offline. The team collected direct feedback from unhappy members, asking them to detail every complaint. SunWest then sent emails and texts telling members Sonny was “going back to training” because she didn’t meet their needs.

In a smart move, they brought those same unhappy members back to test the rebuilt Sonny before re-launching. When Sonny relaunched, SunWest framed it as: “We used your voice to make her better.” Now, if a member calls in and says Sonny made a mistake, they can trust SunWest is dedicated to listening and making things right. (link)

Tips & Use Cases

Learn to apply AI…

BCU’s Chief Digital Officer built an AI skilling program: Baxter Credit Union launched a cross-functional AI committee 18 months ago, with a tiered skilling program that advances employees from AI Cadet to AI Wizard. The CU has since deployed AI for internal summarization, presentations, and employee efficiency, and has built some member-facing tools, with more to come. (link)

Seattle Credit Union pilots AI underwriting and staff knowledge tool: The Credit Union is testing a Copilot-style tool that puts internal policies at staff fingertips and exploring AI underwriting to expand loan access. CFO Michael Cruz advises staff skeptical of AI to treat it like a calculator: something that augments your work, not replaces it. (link)

Sundeep Kapur deploys AI across four Credit Unions at once: The technology educator is running AI chatbots, call monitoring, and lending tools across four Credit Unions. His goal: cut the 25-minute account opening process down so staff spend less time on data entry and more time building member relationships. (link)

Arizona Financial tests generative AI for staff operations manual: SVP of R&D Eric Givens is piloting a ChatGPT-style tool that lets call center staff ask plain-language questions to pull up policy and procedure answers instantly. Givens says the first use case for generative AI at most Credit Unions is internal knowledge access, and cautions staff not to trust AI answers 100% or input sensitive data. (link)

PrimeWay FCU cautiously locks down AI access behind approval: To prevent member data leaks, CIO Bob Morgan requires employees to get senior leader sponsorship and his personal sign-off before accessing any AI tools, with the firewall blocking unauthorized use entirely. The FCU is rolling out an Eltropy AI contact center solution and meets monthly as an AI committee to plan next steps. (link)

CUNA Strategic Services urges Credit Unions to start AI with a use case: President Barb Lowman says the biggest mistake Credit Unions make is jumping into AI out of FOMO without a clear problem to solve first. She sees back-office automation and after-hours member self-service as the strongest starting points to free staff for higher-value engagement. (link)

Behavioral agent automation platforms offer Credit Unions a third AI path: Rather than buying off-the-shelf tools or building custom agents, a new model called behavioral agent automation platforms (BAAPs) observes how employees actually work and builds automations around those patterns. Liminal CEO Steven Walchek says early deployments show 15 to 20 hours of time savings per week per employee. (link)

Bland deploys voice AI for financial institutions in under 30 days: The platform handles fully phone, SMS, and chat interactions for banks and Credit Unions, learning each caller’s conversational rhythm to adjust response timing automatically. CEO Isaiah Granite says 1 in 4 Americans has already talked to Bland’s AI, and institutions report longer calls, faster resolutions, and higher member retention. (link)

5 cybersecurity threats Credit Unions must prepare for in 2026: The biggest risks include employees pasting member data into public AI tools, vendor security gaps, unsecured API connections, ransomware with dual extortion, and “harvest now, decrypt later” attacks where criminals steal encrypted data today to crack it with future quantum computers. (link)

Agentic AI purchases are creating a new category of disputes: When AI agents execute purchases autonomously, traditional proof points like authentication checks and delivery confirmation no longer establish intent. Credit Unions should prepare now by tracking what members authorize their agents to do and building evidence trails before dispute volumes climb. (link)

Deutsche Bank’s AI predicts finance jobs face heavy disruption: The bank’s proprietary AI tool dbLumina analyzed its own impact and flagged wealth management, algorithmic trading, fraud detection, and customer service as the most vulnerable finance roles. The global robo-advisory market is projected to grow from $7.39 billion in 2023 to $72 billion by 2032. (link)

Feedzai finds over 50% of fraud now involves AI: With 92% of financial institutions already reporting criminal use of generative AI, a new “Know Your Agent” framework shifts fraud prevention from blocking automation to monitoring how authorized agents behave over time. Credit Unions whose fraud controls assume human initiation will develop blind spots as AI agents gain authority to move member funds. (link)

Harris Poll finds members want AI to inform, not decide: A survey of 2,079 U.S. adults found 68% are open to AI in banking, but comfort varies by use case: answering basic questions (37%), fraud alerts (36%), and explaining transactions (30%) score highest, while suggesting next steps (25%) and submitting payments on their behalf (19%) score lowest. (link)

BofA’s AI struggles show banks underestimate the structure required: Leaked emails reveal Bank of America employees say they were handed a Formula 1 race car but given local car mechanics to operate it. Research shows underwriters need to process roughly 20 loans before developing genuine AI proficiency. (link)

70% of bank CEOs now personally lead AI strategy: A BCG survey found bank CEOs spend nearly seven hours a week expanding their AI knowledge, with 54% saying their job stability depends on getting AI right. (link)

AI-driven underwriting tops Credit Union mortgage tech priorities for 2026: A National Mortgage News survey of 150 mortgage professionals found 57% expect AI-driven underwriting to change how the industry works this year, with real-time income verification (51%) and fraud detection (49%) close behind. (link)

TD Bank targets $1B in annual AI value: SVP Ted Paris says every customer-facing AI interaction keeps a human staff member in the loop, while purpose-built guardrails prevent queries outside a model’s intended scope. (link)

U.S. Treasury releases AI governance framework adapted for financial institutions: The first two resources include an AI lexicon and a customized risk management framework with a maturity questionnaire and risk-to-controls mapping matrix. Four more are coming, with small and mid-sized institutions explicitly named as the target audience. (link)

First Abu Dhabi Bank deploys 30+ agentic AI use cases enterprise-wide: The bank has embedded AI agents across trade, payments, compliance, and client operations, with 90% of structured data now integrated into an agentic AI layer. FAB’s model centers on staff upskilling and governance infrastructure before scaling, not the other way around. (link)

Vivox AI deploys KYB compliance agents that self-improve in two weeks: TransferMate rolled out Vivox AI’s Know Your Business agents globally, with the system’s quality approval rate jumping from 60% to 80% in the first two weeks through human-in-the-loop learning. The platform analyzes up to 100 corporate documents per case and screens across 100+ countries. (link)

b1BANK deploys Covecta’s agentic AI across loan and deposit operations: The platform embeds domain-specific agents directly into existing workflows, delivering policy-aligned assessments with full audit trails in eight weeks and no system migration. UK clients report 50% productivity gains. (link)

J.D. Power finds consumers turning to AI for financial advice: A survey of 4,000 consumers found 51% now use AI tools like ChatGPT and Gemini for financial guidance, yet only 30% trust AI-generated advice. (link)

OpenClaw autonomy raises new cybersecurity risks for financial institutions: Security researchers found 12% of OpenClaw’s third-party “skills” were malicious and warned its agentic autonomy can execute hidden prompt injections or data exfiltration without clear human intent. Unsanctioned AI agents with employee-level access create shadow IT risks that traditional endpoint and network controls struggle to detect. (link)

5 post-deployment processes Credit Unions need to keep AI from drifting: A living model inventory, documented decision rights, periodic red-team testing, an expanded incident response plan, and a value scoreboard with both ROI and risk metrics are the minimum for defensible governance. (link)

Ascend FCU outlines adaptive fraud strategy for digital banking: CIO Rik Reitmaier emphasizes embedding real-time monitoring, alerts, and verification tools directly into mobile banking while pairing member education with cross-team coordination. The approach focuses on stopping emerging AI-driven scams quickly without adding friction to legitimate transactions. (link)

Funding Spotlight

Where the money is flowing for innovation…

Nvidia finalizes $30B investment in OpenAI as part of a $100B+ funding round: The deal replaces an earlier chip supply commitment and signals OpenAI is scaling infrastructure at a level that requires chipmaker-scale capital. (link)

Jump raises $80M Series B to expand its AI operating system for financial advisors: The platform already serves 27,000 advisors, adding 2,000 per month, and automates meeting prep, note-taking, and CRM updates. (link)

Sherpas raises $3.2M seed round to automate financial planning workflows: Led by the family office of Mariner Wealth Advisors founder Marty Bicknell, the platform generates structured, explainable advisory outputs in minutes instead of days after live enterprise testing under compliance supervision. (link)

Stacks raises $23M Series A to automate reconciliations, journal entries, and month-end close for finance teams: The platform claims 100,000+ hours saved annually across 30 enterprise customers using a dedicated financial data layer before deploying AI agents. (link)

Avantos raises $25M Series A to unify client onboarding and servicing across wealth, insurance, retirement, and banking: Its knowledge graph gives AI agents and human teams a shared source of truth across fragmented legacy systems. (link)

Cogent Security raises $42M Series A for AI vulnerability response: The round will help deploy autonomous agents that investigate CVEs, identify system owners, generate remediation steps, and track fixes end-to-end. Clients report cutting vulnerability exposure windows by 97% through traceable agent actions and approval gates. (link)

Zenyard raises pre-seed funding to build a purpose-built AI agent for software reverse engineering: The platform integrates directly into existing decompilers, analyzes entire binaries, and delivers explainable outputs — addressing one of cybersecurity’s most manual workflows already deployed across leading threat intelligence teams. (link)

Basis raises $100M Series B for AI accounting agents: Accel led the round at a $1.15B valuation to help Basis deploy long-horizon agents across tax, audit, and client services, and now supports roughly 30% of the top 25 accounting firms. (link)

Keeping up with Tech

The latest in fintech and tools…

Filene + Vertice AI + Vizo Financial launch CUltivate AI model: The Credit Union-specific model is trained on industry data and overseen by an advisory committee to support regulatory guidance and branch knowledge management. The CUSO deploys within hours without integration work, enabling faster AI adoption across Credit Unions. (link)

Interface.ai launches Smart Collections for Credit Unions: The agentic AI tool automates early-stage delinquency outreach with coordinated messaging and compliance-by-design controls. It helps community financial institutions engage 30-59 day past-due accounts sooner, reducing recovery costs while maintaining member trust. (link)

Anthropic acquires Vercept to improve Claude’s computer use: The deal folds Vercept’s computer vision and interaction technology into Claude, boosting its OSWorld benchmark score from under 15% in 2024 to 72.5% today. Stronger software navigation capabilities could help financial teams automate spreadsheet tasks, form entry, and multi-step workflows inside existing applications. (link)

Vouched launches Agent Checkpoint to govern AI logins: Between 0.5% and 16% of website traffic across Vouched’s customers now comes from AI agents using human credentials. The Know Your Agent suite applies OAuth authentication, delegated permissions, legal authorization controls, and audit trails to help financial institutions detect and manage agent-driven access. (link)

Basware launches governed AI agents for invoice processing: An AP Business Agent provides real-time invoice guidance while an AP Data Agent answers natural language queries, with all actions controlled through a central policy engine. Upcoming agents will automatically contact suppliers to resolve disputes, offering a governed entry point into measurable AP automation. (link)

Rakuten Card launches AI transaction query agent: Available on Android and iOS, the agent lets cardholders query statement data in natural language to summarize monthly spending, filter transactions by date, and estimate category totals. (link)

Synechron + Cognition embed Devin for AI engineering: The partnership integrates Devin, an autonomous AI software engineer, into Synechron’s delivery model to accelerate system upgrades and migration projects for financial institutions. Early testing showed faster modernization, improved testing quality, and productivity gains within existing security and governance frameworks. (link)

Google launches Gemini 3.1 Pro with stronger reasoning: The model is rolling out across Gemini API, Vertex AI, Gemini Enterprise, NotebookLM, and the Gemini app, with Google reporting a 77.1% verified ARC-AGI-2 score. It supports data synthesis, complex problem-solving, and developer workflows, such as generating animated SVGs from text for enterprise use. (link)

Anthropic launches Claude Code Security for vulnerability detection: Built on Claude Opus 4.6, the system reasons through data flows and business logic to identify flaws that static analysis tools miss. It applies multi-stage self-verification, routes patches through human approval, and has surfaced 500+ previously undetected vulnerabilities in open-source production code. (link)

Mastercard builds Agent Suite for AI commerce: Launching in Q2 2026, the suite combines customizable AI agents with Mastercard’s payments infrastructure to power conversational shopping and product recommendations. It includes Agent Pay for AI-initiated transactions and partnerships with PayPal, OpenAI, Google, and Cloudflare to establish safety and transaction standards. (link)

In Other News

Related news you can learn from…

• Microsoft says no single tool can stop deepfakes (link)

• JPMorgan is spending $20 billion on tech in 2026 (link)

• Anthropic says Chinese labs ran 16M+ fake Claude exchanges to clone its AI (link)

• Fed Gov. Michael Barr says AI is reshaping workforces now, with bigger disruption still ahead (link)

Community Corner

Memes and visuals…

@shubhswarcry

Shubh on Instagram: "AI THIS, AI THAT🤷‍♂️

#pov #relatable #mi…

Thanks for reading!

Until next week,

— Credit Union AI Guy

Enjoying this newsletter? Forward it to a colleague who might appreciate practical AI insights.

Have a question or want to share your own AI experiment? Reply to this email or connect with us on LinkedIn. We’re building a community of curious Credit Union professionals. Come join the conversation!

The only question left is whether you have a plan like this week’s featured Credit Unions.

Today, I cover:

• Natco Credit Union audited $42M in loans in a single day

• Grow Financial’s SVP starts AI adoption with the foundation

• Financial Plus CEO says stop worrying and lean into AI

Read time: 9 minutes

Top Stories

The biggest news this week…

1) Natco Credit Union audited $42M in loans in a single day

Validating whether your underwriters are actually following guidelines used to be nearly impossible. Without a way to audit loan decisions at scale, compliance gaps could go undetected for months. And for a CDFI like Natco Credit Union, where delinquency and charge-off rates are under constant scrutiny, that blind spot carries real risk.

Natco, a $152M Credit Union based in Indiana, partnered with Zest AI and implemented LuLu, a generative AI lending intelligence tool. Loan Service Manager Stephanie Harrison led the charge after watching a product demo and immediately seeing ways it could replace work she was doing manually. She worked directly with the Zest AI team to build a custom compliance report that evaluated loans against internal underwriting guidelines and mapped results back to individual underwriters. LuLu audited $42 million in loans in roughly one day. The result: 99.7% of all decisions were within guidelines — a lovely stat to share with the supervisory committee.

The team didn’t stop there. By analyzing 24 months of charge-off data, LuLu identified the characteristics most associated with default risk. Now, when a loan application carries multiple high-risk factors, staff can step in early with tailored support to help members avoid default. On the reporting side, what used to take CEO Cindy Duke hours of manual data pulls from the NCUA website now runs in seconds. That freed-up time helped the team identify home equity lending as a growth opportunity. Natco made it a priority in 2025 and grew that portfolio by 42%. (link)

2) Grow Financial’s SVP starts AI adoption with the foundation

Most Credit Unions want to move fast on AI. The ones that stumble usually skipped the foundation. Because when your 1) data isn’t clean, 2) your processes aren’t documented, and 3) your teams aren’t aligned across channels, layering AI on top just automates the mess.

Emily Nichols, SVP of Enterprise Operations at Grow Financial Federal Credit Union, has spent 25 years watching Credit Unions evolve. She built Grow’s analytics team in 2012, before most Credit Unions were even thinking about data infrastructure. That foundation is now shaping how Grow Financial approaches AI. In 2026, the Credit Union plans to replace its contact center platform with an AI-driven solution. But Nichols isn’t treating it as a technology swap. She’s treating it as an experience overhaul that touches the contact center, digital, and branch channels simultaneously.

Her framework for getting there: start with a proof of concept on a specific use case, validate it, then scale. Don’t take the “rip off the band-aid” approach. Run the crawl-walk journey first. She’s applying the same thinking to account opening to deliver a consistent experience, whether a member calls, walks in, or goes online. (link)

3) Financial Plus CEO says stop worrying and lean into AI

Your employees are already using AI. The question is whether you’re training them or ignoring it.

Brad Bergmooser, President and CEO of Financial Plus Credit Union in Flint, Michigan, found out the hard way. Before his team had a policy or strategy in place, employees were already using AI tools to write performance reviews. His response wasn’t to shut it down. It was to reframe the whole thing. “We shouldn’t be penalizing our employees for utilizing a large language model. We need to train them.” The output, he says, is only as good as the prompt. So that’s where Financial Plus is focusing first.

On the operations side, Bergmooser sees two immediate wins: routing routine contact center calls away from agents so staff can focus on complex member issues, and using AI to handle clear-cut auto loan decisions so officers can spend time on harder cases. For a Credit Union with a unionized frontline workforce, he’s careful to frame it the right way. “It’s not a reduction in workforce mechanism. It’s a tool that, as good employers, it’s our job to upskill our workforce to utilize.”

His bigger concern is what comes next. Agentic AI, he warns, won’t just answer questions. It will act. “By the time this interview is over, an agentic AI feature will have moved a money market because a competitor is offering a higher rate.” His advice to Credit Unions: collaborate, stay at the table, and stop using smaller budgets as an excuse to wait. (link)

Tips & Use Cases

Learn to apply AI…

Small Credit Unions have no excuse to skip AI adoption: Dr. Lamont Black of Wide Open Ventures says Credit Unions under $500M in assets can access tools like Microsoft Copilot or vendor-built platforms without an in-house tech team. The real barrier is board-level fear, not budget. Black recommends starting with a formal AI risk policy to create a safe sandbox that gets leadership comfortable enough to experiment. (link)

Fed Governor Barr warns AI will reshape rates, jobs, and risk models: Barr outlined three scenarios for Credit Unions: productivity gains, an automation-driven jobless boom, or a capital spending surge that shifts risk to the financial system. Most finance firms are still experimenting while the Fed keeps rates elevated as it monitors AI’s economic impact. (link)

68% of staff using AI at work are hiding it from management: Meanwhile, sensitive data appeared in over 4% of generative AI prompts in Q2 2025. Purpose-built tools like Agent IQ limit responses to approved internal sources and can be deployed in two weeks. (link)

Only 11% of businesses have seen ROI from AI pilots so far: Rival’s Eric Fulwiler says Credit Union marketers have shifted from “what’s my AI strategy?” to “we’ve tested it and we’re still waiting on results.” He warns that as AI agents increasingly handle search and purchasing on behalf of users, Credit Unions need to optimize their content for LLMs, not just people. (link)

How Vertice AI helps Credit Unions run lookalike member targeting: The platform pulls existing core data to model member behaviors across hundreds of attributes, then scores prospects from Experian to build targeted acquisition lists. Education Credit Union used it to narrow outreach from tens of thousands of prospects to a focused few thousand, cutting the $500-per-member acquisition cost significantly. (link)

Uptiq CEO says AI should flip the 75/25 ratio of internal work to member time: Uptiq’s agents work across the core, LOS, CRM, and documents simultaneously, handling tasks like loan intake and policy compliance without human involvement. Institutions can see working agents in days, with full core integration adding a few months. (link)

30% of Credit Unions use AI but most lack formal governance: Since ChatGPT’s launch, AI has expanded from back-office scoring to drafting delinquency letters, marketing content, and self-improving chatbots. That shift creates legal, compliance, and ethical risks that boards and executive teams now need to formally address. (link)

Diversified Members Credit Union selects Scienaptic AI to modernize credit underwriting: The Michigan-based Credit Union will use the platform to evaluate members beyond surface-level credit data, aiming for faster and more inclusive lending decisions. (link)

AI-driven fraud hit a record 3.31M cases in the UK in 2024: Synthetic identity attacks drove a 12% year-over-year increase, with over 35% of UK financial institutions reporting AI-related fraud in Q1 2025. Geolocation data, name-to-address matching, and contact data validation can close the gaps fraudsters exploit. (link)

AI is now the top strategic priority for Credit Unions in 2026: CSI’s annual executive survey found AI ranked first across institutions of all sizes, with cybersecurity, digital payments, and core modernization increasingly framed as AI enablers rather than standalone goals. The main obstacle is infrastructure with legacy cores and fragmented data. (link)

Only 1 in 3 Credit Union members feel understood by their institution: White Clay CEO Mac Thompson says most CUs measure satisfaction in ways that confirm what they want to hear, rather than what members actually experience. He argues big banks have a generational lead on AI because they train models on their own internal data, while Credit Unions slapping generic AI onto poor data infrastructure will see little return. (link)

Most banks can’t define their AI strategy because they can’t define their data strategy: Cornerstone Advisors’ Ron Shevlin says Credit Unions are stalling AI implementations by talking about “data” without specifying whether they mean customer, transactional, operational, or market data. His recommendation: hire a chief data and AI officer who is a change agent first, not a technical expert. (link)

Star One Federal Credit Union uses AI to train staff and redirect member calls: New CEO Minal Gupta is integrating AI across voice and digital channels to handle member requests without live agents, and using large language models to train non-technical staff on new processes. (link)

Only 43% of Credit Unions list AI as a top spending priority, trailing banks by 25 points: American Banker’s 2026 Predictions survey found national banks lead AI investment at 68%, followed by regional banks at 54% and community banks at 44%. Credit Unions ranked last despite facing the same technology disruption risks. (link)

NatWest saved 70,000 hours in one year by deploying AI across 60,000 employees: Automated call summaries, complaint responses, and AI coding tools now write 35% of the UK bank’s code, contributing to £100 million in freed investment capacity. In 2026, NatWest is rolling out an agentic financial assistant to 25,000 customers and real-time fraud resolution through natural language conversations. (link)

51% of consumers already use AI tools for financial questions: J.D. Power research shows savings strategies, credit scores, and investing are the top financial queries going to tools like ChatGPT, yet only 27% of bank and Credit Union customers say they currently receive advice from their institution. Virtual assistants close the gap, with users scoring 35 points higher in satisfaction than non-users. (link)

TD Bank’s AI survey finds 89% of Americans are comfortable with AI: TD’s Head of AI Ted Paris says consumers are confident and curious, but cautious about privacy. TD addresses this by keeping humans in the loop before any AI output reaches customers. TD also built a contact center knowledge tool that pulls answers from hundreds of policies in real time to give every agent the same consistent response. (link)

ABNB Federal Credit Union rolls out Eltropy AI voice assistant to eliminate member hold times: The CU consolidated 7 to 8 separate vendor solutions into Eltropy’s single platform over 2025, adding chat and texting before launching AI voice in December. The assistant, nicknamed “Digi” by staff, handles routine account inquiries so employees can focus on complex member requests. (link)

Goldman Sachs deploys Anthropic-powered AI agents in core finance operations: The firm spent six months embedding Anthropic engineers inside its tech teams to build agents handling transaction reconciliation, trade accounting, and client onboarding. It reflects a broader shift among large banks toward agentic AI in structured finance functions, with Credit Unions facing the same automation pressure from larger competitors pulling further ahead. (link)

Agent IQ’s CMO says AI should handle the transactional so staff can focus on the emotional: Matt Phipps argues Credit Unions are losing their relationship banking edge as members shift to digital, and the fix is not less AI but smarter deployment. Agent IQ’s Smart Assist tool lets staff search institution-approved policies in natural language, reducing the time spent hunting for answers so more time goes to the member. (link)

Credit Unions are leading banks on GenAI but data quality will determine who sees results: Cornerstone Advisor’s 2026 report finds 59% of Credit Unions have deployed GenAI vs. 49% of banks, only 8% of Credit Unions have no GenAI plans vs. 23% of banks, and 6 in 10 Credit Unions pursuing agentic AI are targeting contact centers first. (link)

California bank cuts credit memo prep time 63% using Uptiq’s AI lending platform: The unnamed CRE and C&I lender automated document intake, financial spreading, and covenant tracking across its full credit lifecycle. The result was a 47% reduction in manual document review and 36% faster financial data extraction, freeing underwriters to focus on risk analysis instead of data entry. (link)

Funding Spotlight

Where the money is flowing for innovation…

Anthropic raises $30B Series G to scale Claude across enterprise AI: GIC and Coatue led the round, valuing Anthropic at $380B, to fund the research, infrastructure, and product development behind Claude. Run-rate revenue has reached $14B, growing over 10x annually for three consecutive years. (link)

Uptiq secures $25M to bring production-ready AI to Credit Unions and banks: The round was led by Curql, with Uptiq’s platform delivering pre-packaged AI applications across lending, underwriting, and wealth management for 140 financial institutions. Funds will expand its Qore orchestration platform so teams can deploy financial AI in days rather than months. (link)

Bracket raises $7M to scale AI treasury platform for mid-market businesses: Macquarie Group and Blackfinch Ventures led the round to fund expansion into Europe and Australia, with Bracket’s platform centralizing bank accounts, automating FX workflows, and delivering real-time treasury intelligence without legacy system costs. The company grew revenue 600% YoY in 2025. (link)

Bretton AI raises $75M Series B to expand AI compliance agents across regulated financial institutions: Sapphire Ventures led the round, with Bretton AI’s agents handling KYC, AML, and sanctions investigations in minutes rather than days. Clients have saved over $10M in compliance headcount costs and eliminated 195,000 hours of manual work. (link)

Reco raises $30M Series B to secure AI tools inside enterprise SaaS environments: Zeev Ventures led the round, with Reco’s platform continuously monitoring SaaS environments to track AI apps, agent permissions, and data flows across tools like Salesforce, ChatGPT, and Copilot. The company grew 400% YoY in 2025 on an already expanded base. (link)

