Advocacy and AI now sit on the same agenda for credit unions. Here’s how to defend members, stay compliant, and build truly member-centric AI services.
Credit unions are losing ground where they’re needed most.
In rural counties and distressed urban neighborhoods, branches are closing, consolidation is accelerating, and members are getting pushed toward providers that don’t always have their interests at heart. At the same time, regulatory pressure and legislation like the Credit Card Competition Act of 2022 are reshaping how credit unions operate and invest.
Here’s the thing about this moment: advocacy and AI strategy are now the same conversation. If your credit union isn’t actively engaged in government affairs and planning how AI will support member-centric banking, you’re putting your future in someone else’s hands.
This post builds on themes from Greg Mesack, SVP of Government Affairs at NAFCU, who spends his days defending credit unions on Capitol Hill. We’ll connect his advocacy perspective with practical ways credit unions can use AI—responsibly—to protect members, stay competitive, and keep serving communities that banks and fintechs often ignore.
Why Advocacy Still Decides What AI You Can Use
Advocacy sets the rules of the game. AI decides how well you can play.
Greg Mesack’s core message—“get engaged and stay engaged”—isn’t just about lobbying. It’s about making sure credit unions still have the permission, economics, and infrastructure to deploy the tools members now expect, including AI for fraud detection, loan decisioning, and member service.
When Congress debates things like the Credit Card Competition Act of 2022 (CCCA), they’re not only arguing about interchange. They’re deciding:
- How much revenue you’ll have to reinvest in member service and technology
- Whether smaller credit unions can afford advanced fraud analytics
- Whether rural and inner-city branches stay viable
If interchange revenue is squeezed without any offset, here’s what typically happens:
- Margins tighten and tech budgets get cut first.
- Fraud losses become harder to absorb, especially in card portfolios.
- Consolidation accelerates as smaller institutions can’t keep up.
That’s exactly the pattern Greg warns about—resources being pulled from the communities that can least afford to lose local financial institutions.
Where AI fits: Credit unions that stay involved in advocacy can push for:
- Regulatory clarity on AI in underwriting and member service
- Reasonable expectations for model explainability and bias monitoring
- Support for community institutions that invest in financial wellness tools
If you’re not in those conversations, you’re stuck reacting to rules written around mega-banks and big tech, not member-centric credit unions.
Member-Centric AI Starts With a Clear Philosophy
The reality? AI in credit unions isn’t mainly a technology problem. It’s a values problem.
NAFCU’s mission is to represent, assist, educate, and defend member credit unions. Your AI strategy should mirror that mindset:
AI in a credit union should first protect members, then empower them, and only then optimize the balance sheet.
Most institutions get this backwards. They chase cost savings and call center deflection, then scramble to bolt on a “member-first” message afterward.
A better framework for member-centric AI:
-
Protect – Reduce harm and friction
- Real-time fraud detection on cards and accounts
- Smarter alerts for unusual activity based on behavior patterns
- Early detection of financial distress using transaction signals
-
Empower – Improve decisions and financial wellness
- AI-powered financial coaching in digital channels
- Scenario tools that show how choices affect savings, debt, and credit
- Personalized nudges that actually help (not just cross-sell)
-
Optimize – Support sustainable growth
- More accurate credit risk models that expand approval rates safely
- Automated workflows in lending, collections, and servicing
- Better pricing and product design tied to member outcomes
If you start every AI conversation by asking, “Does this protect or empower members?” you’ll quickly see which projects belong on your roadmap—and which belong in the trash.
Three High-Impact AI Uses That Defend Members
The most compelling argument Greg makes for advocacy is protection: protecting members from institutions that don’t prioritize consumer interests. AI can be your strongest ally in that mission if you apply it to the right problems.
1. AI Fraud Detection That Protects Rural and Vulnerable Members
Fraud hits hardest where people have the fewest alternatives. When a member in a rural town loses access to their debit card for a week, that’s not a minor inconvenience; that’s lost wages, missed bills, and stress.
AI-based fraud systems can:
- Analyze hundreds of signals per transaction instead of a handful of static rules
- Adapt to new fraud patterns in days instead of months
- Reduce false positives so fewer legitimate transactions are declined
A practical approach for credit unions:
- Start with card fraud analytics, where data is rich and value is clear.
- Set a member-centric metric: fraud prevented and false positive rate.
- Train staff to explain alerts and decisions in plain language.
This is where advocacy and AI collide: if regulatory or legislative changes cut your interchange revenue, your ability to afford advanced fraud tools shrinks. That’s why staying engaged in conversations around payment regulation is directly tied to member safety.
