Credit card and merchant programs are now core to AI for credit unions. Here’s how to use partners, data, and AI to grow risk‑free income while staying member‑centric.
Why credit card strategy is now an AI problem
Credit card spending in the U.S. has grown more than 15% since 2020, and a huge share of that growth is digital and card‑not‑present. For credit unions, that’s both opportunity and risk: more interchange income on one side, more fraud, compliance pressure, and member expectations on the other.
Here’s the thing about card programs in 2025: if they’re not data‑driven and AI‑assisted, they’re quietly falling behind. Members are comparing your experience to big banks and fintechs every time they tap, click, or add a card to a digital wallet.
In a recent CUInsight Network episode, Matt Good from Elan Credit Card talked about how credit unions can expand credit card offerings and merchant services while offloading risk. That same mindset—outsourcing the heavy lift while staying member‑centric—is exactly how AI should fit into your strategy too.
This article connects those dots: how AI, smart partnerships, and a modern credit card program can help credit unions grow risk‑free income, serve small businesses better, and stay true to the “people helping people” mantra.
From plastic to data: the new role of credit card programs
A modern credit card program isn’t just a product; it’s a data engine for your entire credit union.
When members use their credit union credit card, you’re not just earning interchange—you’re learning:
- Where they shop
- How they travel
- Which digital wallets and devices they prefer
- Their risk patterns and repayment behavior
That’s the raw fuel AI needs to power member‑centric banking.
Why this matters for member experience
AI tools can turn card data into:
- Real‑time fraud detection that blocks suspicious activity in seconds
- Proactive alerts when spending looks unusual or risky
- Personalized offers that match real behavior (not generic campaigns)
- Contextual credit line management, increasing or tightening limits based on patterns
Most credit unions don’t have the in‑house resources to build all of this from scratch. That’s where partnerships like Elan come in: they run the engine, you bring the trust and member relationship.
The reality? Members don’t care who your card processor or AI vendor is. They care that:
- Their card works everywhere
- Disputes get resolved quickly
- Fraud is handled before it becomes their problem
- Offers actually feel relevant
AI is what makes that possible at scale.
Offloading risk while upgrading digital: what Elan gets right
Matt Good emphasizes that Elan’s credit card model removes credit risk and compliance risk from the credit union while still providing a strong, branded solution. That structure pairs surprisingly well with AI.
How AI + outsourced credit risk can work together
When a partner takes on credit and compliance risk, they’re naturally motivated to invest in:
- Advanced fraud models using machine learning
- Real‑time transaction monitoring across millions of cards
- Regulatory change management, including model governance and explainability
That’s work most small and mid‑size credit unions don’t want on their plate—especially as AI regulation tightens.
In a member‑centric AI strategy, your role shifts:
- You set the experience standards: how fast disputes are handled, what member communication looks like, and how generous you want rewards to feel.
- Your partner handles invisible complexity: model tuning, data pipelines, compliance, and back‑office operations.
I’ve seen this go wrong when the credit union thinks “outsourced” means “hands‑off.” The better approach: treat your card partner like a key AI infrastructure provider and hold them to that bar.
Ask blunt questions:
- How are you using AI for fraud detection and chargeback prevention?
- How do you explain AI‑driven declines to members and staff?
- How do you prevent bias in credit decisioning models?
- What transparency can you offer on model performance and error rates?
If they can’t answer clearly, they’re not ready for your members.
Serving small businesses with AI‑ready merchant services
Matt makes a strong point in the episode: small businesses are looking for all‑in‑one service from their financial institution. They don’t want four different dashboards for deposits, lending, payroll, and payments.
This is exactly where AI‑enabled merchant services and credit card programs can help a credit union stand out.
What small businesses actually want
Most business owners I talk to want three things from their financial partner:
- Simplicity – One place to see cash flow, card settlements, and fees.
- Predictability – Clear pricing, stable funding timelines, no surprises.
- Insight – Help understanding whether they’re healthy or at risk.
AI‑powered tools built into a merchant services platform can:
- Forecast cash flow from card transaction history
- Flag slowing sales or rising refunds
- Identify when a business may need a line of credit
- Benchmark performance against similar local businesses (without exposing identities)
When your credit union offers merchant services through a partner like Elan, you’ve got a foundation to plug these AI tools into. That’s where strategy matters.