ZAST.AI raises $6M Pre-A to eliminate false positives in code vulnerability detection: Hillhouse Capital led the round, with ZAST.AI’s platform automatically generating and executing proof-of-concept exploits to confirm whether vulnerabilities are real before flagging them. In 2025, the platform identified hundreds of zero-day vulnerabilities, resulting in 119 CVE assignments across projects, including Microsoft Azure SDK and Apache Struts. (link)

Samaya AI secures undisclosed funding to scale AI agents for investment workflows: NVentures and Databricks Ventures backed the round to expand Samaya’s Agent Control Plane, a purpose-built architecture that lets financial institutions design, run, and govern AI agents across earnings analysis, scenario modeling, and real-time market decisions. The platform is already in production with 10,000+ professionals at one of the world’s largest banks. (link)

Keeping up with Tech

The latest in fintech and tools…

Commonwealth Credit Union and Zest AI launch CUSO to bring AI lending to small Credit Unions: CU Lending Collective gives smaller institutions access to a custom AI credit scoring model covering auto loans, personal loans, and credit cards, with built-in fair lending compliance and hands-on operational support. Commonwealth CU exceeded 14% loan growth in 2025 after deploying Zest AI, while maintaining strong delinquency and charge-off performance. (link)

Multimodal joins Filene’s 2026 FiLab to help Credit Unions test agentic AI in lending and member services: The program runs January through July 2026, delivering sandboxed proofs of concept in account opening, consumer lending, and member assistance workflows without requiring core system integration. Participating Credit Unions will receive vendor-agnostic implementation roadmaps and ROI modeling frameworks. (link)

Anthropic releases Claude Sonnet 4.6 with 1M token context window and major coding upgrades: The model is now the default on claude.ai Free and Pro plans, with users preferring it over the previous frontier model 59% of the time in Claude Code testing. Claude in Excel now connects directly to S&P Global, PitchBook, Moody’s, and FactSet via MCP, pulling financial data without leaving the spreadsheet. (link)

Anthropic and Infosys partner to build AI agents for financial services: The collaboration integrates Claude models and Claude Code with Infosys Topaz to help regulated industries automate compliance reporting, risk detection, and legacy system modernization. Financial services use cases include faster risk assessment, automated compliance reporting, and personalized client interactions. (link)

OpenAI releases GABRIEL to turn unstructured text and images into quantitative data: The open-source Python toolkit uses GPT to apply researcher-defined measurements consistently across thousands of documents, returning a score for each one. It requires minimal technical background and is designed for economists, social scientists, and data scientists working with qualitative data at scale. (link)

OpenAI launches Lockdown Mode and Elevated Risk labels in ChatGPT to guard against prompt injection attacks: Lockdown Mode restricts how ChatGPT interacts with external systems, limiting web browsing to cached content and disabling features that could expose sensitive data. It is available now for ChatGPT Enterprise, Edu, Healthcare, and Teachers plans, with consumer availability planned for coming months. (link)

Cemex deploys AI financial agent LUCA Bot to give executives instant access to internal data: Built on Microsoft Azure OpenAI, the tool processes 120+ KPIs across regions, countries, and plants, answering natural language queries that previously required hours of searching through reports. The agent handles 400-500 queries per month with 92% accuracy on data retrieval. (link)

Provenir launches Decision Intelligence platform with agentic AI for credit risk decisioning: The platform connects data, models, and decisioning in one system, cutting strategy testing time from months to weeks while providing real-time, personalized risk decisions. Financial institutions can now access OpenAI and Anthropic models through pre-integrated APIs or private AWS Bedrock instances directly within Provenir’s workflows. (link)

OpenAI releases GPT-5.3-Codex-Spark for real-time coding with 1,000+ tokens per second: Built on Cerebras’ low-latency hardware, the model delivers near-instant responses for interactive coding tasks like targeted edits and logic refinements. It is rolling out now as a research preview for ChatGPT Pro users in the Codex app, CLI, and VS Code extension. (link)

In Other News

Related news you can learn from…

• AI should not shrink the web’s freedom to learn (link)

• Salesforce manager oversees AI agents like human employees (link)

• OpenAI team ships a real product with zero human-written code (link)

• FinovateEurope 2026 spotlights AI urgency and quantum risk for banks (link)

• Vizo Financial spotlights AI-driven risk at its 2026 Risk Management Conference (link)

Community Corner

Memes and visuals…

@xtract.ai

Xtract.ai | Hows the cope? Bud | Instagram

Thanks for reading!

Until next week,

— Credit Union AI Guy

Enjoying this newsletter? Forward it to a colleague who might appreciate practical AI insights.

Have a question or want to share your own AI experiment? Reply to this email or connect with us on LinkedIn. We’re building a community of curious Credit Union professionals. Come join the conversation!

The winners in 2026 will be the Credit Unions that deepen relationships, earn primary financial institution status, and use AI to move at fintech speed without losing trust.

Today, I cover:

• Navy Federal scales AI to 35 use cases without layoffs

• The 2026 AI game plan from four Credit Union execs

• Golden 1’s CMO blends AI speed with authenticity

Read time: 7 minutes

Top Stories

The biggest news this week…

1) Navy Federal scales AI to 35 use cases without layoffs

At Money20/20 USA 2025, Navy Federal Credit Union CEO Dietrich Kuhlmann made it clear: they’re “all in” on AI. The 15M-member institution currently has about 35 AI use cases either live or actively underway, and he says they’re already seeing returns.

But Kuhlmann is intentional about the framing. At Navy Federal, they prefer the term “augmented intelligence.” The goal isn’t to replace people. It’s to make employees more effective in serving members. In his view, AI is a workforce amplifier, not a headcount reduction strategy.

That distinction is especially important given Navy Federal’s scale and culture. The organization employs roughly 25,000 staff and, in its 92-year history, has never executed a layoff. Instead, when demand shifts, they retrain and redeploy.

Now, AI and real-time banking represent the next major evolution. Kuhlmann said that between the move to real-time banking and augmented intelligence, “I don’t think a single process or procedure we do today will be done the same way.” For him, the biggest risk is workforce readiness. His advice on adoption is to treat AI as a workforce transformation effort. Align leadership on a clear vision, invest heavily in training, and communicate constantly. In his words, you have to “talk about it a lot” and back it up by showing employees you have their interests at heart.

This AI push didn’t happen overnight. Navy Federal has been investing in data infrastructure and data quality for more than five years. In November 2024, they rolled out a single omni-channel backbone across branch, contact center, online, and mobile, replacing four separate systems with one unified platform. With that foundation in place, their top tech priorities now include transitioning to a new core system to enable real-time banking and moving their entire banking platform to the cloud. (link)

2) The 2026 AI game plan from four Credit Union execs

In a special roundtable edition of The Outlier Podcast, four executives from across the Credit Union space compare notes on their 2026 priorities:

At Langley Federal Credit Union, COO Fred Haggerman is personally driving experimentation. He’s testing tools like Gemini and ChatGPT, plus workflow platforms like n8n and Zapier, and encouraging teams to do the same. His view is simple: the people who learn to use these tools best will win, and leaders must reduce fear so teams can find member-focused use cases.

At Addition Financial, CLO Miriam Mitchell is applying AI directly inside lending. The Credit Union is in its fourth year using Zest for underwriting, and she says it delivers efficiency and more predictable risk decisions than manual processes. They have also layered AI into fraud detection on loan applications and are rolling out Copilot-style tools to help staff complete work in minutes instead of hours.

At Citadel Credit Union, CFO Anand Solanki sees AI in two lanes. First, he found about 30 existing systems already using AI across fraud, HR, contracts, and predictive modeling. Second, he’s pushing internal copilots and automation, including a plan to automate most indirect auto loan processing, which is currently manual.

At Affinity Plus Credit Union, CIO Radha Chavali is narrowing the focus. After running seven AI pilots, the team plans to scale three, including a lending pre-approval use case that improved efficiency and conversion. She says the conversation has moved from hype to realism, with more attention on risk, security, and measurable outcomes. (link)

3) Golden 1’s CMO blends AI speed with authenticity

When Golden 1 Credit Union needed new creative for a campaign rollout, Michael Daum didn’t turn to stock footage or synthetic visuals. He traveled across California with a film crew to capture real communities and stories.

Daum, SVP and CMOr at Golden 1 Credit Union, says AI has a growing role in marketing, but it has limits. The team uses AI to condense timelines and simplify production steps. But the core creative decisions still remain human and rooted in the brand.

He’s also pushing deeper collaboration. Ahead of his session at The Financial Brand Forum, Daum planned a working session with Golden 1’s creative and PR agencies. Each group is using AI differently, so he wants to share lessons rather than relying on siloed experimentation.

On the personalization front, Golden 1 is combining martech tools with machine learning to move beyond time-based onboarding. Instead of waiting three or six months to cross-sell, the Credit Union is building real-time offers based on behavior and demographics. Meanwhile, the refreshed website and mobile app will adjust content, imagery, and financial wellness resources to match what members are actively exploring. (link)

Tips & Use Cases

Learn to apply AI…

US financial institutions outpace global peers in AI adoption: A Finastra survey of 1,500 FI leaders found 93% of U.S. respondents are excited about rapid tech change vs 86% globally, and 65% are actively deploying AI vs 61% worldwide. Another 42% plan to increase AI investment by more than 50% in 2026. U.S. use cases lead in data analysis (47%), document intelligence (41%), and credit decisioning (35%), but 50% cite compliance and 50% cite talent gaps as key barriers. (link)

Gen Z demands embedded payments and AI guidance: Only 12% of Gen Z view a community or regional bank as their primary institution, as PayPal, Venmo, and Zelle are where daily money movement occurs. Credit Union teams can respond by using AI to deliver “so what” insights from transaction data and proactive next steps. (link)

Benjamin Conant of Alkami warns against “vendor stacking” digital banking: Map account opening through first login, onboarding, and servicing as one flow. Prioritize integrations that remove duplicate data entry and separate logins, and use post-open activation checklists to reduce abandonment and grow deposits. (link)

Cornerstone League + GoWest Credit Union Association adopt Zest AI’s LuLu lending intelligence platform: Leaders say the GenAI tool delivers real-time lending and economic insights that strengthen advocacy, policy work, and member education, giving hundreds of Credit Unions access to industry benchmarking and intelligence they could not produce on their own. (link)

ANZ deploys agentic AI in CRM to reduce banker workload: ANZ replaced legacy systems with a unified Salesforce CRM powered by Agentforce, consolidating data from 20 platforms and automating tasks like real-time account summaries and intelligent search. (link)

First Financial of Maryland FCU selects Scienaptic AI for credit decisioning: The $1.3B Credit Union will use advanced analytics to improve lending consistency, speed decisions, and incorporate more relevant data, helping responsibly expand member access to credit while maintaining human oversight and regulatory compliance. (link)

Payments leaders call for explainable AI in fraud and transaction decisions: As AI models power real-time declines and approvals, financial institutions need audit trails and clear decision logic to defend disputes, meet compliance demands, and preserve member trust. Accuracy alone is not enough in high-stakes payment systems. (link)

How AI can speed up cash flow forecasting inside Excel: Finance teams can now use tools like Claude AI to generate and update 13-week rolling cash flow forecasts directly in Excel, reducing manual errors and last-minute model rebuilds before board meetings. (link)

CommBank launches AI Attitudes Barometer with Melbourne Business School: Early polling of 5,109 Australians found 69% would be more likely to use a bank whose staff are trained in safe and responsible AI, prompting the bank to publish its safeguards and fraud use cases to strengthen public trust as adoption grows. (link)

Bank of America scales AI with $4B annual tech investment: The bank invests roughly $4 billion annually in tech, embedding AI across digital channels serving 59 million clients, with Erica reaching 50 million users and surpassing 3 billion interactions. (link)

Credit Unions deploy agentic AI for fraud disputes but rarely share intelligence: Some Credit Unions report agentic AI resolves 50% to 60% of digital disputes and cuts fraud losses by 20% to 30%. But experts warn that institutions still fight fraud in silos rather than sharing anonymized behavioral signals that could help stop emerging threats faster. (link)

PYMNTS report finds AI becomes the first stop for over 60% of consumers: The study also shows more than one-third of Gen Z now begin tasks in AI instead of search, and 42% of primary AI users report using search engines less. Credit Unions risk losing early discovery if they’re not visible in AI-driven journeys. (link)

AOBA 2026 takeaways on deposits, fraud, and vendor sprawl: Panelists said deposit retention is now mission-critical as $2T has flowed from banks and Credit Unions to fintechs, while AI-driven fraud is rising and requires “AI vs AI” defenses. They also warned that vendor sprawl creates data headaches, pushing teams to consolidate platforms so bankers can solve problems faster. (link)

AI-generated receipts and ID documents raise a new fraud risk for banks: A Klaros Group partner showed Microsoft Copilot can create realistic receipts, bank statements, and utility bills with a simple prompt, making fake documents harder to spot in account opening and lending. Banks are responding with AI document checks for metadata and formatting issues, plus human review. (link)

AI can hollow out bank work, leaving only the hardest cases for humans: If AI removes routine work, the remaining job becomes exceptions, judgment calls, and emotional labor, which raises burnout risk and makes traditional “productivity” metrics misleading. Credit Unions can prepare by redefining roles, retraining staff for escalations, and building clear human handoff paths. (link)

Small AI efficiency wins can hide bigger risks: Banks brag about “6% operational uplift” without defining the real metrics like rework, errors, unit costs, or risk exposure. Leaders must test how AI could reshape their business model and train teams for edge cases, not just optimize workflows. (link)

Funding Spotlight

Where the money is flowing for innovation…

Veritus raises $10.1M seed to deploy voice-first AI agents across consumer lending: Veritus is scaling omnichannel, PCI and SOC 2-compliant AI agents that integrate into lenders’ LMS systems to run application-funnel outreach, early-stage delinquency engagement, KYC verification, and live payment negotiations using a dual-agent architecture. (link)

ORION secures $32M funding to replace policy-based DLP with autonomous AI detection: ORION is scaling proprietary LLMs and specialised AI agents that analyse content sensitivity, user intent, data lineage, and environmental context in real time to prevent data exfiltration and reduce false positives across large enterprises. (link)

EnFi raises $15M Series A to deploy AI agents across commercial lending: EnFi is scaling AI “credit workforce” agents that automate workflows from deal screening to portfolio monitoring, going live in 60-90 days to expand lender capacity while strengthening risk oversight. (link)

Airrived raises $6.1M to deploy agentic AI across security and IT: Its Agentic OS embeds deep-reasoning AI agents into security, compliance, identity, and IT workflows, replacing fragmented automation tools with a unified intelligence layer. (link)

Keeping up with Tech

The latest in fintech and tools…

9Squid launches AI securitization modeling platform for Credit Unions: The platform lets you simulate securitization outcomes for personal loans, auto loans, and HELOCs before executing, so you can see impacts on cash flow, capital, earnings, and risk without the usual cost and complexity barriers. (link)

OpenAI unveils Frontier platform to manage enterprise AI agents: The new system gives agents shared business context, permissions, and feedback loops so they can operate across real workflows. Early adopters include HP, Oracle, State Farm, and Uber. (link)

OpenAI debuts GPT-5.3-Codex with self-improving agent capabilities: The model runs about 25% faster while handling long, multi-step coding and research tasks, and was even used internally to debug its own training and deployments. (link)

Anthropic upgrades Claude Opus 4.6 with 1M-token context and agent teams: The update strengthens long-running coding and planning tasks, adds parallel subagents in Claude Code, and introduces deeper Excel and PowerPoint integrations so AI can work directly inside enterprise tools with greater reliability. (link)

OpenAI pilots trusted access framework to steer advanced AI toward cyber defense: GPT-5.3-Codex can autonomously handle complex tasks like vulnerability discovery and remediation, with identity verification, enterprise controls, monitoring, and a $10M cybersecurity grant program. (link)

OpenAI begins testing clearly labeled ads in ChatGPT Free tier: Ads will appear for logged-in adult users on Free and Go plans while Plus and higher tiers remain ad-free. OpenAI claims ads won’t influence answers or expose conversations, and users can control personalization or opt out with reduced free usage. (link)

Square rolls out free AI assistant inside its business dashboard: The built-in conversational tool lets small businesses ask natural-language questions about sales, customers, and labor data, raising expectations for faster, AI-driven insights. (link)

Affirm deploys BoostAI to lift merchant conversion rates: The AI tool enables real-time A/B testing of promotional financing offers, with early data showing 5% to 15% increases in gross merchandise volume as 0% options are optimized for conversion. (link)

Klarna joins Google’s commerce protocol for agentic AI shopping: The Sweden-based BNPL lender will use Google’s Universal Commerce Protocol to let AI agents complete purchases through AI Mode and Gemini. (link)

Cleo re-enters the UK with its AI-powered money coaching app: The conversational chatbot delivers personalized spending, budgeting, and saving insights using interactive features like Roast Mode and Hype Mode to drive engagement. (link)

In Other News

Related news you can learn from…

• AI fears trigger selloff in software and data stocks (link)

• What teams learn when building real-world ChatGPT apps (link)

• AI is not conscious, but leadership decisions still carry risk (link)

• The Fed says AI could keep interest rates higher for longer (link)

• Sam Altman outlines a bold and controversial future for OpenAI (link)

• Scaling AI is a leadership and trust challenge, not a technical one (link)

• Why the Fed’s economic playbook could fail in an AI-driven economy (link)

Community Corner

Memes and visuals…

@weworkremotelycom

We Work Remotely on Instagram: "Modern problems require modern …

Thanks for reading!

Until next week,

— Credit Union AI Guy

Enjoying this newsletter? Forward it to a colleague who might appreciate practical AI insights.

Have a question or want to share your own AI experiment? Reply to this email or connect with us on LinkedIn. We’re building a community of curious Credit Union professionals. Come join the conversation!

Today, I cover:

• Volt Credit Union uses AI to fix internal knowledge chaos

• Mountain America Credit Union builds an AI-ready workforce through HR

• How to deploy AI agents safely without risking member trust

Read time: 9 minutes

Top Stories

The biggest news this week…

1) Volt Credit Union uses AI to fix internal knowledge chaos

At Volt Credit Union, CEO Chris Moss found a call center employee using a 3-inch binder of printed policies that was already outdated. That’s a trap with many Credit Unions. Staff create their own shortcuts when finding the right documentation takes too long. So, they end up saving “final” files to desktops to reuse, even when the material is outdated.

Moss knew the goal was to speed up answers without letting member data or internal policies leak.

The biggest worry was crossmingling between the public widget and internal knowledge. They needed clear separation. So Volt started internal-only, uploaded a small trickle of documents, tested answers, then expanded. They manually chose what went in, kept it a closed loop, and avoided connecting AI to the core or a shared drive. They also segmented content by department to reduce wrong-process mistakes and speed up retrieval.

Results came as speed, exam readiness, and better insight. Most of their questions are answered within five seconds. During an exam, their IT director asked their AI knowledge management tool, “Ask Moxy,” and had an answer in five seconds to send to the examiner. The cherry on top: Weekly question summaries now show what staff and members ask most, flag training gaps, and reveal missing website content to improve self-serve. (link)

2) Mountain America Credit Union builds an AI-ready workforce through HR

Mountain America Credit Union employs 3,700 people across five states, with two-thirds serving members on the front line. CHRO Trent Savage said growth from $8B to $22B in eight years forced a rethink of how work gets done. That pressure is increasing as retirements accelerate and the labor pool tightens.

Savage frames AI as the lever to absorb that strain through productivity. “There are huge opportunities with productivity savings,” he said, but only if AI is used intentionally. He warned many organizations are still in the “dabble phase,” which creates fear when leaders stay vague. Employees worry that AI will replace their jobs, so HR must overcommunicate the strategy and its impact before rumors spread.

His core tactic is making HR a full owner of the AI strategy. Savage said if the business is building AI plans, HR needs to be in those conversations. He views AI as a sociotechnical shift that requires balancing technology, culture, and trust, especially as agentic AI expands. On the workforce side, the time for upskilling is now. AI should automate transactional work and shift people toward problem-solving, collaboration, and leveraging technology.

The most concrete move is skills intelligence. Mountain America is building a skills ontology and using AI to benchmark internal roles against the external market, because skills data is fluid and constantly changing. The goal is transparency: showing employees which skills they are building, which roles fit them, and which skills they need next, all tied directly to learning. (link)

3) How to deploy AI agents safely without risking member trust

If an AI agent screws up in your back office, you learn. But if it screws up with a member, you lose trust. On an episode of C.U. On The Show, Doug English spoke with Velera’s Elizabeth Wadsworth about what comes next. “Agents are the next evolution of AI… moving from questions to completing tasks.” A copilot gives an answer. But an agent must be directed to do something.

Wadsworth recommends starting where mistakes don’t break member trust. The first agent use cases should land in back-office work, where tasks are repeatable and easier to control. To keep things safe, push governance before deployment. Responsible AI is a process built around transparency, accountability, fairness, privacy, explainability, and security. The practical test is explainability. If you cannot explain how a system works in one sentence, you’re not ready to run it. She also warns that bias can be hiding in your data, and even if a vendor is involved, the liability still sits with your Credit Union.

Here’s the easiest way to think about agents: Treat them like digital employees. You start with limited access, a narrow job, and earn more permissions over time. That approach lets you explore agents thoughtfully, without risking the trust your members already give you. (link)

Tips & Use Cases

Learn to apply AI…

3 AI adoption traps that could cost you members: Many Credit Unions rush into AI without fixing data, legacy systems, or member experience gaps, which amplifies friction. Focus on clean data, integrated systems, and self-service workflows first, or you risk losing younger members and deposits as $100T of Baby Boomer wealth gets inherited by younger generations over the next two decades. (link)

Affinity Plus Federal Credit Union reframes digital transformation as data-driven empathy: CIO Radha Chavali says AI only works when you break down silos and build a trusted “member plus outcomes” view, grounded in strong data governance before scaling use cases. Use member insights for just-in-time preapprovals, early risk detection before delinquency, and internal analytics to spot operational gaps, while investing in continuous upskilling so staff can act on what AI surfaces. (link)

AI-powered payments can help CUs win more SMB relationships: PayOnward CEO Cary Strange says AI should free your team from repetitive work so you can spend more time advising SMB members. Offering AI-based AR and bill pay with cash-flow forecasting lets you spot shortfalls weeks early and reach out with the right lending option. (link)

Glia’s voice AI playbook for faster Credit Union member service: Automate up to 60% of routine calls and chats with voice AI, then pass complex cases to staff with full context. With Glia, Azura CU cut wait times 50% and pushed abandonment below 1%, while Service First FCU saw a 21% lift in digital center loan dollars in H1 2025. (link)

Accenture warns AI agents could drain Credit Union income: As AI tools automatically compare rates and optimize cash, even loyal members will get nudged toward better offers, putting ~22% of pretax income at risk. Use genAI beyond cost-cutting to make proactive save offers, reprice faster, and approve interventions in real time before money moves outside your channels. (link)

Fraud is surging at Credit Unions as synthetic IDs mature: Alloy reports a 72% jump in fraud events in 2026, the steepest increase of any segment, driven by synthetic identities and rising in-branch schemes. Tighten onboarding with KYC waterfalls, add stronger synthetic ID checks, and use AI anomaly detection to catch slow-burning fraud without adding member friction. (link)

AI-ready modernization requires real-time checks across every channel: If your email, text, voice, and branch do not sync in real time, you remind members after they paid and you lose trust. Start with your top call drivers, get real-time data flowing, then use internal AI agent-assist and orchestration to cut decision cycles from weeks to seconds. (link)

Banks move away from OpenAI as AI strategies mature: Evident data shows OpenAI’s share of banking AI use cases fell from about half to one-third as banks adopt Anthropic and Google for performance and easier integration. (link)

Rezolve.ai shows how to build AI agents IT can actually govern and trust: Agents reason and use tools like employees, but without deterministic workflows, tool-level controls, and human-in-the-loop approvals, they’re too risky. Rezolve’s Agentic Studio adds workflows, tool controls, and human approvals to autonomous agents so Credit Unions can automate safely with full audit trails. (link)

Rezolve.ai shows multimodal AI handling real support work end to end: Rezolve.ai demoed one AI resolving voice calls, emails, Teams chats, and screenshots, completing password resets, creating tickets, and troubleshooting issues without handoffs. (link)

AI credit decisioning vendors help Credit Unions catch up to top banks: McKinsey says 20% of top banks already use genAI in credit risk, and 60% expect a use case within a year. Vendors like Zest AI and Upstart support AI-driven credit decisioning for CUs, while other platforms like Multimodal offer agentic workflows for regulated lending. (link)

If your AI can’t guide members, they’ll switch providers: McKinsey says over half of banking consumers already use genAI, and nearly all would leave if their bank does not keep up. Credit Unions must move AI beyond chatbots into predictive guidance and automated insights that help members make confident decisions during high-stakes financial moments. (link)

AI is becoming a finance “employee” that does the work: Personal agents already schedule calendars, draft invoices, summarize meetings, and keep conversations going on autopilot. For your finance team, start piloting an AI “employee” that holds context across FP&A tools and ERP, then executes repeatable workflows with human approval. (link)

AI is slowing bank hiring more than eliminating jobs: Fortune reports that despite AI fears and 2025 layoffs, banks are cutting fewer roles than expected and using AI to avoid hiring the next 100 employees. For Credit Unions, the signal is to deploy AI for productivity gains and capacity relief, not headcount reduction, while reskilling staff for higher-judgment work. (link)