2. Fair, Explainable AI in Loan Decisioning
Greg calls out consolidation and inflation as forces draining resources from distressed communities. One quiet contributor? Credit standards that don’t flex for members with thin files or non-traditional income.
Well-designed AI underwriting can actually expand access to credit for:
- Members with limited credit history but strong transaction behavior
- Gig workers and small business owners with irregular income
- Immigrant and first-time borrowers who don’t fit conventional molds
The must-haves for credit unions:
- Explainability: If a model denies a loan, you need clear reasons a member can understand.
- Bias monitoring: Regular testing for disparate impact across protected classes.
- Override policies: Human lenders can and should override AI where local knowledge matters.
Done right, AI loan decisioning aligns perfectly with the cooperative mission: more approvals for good members, fewer surprises, and better resilience in inflationary periods.
3. AI Member Service Automation That Doesn’t Feel Robotic
Members don’t want to talk to a chatbot. They want fast, accurate help—from a system that actually understands them.
AI-powered member service can help credit unions:
- Provide 24/7 support for common questions: balances, card controls, payments, disputes
- Route complex issues directly to the right human expert
- Maintain consistency across phone, chat, mobile app, and email
The member-centric twist:
- Make escalation to humans obvious and easy.
- Train the virtual assistant on your policies, products, and tone.
- Use interactions to feed better financial wellness recommendations over time.
Advocacy is already shaping the rules around data privacy and AI transparency. If credit unions aren’t visible in those debates, they’ll end up stuck with rules written for big tech chatbots, not community-focused financial guidance.
How Credit Union Leaders Can “Get Engaged and Stay Engaged”
Greg Mesack’s advice applies equally to Capitol Hill and the boardroom: passive institutions lose.
Here’s how I’ve seen progressive credit unions approach both advocacy and AI in a way that actually sticks.
1. Build an Internal Advocacy & AI Task Force
You don’t need a team of 20. You need a cross-functional group that meets regularly:
- Government affairs / compliance
- Lending
- Operations
- IT / data
- Member experience or marketing
Their job isn’t just to receive updates. It’s to answer three questions, every quarter:
- Which regulatory or legislative changes could affect our ability to serve members with AI-enabled services?
- Where can AI reduce member pain or expand access to credit in the next 6–12 months?
- What do we need from NAFCU and other associations to support those goals?
2. Turn Frontline Pain Points Into AI Use Cases
Greg spends his time hearing about structural threats—consolidation, inflation, CCCA. Your frontline staff see the day-to-day fallout.
Ask them:
- Where are members most frustrated today?
- What questions or issues repeat every day or every week?
- Which manual tasks are stopping you from giving members more attention?
Then map those problems to specific AI capabilities:
- Repetitive questions → virtual assistant or smart knowledge base
- Manual document review → document understanding and workflow automation
- Missed early signs of trouble → predictive analytics on account activity
Suddenly, AI stops being a buzzword and becomes a practical response to the pressures Greg is talking about.
3. Use NAFCU and Peers as Force Multipliers
NAFCU’s role—“representing, assisting, educating, and defending”—is exactly what most credit unions need for AI as well:
- Representing: Making sure community institutions are at the table during AI and payments policy debates.
- Assisting: Providing frameworks, templates, and vendor due diligence questions for AI projects.
- Educating: Sharing playbooks and case studies on AI for fraud detection, lending, and member service.
- Defending: Pushing back when regulations or legislation unintentionally penalize responsible AI adoption.
If your team doesn’t know who at NAFCU to call about AI implications of a regulation or a new bill, fix that this month. Greg’s message is clear: engagement isn’t a one-off email; it’s a relationship.
What’s Next for AI, Advocacy, and Member-Centric Banking
The pressures Greg Mesack highlights—consolidation, inflation, the Credit Card Competition Act, and the ongoing battle between banks and retailers—are all symptoms of a bigger shift: the economics of community banking are being rewritten.
Credit unions that thrive over the next five years will do two things well:
- Show up in the policy arena to defend the cooperative model and the communities they serve.
- Adopt AI in a way that’s unapologetically member-centric, focusing first on protection and empowerment.
If you’re leading a credit union today, the next step is straightforward:
- Identify one advocacy issue that could materially affect your ability to invest in technology and AI.
- Identify one AI project that would clearly improve life for members in the next 6–12 months.
- Commit, as a leadership team, to move both forward in parallel.
Member-centric banking in 2026 and beyond won’t be defined by slogans. It’ll be defined by which credit unions fight for the right rules—and which use AI to make those rules work for their members instead of against them.