Best practices for choosing a merchant services / card partner
From Matt’s comments and what I’ve seen with successful credit unions, a solid partner should:
- Own the complex risk (chargebacks, PCI, fraud models) so you don’t have to
- Offer white‑label or strong co‑branding so the experience still feels like your credit union
- Provide open data access or usable reporting so you can feed data into your AI stack
- Include API‑driven integration with your digital banking and CRM
- Support embedded financial wellness tools for business owners
If a vendor only talks about rates and terminals, they’re missing the bigger picture. You’re not buying hardware; you’re buying a data and AI foundation for serving local businesses.
Community impact: AI, cards, and “people helping people”
Matt Good calls out something a lot of tech conversations skip: community impact and charitable giving. For credit unions, that’s not a side project; it’s the brand.
Here’s where AI and card programs can quietly amplify that impact instead of diluting it.
Turning card spend into local impact
A few practical ideas I’ve seen work:
- Round‑up donations on card purchases that automatically support local nonprofits
- Category‑based rewards that give bonus points for spending at local businesses
- Community goals where members can vote on which cause receives pooled rewards or program funds
AI can add another layer:
- Identify which members are most engaged with community offers and target them with more meaningful campaigns
- Use transaction data to highlight how much spend is staying local vs. going to national brands
- Flag members who show signs of financial stress, then route them to human financial counselors or digital wellness tools instead of bombarding them with credit offers
If you’re serious about “people helping people,” your AI strategy needs hard guardrails: no predatory cross‑sell, transparent explanations when models decline or flag activity, and clear opt‑outs for data use.
The negative impact Matt warns about—credit unions not showing up in their communities—absolutely applies to AI decisions too. Silent, opaque models that harm vulnerable members will undo years of trust.
Practical roadmap: AI‑ready credit card and merchant strategy
Here’s a straightforward way for a credit union to align credit cards, AI, and member‑centric banking over the next 12–24 months.
1. Clarify your goals
Decide what you actually want from your card and merchant programs:
- Higher interchange income with limited risk?
- Better fraud detection and lower losses?
- Deeper relationships with small businesses?
- Stronger financial wellness outcomes for members?
Pick 2–3 primary goals. Everything else supports them.
2. Audit your current capabilities
Ask your internal teams and your existing partners:
- How is fraud handled today? Is AI involved? What’s the false‑positive rate?
- Can we see granular card and merchant data by member segment?
- How quickly can we change credit line strategies or offers?
- Where do members feel the most friction in disputes and chargebacks?
Document the gaps. You’ll use them as a checklist when evaluating vendors.
3. Choose partners that think in AI terms
When you evaluate card issuers or merchant services providers, push beyond the sales deck:
- Do they talk specifically about model governance, fairness, and explainability?
- Can they support real‑time decisioning for fraud and offers?
- How do they handle data sharing back to your credit union while staying compliant?
- Will they collaborate on AI‑driven member journeys, not just vanilla campaigns?
Partners like Elan that already absorb credit and compliance risk are often more prepared to manage AI risk too—but you still have to ask.
4. Build member‑centric AI use cases, not just models
Start with experiences, not algorithms:
- A fraud alert flow that reassures members instead of panicking them
- A credit line increase experience that feels like a reward, not a mystery
- A business insights dashboard for small business members, powered by their own card and merchant data
Work backward from those journeys to the data and AI capabilities required. Most of the time, you’ll use a mix of:
- Vendor‑provided models (fraud, risk scoring)
- Your own analytics (segmenting members, community impact tracking)
- Simple rules‑based logic to keep things transparent and fair
5. Keep humans in the loop
Even the best AI‑driven card program still needs:
- Trained staff who can explain why a transaction was declined
- Clear escalation paths when members disagree with a model’s decision
- Ongoing review of outcomes across demographics to spot bias
The target state isn’t “AI vs. human.” It’s AI doing the pattern recognition and heavy lifting so your people can focus on empathy and judgment.
Where this fits in your AI for Credit Unions journey
This article is part of a broader AI for Credit Unions: Member‑Centric Banking series for a reason: credit card and merchant programs are often the first and most impactful place to apply AI.
You already have the data. Your members already use the products daily. And partners like Elan already shoulder much of the risk and infrastructure.
The next step is strategic: treating your credit card and merchant services programs as core to your AI roadmap, not side products.
If you’re a credit union leader, the question to ask right now isn’t “Should we use AI?” It’s:
Are we using AI, partnerships, and card data in a way that makes members feel safer, better served, and more connected to their community?
If the answer is “not yet,” this is the part of your strategy that can change fastest—and have the clearest impact on member trust and non‑interest income.