AI is slowing bank hiring more than driving mass layoffs: Despite warnings, headcounts at JPMorgan Chase, Bank of America, and Goldman Sachs have stayed largely stable, as banks slow hiring. Experts say recent cuts reflect pandemic-era overhiring and economic uncertainty. Banks seek AI productivity so they don’t need to hire the “next 100 people.” (link)

Agentic AI emerges as the next inflection point for financial services: Leaders at the World Economic Forum say AI systems that can act autonomously could automate credit, fraud, compliance, and payments far beyond today’s genAI. (link)

Lloyds Banking Group reports £50M in genAI value in 2025: The value was delivered across service, engineering, search, and HR, with £100M+ expected in 2026 as usage scales. The bank is now training all 67,000 employees through an AI Academy, and preparing agentic AI and an in-app financial assistant. (link)

Standard Chartered launches AI platform for transaction banking teams: The new system automates knowledge search and solution tailoring so bankers spend less time hunting for information and more time advising clients. AI-driven knowledge hubs and recommendations speed proposals, personalize responses, and scale high-touch service. (link)

Bankwell invites peers to align on AI risk before it scales: Bankwell Bank convened a regtech summit with peer banks to pressure-test AI use cases, risks, and governance together. Leaders flagged data loss prevention, synthetic ID fraud, and explainability as top concerns. Bankwell already uses genAI to help vet small-business loans, and it’s evaluating AI to speed compliance reviews like BSA/AML with humans in the loop. (link)

AI flags forged signatures as check fraud stays stubbornly high: 63% of organizations faced check fraud in 2025, keeping signatures a major weak spot. AI tools from vendors like ParaScript can compare signatures against historical data and stop bad items before posting. (link)

Funding Spotlight

Where the money is flowing for innovation…

Sixfold raises $30M Series B to build an autonomous AI underwriter: The round scales agentic AI that plugs into existing P&C systems to automate underwriting across structured and unstructured data without changing workflows. (link)

WealthAi raises $800K pre-seed to build an AI-native OS for wealth managers: WealthAi is building an AI-driven operating system for advisers, family offices, and private banks that automates adviser workflows, unifies data, and reduces manual rekeying without replacing core systems. (link)

Datatruck raises Series A to build an AI-native TMS for real-time profitability: Datatruck is scaling an AI-first platform that embeds profit visibility into dispatch and documents, tracking margins by load, truck, and lane across 1,000+ companies and $1.7B+ in freight activity. (link)

Outtake raises $40M Series B to combat AI-driven impersonation: Outtake is scaling AI that detects and disrupts impersonation across text, image, and video, helping enterprises investigate identity-based threats faster and reduce takedown times as deepfake abuse accelerates. (link)

Rogo raises $75M Series C to expand agentic AI for finance teams: Rogo is scaling an end-to-end AI system that supports complex financial analysis and decision workflows, now used by 25,000+ finance professionals across banks and investment firms. (link)

HAQQ Legal AI raises $3M to build an AI operating system for legal work: HAQQ is expanding a vertically integrated platform that combines AI legal intelligence, practice management, payments, and jurisdiction-aware infrastructure into one system of record. (link)

Keeping up with Tech

The latest in fintech and tools…

New CUSO brings AI-driven balance-sheet analytics to Credit Unions: One Washington Financial launched a CUSO with Delfi Labs to give Credit Unions large-bank asset-liability modeling without large teams. Early adopter Maps Credit Union will use AI scenario analysis to make faster, clearer tradeoffs as rates and liquidity pressures shift. (link)

Google brings browser-level AI agents to Chrome: New Gemini-powered “auto browse” agents can navigate sites and complete multi-step tasks for users. For Credit Unions, assume AI will handle onboarding and product research, and plan stronger authentication, fraud controls, and agent-aware account protections. (link)

FICO and Tech Mahindra launch AI decisioning “Centre of Excellence”: The partnership aims to move AI decisioning to production by pairing FICO models with large-scale implementation support. The effort plans to reduce deployment risk, modernize legacy cores, and accelerate time-to-value. (link)

Fingerprint launches system to identify authorized AI agents on the web: The platform verifies signed AI agents from providers like OpenAI and Amazon Web Services, letting organizations allow trusted automation while blocking malicious bots. Credit Unions should plan for agent-aware controls, instead of banning all bots. (link)

AXA launches AI platform to guide financial advisors: Quest by AXA combines real-time macroeconomic data, market news, and proprietary research to help advisors deliver more consistent, insight-led financial and insurance advice without replacing the human relationship. (link)

OpenAI launches Codex app to orchestrate multiple AI agents: The new macOS app lets developers run, supervise, and coordinate multiple agents across long-running projects using isolated workspaces and reusable skills. (link)

OpenAI builds in-house AI data agent to speed internal decision-making: The internal agent lets employees query large datasets in natural language and receive validated, self-correcting insights in minutes by combining code-level context and institutional knowledge. (link)

Say adios to GPT-4o and older ChatGPT models as GPT-5.2 becomes standard: GPT-4o, GPT-4.1, GPT-4.1 mini, and o4-mini leave ChatGPT on Feb. 13, 2026, with no API changes. OpenAI is shifting focus to customization, personality controls, and tuning response behavior. (link)

OpenAI adds safeguards to stop AI agents from leaking data via URLs: Agentic browsing is now restricted to publicly observed links, while unverified URLs trigger warnings or require user action. The change reduces silent data exfiltration without breaking legitimate web tasks. (link)

In Other News

Related news you can learn from…

• What banks expected in 2025 didn’t fully materialize (link)

• AI agents get their own social network, chaos ensues (link)

• Most AI vibe coding tools still don’t work for regular people (link)

• Enterprise AI leaders are emerging, but the market is still in flux (link)

• How Gemini could become a hands-on budgeting assistant in 2026 (link)

• What Goldman and a16z see coming next for AI, capital, and growth (link)

• Spacex merges with XAI to create a $1.25T AI-and-space powerhouse (link)

• Credit Union leaders see 2026 as a turning point for AI, automation, and growth (link)

Community Corner

Memes and visuals…

Thanks for reading!

Until next week,

— Credit Union AI Guy

Enjoying this newsletter? Forward it to a colleague who might appreciate practical AI insights.

Have a question or want to share your own AI experiment? Reply to this email or connect with us on LinkedIn. We’re building a community of curious Credit Union professionals. Come join the conversation!

AI can help your team deliver both when it matters most.

Today, I cover:

• How One Nevada CU uses AI to spot silent attrition

• How BCU used AI voice agents to deliver hurricane relief faster

• New CSI 2026 Banking Priorities Report

Read time: 9 minutes

Top Stories

The biggest news this week…

1) How One Nevada CU uses AI to spot silent attrition

Credit Unions often only learn that a member is unhappy after the account is closed. One Nevada Credit Union’s new CEO, Steve O’Donnell, is trying to flip that by using AI to surface “silent attrition” signals earlier, before churn becomes irreversible. The bet is that transactional data alone won’t warn you when a member is frustrated, but intent and sentiment from calls and interactions can, especially when that layer is tied back into the Credit Union’s evolving “360 view” data strategy, so the team can act on warning signs sooner.

The foundation for that work started with a deliberately unglamorous first win: cleaning up the contact center’s messy knowledge base. They digitized the scattered documents reps used to answer questions and resolved inconsistencies, making answers faster and more consistent. That matters because One Nevada is increasingly digital-first, and O’Donnell says that shift has eroded “connection” over time. So the next step is turning newly organized knowledge and interaction data into better personalization and a stronger bridge between digital and physical service.

Now the “real AI story” is in progress: the team is analyzing what members said, why they reached out, and how they sounded before closure events, then looking for repeatable patterns they can operationalize into retention plays. O’Donnell also frames AI as a forcing function to rethink old workflows, like not treating a mailed “close my account” letter as an automatic exit, but as a trigger for smarter review and intervention. And he’s pushing AI internally as well, from automating board packet assembly and insight generation to seeding champions across departments, because the faster employees adopt and refine workflows, the faster the Credit Union can respond faster when warning signs show up in member interactions. (link)

2) How BCU used AI voice agents to deliver hurricane relief faster without overwhelming staff

Faced with the dual threat of Hurricanes Helene and Milton, BCU needed to reach affected members fast, even as some local branches were closed due to storm damage. So the Credit Union partnered with AviaryAI to deploy AI-powered voice agents that could launch quickly and handle high volume without overwhelming staff with a flood of inquiries.

In just 4 days, BCU rolled out an outreach campaign that delivered personalized relief information based on each member’s situation. The voice agents shared options such as fee reimbursements, emergency loans, and insurance claim assistance. For members in the most impacted areas, they also provided details on temporary branch locations and available services. Because the calls were two-way, members could ask questions and get answers immediately. BCU also implemented follow-up calls to improve message delivery.

In under 10 days, the agents placed 55,324 calls to 33,117 members. BCU reports 46% answered, and 52% of answered calls were successful, while reducing costs by 90% compared to human outbound calling. The campaign also helped BCU identify which members were most impacted, so employees could focus on people with more complex needs. As BCU CEO Mike Valentine put it, the effort showed how AI can deliver “timely, compassionate, and effective support to our members when they need it most.” (link)

3) New CSI 2026 Banking Priorities Report

CSI’s 2026 Banking Priorities Executive Report surveyed 252 leaders and found AI is now the top opportunity and top worry. Half of respondents named AI the leading tech trend, ahead of digital assets (20%) and digital transformation (11%). AI-enhanced social engineering, including voice cloning and deepfakes, jumped to the top cybersecurity concern. 85% say institutions adopting AI will gain a meaningful competitive edge.

Credit Union leaders should note two gaps between banks and CUs. Banks were almost twice as likely to cite back-office efficiency as an AI win (38% vs. 21%). And fewer Credit Unions feel well-prepared for a cyberattack (72% vs. 85% for banks).

Leaders also expect branches to stay relevant, with 91% saying they matter over the next decade. That puts pressure to modernize without losing the relationship feel. (link)

Tips & Use Cases

Learn to apply AI…

6 reasonable AI predictions for 2026 from CU 2.0: AI will be embedded by default, adopted quietly by staff, expose data quality gaps, reset member speed expectations, face cultural resistance, and reward Credit Unions that deploy agentic automation early. (link)

Data-driven marketing is now table stakes for Credit Unions: If you treat targeting, messaging, and channels as separate projects, you’ll waste spend and struggle to repeat wins. Pair predictive behavior models with coordinated digital and direct mail campaigns to lift response rates ~20% on average. (link)

Stablecoins + consumer AI agents could reshape member relationships: As stablecoins bypass cards and AI consumer agents shop on behalf of members, your website and app may disappear from the decision flow. Credit Unions must compete on trust, direct value, and agent-readable products or risk losing influence, deposits, and interchange. (link)

How to move Credit Union AI adoption faster through collaborations: If you try to solve AI, deepfake detection, business banking onboarding, and stablecoins alone, you move at legacy speed. Use shared sandboxes and early-access partnerships, like MDC’s model, to test fast, share lessons, and deploy with peer Credit Unions. (link)

Credit Unions need to shape AI ethics and alternative ID rules now: The World Council of Credit Unions is pushing proactive AI ethics and alternative ID frameworks so you influence regulators instead of inheriting bank-first rules. If you stay passive, you risk higher compliance burden, weaker member protections, and fewer options to expand access. (link)

Modern infrastructure matters more than “cool” AI features: Jody Bhagat from Engine by Starling says most banks spend 70-80% of tech budgets maintaining legacy cores, leaving little room for differentiation or AI at scale. Real-time, API-driven architecture enables 40% faster call handling, 50% fewer handoffs, and rapid launches of fraud and elder-protection tools. (link)

Blue Eagle Credit Union adopts Scienaptic AI to modernize lending: Blue Eagle CU plans to use AI credit decisioning to deliver faster, more inclusive loan decisions, helping say yes more often without increasing risk. (link)

Lawsuit against Eightfold AI exposes risks of non-transparent AI hiring tools: The complaint alleges qualified candidates were auto-rejected without disclosure, data visibility, or appeal rights. Credit Unions using AI in hiring should audit vendors for transparency, bias controls, and compliance before regulators do. (link)

AI credit scoring is replacing rigid models as regulators push for transparency: FIs are moving beyond static scorecards amid rising volatility and supervision, using explainable AI models and governed alternative data to assess risk more fairly. The real challenge is execution, integrating scores into underwriting with clear oversight and audit trails. (link)

53% of risk teams are already adopting AI in credit risk management: Use AI in KYC and document review to cut processing time 60% and manual review effort 70%, and automate 50% of contract generation. Plan for data quality and explainability gaps, challenges cited by 45% and 39% of teams, and build audit trails before your Credit Union scales monitoring. (link)

4 ways Credit Unions can use agentic AI to prevent fraud: Use it to 1) catch synthetic IDs during onboarding, 2) flag mismatched income and employment in loan origination, and 3) monitor transactions for first-party fraud that rules miss. Plus, 4) speed dispute and chargeback triage, since 66% of consumers would switch banks over slow dispute resolution. (link)

AI-powered financial nudges are reshaping how people save, spend, and manage money: By using behavioral data and predictive analytics, AI can deliver timely prompts that help members save more, spend smarter, and reduce debt. These nudges offer a scalable way to boost financial wellness and engagement without adding operational lift. (link)

Sonata Bank bets on practical AI to streamline core operations: Sonata Bank is focusing AI on clear operational wins like fraud detection, KYC indexing, and underwriting support instead of broad experimentation. (link)

3 AI use cases fixing accounting, AR, and AP where finance actually breaks: Use AI to apply judgment before posting in accounting, route AR decisions based on customer behavior to unlock cash faster, and stop AP errors by isolating invoice mismatches before they hit the ledger. (link)

Intelligent Lending Group cuts marketing compliance review time with AI: By using AI-driven review tools from Adclear, Intelligent Lending Group is automating financial promotions checks across its TotallyMoney and CredAbility apps, and Ocean. (link)

Older members are adopting AI when it removes friction: Voice-first, conversational AI is seeing strong adoption among adults 50+ because it feels intuitive, predictable, and service-oriented, challenging assumptions about who AI is really for. (link)

AI amplifies broken member experience when research is weak: Research shows 91% of business customers want streamlined digital insurance journeys, but only 34% feel they get them. If your Credit Union skips deep, authenticated research, AI will scale noise and friction instead of improving lending, claims, and protection experiences. (link).

$723B in cloud spending signals the shift to AI-native banking architectures: With 1.75B digital banking accounts processing $1.4T annually and 76% of U.S. consumers using mobile apps, speed and intelligence now define competitiveness. Nearly half of digital users will switch for a better experience, making AI-native cores essential as branches close and loyalty shifts to real-time performance. (link)

AI agents and stablecoins threaten card payments’ dominance: Autonomous AI agents are starting to execute payments at machine speed, and analysts estimate up to 20% of card settlement volume could shift by 2026. Push-based, programmable stablecoin payments offer instant finality and near-zero fees that card rails cannot match in an agentic-driven economy. (link)

Fintech Takes’ Alex Johnson lists 10 banking priorities for 2026: Stop chasing predictions and resolutions and set 2026 priorities, like investing early in AI governance while LLMs stay out of high-risk credit decisions. Keep open banking moving despite U.S. 1033 limbo, make stablecoin money legible, add self-exclusion tools, and design shared-access banking for aging households. (link)

Funding Spotlight

Where the money is flowing for innovation…

PayPal buys Cymbio to lock up agentic commerce infrastructure: PayPal’s acquisition of Cymbio brings AI-driven product discovery, catalog management, and agent-ready commerce rails in-house as agentic shopping accelerates. (link)

Zocks raises $45M Series B to scale agentic AI for financial advisers: Zocks is expanding its agentic assistant used by 5,000+ firms to automate onboarding, meeting prep, and document workflows, saving advisers 10+ hours per week while adding enterprise-grade security and compliance. (link)

skrooge.ai raises $1.85M seed round to blend AI with managed accounting services: skrooge.ai is expanding AI-enabled accounting and tax support for SMBs, combining automation with human accountants to streamline compliance, reporting, and plain-English financial insights. (link)

Mine pulls in $14M Series A to launch an AI money agent for young adults: Mine is rolling out MoneyGPT, an AI-powered finance agent that adapts to gig income, credit use, and competing goals to deliver hyper-personalized guidance and build financial confidence early. (link)

Jelou raises $10M Series A to bring agentic financial transactions into WhatsApp: Jelou is scaling Brain, its platform for deploying AI agents that execute payments, onboarding, ID checks, and credit workflows directly inside WhatsApp conversations. (link)

AiStrike raises $7M seed round to push preemptive, agentic AI cyber defence: AiStrike is scaling an AI-native security platform that uses autonomous agents to detect, prioritize, and respond to threats in real time without relying on SIEM-heavy architectures. (link)

Armilla AI raises $25M to insure the growing risks of generative and agentic AI: The funding expands AI-specific liability coverage for model errors, harmful outputs, regulatory violations, and agent failures as AI regulation tightens globally. (link)

Datarails raises $70M Series C to expand its AI-native FinanceOS for CFO teams: Datarails is scaling an Excel-first FinanceOS that unifies FP&A, close, cash, and spend management while using AI to cut manual data stitching and improve real-time financial visibility. (link)

Keeping up with Tech

The latest in fintech and tools…

Shopify adds a 4% OpenAI fee to sales completed through ChatGPT checkout: The fee on sales completed through ChatGPT checkout creates a new layer of transaction economics as “agentic storefronts” move purchases directly into AI conversations. (link)

Concourse launches finance AI agent platform alongside $12M Series A: The enterprise-grade agent platform connects directly to ERPs, QuickBooks, Stripe, Ramp, and data warehouses to automate analysis and reporting with explainable, multi-step workflows. (link)

Mortgage Magic embeds AI-assisted mortgage sourcing directly into broker CRMs: The AI-assisted sourcing workflow filters products transparently from fact-find data while preserving adviser control and FCA-ready audit trails inside the CRM. (link)

PlannerPal launches AI pre-meeting prep tool for financial advisers: The workflow pulls data from CRMs, documents, valuations, emails, and prior notes to standardize client readiness before meetings. It cuts prep time while improving agenda clarity and compliance confidence. (link)

Mastercard launches Agent Suite to bring agentic AI into payments and commerce: Mastercard is combining AI agents with payments, fraud, identity, and advisory services to automate decisioning, offers, and campaigns for financial institutions. Merchants can also use agents for pricing, inventory, and personalized engagement at scale. (link)

Intellect Design Arena accelerates U.S. expansion with AI-first real-time payments platform: The AI-first platform applies intelligence across pre, in-flight, and post-payment stages for RTP, FedNow, ACH, Fedwire, and SWIFT. The composable, low-code architecture enables real-time validation, anomaly detection, and orchestration without ripping out existing cores. (link)

Nets partners with Triple to add AI-driven transaction clarity for European banks: Nets is integrating Triple’s AI-powered merchant enrichment to turn raw card transactions into clear names, logos, and locations. The move targets rising friendly fraud, cutting support calls and chargebacks while meeting new Mastercard and Visa data mandates. (link)

Mastercard expands Start Path to recruit agentic AI startups: Mastercard is adding agentic AI firms to its Start Path program to source emerging partners beyond big tech as it builds agentic commerce capabilities. The program has supported 500+ startups and now serves as a pipeline for global agentic AI talent. (link)

PayPal partners with Microsoft to revive branded checkout inside Copilot: PayPal will power Copilot Checkout so shoppers can discover products, select options, and complete payments without leaving Microsoft’s AI interface. (link)

In Other News

Related news you can learn from…

• BIS warns AI and digital finance could amplify financial stability risks (link)

• House passes bipartisan bills to expand AI adoption support for small businesses (link)

• UK regulator launches forward-looking review on advanced AI in financial services (link)

• Why traditional risk models are no longer enough for modern wealth management (link)

Community Corner

Memes and visuals…

@weworkremotelycom

We Work Remotely on Instagram: "AI AI AI AI…

#workhumor #corpo…

Thanks for reading!

Until next week,

— Credit Union AI Guy

Enjoying this newsletter? Forward it to a colleague who might appreciate practical AI insights.

Have a question or want to share your own AI experiment? Reply to this email or connect with us on LinkedIn. We’re building a community of curious Credit Union professionals. Come join the conversation!

Hint: It’s not where your members can see.

Today, I cover:

• Kitsap turns agentic AI into ROI by starting with the “boring” first

• Where AI is delivering & failing for Credit Unions

• Great Lakes CU is making small-dollar lending work

Read time: 8 minutes

Top Stories

The biggest news this week…

1) Kitsap turns agentic AI into ROI by starting with the “boring” first

Kitsap Credit Union didn’t kick off its agentic AI push with anything member-facing. CEO Shawn Gilfedder said it started with a three-year idea and an “unsexy” use case: improving internal audit processes. After a breakfast meeting with Troy Wyatt, CEO of D8TAOPS, Kitsap deliberately chose to look inward first and deploy agentic tech within employee workflows, especially in compliance and audit, before letting anything touch members.

D8TAOPS’ approach is to start at the data layer (cleaning, governing, and securing data), then break work into small business processes that become repeatable agents, eventually rolling up into something like a “Kitsap GPT.” So, Kitsap had to set the foundational infrastructure by cleaning and organizing data, setting up reliable ingestion pipelines, and standing up a private language model in their Azure environment. Once that groundwork was in place, the data could be standardized and made accessible across the organization, enabling it to be reused safely and consistently in new AI-driven workflows.

They addressed the “what about my core?” problem by treating the core as one data source among many, important for inputs/outputs, but not the experience layer. Meanwhile, they used platforms like Salesforce and others to deliver service and personalization.

Gilfedder framed the payoff as “return on innovation,” where improvement becomes an “X factor” driven by data and bandwidth. When they automate the “digital janitorial” work, employees can spend more time building relationships. For example, their contact center’s average talk time is already over six minutes because bots and automation removed routine work. But the goal is to turn that into a deeper 15-minute discussion about financial wellness by letting agents “pick up the other work along the way.” (link)

2) Where AI is delivering & failing for Credit Unions

AI demand is no longer theoretical for Credit Unions. A new report from PYMNTS Intelligence and Velera finds:

• 30% of consumers use AI tools multiple times per week

• 55% already rely on AI for financial planning or budgeting

• 42% say they’d feel comfortable using AI to complete financial transactions

That comfort is sharply generational: 80% of Gen Z and younger millennials use AI for financial planning, and their comfort with agentic AI is similarly high (78% for Gen Z and 77% for younger millennials), versus 13% among baby boomers and older consumers.

Where AI is delivering today is in high-trust, high-impact use cases. The report highlights personalization, member service, and fraud prevention as areas where AI is producing tangible value. Chatbots and virtual assistants are the leading application, with 58% adoption cited by CULytics. Fraud management is also emerging as a standout use case: Cornerstone Advisors lists it as the second-most common generative AI application at 48% (behind contact centers at 74%), and Alloy reports a 92% net increase in AI fraud-prevention investment among CUs in 2025.

Where AI struggles is scale. A CULytics survey cited in the report found 42% of CUs have implemented AI in specific areas. But only 8% say AI is used across multiple facets of the organization, largely due to gaps in data readiness, governance, and integration. (link)

3) Great Lakes CU is making small-dollar lending work

Small-dollar lending gets expensive fast at scale because servicing volume can overwhelm margin. Great Lakes Credit Union (a $1.4B CU with 100,000+ members, 51%+ being low-income) is leaning on automation to reduce cost-to-serve, while keeping humans in the loop where financial coaching improves outcomes.

The clearest proof is the contact center. CEO Steve Bugg said their AI assistant, Olive, now answers all inbound calls and fully handles 60% end-to-end with no human interaction. On lending, Bugg described a fully automated, app-based, unsecured process driven by member behavior data. With a “couple clicks… you’re approved… funded… we don’t touch it,” and he said losses have been minimal. The direction from here is a blended model. Automate the loan workflow and digitize the repeatable parts of financial literacy, while keeping staff available for members who want deeper guidance. (link)

Tips & Use Cases

Learn to apply AI…

5 ways Credit Unions are using tech to drive growth in 2026: Growth leaders are personalizing incentives with transaction data, using agentic AI to automate onboarding and loan decisions, and embedding smart guidance into digital channels. They’re also improving mobile and web account opening and using tech to differentiate products, bundles, and onboarding journeys. (link)

How to pair AI with branches to build trust in an AI-driven world: Use AI for real-time decisioning and personalization while positioning branches as places for control, consultation, and problem resolution when digital options feel overwhelming. Research from Accenture shows physical presence reinforces safety and brand visibility as AI search and choice overload increase. (link)

How to evaluate agentic AI for financial crime compliance: Treat agents like L1 investigators that clear low-risk AML and KYC alerts and escalate exceptions. Validate them on your Credit Union’s historical cases for repeatable decisions, clear data provenance, and examiner-ready documentation with a named compliance owner and confidence thresholds. (link)

How to use Claude Cowork as a finance data quality gatekeeper: Give Claude Cowork access to your board deck, P&L, and budget files so it can cross-check numbers and narratives inside the same workspace. It flags inconsistencies like mismatched EBITDA, unsupported growth claims, or deteriorating cash conversion. (link)

How AI agents move past the automation ceiling in lending operations: Use AI agents to handle complex borrower cases that rule-based automation can’t, like uneven income, alternative data, or policy exceptions. Let agents flag risk, explain decisions, and escalate edge cases so your team scales volume without sacrificing credit quality or compliance. (link)

Agentic workflows reshape commercial lending fraud detection: Fraud slips through when intake, underwriting, and funding decisions live in disconnected tools, and human judgment varies by analyst. Agentic systems enforce a single fraud playbook across the loan lifecycle with explainable decisions, confidence scoring, and built-in escalation. (link)

How to achieve AI ROI by starting with internal workflows: Focus first on low-risk internal use cases like document intelligence, case summarization, and coding assistance, where AI can deliver fast productivity gains without regulatory friction. Measure success against clear KPIs, modernize data access, and upskill teams continuously so AI tools are actually used. (link)

Crypto scams drove losses of up to $17 billion in 2025: Chainalysis estimates AI-enabled impersonation scams grew 1,400% year over year. Average scam payments more than tripled as criminals used AI, SMS phishing, and laundering networks to scale faster. (link)

Kentucky AG lawsuit puts AI data practices under the microscope: Kentucky’s attorney general sued Character.AI for alleged violations of the state’s new data privacy law, citing mishandling of sensitive conversational data, including from minors. The case raises new consent and vendor risk questions about AI systems that retain user conversations. (link)

Credit Union leaders flag stablecoins and AI as near-term governance tests: Speaking to Credit Union boards, leaders from the Hawaii Credit Union League and NASCUS cited the GENIUS Act, warned the U.S. lags global stablecoin adoption, and noted Tether already exceeds $180B in value. They also cautioned AI due diligence now extends to exams. (link)

Accenture’s Mike Abbott on how AI creates new revenue in banking: Generative and agentic AI are shifting strategy from cost-cutting to growth by enabling one-to-one marketing, guiding relationship managers, and embedding intelligence directly into products like payments and cash management. (link)

AI-first banking removes channels but raises the bar on trust: A Brazilian bank runs entirely through a WhatsApp chatbot, eliminating branches and apps, but it faces increased identity and takeover risk. Banks must pair agentic AI with continuous verification, behavioral biometrics, and self-healing fraud responses to prevent account takeovers in 24/7 agent-led banking. (link)

AI must earn funding with owners, outcomes, and a kill switch: Cornerstone Advisors says boards now want measurable productivity or growth results, not “AI for AI’s sake,” with a clear initiative owner and quantifiable outcomes. If value does not show up, leadership needs a kill switch and the middle management muscle to operationalize AI. (link)

U.S. Bank brings gen AI into its developer portal to reduce embedded banking friction: The new AI assistant helps partners navigate APIs, integration patterns, security requirements, and error resolution directly inside a gated developer environment. The tool shortens onboarding and troubleshooting cycles, cutting embedded banking integration timelines by weeks. (link)

AI fakery is pushing banks toward blockchain as a new trust layer: Michael Toner of Profor argues AI and the blockchain are converging as GenAI makes fake bank messages, videos, and identities harder to detect. He says blockchain can act as a verifiable “truth layer,” letting banks prove which communications, payments, and lending terms are authentic as regulation around digital assets firms up. (link)

Funding Spotlight

Where the money is flowing for innovation…

Monnai lands $12M to expand real-time identity and risk infrastructure: Monnai is building sub-second decisioning used across onboarding, fraud, and credit, with global deployments designed to support real-time risk assessment at scale. (link)

Novee raises $51.5M to bring continuous AI penetration testing to security teams: The startup emerged from stealth with an AI-driven platform that continuously simulates real attacker behavior, helping lean security teams surface exploitable vulnerabilities earlier as AI accelerates both software changes and attack cycles. (link)

GrowthPal secures $2.6M to accelerate AI-led M&A discovery: GrowthPal is scaling a platform that turns growth strategies into acquisition theses and scans millions of companies to surface high-fit, often off-market targets in days, compressing deal sourcing timelines and reducing reliance on banker-led networks. (link)

WitnessAI lands $58M to expand enterprise AI security and governance: WitnessAI helps regulated organizations govern how AI models, applications, and autonomous agents are used, monitored, and constrained, as enterprises move from pilots to large-scale AI deployment. (link)

Aikido Security hits unicorn status with $60M Series B: Aikido Security reached a $1B valuation after a DST Global–led round, backing its push to embed vulnerability detection and automated remediation directly into software development workflows rather than bolting security on after release. (link)

Depthfirst secures $40M to protect AI-accelerated software pipelines: Depthfirst builds autonomous agents that identify, triage, and remediate vulnerabilities across code, cloud, and infrastructure, targeting the new risk created as AI-assisted development compresses release cycles. (link)

Keeping up with Tech

The latest in fintech and tools…

Keye introduces audit-ready AI copilot for investment due diligence: Odin answers plain-English diligence questions while producing deterministic, auditable outputs instead of probabilistic summaries. By executing analysis through code and embedded investor heuristics, the tool aims to eliminate hallucinations and make diligence results repeatable and regulator-ready. (link)

Gemini adds opt-in personal context to enable more personalized AI assistance: Personal Intelligence allows Gemini to reason across connected apps like Gmail, Photos, YouTube, and Search to take real-time action. The feature is opt-in, privacy-first, and designed with controls that prevent private content from being used to train models. (link)

Hawk launches Analytics Studio to govern AI models for fraud and AML: As 91% of banks now encourage AI use, Hawk’s new Analytics Studio tool lets compliance teams build, retrain, and approve models with built-in explainability, documentation, and version control to meet evolving regulatory expectations. (link)

Feedzai teams up with Matrix USA to fast-track modern fraud defenses: Feedzai is partnering with Matrix USA to pair AI-native fraud and AML technology with hands-on deployment and advisory support. The alliance includes a joint Center of Excellence to help banks roll out scalable, regulator-ready controls as criminals increasingly use AI to automate fraud. (link)

Microsoft Marketplace positions itself as a central hub for enterprise AI and agents: Microsoft is pitching its Marketplace as an easier way to move from AI pilots to real deployment, letting teams plug vetted AI apps and agents directly into tools they already use, like Azure and Microsoft 365. The idea is simpler adoption with built-in guardrails, so companies can build or buy AI without adding new governance or cost headaches. (link)

Anthropic publishes a public “constitution” to govern how Claude behaves: The constitution explains why Claude responds the way it does, not just what rules to follow. The document acts as a final authority for training and is also used to generate synthetic conversations and rankings, helping Claude apply consistent judgment in new situations while enforcing hard limits in high-risk cases. (link)

Google’s TranslateGemma brings high-quality AI translation across 55 languages: TranslateGemma makes accurate translation available on everyday devices, from phones to laptops, without requiring expensive cloud systems. By offering smaller, efficient models that still deliver strong results, it lets organizations support more languages, including underserved ones, while reducing cost and delay. (link)

AI is becoming a core security layer around Bitcoin’s ecosystem: As attacks shift from breaking cryptography to exploiting wallets, exchanges, infrastructure, and human behavior, traditional rules-based defenses are falling behind. AI-driven security is emerging to detect anomalous activity, automate response, and protect Bitcoin’s surrounding ecosystem as threats become faster, adaptive, and machine-driven. (link)

Filene launches payments research hub for Credit Unions: Filene Research Institute’s “All Things Payments Center” will help CUs navigate real-time payments, AI-driven fraud, stablecoins, and shifting deposit economics. The initiative will deliver CU specific benchmarking, research, and implementation roadmaps as Amazon, Walmart, and OpenAI push deeper into payments. (link)

In Other News

Related news you can learn from…

• OpenAI outlines its upcoming approach to ads (link)

• OpenAI expands ChatGPT Go globally with $8/month tier (link)

• 4 ways AI is reshaping discovery, health, work, and responsibility (link)

• State Street lifts tech spend 11% ahead of 2026 AI and agent rollout (link)

Community Corner

Memes and visuals…

Thanks for reading!

Until next week,

— Credit Union AI Guy

Enjoying this newsletter? Forward it to a colleague who might appreciate practical AI insights.

Have a question or want to share your own AI experiment? Reply to this email or connect with us on LinkedIn. We’re building a community of curious Credit Union professionals. Come join the conversation!

This week’s stories show how Credit Unions are fighting back, using data, governance, and practical AI to protect member relationships.

Today, I cover:

• How American Eagle FCU uses AI to power financial wellness

• State of Fintech 2026 hits an inflection point

• UKFCU’s playbook for AI governance and exams

Read time: 8 minutes

Top Stories

The biggest news this week…

1) How American Eagle FCU uses AI to power financial wellness

Many Credit Unions want to improve financial wellness but struggle to move beyond generic education tools and one-size-fits-all digital experiences. At American Eagle Financial Credit Union, that challenge was amplified by a five-person digital team that owns everything from online account opening and bill pay to fraud mitigation and frontline support. As SVP of Digital Services, Pamela Villanova explained on the FIsionaries podcast, the Credit Union isn’t just competing with other financial institutions anymore — it’s competing with the digital experiences members get from Amazon and Uber.

Their playbook was to get specific before buying tech. Villanova said American Eagle started with a deep digital assessment to define its “north star” before shopping for vendors. The team aligned on three priorities: improving user experience, gaining better access to member data, and turning that data into timely, relevant outreach. Those requirements led American Eagle to Alkami, which gave the Credit Union more control over personalization, campaign setup, and gradual rollouts without relying on vendor tickets. Mari Gadlin, Director of Digital Banking Services, said that shift alone made the team more nimble and reduced internal friction around change.

On the financial wellness side, American Eagle focused on behavior change rather than just education. The Credit Union uses a FinHealth survey to help members self-assess, runs targeted wellness outreach, and is moving SavvyMoney into Alkami because it helps members understand their finances in plain language. Early validation came from feedback loops. Member-facing teams shared real-world input, and a digital-banking-specific CSAT survey delivered a high response rate, confirming the same gaps leadership had already identified. (link)

2) State of Fintech 2026 hits an inflection point

The State of Fintech 2026 report from fintech analyst Simon Taylor argues the industry has crossed a structural threshold. Fintech is no longer “challenging” banks. It’s operating at bank-level scale. Taylor points to hyperscalers like Nubank, Revolut, and Robinhood, which now serve tens or hundreds of millions of users globally. Nubank grew from 110M to 127M customers, Revolut from 50M to 64M, and Robinhood has nearly doubled assets under custody, putting these firms firmly on the same axis as traditional banks.

AI is the second force driving the shift, and it’s already reshaping consumer behavior. Taylor cites data showing one in six Black Friday purchases was AI-assisted, and roughly 50% of consumers now use AI tools to research purchases before buying. That positions large language models as a new “pre-purchase decision engine,” potentially rivaling traditional search and ads.

The third inflection point is infrastructure. Stablecoin supply has surpassed $350B, with growth decoupling from crypto prices, signaling real payment utility rather than speculation. Most volume is coming from B2B payments, treasury, and card-linked use cases. At the same time, AI-driven “agentic commerce” is pushing payments into a fragmented, early-stage protocol war, as card networks, stablecoins, and new AI-native rails all compete to power automated transactions. (link)

3) University of Kentucky FCU’s playbook for AI governance and exams

Most Credit Unions still treat cybersecurity exams like a fire drill: you get the request list, everyone drops their day jobs, and the “evidence scramble” begins. Mike Sloan, AVP of Information Security at University of Kentucky Federal Credit Union, said UKFCU broke that pattern by moving to continuous compliance in late 2024, collecting artifacts throughout the year instead of racing at exam time. The payoff showed up in the 2025 exam. UKFCU delivered what examiners asked for, heard very little follow-up, and Sloan estimated the new approach saved ~12 hours across teams while keeping other departments from having to “drop what they’re working on” to chase documentation.

UKFCU applied the same mindset to AI: assume it’s not going away, and govern it before you scale it. Sloan said the Credit Union started with acceptable-use policies, then built employee training with its L&D team to make expectations operational (not just legal language). From there, UKFCU moved into monitoring and enforcement using Microsoft Purview, which tracks who is using AI tools and blocks or allows tools based on a defined risk score. Anything below an “8” risk score is unsanctioned and blocked. But tools above that are allowed as the team matures, with controls around which data is used in prompts.

Heading into 2026, UKFCU’s next step is to use AI to standardize and streamline vendor reviews, while strengthening SLAs and notification expectations so incident-response obligations are clear when something breaks. (link)

Tips & Use Cases

Learn to apply AI…

SELCO Community Credit Union modernizes internal knowledge with AI Knowledge Hub: SELCO is rolling out eGain’s AI Knowledge Hub and AI Agent to replace SharePoint with a single, governed source of truth for ~500 employees across branches, lending, and operations. The platform embeds directly into the Genesys agent desktop, improving onboarding, compliance visibility, and day-to-day decision support. (link)

IgniteFI outlines how AI helps Credit Unions compete with fintechs: AI is pushing Credit Unions beyond small pilots toward focused use cases tied to real member and operational needs, with success depending on strong governance and aligned fintech partners. CUSOs and consortium models enable smaller CUs to share AI capabilities, reduce risk, and free staff to focus on high-touch member service. (link)

How AI turns payments data into proactive member guidance: On Fintech Unleashed, Virginia Heyburn and Dr. Art Harper of Engage fi describe how AI drives real-time “next best offer” prompts, dynamic credit limits, and personalized rewards using a full, relationship-level view of the member. The same decisioning supports smarter fraud prevention, financial literacy journeys, and life-stage product recommendations powered by CRM systems. (link)

How CRM + AI turns member data into real-time action: AI transforms CRM from a static system of record into a system of action by cleaning data, surfacing next-best actions, and automating workflows across marketing, lending, and service. Institutions using AI-powered CRM ecosystems are already handling more volume with the same staff while improving approval speed, operating efficiency, and member satisfaction. (link)

Fraud and AI are now inseparable in financial services: New data from American Banker shows 53% of financial institutions rank AI and machine learning among their top five tech spending priorities for 2026, while 53% also prioritize enhanced security and fraud mitigation. Real-time payments fraud is expected to have the biggest negative impact on organizations this year. (link)

Why AI, crypto, and fraud are colliding faster than most institutions expect: Ron Shevlin and Stacy Bryant of Cornerstone Advisors describe AI, crypto, and fraud as the three biggest unknowns shaping 2026, with AI accelerating new fraud types when combined with tokenization and real-time payments. They caution that agentic AI isn’t ready for prime time due to data silos, pointing instead to coordination layers like MCP as the real unlock for real-time, AI-driven engagement. (link)

Why generic AI creates compliance risk, but regulated AI avoids it: General-purpose LLMs pose real regulatory risk by drifting into unauthorized financial advice, creating exposure around NCUA, TILA, and FFIEC rules. Meanwhile, interface.ai’s BankGPT platform uses NCUA-trained models, real-time compliance monitoring, and automated guardrails to deliver accurate, auditable responses. (link)

AI success depends on rebuilding banking architecture: AI will only deliver real advantage for banks and Credit Unions built on genuinely new, multi-cloud, intelligence-first architectures, not containerized legacy systems or workflow automation. Agentic banking, AI-native competitors, and new digital-asset business models will separate institutions that redesign from the foundation from those optimizing yesterday’s systems. (link)

SMBC Americas plans to use AI for scaling compliance and onboarding: SMBC Americas is deploying Fenergo’s AI platform to automate KYC, AML, and client lifecycle management, reducing manual reviews and accelerating onboarding as part of a multi-year transformation. (link)

What “AI loan approval” really means inside modern lending teams: Most AI loan approval systems combine rules-based checks, machine learning risk models, and AI agents that orchestrate document processing, fraud detection, and human escalation, rather than replacing underwriters outright. Platforms like Multimodal’s AgentFlow coordinate OCR, credit risk models, confidence thresholds, audit logging, and human-in-the-loop reviews to deliver faster, explainable, and regulator-ready loan decisions. (link)

How agentic AI helps Credit Unions boost member growth in 2026: Early deployments of Multimodal’s AgentFlow show up to a 17% lift in cross-sell conversions and a 12% reduction in churn by turning data, documents, and decisions into coordinated member journeys. As younger members flock to fintechs offering instant onboarding and cash incentives, agentic AI platforms enable CUs to automate digital account opening, deliver real-time funding offers, and personalize engagement at scale with full auditability. (link)

How AI reduces CRE risk without loosening credit standards: In commercial real estate lending, AI is improving visibility into gray-area deals and portfolio risk rather than replacing underwriter judgment. One regional bank using Blooma, a CRE intelligence platform, cut manual data entry by 80% across a $17B CRE portfolio. (link)

What regulators expect banks to prove before trusting an AI vendor: AI vendor selection now requires regulator-grade scrutiny, not traditional TPRM checklists. With nearly 50% of financial institutions piloting or deploying generative AI and 8-in-10 bankers worried about falling behind, regulators are focused on explainability, actionability, bias testing, and clear accountability, all of which fall on the institution. (link)

How agentic AI is separating growing Credit Unions from shrinking ones: While total CU assets rose $86B last year, membership growth is stalling, as the average member age climbs into the early 50s and younger consumers expect fintech-grade digital experiences. 75% of Credit Unions still run on legacy LOSs. Leaders are embedding agentic AI directly into onboarding, lending, and servicing to scale efficiently, retain institutional knowledge, and adapt faster as member needs shift. (link)

How much work AI can already do is higher than most realize: A new study from MIT finds AI can already perform tasks equivalent to 11.7% of total U.S. workforce activity (about $1.2T in wages), even though only 2.2% is currently visible in real-world deployment. (link)

How CFOs are using AI to challenge assumptions before decisions are made: A new AI “decision cockpit” reframes how finance teams use models by pushing back on assumptions while decisions are being formed. Instead of entering static inputs, CFOs can interact with AI that asks about timing, capital allocation, and risk trade-offs in plain language to surface flawed assumptions early. (link)

The biggest risk with GenAI is inaction: An analysis of 765 enterprise GenAI case studies found only 21% measured financial impact, even as model capabilities surge and costs collapse by orders of magnitude. Waiting creates asymmetric risk: teams that don’t act now may preserve cash short term, but face costly catch-up, talent gaps, and lost momentum if AI becomes a true differentiator. (link)

How AI agents are transforming wealth management workflows end to end: AI agents are moving wealth management beyond surface-level personalization by automating portfolio monitoring, client engagement, onboarding, and compliance reporting in real time. By handling data-heavy, repetitive tasks, these systems free advisors to focus on strategy and relationships while enabling firms to deliver more timely, personalized advice without adding headcount. (link)

Credit Unions winning trust in 2026 are pairing modernized branches with member-first AI: New research shows that 55% of consumers say more physical locations signal a more trustworthy financial institution. At the same time, AI adoption is paying off when tied to clear member value. (link)

How a product mindset turns digital banking into a growth channel: Credit Unions must stop treating digital banking as an IT project and start managing it as a continuously evolving product. By using behavior data, segmentation, and in-app guidance, institutions are increasing adoption, doubling CRM engagement, reducing support costs, and even preventing over $1.2 million in fraud. (link)

How AI is reducing false positives and speeding AML investigations: As transaction volumes rise, legacy AML systems are overwhelming compliance teams. Research from Wipro estimates 90-95% of traditional AML alerts are false positives. AI-driven monitoring and perpetual KYC are helping institutions surface real risk faster and investigate complex laundering patterns with fewer manual reviews. (link)

Funding Spotlight

Where the money is flowing for innovation…

Torq raises $140M Series D at $1.2B valuation: Led by Merlin Ventures, the round will help Torq expand its agentic AI platform that automates SOC alert triage, investigation, and response as cyber threats outpace human teams. (link)

Cyera raises $400M Series F at $9B valuation: Led by Blackstone, the round will help Cyera expand AI-native data security and governance across cloud, on-prem, and hybrid environments. The funding reflects rising enterprise demand for platforms that secure sensitive data while enabling large-scale AI adoption without increasing regulatory or trust risk. (link)

Blackbird.AI secures $28M to counter AI disinformation: The funding brings Blackbird.AI’s total capital to $58M as enterprises and governments respond to deepfakes, narrative attacks, and synthetic media threats. With 118% year-over-year ARR growth and expanding Global 2000 adoption, narrative intelligence is emerging as a new security layer focused on protecting trust, reputation, and decision integrity. (link)

OpenAI and SoftBank invest $1B in SB Energy to secure AI infrastructure: OpenAI and SoftBank Group are each committing $500 million as part of a deal that includes a 1.2 GW data center lease and a new flagship AI campus built and operated by SB Energy. (link)

Keeping up with Tech

The latest in fintech and tools…

Claude Desktop is becoming a hands-off work executor with Cowork: Cowork brings agentic workflows into Claude Desktop so users can hand off multi-step work like research, document creation, and file organization. It can access local files and run long autonomous tasks. (link)

Revolut launches AI-driven call verification to fight impersonation scams: Revolut’s new in-app call verification detects when a user is on a phone call and confirms whether the caller is a real Revolut agent or a scammer. The feature targets AI voice deepfakes, which only about 25% of people can spot. (link)

Plumery launches AI Fabric to help banks move AI from pilots to production:. AI Fabric uses an event-driven data mesh to connect AI models to live banking data with governance and auditability. The goal is to move AI from pilots to production while enabling real-time decisions inside digital journeys. (link)

Google’s Veo 3.1 makes AI video generation more production-ready: Google’s Veo 3.1 improves character and object consistency, supports vertical (9:16) video, and adds 1080p/4K upscaling. SynthID watermarks and in-app verification add traceability as AI video moves toward mainstream use. (link)

Fiserv and Mastercard expand partnership to support agentic AI: Fiserv and Mastercard integrated Mastercard’s Agent Pay Acceptance Framework into Fiserv’s acceptance stack to support agent-initiated payments. Tokenization, authentication, and fraud controls let AI-driven transactions run on existing card rails without exposing credentials. (link)

The state of generative coding in 2026: Coding tools like Copilot, Cursor, Replit, and Lovable are increasingly writing, testing, and debugging production code, speeding delivery for experienced teams. The risk shifts to governance, reliability, security, and less room for entry-level learning. (link)

Fiserv doubles down on AI with Microsoft: Fiserv is rolling out Microsoft 365 Copilot across its global workforce and expanding use of Azure-based Foundry to build, deploy, and govern AI applications at scale. (link)

Extend introduces Memory for example-based learning in document AI: Extend launched Memory, a visual retrieval system that lets document processors learn from validated layout examples instead of relying on increasingly complex prompt tuning. The update improves classification, splitting, and extraction accuracy over time, especially for visually driven edge cases that language alone can’t capture. (link)

Microsoft partners with PayPal and Stripe for Copilot AI shopping: Microsoft is rolling out Copilot Checkout, letting users complete purchases directly inside Copilot chat as discovery, checkout, and payment collapse into a single AI-driven flow. (link)

Where AI Apps are heading in 2026: As coding and automation become cheap and reliable, the constraint in AI-driven work is no longer speed of building but clarity of judgment. New AI apps are focusing on exploration, decision framing, and human-AI collaboration, positioning software as a thinking partner rather than just a faster way to execute. (link)

Allianz integrates Anthropic’s Claude to scale governed AI across insurance workflows:
Allianz is embedding Anthropic’s Claude models into its internal AI platform to support developers, automate claims processing, and document decisions for regulatory compliance. (link)

In Other News

Related news you can learn from…

• Big banks hold 75% of banking AI patents as genAI rises (link)

• AI inaction is now a competitive risk for banks and Credit Unions (link)

• Gen Z awareness gap threatens future Credit Union growth, survey finds (link)

• Danske Bank UK appoints Dr Fiona Browne as head of AI (link)

• TD Bank’s head of AI to speak on scaling enterprise AI at FinAi Banking Summit (link)

Community Corner

Memes and visuals…

@corporateweapon

Corporate Weapon on Instagram: "It’s so over"

Thanks for reading!

Until next week,

— Credit Union AI Guy

Enjoying this newsletter? Forward it to a colleague who might appreciate practical AI insights.

Have a question or want to share your own AI experiment? Reply to this email or connect with us on LinkedIn. We’re building a community of curious Credit Union professionals. Come join the conversation!

The catch? Many institutions still lack the integrated data foundation (core + digital channels + clean, accessible data) that AI needs, leaving a lot of opportunity on the table.

Today, I cover:

• Cobalt Credit Union achieves 83% session containment with Eltropy AI Voice

• ConnectOne Bank is using AI internally first while preserving white-glove service

• Why AI won’t ship on legacy cores

Read time: 7 minutes

Top Stories

The biggest news this week…

1) Cobalt Credit Union achieves 83% session containment with Eltropy AI Voice

Cobalt Credit Union serves 116,000 members, many of whom are military members stationed around the world, so 24/7 support isn’t a nice-to-have. Instead of jumping straight to voice AI, the Credit Union built toward it in phases: starting with video banking through POPi/o (now part of Eltropy), expanding into chat and text messaging, and only then layering in AI once members were already used to engaging digitally across channels.

That staged rollout continued in August 2024, when Cobalt launched its first AI intent-based assistant “Coby” alongside a new digital banking platform. Two months later, it added generative AI so Coby could handle a broader range of questions. The latest step, Eltropy AI Voice, completed the multi-channel strategy, now hitting a 83% session containment rate while being able to take actions, like handling authentication, processing transactions, and providing confirmation.

As Cobalt’s VP of Digital Banking Chasmine McIntosh put it, “[Coby] frees up our team to focus on the complex situations where members really need that human touch.” (link)

2) ConnectOne Bank is using AI internally first while preserving white-glove service

On the Banking Transformed Podcast, Jim Marous interviewed ConnectOne Bank’s Siya Vansia, where she explained why her team is starting with AI behind the scenes, not in front of customers. For the $14B commercial bank that’s quickly grown since being founded in 2005, their brand promise is “white glove service.” That’s why Vansia says they’re being deliberate about where AI shows up: “If we were to expose AI to our clients, we should be really thoughtful about it.”

So the first AI priority is internal: admin support, content creation, marketing, and research, aimed at eliminating the manual “zombie work” that eats up back-office time. Vansia also called out near-term value in stronger fraud monitoring and in using AI to scour internal data faster during high-stakes moments like a data leak. The point isn’t to bolt AI onto old workflows. It’s to reimagine a process, which is why she emphasized aligning teams on outcomes early and defining success up front with partners (“measure twice, cut once”). (link)

3) Why AI won’t ship on legacy cores

Temenos CPO Sai Rangachari has made a great point: banks aren’t struggling to “productionize AI” because AI is uniquely hard. They’re struggling because shipping anything is hard when your core is a constraint. As Jim Marous says, “you can’t operate a digital institution with a core system that hasn’t been updated since before the iPhone was introduced.”

Rangachari calls the current wave of pilots “innovation theater,” arguing many institutions can’t get any project to production, nonetheless AI, which is why “pilots at scale… never see the light of day.” Temenos says it’s investing in three buckets: 1) conversational copilots embedded inside banking products, 2) autonomous agents that start in “listen-only” and human-in-the-loop modes until trust is proven, and 3) AI that reduces upgrade/lifecycle pain by analyzing custom code and version changes.

His most concrete example: a financial crime mitigation agent at a Tier 1 European bank reportedly reduced false positives by ~30%, redeployed ~15-25 staff to higher-value work, and only moved to autonomy after achieving 99%+ accuracy through staged rollout. (link)

Tips & Use Cases

Learn to apply AI…

How Credit Unions and fintechs team up for AI-enabled banking: PYMNTS Intelligence finds 66% of FinTechs see Credit Unions as clients and 9 in 10 as collaborators. AI underwriting partnerships like Scienaptic AI + Kentucky’s Credit Unions show how CUs can modernize decisioning and expand access at scale. (link)

AI helps Credit Union marketers scale content without losing voice: Many Credit Union marketers use tools like ChatGPT for brainstorming, editing, repurposing content across channels, and jumpstarting research. But humans must stay in charge of strategy, final copy, and keeping confidential information out of public AI tools. (link)

4 AI imperatives for banking CMOs in 2026: BCG finds only 15% of marketing AI runs cross-functionally at scale, so CMOs should redesign end-to-end creative and media workflows. Agentic AI is expected to take ~20% of all marketing work within 2-3 years, pushing Credit Unions to reset agency roles and refocus teams on strategy. (link)

CRE lenders use AI to surface hidden risk, not loosen standards: Lenders are applying AI to flag grey-area deals, concentration risk, and early warning signals that traditional models miss, while keeping humans in the loop to meet regulatory and trust requirements. (link)

Cornerstone Advisors benchmarks Data EQ for AI readiness: A survey of 124 institutions finds Credit Unions score 271/500 on Data Execution Quality vs banks at 211/500. 35% already use chatbots, and 25% use generative AI, but the report warns weak data execution makes AI underperform. (link)

AI becomes a default work tool, but governance lags: A PYMNTS survey found about 70% of AI-using employees say their employer now encourages AI use, but only ~30% report mature controls for approvals, disclosures, and quality monitoring. (link)

How to level up your AI productivity in 2026: If you’re stuck at using AI as a “search substitute” like ~25% of users, you’ll only gain 1-3 hours/week. To reach 3-6+ hours/week, start every project by uploading context, go three follow-ups deeper, ask for alternatives, and force AI to flag risks and blind spots. (link)

How Credit Unions can run a 90-day AI readiness proof of value: Pick one workflow, connect knowledge + security guardrails, and pilot for 90 days, using decision gates before expanding into authenticated flows. Run pilots with 10-20% of self-service traffic. Aim for 30%+ containment, 90%+ grounded answers, ≤2% hallucinations, and 20% AHT cuts. (link)

GHS Federal Credit Union adopts Scienaptic AI for faster, more inclusive lending: GHS selected Scienaptic’s AI credit decisioning to speed approvals and move beyond single-score evaluations. (link)

How an internal “talent marketplace” can accelerate AI gains: At Standard Chartered, 60% of employees take short internal “gigs” that accelerate AI projects, creating $8.5M in value. Credit Union leaders can copy this by matching staff skills to AI pilots before hiring. (link)

Beware of AI-era security fraud risks caused by complacency: A PYMNTS report found companies lose an average 3.1% of annual revenue to identity verification failures, even as 96% believe their defenses are effective. “Good-enough” AI and bot controls can quietly increase fraud, onboarding drop-off, and trust erosion if not continuously tested and governed. (link)

Agentic AI will reshape banking across three tracks: More than 50% of financial institutions already use AI agents, but while banks see returns mainly in back-office efficiency (68%), only 32% get value from customer-facing AI. Meanwhile, fintechs embed agentic AI directly into products and customer journeys through full-service agents, adaptive experiences, and customer “agentic twins.” (link)

How to prepare for the risk of AI systems going offline at your bank: As AI runs fraud, AML, credit, and member service workflows, outages can halt approvals, stall fraud detection, or force compliance shutdowns. With 70% of large banks using chatbots, leaders should test whether “manual fallbacks” actually work at scale (link)

Bank of America uses AI copilots to make branches faster and lift digital sales: Erica Assist helps bankers find the right policy instantly, reducing mistakes and speeding service transactions. It also shares digital context across chat, phone, and branch to route customers to self-serve or an appointment, supporting a goal of 10M→30M appointments. (link)

CaixaBank’s new Artificial Intelligence Office will centralize oversight: The 100+ person team will oversee governance, operations, strategy, and culture across all AI use cases. (link)

CFOs say AI matters, but few are scaling it: In a survey of 5,000 global CFOs from Egon Zehnder, 44% rate AI “very important” to “critical,” yet less than 10% are scaling use cases due to data and talent gaps. 80%+ of AI use today sits in controllership (AP, AR, invoicing), with FP&A and treasury next. (link)

Funding Spotlight

Where the money is flowing for innovation…

xAI raises $20B Series E to scale AI infrastructure: Surpassing its $15B target, the funding will accelerate large-scale GPU infrastructure buildout and support continued development of Grok models, voice agents, and consumer and enterprise AI products. (link)

Pluto raises $8.6M seed round to use AI for lending against private assets: Pluto Financial Technologies is building AI-driven credit infrastructure that lets investors borrow against private equity and alternative assets using future fund distributions for repayment. (link)

Fireblocks acquires TRES Finance for $130M to bring CFO-grade controls to crypto assets: Fireblocks adds crypto accounting, reconciliation, and reporting by acquiring TRES Finance, giving CFOs visibility across wallets and platforms. (link)

Keeping up with Tech

The latest in fintech and tools…

Microsoft renames Microsoft 365 app to “Microsoft 365 Copilot”: Copilot integrates directly into Word, Excel, PowerPoint, and file workflows across web, mobile, and Windows. Office.com now redirects to m365.cloud.microsoft. (link)

OpenAI’s developer platform went agent-native in 2025: Reasoning-capable models, multimodal inputs (text, PDFs, images, audio, video), and new building blocks like the Responses API, Agents SDK, and Codex made it easier to run multi-step AI workflows in production. These changes make it more practical to deploy AI agents that read documents, use tools, manage state, and operate reliably inside real systems. (link)

In Other News

Related news you can learn from…

• Morgan Stanley forecasts AI will displace 200,000+ European banking jobs by 2030 (link)

• Most-read AI stories of 2025 show banks racing toward agentic AI (link)

• Agentic AI handles end-to-end member requests beyond chatbots (link)

• AI boosts creativity unevenly across teams using generative tools (link)

• CFOs tie AI spend to decision speed (link)

Community Corner

Memes and visuals…

Thanks for reading!

Until next week,

— Credit Union AI Guy

Enjoying this newsletter? Forward it to a colleague who might appreciate practical AI insights.

Have a question or want to share your own AI experiment? Reply to this email or connect with us on LinkedIn. We’re building a community of curious Credit Union professionals. Come join the conversation!

As 2026 begins, let’s take a look into a crystal ball to see what AI has in store for us.

I put together my top 10 AI predictions based on upcoming tech, use cases, and industry data:

1. AI stops being a pilot and becomes core infrastructure

2. Lending gets faster, more automated, and more dependent on data you can defend

3. Autonomous agents eat 40-60% of routine work

4. Personalization becomes a deposit-retention lever

5. Trust stops being a brand promise and becomes something you have to prove

6. Payments move to digital wallets + real-time rails

7. Fraud goes synthetic

8. Governance and explainability become the blocker… and differentiator

9. The workforce shifts to exception-handling and oversight

10. Data becomes the moat

Read time: 8 minutes

Top AI Predictions for 2026

What to expect from AI this new year…

1) AI stops being a pilot and becomes core infrastructure

Agentic AI is moving from isolated experiments to becoming the main engine of Credit Union operations as members expect AI-level speed and accuracy. As a result, workflows will need end-to-end agentic automation that can read documents, extract data, make preliminary decisions, validate compliance, and escalate exceptions to complete processes.

Nearly half of Credit Unions already use chatbots/virtual assistants, more than two-thirds plan to use AI-driven lending decisioning, and ~66% plan to use AI for credit decisioning. Yet fewer than 20% say their AI deployments are “enterprise-ready.” The ROI is already showing up as infrastructure-level wins: FORUM Credit Union drove a 70% increase in loan processing capacity with agentic AI for document classification and data extraction, Suncoast CU prevented $800,000+ in fraud in six months, Teachers FCU eliminated 8 million manual clicks (13,000+ staff days), and PSCU avoided $35 million in fraud losses.

The most competitive Credit Unions will run lending, fraud, servicing, and compliance on AI-powered workflows that are governed, explainable, and connected to clean data, because legacy cores, siloed systems, and weak AI governance won’t scale past pilots. (link)

2) Lending gets faster, more automated, and more dependent on data you can defend

AI-powered decision engines and agentic workflows are collapsing loan timelines from days to minutes, and in some cases, seconds. The catch is that this speed will only be sustainable for Credit Unions with clean, permissioned data and models that can be clearly explained to regulators.

Research from Celent commissioned by Zest AI shows 67% of lenders expect to have GenAI strategies in place by 2026, with 83% planning to increase GenAI budgets in consumer lending. More than two-thirds of Credit Unions plan to adopt AI-driven lending decisioning. But legacy cores, siloed data, and weak governance continue to limit how fast and safely many institutions can move.

Early adopters like Commonwealth Credit Union illustrate what 2026-ready lending looks like, having automated 70–83% of consumer loan decisions after modernizing underwriting with AI. (link)

3) Autonomous agents eat 40-60% of routine work

Autonomous agents will move beyond assistive automation and begin fully handling high-volume, rules-driven back-office work at Credit Unions. Projections now indicate agents will handle roughly 40-60% of routine banking tasks as workflows mature.

Gartner predicts 40% of enterprise applications will embed task-specific AI agents by 2026, up from under 5% in 2025. In production today, Grasshopper Bank reports agents autonomously handling about 70% of natural-language business queries, contributing to an 18% retention lift. Capital One has also evolved its Eno assistant from a chatbot into an agentic fraud system that resolves disputes and issues refunds without human intervention. Across financial institutions, autonomous agents are already delivering 20-35% operating cost reductions by removing manual steps from back-office workflows.

As agents absorb routine volume, CUs will need fewer staff doing repetitive processing and more staff supervising agents, investigating exceptions, auditing decisions, and improving workflows. (link)

4) Personalization becomes a deposit-retention lever

Personalization is becoming a practical deposit-retention tool as AI copilots and agents anticipate needs, automate money movement, and guide financial decisions in real time. The institutions that get this right will materially reduce deposit churn.

Research from Bain & Company shows proactive, context-aware personalization can lift engagement by 25-30% and keep balances higher with fewer account switches. Industry models estimate AI-driven personalization could retain roughly 15% more checking and savings balances (more than $200B across financial institutions).

Credit Unions that can orchestrate data, personalization, and payments across channels (while maintaining trust, governance, and transparency) will turn personalization into a durable moat. (link)

5) Trust stops being a brand promise and becomes something you have to prove

Trust now needs to be more than just marketing language. It must translate into operational requirements, as autonomous agents make real decisions at scale and regulators, members, and boards demand clear evidence of how decisions were made, with what data, and under which controls.

As Alex Kwiatkowski, Director of Global Financial Services at SAS, puts it, trust is moving from “model-driven” to “proof-driven” intelligence, where every prediction, decision, and interaction must be verifiable, explainable, and auditable. Regulators are reinforcing this shift by raising expectations around transparency, digital identity, fraud controls, and AI governance.

Credit Unions will be judged on how clearly they can show members and examiners why an AI system approved a loan, blocked a payment, flagged fraud, or routed a service request. Institutions that operationalize trust, through embedded audit logs, explainable models, continuous verification, and transparent fraud-resolution processes, will turn regulation into an advantage. (link)

6) Payments move to digital wallets + real-time rails

Payments continue to shift decisively toward digital wallets, real-time rails, and tokenized money movement, with AI agents increasingly initiating transactions on behalf of users. For many members, payments now happen inside wallets and embedded payment flows, with the financial institution operating in the background rather than as the primary interface.

As agentic commerce expands, disputes and fraud increase when autonomous agents transact or are hijacked by bad actors. Adam Neiberg of SAS warns institutions will need to authenticate not just people, but AI agents using techniques like agent tokens, behavioral signatures, and dynamic risk scoring. In parallel, regulated stablecoins, tokenized deposits, and real-time payment rails are entering live pilots for settlement and treasury, promising faster settlement, lower costs, and stronger auditability. (link) (link)

7) Fraud goes synthetic

Fraud is evolving from stolen credentials and basic social engineering to synthetic identities, deepfakes, agent-driven scams, and AI-powered ACH manipulation.

AI-driven fraud is scaling faster than traditional controls: deepfake-related fraud attempts have surged more than 2,100% over the past three years, and genAI-enabled fraud losses could reach $40B annually in the U.S. by 2027. Fraud teams now face disputes triggered by autonomous agents making unauthorized purchases and criminals hijacking or mimicking legitimate agents. At the same time, Nacha’s 2026 ACH rule changes and broader payments regulation are raising expectations for continuous monitoring, faster incident reporting, and stronger controls.

The most effective defenses will come from Credit Unions that leverage their proprietary transaction history, repayment data, and member behavior to spot patterns that synthetic fraud can’t easily fake. (link)

8) Governance and explainability become the blocker… and differentiator

As AI takes on more autonomous work in lending, fraud, and compliance, the hardest part will be proving decisions are fair, explainable, and controlled as regulatory scrutiny tightens.

A Deloitte survey shows governance pressure is rising fast: 38% of AI leaders say data residency/regional compute is very important, and 49% expect it to be a significant factor within the next 1-2 years. On the Credit Union side, the readiness gap is real: fewer than 20% of Credit Unions describe their current AI deployments as “enterprise-ready,” and uncertainty around explainability and fairness is explicitly cited as a top scaling challenge. On the compliance front, institutions that can show audit trails, change controls, model oversight, and defensible decisions will deploy faster and with more confidence. (link)

9) The workforce shifts to exception-handling and oversight

The “human job” inside Credit Unions will change materially as copilots and agentic systems take over routine tasks across lending, servicing, and back-office operations. Day-to-day work will shift away from manual processing and toward handling exceptions, reviewing edge cases, and overseeing risk, compliance, and model behavior.

Forecasts suggest copilots will be embedded in as much as 80% of enterprise applications by 2026, pushing everyday work toward AI-assisted execution with human judgment layered on top. At the same time, labor impact is becoming tangible. Research from MIT, cited in multiple industry outlooks, estimates that AI could replace roughly 11.7% of U.S. jobs (over $1T in wages) with disproportionate pressure on entry-level and repetitive-task roles. Analysts also point to the rise of “agent ops” teams: dedicated roles responsible for training, monitoring, and continuously improving AI agents because reliability is still shaky for full autonomy everywhere. (link)

10) Data becomes the moat

The competitive advantage in AI will come from having the cleanest, most defensible member and transaction data. As synthetic and AI-generated data become easier to produce, the risk is that data will pollute core systems in ways that are difficult to detect but costly to unwind.

Multiple 2026 outlooks point to the same conclusion: a solid model trained on proprietary, high-quality data will outperform a more sophisticated model trained on generic inputs. Repayment histories, transaction patterns, and local market signals are hard to replicate and uniquely valuable to Credit Unions. But that advantage flips into risk if the data foundation is compromised. Synthetic data and GenAI can introduce errors and bias at scale, contaminating credit, fraud, and risk pipelines.

At the same time, previously unusable data is becoming more actionable: AI knowledge agents can access the 80%+ of enterprise data that sits in unstructured formats like text and images, growing 50-60% per year. Winners will unify and govern their data so it can safely power underwriting, fraud detection, and member-facing decisions at scale. (link)

Tips & Use Cases

Learn to apply AI…

Optiri outlines “intentional AI” readiness for Credit Unions: The IT company’s COO & CRO Shane Butcher argued that AI is already embedded in everyday tools, so Credit Unions should focus on data visibility, permissions, vendor policies, and 1-2 high-value use cases instead of chasing hype, especially as AI reshapes both cyber threats and defenses. (link)

Automated underwriting becomes a pillar of Credit Union lending strategy: CU loan balances are projected to grow just 4.5% this year (below the 7% average) before rebounding in 2026. To prepare, CUs are adopting automated decision engines to handle complex data, deliver minute-level approvals, and keep delinquency rates flat or improved while reducing manual underwriting bottlenecks. (link)

Smaller banks lag in GenAI adoption but find gains through internal use cases: Temenos data shows 79% of banks over $250B in assets have GenAI live or planned, compared to just ~40% of banks under $10B. At Grasshopper Bank, internal GenAI use cut repetitive lending follow-ups from two to three hours per loan to two to three minutes, showing how smaller institutions can start with lower-risk, staff-facing workflows. (link)

AI role-play helps Credit Unions pressure-test AI strategy: Try using an AI chatbot to role-play as an executive, member, service rep, or regulator to surface blind spots around trust, access, and where automation helps versus harms the member experience. (link)

How to use the “Frontier Firm” framework to scale AI beyond pilots: Generative AI could unlock up to $340B in annual banking value, with AI-driven banks already seeing 20% productivity gains and 40% fewer fraud false positives as industry AI spend grows to $97B by 2027. ABN AMRO, Ally Financial, and UBS show the Frontier Firm approach in action by starting with AI assistants for staff, progressing to human-led agents, and selectively automating workflows without giving up control. (link)

Why GenAI projects show fast demos but struggle in real-world rollout: Generative AI makes it easy to build impressive prototypes quickly, but many initiatives stall later when teams discover the data, workflows, testing, or staffing aren’t ready to support production. Stay focused on solving real business problems early, so promising demos turn into tools that actually work at scale. (link)

Keeping up with Tech

The latest in fintech and tools…

Visa and Fiserv expand agentic AI payments: Fiserv will enable Visa Intelligent Commerce and Trusted Agent Protocol across their merchant networks, allowing AI-driven transactions with built-in bot detection, consumer authorization, and checkout validation. Similar agentic payment protocols are also rolling out from Mastercard, Stripe, and PayPal, increasing pressure on banks to prepare for AI-initiated payments. (link)

Google rolls out December AI updates focused on speed, verification, and translation: Google launched Gemini 3 Flash across the Gemini app and Search for faster reasoning at lower cost, added AI video verification using SynthID watermarks, and introduced live speech translation in Google Translate across 70+ languages. (link)

Google highlights AI agents and reasoning breakthroughs in 2025 review: 2025 was the year AI began reasoning and acting through agentic systems, led by Gemini 3 and Gemini 3 Flash, with major gains in multimodal understanding, speed, and efficiency. The impact includes 20%+ productivity gains in AI-driven workflows and rapid adoption of AI across science, products, and infrastructure. (link)

In Other News

Related news you can learn from…

• High-agency CFOs focus on decision systems over AI outputs (link)

• Top AI stories of 2025 show where banking innovation is heading (link)

• Job-simulation academies build AI-ready talent outside traditional pipelines (link)

Community Corner

Memes and visuals…

(link)

Thanks for reading!

Until next week,

— Credit Union AI Guy

Enjoying this newsletter? Forward it to a colleague who might appreciate practical AI insights.

Have a question or want to share your own AI experiment? Reply to this email or connect with us on LinkedIn. We’re building a community of curious Credit Union professionals. Come join the conversation!

A LOT has happened this year… some really big news, some less.

So, I picked the biggest AI wins with real, tangible results:

1. Commonwealth CU automates 70%+ of consumer loan decisions

2. WEOKIE FCU saves $800K per year by automating 66% of calls

3. Heritage FCU drives 2.5x loan growth

4. Capitol CU of Texas grows new membership 59%

5. Nutmeg State FCU automates 97.6% of back-office work

6. Sound CU saves $15K+ per month with 24/7 AI self-service

7. Towpath CU grows revenue 15% YoY

8. 3Rivers FCU takes down 250+ phishing sites in minutes

9. Verity CU lifts approvals 235% across protected classes

10. First City CU cuts early-stage collections costs 54%

Read time: 9 minutes

Top Stories of 2025

The biggest news this year…

1) Commonwealth Credit Union automates 70%+ of consumer loan decisions while cutting delinquency 30%

Commonwealth Credit Union, a $2.2B CU serving 120,000 members, needed to lend faster and more consistently while managing risk. Meanwhile, experienced underwriters became harder to retain, and member demand for instant decisions increased.

After modernizing its lending decisioning, Commonwealth saw:

• 70-83% of consumer loan decisions automated

• 30-40% lower delinquency compared to traditional scoring models

• 340% increase in automation for auto and personal loan decisions

• $324M+ in consumer loans approved across 18,000+ loans since 2021

What changed behind the scenes: Commonwealth implemented Zest AI underwriting across auto, credit card, and personal loans, integrated AI decisioning into its digital application flows, and expanded automation to pre-screen, pre-approve, and manage risk at scale. (link)

2) WEOKIE Federal Credit Union saves $800K per year by automating 66% of calls

WEOKIE Federal Credit Union, with 64,000 members, was facing surging call volumes, up to 30-minute hold times, and rising agent burnout just as its legacy phone banking system was being discontinued. With 20,000-25,000 calls per month and high staff attrition, expanding headcount wasn’t sustainable. But member experience was at risk.

After upgrading from IVR to AI-powered voice automation, WEOKIE achieved:

• 66%+ of incoming calls automated

• Member wait times reduced to under 30 seconds

• 9,000+ after-hours calls handled per month

• $800,000 saved annually in staffing and operational costs

• Significant reduction in agent burnout and turnover

• 24/7 member support without adding headcount

To drive those results, WEOKIE rolled out a phased Voice AI deployment with interface.ai that automated high-frequency inquiries, integrated securely with core systems, and routed complex issues to agents with full context. (link)

3) Heritage Federal Credit Union drives 2.5x loan growth after exceeding 151% of its annual target

Heritage Federal Credit Union, with ~$1B AUM and 65,000 members, was constrained by legacy contact center tech that left agents buried in low-value calls, limited service-level improvements, and made scaling growth without hiring nearly impossible. The contact center was operating defensively, focused on keeping up rather than driving revenue.

After shifting to an AI-powered contact center model, Heritage unlocked:

• 2.5x year-over-year increase in loan volume

• 151%+ of annual loan growth target achieved

• 2x more member volume handled with no additional headcount

• 20% improvement in workforce efficiency

• 100% of member interactions automated or AI-enhanced

• 18% reduction in average handle time

• 16% increase in service levels

So what did they actually do? Heritage replaced its legacy CCaaS with Glia Voice and AI agent Heidi. Then, they deployed Glia Digital across web, SMS, digital banking, and voice, using AI to deflect calls and free up agent time. (link)

4) Capitol Credit Union of Texas grows new membership 59% and makes digital its #1 account-opening channel in 90 days

Capitol Credit Union of Texas needed to move beyond an aging membership and compete for younger, digital-first members, but its existing account-opening experience couldn’t scale or show which marketing investments were actually working.

Once digital account origination was rebuilt around automation and analytics, Capitol saw:

• 59% increase in new memberships (vs. prior three months)

• ~$10,000 in average new deposits per new member

• 70% reduction in employee processing time

• Digital became the #1 channel for new accounts within 90 days

• Faster onboarding with improved fraud controls

Behind the lift, Capitol got rid of its legacy account-opening stack for Cotribute’s digital account origination and decision intelligence platform. Now, back-office reviews are automated, Jack Henry Symitar is integrated, and analytics are used to scale growth. (link)

5) Nutmeg State Financial Credit Union automates 97.6% of back-office work and enables instant decisions for 89.5% of applications

Nutmeg State Financial Credit Union was dealing with rising fraud attempts, low conversion rates, and heavy operational strain from manual reviews that slowed decisions and overburdened staff. As application volume grew, the existing process increased both cost and error risk.

Once account and loan processing was restructured around rules-based decisioning, Nutmeg State saw:

• 97.6% of manual back-office processing steps automated

• 89.5% of account opening applications decisioned instantly

• Fewer fraudulent applications reaching staff review queues

Behind the scenes, Nutmeg State moved high-volume loan, membership, and deposit applications onto Cotribute’s decision intelligence platform. Cotribute uses 40+ rules to route applications into auto-approval, auto-denial, or manual review queues, reducing reliance on manual processing. (link)

6) Sound Credit Union saves $15K+ per month by launching 24/7 AI self-service

Sound Credit Union, with $3B in assets and 26 full-service branches, was struggling with inconsistent answers, rising chat abandonment, and limited staffing that made it risky to expand into mobile chat without hurting service levels. As digital demand grew, the Credit Union needed a way to scale support across channels without adding headcount.

After rolling out AI-powered self-service, Sound CU achieved measurable gains:

• 77% of member inquiries fully resolved without a live agent

• Wait times cut from 1.5 minutes to 19 seconds

• Chat abandonment reduced from 4.8% to 1.3%

• 3.5 FTE per month avoided, saving $15K+ in monthly staff costs

• Member satisfaction jumped from 4.0 to 4.4 out of 5

Sound CU achieved these results by deploying Posh across web, online banking, and mobile banking using prebuilt AI topics and a single unified platform that requires under two hours per month to maintain. (link)

7) Towpath Credit Union grows revenue 15% year over year after a one-day digital banking overhaul

Towpath Credit Union, a $205M Credit Union serving 25,000 members, was held back by digital gaps that risked frustrating members, slowing growth, and limiting engagement. Leadership needed a modern digital foundation that could scale relationships beyond just transactions.

Following a full-stack digital conversion, Towpath saw:

• 15% year-over-year revenue growth

• 8.7% year-over-year loan growth

• 9.5% year-to-date growth in new account holders

• Digital banking adoption increase from 40% to 57%

• Products per member growth from 1.7 to 2.4

• Efficiency ratio improvement from 83% to 81%

Towpath completed a one-day, full digital conversion with Alkami, centralizing digital banking, onboarding, data-driven marketing, and financial wellness tools into a single platform. Then, they used member data to drive engagement and recapture wallet share. (link)

8) 3Rivers Federal Credit Union takes down 250+ phishing sites in minutes with automated fraud response

3Rivers Federal Credit Union, with $2.47B in assets and 106,000 members, was dealing with a surge in phishing attacks that led to account takeovers and heavy manual work to remove fake websites and mobile apps. The fraud team needed a faster way to neutralize threats without tying up staff.

With automated phishing detection and takedowns in place, 3Rivers reported:

• 250+ phishing sites, fake apps, and social accounts taken down

• Takedowns typically completed in under 15 minutes

• Reduced manual workload for fraud and digital teams

• Fewer active phishing threats targeting members

• Improved member communication around fraud trends

3Rivers centralized phishing reporting through Alkami and routed takedowns to Appgate, allowing suspicious sites to be flagged, ticketed, and removed quickly while using reporting data to proactively educate members. (link)

9) Verity Credit Union lifts approvals 235% across protected classes with inclusive AI underwriting

Verity Credit Union, an $859M CDFI with 40,000 members, was constrained by generic credit scoring models that excluded qualified borrowers, introduced bias into decisioning, and limited its ability to expand inclusive lending programs. To stay true to its “People, Planet, Prosperity” mission, Verity needed faster, fairer underwriting without increasing risk.

With AI underwriting in place, Verity reported:

• 235% average jump in approvals across protected classes

• 84% more instant credit card approvals

• 100% more instant auto loan approvals

• 69% more in instant personal loan approvals

• Significant approval gains across underserved segments, including seniors (271%), women (194%), and minority borrowers (158%-375%)

The key: Verity replaced generic credit scoring with Zest AI underwriting across auto, personal loan, and credit card portfolios, embedding AI decisioning directly into its LOS. (link)

10) First City Credit Union cuts early-stage collections costs 54% by shifting reminders from calls to automated texts

First City Credit Union, with $900M in assets and 56,000 members, was spending nearly $90,000 per year on third-party collection calls for early-stage delinquencies. The calls were costly, uncomfortable for members, and pulled staff away from higher-value recovery work.

Once early-stage collections moved from phone calls to automated texting, First City achieved:

• 54% reduction in third-party collections costs

• ~$48,000 in annual savings

• Very low opt-out rates from members

• Increase in member compliments to loan servicing staff

• Collectors freed up to focus on complex recoveries

First City shifted early-stage collections to automated text campaigns using Eltropy and integrated those workflows with Akuvo, triggering reminders based on delinquency status and embedding payment links directly into messages. (link)

Tips & Use Cases

Learn to apply AI…

Reseda Group partners with Constant AI to automate loan servicing: The CUSO is expanding its fintech marketplace for Credit Unions with digital self-service for loan requests like payoff quotes, deferrals, and due date changes. Constant AI says 30-40% of loan operations capacity can be automated. (link)

4 Credit Union AI priorities for 2026: Credit Unions must move from isolated AI pilots to enterprise strategy, focusing on algorithmic lending, back-office automation, Gen Z onboarding, and AI-driven fraud defense. Efficiency and member trust must scale together in an AI-first operating model. (link)

6 traits of the 2026 Credit Union member: Members will be more anxious, more selective, and less tolerant of friction, expecting personalization, simplicity, and real human guidance alongside digital convenience. To stay relevant, Credit Unions must simplify experiences, act hyperlocal, and build true relationships. (link)

Why agentic AI adoption stalls without trust: Even as interest grows, 98% of product leaders aren’t ready to give AI agents access to core systems, and 75% cite governance and security risks. Reliable, well-controlled automation (not budget) is the real prerequisite for trusted AI decision-making. (link)

Firms that use AI for client-facing value will beat those that only focus on efficiency: You can use AI to cut costs and run leaner, or you can productize it to deliver client-facing insights, personalization, and new revenue. Firms that only optimize operations may survive, but those that turn AI into something clients value are the ones positioned to grow. (link)

How to build a budgeting review app with ChatGPT 5.2 in 5 minutes: Turn budget reviews from slow, messy meetings into fast decisions by using this ChatGPT prompt to structure assumptions, surface tradeoffs, and flag risks instantly. (link)

Barclays tests AI platform to turn sustainability into profit insights: Starting in early 2026, Barclays will pilot ExpectAI’s Una platform, which builds digital twins that model how a small or medium-sized business operates so leaders can test energy and cost changes before acting. (link)

Bunq upgrades its AI assistant to handle member support: The neobank’s upgraded GenAI assistant, Finn, now handles about 97% of support interactions using real-time speech-to-speech, answering everyday questions like monthly spending instantly. (link)

BBVA launches “The Eight” to embed AI across the entire bank: The roadmap includes six AI “robots” covering customer service, relationship managers, risk, operations, software development, and employee productivity, supported by shared data and AI architecture. The strategy moves beyond isolated automation toward AI that anticipates needs, personalizes at scale, and improves decisions across the organization. (link)

How CX and compliance can converge to fight attrition: About 13% of retail bank customers are considering switching primary institutions, often through “soft switching” that goes unnoticed. Use AI to turn compliance functions like fraud prevention, identity verification, and complaint analysis into proactive CX advantages that build trust and reduce churn. (link)

Dext finds businesses are losing money by using general AI for financial advice: A survey of 500 UK accountants found that 50% have seen clients lose money due to bad AI advice. 77% have seen increased use of AI tools, and 72% have seen clients challenge professional guidance with AI. Meanwhile, 40% spend 4-10 hours a month fixing AI errors. (link)

Cornerstone Advisors says 2026 will push AI into vendor workflows: 2025 focused on conversions and core modernization, but 2026 will be defined by AI embedded directly inside core, payments, lending, and workflow vendors. The real AI strategy will come less from in-house systems and more from how effectively vendors bake AI into everyday systems. (link)

Credit Union fintech leaders say AI, real-time payments, and embedded lending defined 2025 and set 2026 priorities: In 2025, Credit Unions moved AI from experiments into lending, underwriting, and back-office workflows while pushing real-time payments and embedded finance. Heading into 2026, the focus shifts to AI-first strategies, hyper-personalization, trusted fintech partnerships, and balancing automation with human oversight. (link)

Manual AI compliance is becoming a growth bottleneck: As AI use accelerates, 95% of financial institutions report rising model risk requirements, yet 60% still rely on manual compliance. Model documentation involves an average of 29 people per institution, sometimes more than 50, while 87% plan to adopt automated model documentation within two years to keep pace with regulation and innovation. (link)

Funding Spotlight

Where the money is flowing for innovation…

Thread Bancorp raises $30.5M to scale embedded banking model: The parent of Thread Bank closed a $27.6M round plus a $2.9M extension led by Portage Ventures to expand its embedded banking and digital branch strategy. Thread now manages over $2B in partner deposits and saw roughly 75% annualized growth in embedded deposits. (link)

OnCorps AI raises $55M growth round for agentic fund operations automation: The platform autonomously investigates and resolves exceptions across trade reconciliations, fund accounting, and financial reporting reviews using AI agents trained on millions of real-world discrepancies. Firms representing $13T in assets use the system to cut manual effort as operating margins compress. (link)

Adaptive Security raises $81M Series B to counter AI-driven impersonation attacks: The funding led by Bain Capital Ventures backs expansion of a human-layer security platform that detects and mitigates deepfake voice, video, text scams, and AI-powered phishing that bypass traditional controls. Adaptive has grown to 500+ enterprise customers in under a year and reports a 94 NPS. (link)

FINNY AI closes Series A to automate financial advisor prospecting with AI: The platform uses AI to identify high-intent prospects, automate outreach, and prioritize leads using money-in-motion signals like liquidity events and career changes. FINNY says advisors generate an average of $7.7M in new client assets annually with near-zero acquisition costs. (link)

Keeping up with Tech

The latest in fintech and tools…

The state of consumer AI usage: Despite dozens of launches in 2025, usage and spending are concentrating around one primary AI per user. ChatGPT leads with roughly 800-900M weekly users, while Gemini is growing fast but still trails on engagement and retention. (link)

BlackLine acquires WiseLayer to embed AI agents into finance operations: BlackLine is acquiring WiseLayer to integrate its AI accounting agents, which automate judgment-heavy tasks such as accruals, revenue recognition, and payroll. (link)

Ani Tech launches AI command center to run financial advisor workflows: Ani Pulse, an AI-driven command center that sits on top of existing CRMs to proactively prioritize daily actions, automate admin tasks, and monitor firm health. The system replaces static dashboards with autonomous, real-time workflow orchestration. (link)

OnePay joins Google’s AP2 to secure agentic AI payments: OnePay joined Google’s Agent Payments Protocol to enable AI agents to transact with clear user authorization, secure credential reuse, and transparent financing options. The move aims to keep AI-led commerce aligned with human intent and control. (link)

Visa and Aldar complete first live agentic payment using AI: Visa and Aldar executed a real-world AI-led payment, allowing customers to pay service charges via a voice-enabled AI agent using tokenized Visa credentials. (link)

TCS upgrades BaNCS core with built-in AI agents: Tata Consultancy Services launched BaNCS AI Compass, embedding machine learning, generative AI, and pre-built agents directly into its banking core. The upgrade lets institutions deploy explainable, governed AI across onboarding, underwriting, servicing, and risk workflows without rebuilding systems. (link)

PayPal positions itself as the infrastructure layer for AI shopping: PayPal is building a single integration that lets merchants sell through AI assistants like ChatGPT and Gemini without managing multiple protocols. (link)

Google rolls out Gemini 3 Flash to bring faster AI at lower cost: Gemini 3 Flash is a new model that combines frontier-level reasoning with significantly faster speed and lower pricing. It’s now the default model across the Gemini app, Search AI Mode, and developer platforms. (link)

OpenAI releases GPT-5.2-Codex for long-horizon, agentic coding: The new Codex model improves large refactors, migrations, and real-world software engineering with stronger context handling and cybersecurity performance. (link)

OpenAI strengthens security for ChatGPT’s web-browsing AI: ChatGPT Atlas, OpenAI’s feature that lets an AI agent browse websites and take actions online on a user’s behalf, updated to better block hidden instructions on webpages or emails that could trick the AI into doing the wrong thing. (link)

In Other News

Related news you can learn from…

• ChatGPT mobile app consumer spending tops $3B (link)

• AI could displace banking jobs without causing mass unemployment (link)

• Anthropic publishes public AI risk framework to comply with California (link)

• NIST releases AI cybersecurity profile to align AI risk with existing security frameworks (link)

• AI transformation in financial services will hinge on agents, talent, and governance in 2026 (link)

Community Corner

Memes and visuals…

Thanks for reading!

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— Credit Union AI Guy

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America’s Credit Unions is pushing regulators for balanced oversight, and this week's case studies show what works in practice.

If you’re new here, I find the hottest AI news for Credit Unions to bring you practical insights in a quick, digestible weekly newsletter.

Today, I cover:

• CPM Federal Credit Union drives 32% more accounts opened with Cotribute

• Cornerstone lays out a practical AI playbook for Credit Unions

• Meridian Trust FCU books $22M in new loans using AI underwriting

Read time: 9 minutes

Top Stories

The biggest news this week…

1) CPM Federal Credit Union drives 32% more accounts opened with Cotribute

Many Credit Unions lose would-be members before the relationship even starts, all due to a high-friction digital onboarding experience that feels like a branch process shoved onto a screen. On a recent CU 2.0 podcast with Kathy Richardson, VP of Digital Products and Services at CPM Federal Credit Union and Cotribute CEO Philip Paul, Richardson explained how their COVID-era setup was stalling online growth. So CPM FCU (about $650M in assets) partnered with Cotribute to redesign their digital onboarding flow.

Instead of duplicating branch steps, the platform automates identity checks, fraud signals, and decisioning automatically, while letting CPM’s own team configure flows, copy, and screens without filing IT tickets. Cotribute moved so quickly on integrations and baseline setup that CPM actually asked to slow down while internal vendor reviews caught up, a rare problem for any CU tech vendor.

The results followed fast: a 32% increase in new accounts in 90 days, an 82% reduction in manual reviews, and significant staff time freed from post-fraud cleanup. CPM tested the new flow through a soft launch in branches, where staff walked members through the experience while keeping a fallback to the old core process if anything broke. The flow works consistently across desktop and mobile, and identity verification uses a QR-code handoff to mobile via Plaid, drastically reducing “stuck” moments and contact-center calls. (link)

2) Cornerstone lays out a practical AI playbook for Credit Unions

Cornerstone Advisors released a detailed AI playbook aimed squarely at banks and Credit Unions that feel pressure to “do something with AI” but aren’t sure where to start. Instead of pitching enterprise-wide transformation, the playbook urges leaders to pick just 1-3 concrete AI use cases per business unit (finance, operations, lending, retail, digital, IT, or marketing). Then, deploy, iterate, and learn. The focus is on leveraging tools already in use today, including three types of AI: supervised and unsupervised machine learning, and robotic process automation.

Across roles, the examples are intentionally realistic. CFO teams are using AI for financial reporting, reconciliations, variance analysis, and early credit risk monitoring. Operations leaders are automating scorecards, quality control, data extraction, and internal documentation. Lending teams are applying AI to pipeline reporting, pricing, credit decisioning, and early-warning systems for default, while marketing and digital teams use AI for segmentation, personalization, chatbots, and retention. Throughout the playbook, Cornerstone repeatedly flags governance risks — emphasizing explainability, bias controls, and regulatory compliance as non-negotiables. (link)

3) Meridian Trust FCU books $22M in new loans using AI underwriting

In a recent webinar, Meridian Trust Federal Credit Union shared how it embedded Scienaptic AI directly into the Sync1 loan origination system to modernize underwriting, especially for borrowers in the “messy middle” (like marginal and thin-file applicants). Instead of relying on variable human-only reviews, the setup pulls bureau data first, then taps core and alternative data only when needed, returning fast, consistent recommendations that underwriters can act on.

Meridian paired the AI rollout with operational changes like centralized underwriting, a migration to Sync1, and expanded access to deeper core insights to support better, faster decisions. The payoff showed up during a summer auto campaign, when the CU processed an additional 1,100 applications and booked $22M in new loans over roughly three months, while keeping human-in-the-loop decision turnaround under 30 minutes even before re-enabling full auto-decisioning.

Compliance was built into the foundation with explainable decisions, continuous fair-lending testing, and fully documented model parameters to keep the system audit-ready and reduce disparate-impact risk. (link)

Tips & Use Cases

Learn to apply AI…

We Florida Financial Credit Union automates 58% of calls with voice AI: Anticipating a surge in call volume, the CU deployed Interface.ai’s Voice AI to handle balance checks, transaction history, password resets, and card issues, replacing a limited IVR system. The rollout also reduced support staffing needs by 19% and maintains a 90-95% answer rate. (link)

Member Business Financial Services uses Microsoft Copilot to scale business lending without adding staff: The CUSO CEO Mark Ritter says only about 800 U.S. CUs do even minimal member business lending, a number that hasn’t moved in 10 years, with most growth concentrated among the top ~150 lenders. MBFS is “very deep” in Copilot as its entry point to AI, using it to speed up simple, repeatable back-office work so experienced lenders can focus on complex deals while keeping headcount flat. (link)

KEMBA Financial Credit Union grows deposits 37% by converting indirect auto borrowers into primary members: KEMBA used relationship-based pricing to encourage indirect auto loan borrowers to open checking accounts and deepen their relationship by offering better rates. After a 6-8 month rollout, the CU also reported ~40% higher checking penetration and ~15% more engaged members in its indirect program. (link)

Red Rocks Credit Union debuts voice AI assistant: “Roxie,” powered by Interface.ai, delivers 24/7 phone-based support for routine requests like balance checks, transaction history, and branch information using secure multifactor authentication. Red Rocks expects the AI to handle more than half of routine inquiries by year-end. (link)

Speed, not size, is becoming banking’s AI advantage: PwC reports that 58% of banking leaders see generative and agentic AI as the most transformative force over the next three years, and 55% already rank it as their top investment priority. At the same time, 90% say they lack the capabilities needed for tomorrow, while only 25% prioritize workforce reinvention. (link)

Credit Unions keep digital banking knowledge in-house more than banks: Survey data shows 63% of CUs say internal staff manages most digital banking platform details with provider support, compared with 55% of banks. Meanwhile, banks are nearly twice as likely to rely primarily on providers (41% vs. 22%). (link)

Use AI as a strategic advisor with the PCACI method: Securityplus Federal Credit Union CIO Ray Ragan says executives can use tools like ChatGPT, Gemini, and Claude as strategic consultants by structuring prompts around Persona, Context, Ask, Constraints, and Interviews (PCACI). This helps leaders pressure-test strategic plans, model scenarios, and identify gaps in talent and execution. (link)

AI-driven document intelligence cuts underwriting from weeks to hours: Purpose-built lending AI replaces manual PDF review by instantly classifying, extracting, and validating data across bank statements, tax forms, SBA documents, appraisals, and contracts. Platforms like Uptiq go beyond OCR by flagging missing documents, inconsistencies, and fraud signals. (link)

Finance roles are shifting from reporting to AI-assisted judgement: Institutions like JPMorgan (with 700+ AI-related roles) and Morgan Stanley are restructuring finance teams around AI leverage, while manual, spreadsheet-heavy work continues to disappear as AI handles reconciliation, forecasting, and summarization faster and more reliably. The emerging role for finance leaders is translating AI outputs into clear decisions and narratives. (link)

Agentic AI makes banking more human by removing service friction: Agentic AI can resolve routine requests end-to-end, understand context, and escalate to humans at the right moment, eliminating the tradeoff between automation and empathy. For example, at Navigator Credit Union, Interface.ai’s Voice AI now handles common inquiries so staff can focus on fraud, lending, and high-touch conversations. (link)

Gemini 3 Pro uncovers $30K in hidden vendor savings: Wouter Born explains how he used Gemini 3 Pro to spot duplicate vendor records (like multiple “AWS” entries) that fragment spend totals. The workflow pairs an LLM-powered interface with deterministic fuzzy matching inside a private app that keeps sensitive finance data in-house. (link)

Experian’s Molly Poppie explains why AI in finance lives or dies by data quality: AI’s impact in lending depends less on advanced models and more on fresh, complete data like cash flow, income, and BNPL signals. 95% of financial institutions report rising model risk management scrutiny, while 60% still rely on manual processes that consume up to 30% of staff time. (link)

OceanFirst Bank cuts AML and portfolio analysis time with Microsoft Copilot: OceanFirst has onboarded 150 employees to Microsoft Copilot, using it to speed up anti-money-laundering investigations and investment analysis after a major data cleanup effort. AML reviews that once took 6-8 hours can now be done in minutes, while bond portfolio analysis has dropped to about 15 minutes. (link)

CFOs use AI for core finance tasks but keep humans in control of big decisions: A PYMNTS Intelligence survey found all CFOs (60 surveyed) at $1B+ companies now use AI for at least one finance function, with nearly half applying it to continuous cash-flow tracking and many using it for audit readiness and data governance. But only 22% use AI for cross-system workflows, showing CFOs still want a human hand on the wheel. (link)

JPMorgan Chase outlines its push to become an AI-connected enterprise: JPMorgan is rolling out an internal “LLM Suite” that connects models from OpenAI and Anthropic to its proprietary data, already delivering productivity gains like generating investment banking decks in seconds. But fully integrating AI across thousands of systems will still take years, even with an $18B annual tech budget.(link)

AI is no longer optional for Credit Unions: LaMacchia Group says AI has become a competitive necessity for Credit Unions, driving gains in member service, fraud prevention, and lending. The firm points to near-term use cases such as conversational AI and AI-assisted underwriting, supported by robust data governance. (link)

How AI could make Credit Unions the unexpected winners: AI removes the tradeoff between efficiency and member experience by automating routine work and freeing staff to focus on high-value member interactions. This gives CUs a realistic way to compete with fintechs and big banks while leaning into their community and human advantage. (link)

AI fatigue is pushing customers back toward human-centered institutions: Only 17% of U.S. households say they’re very comfortable with AI-driven banking. Community banks and Credit Unions are gaining ground by using digital tools to reduce friction and focusing on empathy, continuity, and local understanding. (link)

How Lloyds Banking Group AI is reshaping traditional banking from the inside: Lloyds is using generative AI to search unstructured data across chats, calls, and documents, with a knowledge chatbot now used by 11,000 employees supporting 28 million customer calls a year. The biggest bottlenecks are data quality and building flexible architecture with agentic AI and humans-in-the-loop. (link)

Beware of AI prioritizing consensus over original insights: Most organizations use AI to double down on what already worked, helping everyone reach the same “safe” conclusions faster instead of uncovering new opportunities. The real advantage comes from using AI to flag what looks different or risky, then relying on human judgment to decide what truly matters. (link)

5 unavoidable tensions leaders face as AI enters the workplace: AI adoption is a balancing act among 1) experts vs. novices, 2) centralized vs. decentralized control, 3) flatter vs. taller organizational structures, 4) moving fast vs. protecting slow, thoughtful work, and 5) top-down change vs. peer-driven adoption. (link)

BBVA expands ChatGPT Enterprise to 120,000 employees with OpenAI partnership: BBVA is rolling out ChatGPT Enterprise across its workforce after pilots showed over 80% daily usage and nearly three hours saved per employee per week. The bank plans to use the platform for internal productivity, software development, risk analysis, and personalized banking under enterprise security and governance controls. (link)

Capital One, Bank of America, and JPMorgan Chase account for 75% of banking AI patents: New data from Evident shows these three big banks account for roughly 75% of banking AI patents since 2023, with heavy focus on GenAI, customer service, and early agentic systems. (link)

Banking futurist warns banks have 5 years to prepare for agentic AI: Brett King says AI agents will soon handle discovery, product matching, funding, and payments in seconds, with humans overseeing higher-risk decisions. He argues banks must rebuild data foundations, break internal silos, and redesign workflows now or risk falling behind as AI-to-AI financial interactions become standard. (link)

Funding Spotlight

Where the money is flowing for innovation…

Informed.IQ lands $63M growth equity round to scale AI loan verification: The funding backs expansion of its agentic platform, which verifies income, assets, residence, insurance, and identity using more than 2 billion data points from 100+ million loan documents. The system already supports over $350B in originations for 7 of the top 10 U.S. auto lenders. (link)

AIR raises $6.1M seed round to build real-time AI credit ratings: The company is developing an autonomous system that continuously assesses the financial health of public and private companies using decades of financial and alternative data. Early customers include institutions managing more than $4T in assets that rely on up-to-date risk signals. (link)

Safebooks AI raises $15M seed round to automate revenue data integrity: The platform overlays existing CRM, ERP, and billing systems to continuously monitor, validate, and reconcile revenue data in real time. It already tracks more than $40B in transactions and has eliminated thousands of hours of manual reconciliation for finance teams. (link)

Saviynt closes $700M Series B to expand AI-era identity security: The round supports expansion of a unified identity platform that governs access for human users, machine identities, and AI agents across applications, data, and infrastructure. Saviynt now serves more than 600 enterprise customers, including over 20% of the Fortune 100, and plans to accelerate R&D, deepen integrations, and support customer migrations from legacy systems. (link)

DeepWorq AI raises a pre-seed round to build modular finance automation: The company is developing AI modules that handle invoicing, payment reminders, tax reporting, and financial document analysis, while adapting to regulatory and business contexts in real time. The funding will support compliance research and production deployments that replace labor-intensive back-office workflows without ripping out existing systems. (link)

Keeping up with Tech

The latest in fintech and tools…

GPT-5.2 underperforms vs. GPT-5.1 on finance agent benchmarks: Most AI models are around coin-flip reliability, with GPT-5.1 currently leading at 56.55% accuracy. GPT-5.2 (52.79%) scores lower than GPT-5.1 on the same benchmark despite running at ~2x the cost. Finance teams still need to rely more on workflow design, tool use, validation layers, and governance. (link)

Posh AI introduces agentic Operating Procedures for governed banking automation: The AI vendor launched a governance and reasoning layer that lets AI carry out real banking workflows like payments, resets, and account actions while enforcing compliance and policy guardrails. By defining outcomes and rules, the system enables agentic execution that stays auditable and controlled inside regulated environments. (link)

Klarna launches open protocol to make products usable by AI agents: Klarna introduced an API standard that gives AI agents a structured, real-time view of product and pricing data across markets, enabling discovery, comparison, and recommendations at scale. The protocol works with existing merchant feeds like Google Merchant, Shopify, and Facebook Catalog. (link)

Axyon AI debuts agentic platform for thematic investing research: Axyon Foresight is a human-in-the-loop system that scans thousands of stocks to construct thematic investment universes in hours using transparent, auditable scoring. (link)

Stripe rolls out agentic commerce tools for AI-driven sales: The Agentic Commerce Suite is a low-code platform that enables businesses to sell through multiple AI agents via a single integration. The setup helps merchants accept agent-driven transactions without rebuilding checkout or payments infrastructure. (link)

BridgeWise releases AI for corporate bond analytics: FixedWise delivers standardized, bond-level insights across global corporate debt using proprietary micro language models. The system translates complex fixed-income data into clear, regulation-aligned analysis of risk, yield, duration, maturity, and ratings for retail and institutional users. (link)

47% plan to use AI agents for Christmas shopping: New Checkout.com research shows nearly half of shoppers expect to use AI agents for Christmas 2025, mainly for gift discovery, price comparison, and routine purchases, with younger shoppers leading adoption. (link)

ChatGPT now offers more precise image generation and editing: The new image model generates visuals up to 4x faster and supports controlled edits that preserve lighting, composition, and key details. (link)

GPT-5.2 arrives as OpenAI’s most capable model for knowledge work: OpenAI says GPT-5.2 sets a new bar for long-running, multi-step knowledge work, outperforming or matching human professionals on more than 70% of tasks across 44 occupations. (link)

Microsoft 365 Copilot rolls out GPT-5.2 for enterprise workflows: Now available in Microsoft 365 Copilot and Copilot Studio, GPT-5.2 Thinking assists with complex reasoning, while GPT-5.2 Instant supports everyday tasks. Integrated with Work IQ, it lets teams reason across emails, meetings, documents, and chats to support more secure, enterprise-grade AI workflows. (link)

Microsoft makes GPT-5.2 available in Foundry: The latest ChatGPT model is now available inside Microsoft Foundry with governance controls, managed identities, and policy enforcement designed for compliance-heavy environments. (link)

Gemini Deep Research adds visual, interactive reports: Google enhanced its research mode to generate reports with charts, images, and interactive simulations that let users explore scenarios and adjust variables in real time. (link)

OpenAI reflects on a decade of progress toward AGI: 10 years ago, OpenAI was born from 15 “nerds” trying to figure out how to progress AI. Over the decade, it grew from early AI experiments and key research wins into launching tools like ChatGPT and GPT-4, which brought AI into everyday use around the world. (link)

In Other News

Related news you can learn from…

• House Financial Services Committee considers AI sandbox to let financial firms test new tools (link)

• America’s Credit Unions urges for flexible AI regulation to protect consumers & innovation (link)

• Bank of America warns of an “AI air pocket” as it trims S&P 500 outlook for 2026 (link)

• Executive order seeks to prevent state AI laws and centralize oversight (link)

• “Frontier Firms” show how leaders unlock real business value from AI (link)

• Regulators need to give banks clearer rules for adopting AI (link)

• AI is reshaping what “fair hiring” actually means (link)

Community Corner

Memes and visuals…

Thanks for reading!

Until next week,

— Credit Union AI Guy

Enjoying this newsletter? Forward it to a colleague who might appreciate practical AI insights.

Have a question or want to share your own AI experiment? Reply to this email or connect with us on LinkedIn. We’re building a community of curious Credit Union professionals. Come join the conversation!

If you’re new here, I find the hottest AI news for Credit Unions to bring you practical insights in a quick, digestible weekly newsletter.

Today, I cover:

• AI video verification stops $80k fraud attempt at APL Federal Credit Union

• How Credit Union West cut time spent developing reports by 94%

• AI lenders outperform humans across 2 million decisions

Read time: 9 minutes

Top Stories

The biggest news this week…

1) AI video verification stops $80k fraud attempt at APL Federal Credit Union

APL Federal Credit Union averted an $80,000 wire fraud attempt after a payment support specialist noticed a subtle mismatch between a member’s profile and the caller requesting the transfer. The documentation looked legitimate, but the funds were headed to an individual instead of a title company. It became a clearer red flag when the caller showed unusual urgency and tried to dodge identity checks.

The saving grace: APL’s policy required video verification, powered by Eltropy Video Banking, for large third-party wires, giving staff the authority to pause the transaction without debate. When the impostor refused to appear on video, the wire was frozen, and three days later, the real member confirmed he had already lost $1.2 million at another institution that lacked similar controls.

For APL FCU, Eltropy Video Banking helps turn instinct into action. Staff can compare IDs live on camera, validate physical characteristics, and close the door on fraud within minutes. The tool has since become critical for high-risk wires and flagged Zelle transactions, remote account openings, and member authentication for out-of-state users. The result: fewer losses, faster workflows, and stronger member trust — reinforced by a Google review rating that jumped two full points. (link)

2) How Credit Union West cut time spent developing reports by 94%

Financial analysts at Credit Union West were drowning in manual reporting work, spending countless hours stitching together data from multiple systems to build peer comparisons and performance reports. The process was time-intensive, repetitive, and slowed down how quickly teams could generate insights for the CU.

With Zest AI’s LuLu analytics platform, tasks that once took three hours now take about ten minutes, cutting reporting time by 94% and saving nearly a full month of labor annually. Analysts now request the data points they want and receive structured, ready-to-use datasets. Beyond peer analytics, 10 other departments use the platform for product engagement, marketing outreach, and identifying operational inefficiencies. In the future, financial analyst Kinnidy Abitz sees future LuLu use cases for product insights, transactional trends, and deposit rate comparisons. (link)

3) AI lenders outperform humans across 2 million decisions

For years, studies have shown that underwriters spend 40% of their time on manual tasks that don’t meaningfully inform decisions about who should receive a loan. Think: retyping PDFs, verifying numbers by hand, and chasing missing signatures…

But a new analysis of two million loans from Ohio State University researchers shows AI decisively outperforms human underwriters in risk accuracy, speed, and profitability. AI-generated decisions produced 10% higher profit per loan, lower default rates (7.6% vs. 8.2%), and 97% accuracy — while reducing decision time from 5.3 days to just 47 minutes. Performance gaps grew with more complex, higher-risk loans where AI’s success rate was more than 20 points higher. The study attributes the difference to human incentive pressures, decision variance, and cognitive overload, compared to AI’s ability to evaluate more than 1,000 variables consistently at scale.

Instead of replacing your team, AI enables an 80/20 lending model in which automation handles pattern recognition and high-volume cases, while your staff focuses on context-rich decisions and member conversations. By eliminating manual data entry and revealing creditworthy applicants that traditional scoring misses (like gig workers or thin-file members with strong payment histories), you extend fairer access while strengthening risk outcomes. (link)

Tips & Use Cases

Learn to apply AI…

How StagePoint FCU grew lending volume 51% without an increase in delinquencies: Zest AI’s underwriting solution increased decision automation by 23%, providing instant approvals that filled staffing gaps and let the Credit Union capture auto dealer applications after hours. LuLu’s GenAI tools also supported M&A evaluation and strategic planning with real-time benchmarking. (link)

Credit Union leaders explain why AI voice success depends on people: Leaders from CUTX, Cobalt CU, and P1FCU say adoption rises when teams help shape the bot, success criteria are defined upfront, and trust issues from past implementations are addressed directly. (link)

Chartway Credit Union cuts dispute costs 86% with AI automation: Casap’s platform reduced Chartway’s dispute workload from three staff members to one, shortened the five-day dispute process to same-day resolution, and dropped write-offs by 72%. Members now receive instant provisional credits, while staff feel more energized thanks to the streamlined workflow. (link)

Kitsap Credit Union uses agentic AI to audit 100% of loans in real time: Kitsap replaced a 24-hour manual audit that sampled only 3% of loans with agentic AI that reviews 100% of applications in near real time. The system provides instant compliance checks and next-best-offer insights while elevating staff into higher-skill oversight roles. (link)

How Horizon Credit Union uses AI to elevate human-led member service: AI turns complex financial data into conversational insights for staff and members, freeing staff for tasks that require emotional connection or decision authority. Offloading routine tasks gives teams more time for coaching and trust-heavy lending conversations. (link)

How Credit Unions can leapfrog fintechs with agentic AI experiences: Agentic AI turns chat into the primary banking interface, allowing members to check balances, move money, or apply for loans through natural language instead of apps or branches. CUs can “disrupt their disruptors” by launching AI-first spin-off brands that deliver agent-only experiences inside platforms like ChatGPT. (link)

AI governance becomes a first line of defense in fintech: As AI tools shape real-time decisions, frontline teams must understand how models work, how data flows, and where risks can emerge. CUs that embed AI awareness into operations, service, and workflow planning reduce compliance pressure and launch smoother, safer digital experiences. (link)

Proactive AI helps stop holiday fraud before members feel the impact: AI analytics layered on top of existing fraud engines use consortium data to flag compromised cards, identify common points of purchase, and detect high-risk merchants long before suspicious charges appear. This lets Credit Unions reissue cards early, adjust rules in real time, and deliver the “non-event” fraud experience that preserves trust and loyalty. (link)

America’s Credit Unions meets with WOCCU to discuss AI challenges and more: America’s Credit Unions’ World Affairs Committee and the World Council of Credit Unions aligned on emerging regulatory risks such as AI, fraud, and digital currency. (link)

AI-powered fraud resolution is a member experience opportunity for Credit Unions: CUs score high on fraud detection (88%) but far lower on provisional credit (56%) and documentation (64%). Meanwhile, 79% of CUs lost over $500K to fraud in 2024. Agentic AI automates investigations, speeds provisional credit, and frees staff for empathetic member outreach. (link)

Meridian Credit Union launches AI financial wellness tools with Personetics: Meridian integrated Personetics’ cognitive banking engine into its new OnYourWay platform, giving 380,000 members personalized insights, budgeting tools, spending alerts, and savings recommendations. (link)

Experian warns of AI-driven cyber threats accelerating into 2026: The firm’s Data Breach Forecast cites over 8,000 global breaches in early 2025 and growing use of AI to create synthetic identities, autonomous malware, and harder-to-detect attacks. With 69% of U.S. adults doubting their bank’s readiness and one in four millennials hit by identity theft, Experian urges institutions to strengthen incident response. (link)

Take this AI readiness assessment to benchmark adoption progress: CU 2.0’s 48-point scoring rubric evaluates policy maturity, culture, data systems, workflows, and fintech partnerships to determine whether a Credit Union is beginning, developing, advanced, or leading in AI integration. (link)

Glia highlights how AI-powered virtual branches keep digital journeys human: A survey of more than 100 leaders found only 5% love their current contact center tech and 93% are ready to evaluate new options, even though just 21% have significant AI experience. Glia’s virtual branch model uses Voice AI and digital channels to offer 24/7 service, free agents from low-value calls, and extend reach without the $4M cost of new physical branches. (link)

Fifth Third partners with Brex to deploy AI-powered commercial finance tools: The multi-year deal unlocks $5.6B in annual commercial card payment volume and gives 8% of U.S. commercial banking clients access to Brex’s AI-native platform for issuing cards, automating expenses, and accelerating close. AI agents handle receipts, accounting, and spend controls in real time, reducing manual work and improving visibility for business customers. (link)

Freddie Mac issues new AI governance requirements for mortgage servicers: The update introduces a comprehensive framework for responsible AI and machine-learning development, mandating stronger requirements around transparency, accountability, and ethical oversight. (link)

BNY adds Gemini 3 to its enterprise AI stack to power agentic workflows: BNY is embedding Google’s Gemini 3 into its internal AI platform, Eliza, enabling employees to run agentic, multi-step workflows across onboarding, document analysis, risk checks, and more. Eliza currently supports 120 automated workflows. (link)

How gen AI experimentation turns uncertainty into an advantage: Treat gen AI as a portfolio of controlled experiments. Although many have adopted it, more than 80% report no earnings impact yet, while structured trials (like a 14% productivity boost and 34% gain for new agents) reveal where it truly works. Run staggered pilots on specific workflows before scaling to de-risk AI and target the highest-ROI use cases. (link)

How financial institutions can build private AI for speed, control, and compliance: With only 14% of organizations targeting enterprise-wide deployment by 2025, Rackspace says private-cloud AI offers a faster, safer path. Its FAIR framework helps teams spin up compliant gen AI environments quickly, align governance upfront, and move from prototypes to production without exposing sensitive data to public models. (link)

What the Concorde teaches about adopting AI responsibly: Dazzling tech doesn’t guarantee broad adoption, just as the supersonic passenger jet failed commercially despite its engineering brilliance. Leaders should avoid the “Concorde Fallacy” of pouring money into AI without clear ROI. Beware of risks like externalities (privacy, cybersecurity), human error, and poor implementation. (link)

Scottish Widows pilots AI to speed up marketing compliance reviews: The insurance and pensions firm is testing Adclear’s FCA-aligned review engine, which analyzes written, visual, and video content and cuts compliance review time by 88% while maintaining a full audit trail. The FCA is actively supervising the pilot. (link)

Gemini 3 turns AI into a no-code FP&A app builder: Gemini 3 Pro’s new Build/Canvas mode lets finance teams spin up interactive planning tools, like a CFO Decision Impact Simulator, in minutes from a single prompt, with everything running locally in the browser so sensitive data never leaves the device. (link)

Use this prompt for more reliable finance AI: Finance teams get burned by AI when they treat LLMs like black-box “answer machines” instead of tools that must interrogate assumptions first. Use this CFO “critical thinking” prompt to force AI to ask 7-12 targeted questions that reduce hallucinations by 80-90%. (link)

Agentic AI shifts from efficiency to experience design: Cornerstone’s Ron Shevlin and Stacy Bryant say AI is moving beyond back-office automation toward building end-to-end member experiences, from planning financial journeys to AI-assisted goal management. The shift means staff roles won’t disappear but will favor employees who pair AI fluency with creativity, while institutions that simply bolt AI onto legacy systems risk falling behind rising expectations. (link)

BBVA builds a conversational banking app inside ChatGPT: The bank now lets users ask natural-language questions about accounts, cards, and savings products directly through ChatGPT. Meanwhile, 11,000 employees already use OpenAI tools and report saving three hours per week. (link)

Bank of America deploys AI tool to answer complex payments questions in seconds: The internal GenAI system, trained on 3,200+ documents, lets staff answer client questions in seconds instead of hours by replacing manual searches and specialist calls. It improves turnaround times, surfaces best practices, and enables more tailored guidance across the Global Payments Solutions team. (link)

HSBC signs multi-year GenAI deal with Mistral AI:The multi-year deal gives HSBC access to Mistral’s commercial models to power internal tools for financial analysis, translation, procurement insights, and personalized marketing. Strengthening its self-hosted AI platform, the bank plans to extend these capabilities to fraud detection, AML, lending, and onboarding. (link)

RBC expects up to C$1B in enterprise value from AI by 2027: The bank reports that its Atom adjudication model, personalization engines, advisor and developer copilots, and redesigned mortgage workflows have positioned AI to generate C$700M-C$1B in enterprise value within two years. (link)

OpenAI report shows AI enabling entirely new employee capabilities: The State of Enterprise AI report finds 75% of workers say AI improves work speed or quality, and the same share say they can now complete tasks they previously lacked the skills or time to handle. Employees save 40-60 minutes a day on average, while heavy users reclaim more than 10 hours a week as advanced features like Projects and Custom GPTs scale. (link)

Funding Spotlight

Where the money is flowing for innovation…

Kobalt Labs lands $11M Series A to modernize financial institution compliance automation: Kobalt’s AI agents handle third-party risk reviews, internal audits, and marketing compliance for institutions including Meriwest CU, Emprise Bank, and Chime. (link)

Flex raises $60M Series B to scale its AI-powered private bank: Flex is building an AI-native platform that unifies credit, payments, ERP, and personal finance for business owners generating $3M-$100M annually. Its embedded agents span underwriting, payments, cash management, and ERP, feeding a unified “AI CFO” that automates complex financial workflows for high-value clients. (link)

Niobium raises $23M to build privacy-preserving chips for sensitive data: Niobium is developing hardware that lets organizations run calculations on encrypted data without ever exposing it, providing strong protection for financial and member information. (link)

Zafran secures $60M Series C for autonomous exposure-management AI: Zafran’s agentic system maps assets, detects vulnerabilities, and coordinates fixes automatically, cutting remediation times from weeks to hours. The funding comes as attackers now exploit new weaknesses within 24 hours, increasing pressure on organizations to adopt autonomous defense models. (link)

imper.ai raises $28M to fight AI impersonation attacks: Imper.ai is rolling out a real-time detection platform that flags deepfake voices, spoofed video, and social-engineering attempts across tools like Zoom, Teams, Slack, and Google Workspace. The system analyzes device and behavior signals to catch identity threats traditional scanners miss. (link)

Pine raises $25M Series A for autonomous consumer AI agent: Pine’s end-to-end agent negotiates bills, cancels subscriptions, secures refunds, books appointments, and handles calls and emails with a 93% success rate. Its shared-memory system learns from every interaction, making the network smarter as users offload more real-world tasks to automation. (link)

Keeping up with Tech

The latest in fintech and tools…

AI Platform Kobalt Labs aims to fix third-party risk for Credit Unions: The platform automates third- and fourth-party risk reviews by checking controls, scanning contracts, validating insurance, and mapping vendor dependencies in seconds. It provides exam-ready traceability and consistent scoring, helping large CUs cut manual workload and enabling smaller teams to handle TPRM, marketing compliance, internal audit, and policy reviews more efficiently. (link)

OpenAI tests “confessions” mechanism to expose hidden model errors: The feature generates a second, honesty-only output where the model flags hallucinations, skipped steps, instruction breaks, or reward hacking that may not appear in the main answer. Early tests show ~96% accuracy in catching misbehavior. (link)

LSEG and Nomura introduce ChatGPT integrations for market data workflows: LSEG will deliver its licensed financial analytics directly into ChatGPT, giving credentialed users real-time access to market data, news, and analytics while 4,000 employees adopt ChatGPT Enterprise for internal productivity. Nomura is blending its proprietary datasets with external sources via ChatGPT to enhance advisory work and develop new AI-enabled revenue models. (link)

Instacart brings fully integrated AI grocery shopping to ChatGPT: Instacart is now the first app to support full cart-building and Instant Checkout directly inside ChatGPT. Powered by OpenAI’s Agentic Commerce Protocol, it connects real-time store data, personalized suggestions, and Instacart’s fulfillment network to streamline end-to-end ordering. (link)

Ramp builds petabyte-scale AI data cloud for company-wide insights: Ramp connected sales calls, emails, tickets, invoices, and other unstructured data into Snowflake Cortex so any employee can query it in plain English. The system speeds decision-making across teams, but misclassified insights or incorrect summaries could pose legal and compliance risks for regulated organizations. (link)

OpenRouter releases large-scale study on real-world AI usage trends: The report analyzes more than 100 trillion tokens of developer traffic across 300+ models and shows a major shift toward agentic workflows. With reasoning models and open-source options rapidly gaining share, future applications will rely less on static chat and more on end-to-end AI agents. (link)

In Other News

Related news you can learn from…

• 7 trends shaping AI’s next phase in 2026 (link)

• FCA begins live testing of AI in UK banks (link)

• Anthropic and OpenAI are racing to their IPOs (link)

• Why some AI products achieve extraordinary early retention (link)

• OpenAI is now in “Code Red” to compete with Google’s Gemini (link)

• Could a “10% for the People” AI dividend prevent a future economic underclass? (link)

Community Corner

Memes and visuals…

Thanks for reading!

Until next week,

— Credit Union AI Guy

Enjoying this newsletter? Forward it to a colleague who might appreciate practical AI insights.

Have a question or want to share your own AI experiment? Reply to this email or connect with us on LinkedIn. We’re building a community of curious Credit Union professionals. Come join the conversation!

If you thought AI-powered commerce was still “emerging,” Black Friday just proved it’s already here.

First time reader? I find the hottest AI news for Credit Unions to bring you practical insights in a quick, digestible newsletter every week.

• GenAI adoption surges faster than any previous lending technology

• Experian bets big on AI-powered financial guidance

• Bank jobs fall to 2019 lows as AI reshapes staffing

Read time: 8 minutes

Top Stories

The biggest news this week…

1) GenAI adoption surges faster than any previous lending technology

A new Celent + Zest AI survey of 106 lenders (including Credit Unions) shows the industry is adopting GenAI faster than any prior lending technology. But are security, risk, and compliance maturity keeping pace? With 83% increasing GenAI budgets in 2026 and 67% already implementing strategies, the pressure to compete on efficiency and experience is pushing institutions from pilots into production before guardrails are fully built.

Consumer lending teams are accelerating the fastest: only 6% have a GenAI strategy today, but 36% will develop one in 2025, closing the gap with broader retail banking, where 32% plan to implement GenAI in 2025. What’s slowing most institutions down: 19% cite security as the top barrier, 20% rank it second, and 15% mention competing priorities as the next biggest obstacle. Agentic AI is also rising fast, creating new governance challenges as 8% already use it, and 28% plan to.

As adoption spreads across copilots, compliance automation, and BI dashboards, the risk of ungoverned model drift and regulatory exposure grows. Yet, the report frames GenAI as a major competitive opportunity, with 36% of lenders identifying as early adopters. Respondents pointed to three areas where GenAI delivers the strongest edge: AI copilots that assist loan staff in navigating policies and documents, automated compliance and regulatory reporting that surfaces potential violations, and advanced business intelligence powered by AI-driven analytics. (link)

2) Experian bets big on AI-powered financial guidance

At Money20/20, Experian Consumer Services President Daisy Yee outlined how the company is shifting from a credit score tool to a full financial copilot — powered heavily by AI and hyper-personalization. With inflation and financial stress rising, Yee said consumers are increasingly turning to AI assistants for non-judgmental, real-time help managing bills, credit, budgeting, and financial decisions.

Experian’s virtual assistant, Eva, now supports natural-language conversations and can take actions on behalf of users, including freezing credit files, monitoring insurance rates, negotiating bills, and cancelling subscriptions. Yee said consumers are surprisingly more willing to disclose sensitive financial issues to AI than to people, enabling Experian to deliver personalized guidance built from transaction history, spending patterns, and credit data. The company’s long-term strategy is evolving from credit monitoring to a lifelong financial companion, reinforced by its new “BFF: Big Financial Friend” campaign. (link)

3) Bank jobs fall to 2019 lows as AI reshapes staffing

U.S. banks have eliminated nearly 81,000 jobs since early 2023, dropping the industry workforce to its lowest level since 2019. A Bureau of Labor Statistics subcategory covering banks and Credit Unions shows a YoY decline of roughly 2,900 jobs. Analysts say AI is a central driver of these cuts, which may be permanent.

The trend is largely driven by banks with $250B+ in assets, reducing full-time staff by 0.8% YoY. Meanwhile, banks with less than $250B in assets saw a slight 0.2% gain in jobs. Citi, Wells Fargo, and BNY Mellon account for the bulk of reductions, each tying workforce changes to AI-driven productivity gains. Citi is rolling out agentic AI to 5,000 employees to automate multistep workflows, while BNY Mellon has already deployed more than 100 digital workers handling payment validations and code repairs.

With interest-rate pressure compressing margins, banks are leaning on tech to remove redundancy rather than wait for economic relief. (link)

Tips & Use Cases

Learn to apply AI…

5 types of GenAI friction Credit Unions must overcome for implementation: A new MIT analysis shows 95% of GenAI projects fail due to organizational friction that slows and misdirects progress. CUs should treat friction as a signal that reveals misaligned goals, scattered data, cultural misalignment, unclear workflows, or governance risks. (link)

Younger members are primed for AI adoption if you earn their trust first: With 70% of Gen X through Gen Z using AI weekly but only 6% relying on it for financial planning, Credit Unions should lean into hyper-personalized insights and guidance. Use AI to deliver real-time financial wellness insights across mobile, email, and SMS to deepen relationships while building the trust needed for future, higher-stakes AI interactions. (link)

Ben Udell from Marquis shares 10 prompts that reduce AI “workslop” in bank marketing: Marketing teams often use GenAI as a content factory, producing polished but generic messaging that weakens trust. These prompts refine tone and strengthen clarity, turning GenAI into an editing partner that helps Credit Unions create more authentic, mission-aligned communication. (link)

Citizens scales 3 high-impact AI use cases: AI-assisted development now supports 800 engineers, delivering a 10-15% productivity lift as genAI rewrites legacy code and accelerates modernization. In member service, the CiZi virtual assistant has reduced calls from the mobile app by 44%, while agentic AI pilots are automating 100% of call-quality reviews and speeding up complaint handling. (link)

BCG outlines leadership playbook for measurable AI transformation: BCG finds only 5% of banks capture AI value at scale, achieving 5x revenue gains and 3x cost reductions compared to laggards. Winners set bold, yet quantifiable targets, rebuild end-to-end workflows, and invest in strong data foundations and reskilling programs that reach 40-50% of employees. (link)

AI disruption forces lenders to rebuild SEO acquisition from scratch: Google’s Helpful Content Update and AI Overviews have erased 50-90% of organic traffic, creating a zero-click environment where LLMs answer questions and drive lenders into costly paid search auctions. Credit Unions should pivot to brand, creator, and owned-audience strategies while optimizing for Generative Engine Optimization so their products and expertise surface inside AI answers. (link)

7 tips for generating pro images and designs with Google’s new Nano Banana Pro: 1) Use detailed prompts that specify subject, composition, action, location, style, and editing instructions. 2) Add advanced camera, lighting, aspect-ratio, and text constraints for sharper outputs. 3) Blend or resize images to maintain character consistency and brand styling across formats. Plus, four more tips for your marketing team! (link)

Santander’s AI ads raise awareness of AI fraud: Santander U.K.’s deepfake ads found that 74% of consumers failed to spot an AI-generated padel bat and 71% missed a deepfake dog feeder scam. The bank reported £16.7M in losses from purchase fraud last year, with 67% originating on social media. (link)

How agentic AI moves banking from self-service to self-resolution: Unlike traditional IVR, apps, or chatbots that give information but leave the work to members, agentic AI interprets intent, authenticates users, reasons across accounts, and completes tasks end-to-end. (link)

3 non-negotiables for safe AI in banking: With AI risk-assessment models still yielding a 15% error margin, financial institutions need compliance-first automation with clear audit trails, explainable AI decisions, and strong governance controls. (link)

“Finance-grade AI” needs to be held to a high standard: Maxa co-founder Raphael Steinman warns that most finance AI projects fail because leaders deploy generative tools atop fragmented, error-prone data, producing unreliable insights. “Finance-grade AI” must fully explain its answers instead of spitting out a probable answer that, even if just 1% wrong, could cause errors costing millions of dollars. (link)

SMB credit personalization is a Credit Union growth opportunity: 83% of SMBs feel confident they’d be approved for a business card, and the average SMB is willing to pay $126/year more for flexible tools like dynamic limits, virtual cards, and installment options. (link)

HSBC adopts self-hosted Mistral AI models for bank-wide automation: HSBC signed a multi-year agreement to deploy Mistral’s foundational models on its own infrastructure, starting with productivity tools for marketing, document analysis, translation, and software development. The bank plans to expand the initiative into credit, onboarding, fraud, and anti-money laundering. (link)

CBA appoints Chief AI Officer to scale enterprise-wide AI adoption: Commonwealth Bank of Australia hired Lloyds’ Chief Data Officer, Ranil Boteju, to lead its AI strategy after he delivered 50+ GenAI initiatives and improved Lloyds’ Evident AI Index ranking. The bank is embedding AI into fraud prevention, loan decisioning, and credit reviews, supported by its AWS-powered “AI Factory” and a multi-year deal with ChatGPT Enterprise. (link)

2026 predictions for AI in banking: Banks will shift from pilots to large-scale AI agents that automate end-to-end workflows, deliver hyper-personalized service, and power embedded finance ecosystems through real-time data. Thin, modular cores, human-in-the-loop governance, and unified data will enable AI agents to safely scale across onboarding, lending, fraud, and operations. (link)

BIS shows AI can safely automate complex financial decision-making: A BIS study found that a ChatGPT-based agent could prioritize payments, manage cash buffers, and minimize delays in simulated stress scenarios — demonstrating AI’s ability to handle complex financial workflows with little guidance. (link)

What IT leaders should know about SOC vs PCI security for Credit Union vendors: SOC 2 verifies that a vendor follows its own policies, but PCI DSS Level 1 enforces prescriptive controls like segmentation, encryption, and continuous scanning, making it the only standard that protects payment data in real time. (link)

Funding Spotlight

Where the money is flowing for innovation…

AI wealth-management startup Nevis lands $35M Series A to scale advisor automation: Backed by Sequoia, Iconiq, and Ribbit, Nevis is building an AI platform that completes operational tasks for financial advisors end-to-end and is already used by fast-growing Registered Investment Advisors overseeing more than $50B in assets. (link)

Codenotary raises $16.5M to grow its AI-driven software-trust platform: The company’s deterministic, audit-ready tech replaces manual software verification with automated integrity checks and continuous policy enforcement across complex systems. (link)

Vijil secures $17M to make agentic AI safer for enterprise use: The AI-resilience platform uses real-world telemetry and reinforcement learning to harden agentic systems against failures, security risks, and compliance gaps. Early customers report a 75% reduction in “time-to-trust.” (link)

Clover raises $36M to prevent security flaws at the design stage: Clover’s AI agents plug into Jira, GitHub, Confluence, and Slack to detect vulnerabilities during product design, mimicking senior security engineers to guide developers in real time. (link)

BKN301 adds £10M credit facility and acquires AI fintech Planky: The acquisition brings Planky’s real-time financial insights, behavioral scoring, and predictive analytics engine into BKN301’s digital banking stack, strengthening its payments, wallets, card issuing, and open banking capabilities. (link)

Keeping up with Tech

The latest in fintech and tools…

Disseqt AI, HCLTech, and Microsoft partner to guide banks on agentic AI adoption: The collaboration combines Disseqt’s lean agentic-automation platform with HCLTech’s banking expertise and Microsoft’s Responsible AI frameworks to help institutions deploy agentic systems with proper oversight. At a recent Dublin roundtable, leaders noted that only 1% of organizations have adequate governance in place and showed how Disseqt can cut costs up to 80%, shorten production cycles by 70%, and strengthen testing and monitoring. (link)

HCLTech and AWS team up to push autonomous, AI-driven financial services: HCLTech will launch pre-built, industry-compliant solutions on AWS to modernize contact centers, enhance digital engagement, and streamline core banking, wealth, and insurance platforms. The collaboration aims to help financial institutions overcome legacy constraints and move toward autonomous operations using cloud and AI. (link)

PayPal doubles down on agentic AI and wallets as its new competitive strategy: PayPal is shifting to an AI-first commerce model, rolling out agentic checkout with Perplexity and OpenAI, adding product-search and autonomous purchase capabilities, and partnering with Mastercard and Google Gemini for agent-driven payments. (link)

AI-native systems are becoming the new operating model for modern organizations: Startups are rebuilding their internal systems around AI, using structured context, agent-driven workflows, and fine-tuned models to boost velocity and automate complex operational tasks end to end. (link)

AI agents get direct payment rails through Omise’s new MCP server: Omise’s MCP server lets AI agents tap into 60+ payment tools to autonomously run acceptance, refunds, reconciliation, payouts, and full payment-lifecycle operations without custom integrations. The platform provides financial-grade, two-way orchestration so agents can execute complex payment tasks reliably in production environments. (link)

Microsoft earns Leader position in Gartner’s Cloud ERP Finance ranking: Dynamics 365 Finance was recognized for its global financial capabilities, embedded AI automation, and Copilot Studio, which lets teams build finance-focused AI agents using natural language. The platform combines multi-entity support, predictive analytics, and low-code automation. (link)

Ant International adds agentic automation across the full merchant payment lifecycle: The merchant payment services provider upgraded its Antom Copilot system to automate onboarding, integration, risk checks, disputes, and payment-success operations using agentic workflows, multi-turn reasoning, and dynamic SOP planning. The platform has already cut integration time by 90% and improved dispute-handling efficiency by 46%, providing proactive, domain-trained operational intelligence for merchants. (link)

In Other News

Related news you can learn from…

• AI solves 30-year math problem (link)

• Emerging tech Credit Unions are buying (link)

• The top 5 AI fintech developments in November (link)

• Agentic commerce is exploding, but guardrails lag behind (link)

• Former OpenAI Chief Scientist claims AI’s “age of scaling” is coming to a close (link)

• Research warns that offloading thinking to AI weakens neural engagement in professionals (link)

Community Corner

Memes and visuals…

Thanks for reading!

Until next week,

— Credit Union AI Guy

Enjoying this newsletter? Forward it to a colleague who might appreciate practical AI insights.

Have a question or want to share your own AI experiment? Reply to this email or connect with us on LinkedIn. We’re building a community of curious Credit Union professionals. Come join the conversation!

Today, I cover:

• How big banks deploy AI agents without alienating staff

• Columbia Credit Union redefines digital-first member service

• Gemini 3 smashes ChatGPT in financial reasoning

Read time: 9 minutes

Top Stories

The biggest news this week…

1) How big banks deploy AI agents without alienating staff

Banks like Citi, Citizens, and TD are learning that the hardest part of rolling out agentic AI isn’t the technology itself, but the people. What triggers excitement for some means anxiety for others.

At the Reuters AI Momentum conference, TD’s Jo Jagadish described the cultural tension: employees who use AI in their personal lives now expect the same convenience at work, while others fear losing core responsibilities. Jagadish said teams must be transparent about how productivity will be redefined and how AI removes redundant tasks so humans can focus on creativity, decision-making, and member interactions. At TD, 80% of contact center agents adopted new generative and agentic tools in just the first month, supported by months of communication and training.

Citi CIO Nikhil Joshi emphasized the same point, saying, “You must take people along,” which is why Citi’s AI training program now reaches more than 175,000 employees with an adaptive curriculum that adjusts to each learner’s skill level. Citi’s 40,000 developers now rely on agents built on Cognition’s Devin software — already used for over one million code reviews, documentation generation, and deterministic tasks like middleware upgrades, all with a human in the loop.

Citizens has rolled out GitHub Copilot’s coding agent to roughly 800 developers (about half the team) and is using Fintech partners to rewrite millions of lines of legacy code for cloud migration. The bank now uses AI agents to classify and respond to incoming complaints and automate quality control, shifting from humans reviewing 5 percent of call transcripts to AI reviewing 100 percent instantly.

Across all three institutions, AI agents are helping redeploy employees into more engaging work instead of replacing them. As Daniel Jameel of Saris AI puts it, “We make you look like a rock star,” by absorbing the work employees least enjoy while preserving human control over high-impact decisions. (link)

2) Columbia Credit Union redefines digital-first member service

Columbia Credit Union is showing what happens when a legacy, channel-bound contact center is rebuilt into a unified digital-first operation. After replacing its fragmented phone and chat systems with Glia Digital + Glia Voice, the Credit Union achieved a 92% first-call resolution rate, cut on-hold wait times by 30% YTD, and maintained a 91% answer rate during a full-day auto-attendant outage — routing 830 audio engagements entirely through Glia.

Digital adoption accelerated too: combined digital interactions grew 62% from 2022-2024, with another 42% annualized growth projected in 2025, driven in part by its AI assistant “River,” which already handles 51% of inquiries with a 94% understanding rate.

Behind the scenes, the unified workflow unlocked meaningful operational gains. Agent availability jumped from 65% to 73% without adding headcount, Multi-Engage enabled agents to handle more concurrent chats, and centralized reporting finally gave leadership real-time visibility across all queues. Even during the outage, Columbia CU resolved 1,073 total engagements, logged 0 member complaints, and kept members fully supported — many of whom shifted into digital channels they hadn’t used before. (link)

3) Gemini 3 smashes ChatGPT in financial reasoning

A new analysis of Gemini 3 suggests Google may have delivered the first AI model capable of supporting real long-horizon financial decision-making — a breakthrough with direct implications for ALM teams, CU CFOs, and finance departments.

Reviewers report that Gemini 3 provides precision “unlike anything else,” consistently pulling accurate numbers from obscure sources, reducing hallucinations, and producing verifiable reasoning across documents that never appear on the public web. The model posted record performance on RadLE, ARC-AGI-2, scientific knowledge tests at 93.8 percent, and multimodal tasks, where it can process an entire YouTube video frame-by-frame. Google deployed Gemini 3 across Search, Workspace, YouTube, Vertex AI, the Gemini app, and Antigravity — an agentic coding environment.

What matters for Credit Unions is how the model performs under long-range financial stress. On VendingBench — a full-year business simulation designed to test whether an AI can manage a dynamic economic environment without unraveling — Gemini 3 finished above 5,000 dollars, outperforming Claude Sonnet 4.5, GPT-5.1, and Gemini 2.5 Pro, all of which plateaued or lost money. Analysts say this is the clearest evidence yet that an AI system can make decisions in month one that still hold up in month twelve. Box.com’s testing showed Gemini 3 outperformed Gemini 2.5 Pro by 22 points on multi-document extraction and reasoning across PDFs, spreadsheets, screenshots, video, audio, and raw text. Finance teams can use it to pull insights from 1,000 invoices or analyze dense audit evidence with a single prompt, reducing hours of manual work.

Credit Unions can treat Gemini 3 as an early signal of what comes next in financial operations — more reliable ALM forecasting, steadier budgeting cycles, and faster cross-document analysis for audits, loan files, and regulatory packets, all of which are long-horizon tasks where earlier models struggled. (link)

Tips & Use Cases

Learn to apply AI…

How Vertice AI enables small CU teams to run big-bank targeting: The 23-person, AI-native company now supports nearly 50 Credit Unions and community banks by turning roughly 50 initial data fields into instant HELOC, deposit, indirect, and churn-risk audiences, letting even 1-person marketing teams act in minutes instead of weeks. (link)

Mac Thompson outlines an 8-step AI implementation framework for financial institutions: Institutions should anchor AI in business strategy, start with imperfect data, avoid hiring full AI labs, create a one-page definition so everyone uses the same terms, and focus on automating paper-heavy workflows instead of automating outdated processes. (link)

WOCCU releases ethical AI playbook to guide responsible Credit Union adoption: It breaks adoption into 3 phases with concrete deliverables like an Ethical AI Committee charter, AI risk-assessment report, data-governance updates, and quarterly board reviews, giving Credit Unions a practical way to deploy AI transparently while protecting members and meeting regulatory expectations. (link)

Curql’s Martin Walker says agentic AI will demand stronger CU infrastructure: Large banks like JPMorgan, Citi, and BNY are upgrading data quality, governance, and small domain models so agents can run multi-step tasks safely. This gives CUs a blueprint for automating onboarding, fraud checks, loan processing, and service without regulatory risk. (link)

AI-driven fraud now demands multilayer defenses and real-time identity intelligence: Fraud losses rose nearly 60% in 2025, US consumers lost an estimated $12.5B in 2024, and only 18% fully trust AI tools. Credit Unions must adopt behavioral analytics, biometrics, and transparent member education to stay ahead. (link)

Call-center AI is turning support hubs into scalable growth engines: Credit Unions are automating routine calls, chat interactions, and ID verification, with results like 84% call automation, 76% chat containment, 20-30 minute waits cut to under 30 seconds, and $800K in annual savings. (link)

Great ChatGPT-powered apps focus on a few sharply scoped capabilities: Teams should define small, clear operations, design structured outputs, limit inputs, and make apps discoverable so users see value on the first turn instead of navigating a full product clone. (link)

Evals turn vague AI goals into predictable, measurable performance: Create golden examples, error taxonomies, and LLM-plus-human grading loops to cut high-severity mistakes, monitor real outputs, and iteratively improve reliability in real workflows. (link)

How behavioral science boosts the ROI of AI investments: Most AI failures stem from human behavior, not technology. Studies show 95% of initiatives fall short and only 26% show ROI. Leaders must design tools around real biases, build trust, and manage adoption as a behavioral change. (link)

5R framework turns AI from pilots into real business impact: Clear roles, responsibilities, rituals, resources, and results helped one company cut risk costs by 8%, scale AI customer interactions from under 3% to nearly 60% in 18 months, and fulfill 100+ analytics requests per quarter. (link)

How agentic AI will reshape risk decisioning: Agentic systems wrap LLMs with tools, memory, and planning so they clean data, communicate with applicants, and orchestrate fraud, compliance, and credit workflows. Credit Unions can start by piloting agents for document parsing, exception handling, and underwriting, with deterministic rules and human reviewers as guardrails as they scale. (link)

How AI and human-centered Fintechs help serve small businesses better: Fintechs like Hello Alice and Bluevine show how AI can speed access to capital, simplify daily operations, and build trust for the microbusinesses that make up half of US GDP. (link)

How CFOs can write better prompts with ChatGPT 5.1: ChatGPT 5.1 now reads financial statements, runs variance and scenario analysis, and drafts board-ready narratives with far more consistent reasoning. Finance leaders who master prompt patterns and use prompt copilots can turn it into a true second brain for FP&A and reporting. (link)

AI-to-human handoffs are breaking member experience: As Credit Unions scale AI, most failures now happen when bots hand members to humans, creating dropped calls, confusion, and inconsistent service across channels. CUs must fix handoff design, retrain frontline staff, and align tech and operations to deliver smoother experiences.(link)

How Credit Unions can stop feeding competitors borrower-intent data: Lead-gen sites like LendingTree sell the same borrower lead for $20-$500 because they capture intent that CUs miss. CUs can counter by using AI-powered calculators that assess qualification, explain results, and log demand. (link)

Wells Fargo elevates AI to the executive suite: Wells Fargo named Saul Van Beurden as its companywide AI leader after rolling out AI tools to 180,000 desktops and training 90,000 employees. The new role gives him full focus to drive bankwide transformation, from ops automation to frontline productivity. (link)

How younger shoppers use AI to surface deals: Over 40% of consumers now use AI to shop, including 61% of Gen Z and 57% of millennials, and roughly half say they’d even let AI buy all their gifts to avoid stress. (link)

Banks are splitting on agentic AI adoption based on size: New survey data shows 64% of large banks are testing or deploying agentic AI, compared with just 38% of smaller institutions. Nearly all banks already using it report strong results, with 94% satisfied and only 2% saying it has no value. (link)

How lenders use AI to cut costs and boost approvals: AI now automates unstructured loan data, reduces cost-per-loan, and scales ops without new headcount. Lenders using AI for instant underwriting and ID verification see faster approvals, higher conversions, and more resilient performance in both boom and downturn markets. (link)

Wells Fargo CEO bluntly claims AI will shrink bank headcount: Wells has already cut staff by nearly 24% over 6 years, and Charlie Scharf says AI will drive further reductions as developer output rises 30-40% and repetitive call-center and credit-memo work shifts to agents. His message to leaders: redesign workflows now, retrain staff early, and avoid hiring for jobs AI will soon replace. (link)

Funding Spotlight

Where the money is flowing for innovation…

Model ML raises $75M Series A to automate deal team workflows: The startup’s AI agents pull, verify, and format data into client-ready Word, PowerPoint, and Excel files. The platform already outperforms McKinsey/Bain consultants and completes verification tasks in under three minutes. (link)

Nudge Security raises $22.5M Series A to secure the Workforce Edge: The company’s platform discovers SaaS and AI tools, maps integrations, and governs human and non-human identities. Nudge Security has grown ARR 3x, adding nearly 200 customers since 2022. (link)

Chargeflow launches AI suite after $35M Series A: Chargeflow is expanding its end-to-end chargeback automation platform as global disputes surge toward 324 million annually by 2028. Its AI achieves up to 80% success rates and 4× higher win rates than manual processes. (link)

Modern Life raises $20M Series A to modernize AI-powered life insurance: The platform gives advisors instant quotes, data-driven underwriting, and Express Decision approvals up to 4x faster while reducing costs by up to 20%. It now integrates over 30 carriers and replaces more than 10 legacy tools with one end-to-end workflow. (link)

AI-native procurement startup Coverbase raises $20M Series A: The startup reports a 90-92% reduction in procurement workloads, saving an estimated $180M in person-hours across 40+ customers. It now plans to expand into healthcare and pharma while adding spend analysis, contract intelligence, and invoicing. (link)

Blackstone invests $50M in Norm AI to scale legal-automation platform: Norm AI is expanding its AI agents for compliance and legal review and launching Norm Law, an AI-native law firm built for financial institutions. The company now serves clients managing over $30T in assets and has trained more than 35 lawyers as “legal engineers.” (link)

Pibit AI raises $7M to automate underwriting with vertical AI: The company’s CURE platform consolidates document intake, data processing, research, and risk scoring into one workflow, cutting underwriting time for US insurers. (link)

Numerai raises $30M at a $500M valuation to scale its AI-powered hedge fund: The firm’s crowdsourced Meta Model delivered a 25.45% net return in 2024 as AUM jumped from $60M to $550M in three years. New capital will expand investment capacity and support growth toward $1B+ in managed assets. (link)

Kaaj raises $3.8M seed to automate SMB credit analysis: The agentic AI platform turns full loan packages into decision-ready analysis in under three minutes, helping lenders make sub-$1M loans profitable and reduce manual underwriting work. (link)

Tidalwave raises $22M Series A to automate mortgage underwriting: The startup uses agentic AI and direct integrations with Fannie Mae, Freddie Mac, Plaid, Argyle, and Truv to cut processing times and reduce errors across the mortgage lifecycle. It aims to process 200K+ loans a year as lenders replace manual workflows. (link)

Maxima raises $41M Seed + Series A to automate month-end accounting: The startup’s AI agents prep reconciliations, journal entries, and close workflows so teams get 80% faster closes, 95% task automation, and fully auditable outputs. It targets one of the most error-prone, overworked functions in finance. (link)

Pay.com.au raises AUD$53M to expand payments and rewards platform: Pay.com.au will invest in its business rewards system and accelerate its US launch after reaching AUD$246M in annualised gross revenue and doubling its valuation to roughly AUD$633M. (link)

Keeping up with Tech

The latest in fintech and tools…

AI platform Gnomi now analyzes earnings calls. Gnomi’s new Finance Mode uses multilingual agentic AI to listen to live calls, score sentiment, and produce instant transcripts with global market context across 50+ regions. (link)

Worldpay rolls out Model Context Protocol for agentic payments: The new open, GitHub-hosted standard lets developers build AI agents that trigger autonomous payments on Worldpay’s global rails, enabling simpler integrations across 52B+ transactions and 135+ currencies. (link)

Backbase adds Unblu’s conversational tools to its banking platform: The partnership brings live chat, video, voice, co-browsing, and AI chatbots directly into Backbase’s unified employee workbench, giving staff full customer context and smoother digital-to-human handoffs across onboarding, wealth, branch, and support journeys. (link)

Dost launches AI invoice-processing and finance automation in the UK: The platform automates procure-to-pay and order-to-cash workflows with 80% lower admin costs, 95%+ accuracy, and 2.5x productivity while outperforming traditional OCR on complex invoices and ERP integrations. (link)

ID-Pal upgrades ID-detection engine to fight deepfakes: The new system flags AI-generated documents, synthetic IDs, portrait swaps, and printed forgeries, blocking four major presentation-attack types while reducing false positives. It also speeds up compliant onboarding by spotting manipulation earlier in the verification flow. (link)

Mastercard brings agent pay to the UAE: Mastercard completed its first Agent Pay transaction outside the US, piloting AI-powered shopping and payments with Majid Al Futtaim and fintech Dataiera so cardholders can use AI agents to search, discover, and transact as part of the UAE’s push to lead in AI-driven commerce. (link)

Mastercard completed its first Agent Pay transaction outside the US: The pilot in the UAE let consumers use AI agents to search, compare, and complete purchases autonomously, showing how Agent Pay could enable fully AI-driven shopping experiences. (link)

Basware rolls out agentic AI to fix error-prone invoices: Two in five invoices arrive with issues or no PO, creating a $549B blind spot. To tackle this issue, Basware’s new InvoiceAI suite uses five agents to read, code, route, and validate both PO and non-PO invoices while saving AP staff 200+ hours a year. (link)

Tech Mahindra ships AI tools for sustainability-linked lending: The new i.GreenFinance platform automates ESG scoring, loan eligibility checks, and audit-ready sustainability reporting by standardizing messy ESG data and verifying milestone-based disbursements across 15+ industries. (link)

OpenAI releases its most advanced agentic coding model: GPT-5.1-Codex-Max can handle million-token contexts, generate and review production code, and run multi-step engineering workflows with built-in defenses like sandboxed execution and prompt-injection protection. (link)

Introducing Claude Opus 4.5: Anthropic’s newest model, Claude Opus 4.5, pushes state-of-the-art performance in coding, agentic workflows, long-context reasoning, and prompt-injection resistance—while running faster and using far fewer tokens across apps, API, Excel, Chrome, and desktop. (link)

Gemini 3 capabilities you need to know: Google’s latest drop adds sharper reasoning, new creative tools like Nano Banana Pro and Veo 3.1, and an experimental Gemini Agent for scheduling and travel tasks. It also upgrades voice controls and language switching. (link)

OpenAI introduces shopping research inside ChatGPT: ChatGPT now acts as a personal buying assistant, asking clarifying questions and pulling from trusted sources to compare products and generate tailored buyer’s guides across categories like electronics, appliances, home, and beauty. (link)

In Other News

Related news you can learn from…

• Fed warns AI-driven trading models could learn collusive behaviors (link)

• UK commits billions to expand national AI capacity (link)

• OpenAI expands independent third-party testing for frontier model safety (link)

• OpenAI teams with Foxconn to build next-generation US AI infrastructure (link)

• OpenAI launches nationwide AI Jam to help 1,000 small businesses build AI tools (link)

Community Corner

Memes and visuals…

@nataliebarbu

NATALIE BARBU on Instagram: "I’m sorry to the people who used t…

Thanks for reading!

Until next week,

— Credit Union AI Guy

Enjoying this newsletter? Forward it to a colleague who might appreciate practical AI insights.

Have a question or want to share your own AI experiment? Reply to this email or connect with us on LinkedIn. We’re building a community of curious Credit Union professionals. Come join the conversation!