Most credit unions don’t have a card problem. They have a growth engine problem. Here’s how AI-powered credit card partnerships can fix it in a member-centric way.
Most credit unions don’t have a credit card problem. They have a growth engine problem.
Interchange is flat, big banks are pouring money into AI-driven rewards and mobile experiences, and members expect their card to “just know” them across channels. Meanwhile, many credit unions are still fighting with batch files, clunky mobile card controls, and marketing campaigns that feel generic.
Here’s the thing about credit card programs: they’re one of the strongest levers you have for member-centric banking—if you combine the right partnership model with the right AI tools.
That’s why Aaron Melnarik’s comment stuck with me from his conversation on The CUInsight Network:
“We’re going to deliver a blueprint for what we know works in our partnerships.”
This post builds on that idea and connects it to a bigger question for 2025: How can credit unions use AI-driven credit card partnerships to grow, protect, and deepen member relationships—without losing control of their brand?
We’ll look at what a modern, AI-enabled partnership actually looks like, how CUs can use data, APIs, and automation to stand out, and practical steps to build a card strategy that serves members first.
1. Why credit card partnerships need an AI upgrade
The smartest credit unions treat their credit card portfolio as a real-time feedback loop about member behavior, not just a product line.
When you combine that data with AI, three things happen:
- You spot risk faster – AI fraud models can flag anomalous behavior in milliseconds, far beyond static rules.
- You grow smarter – propensity models identify which members are ready for a card, a limit increase, or a balance transfer.
- You serve better – personalization engines tailor offers, alerts, and experiences to each member’s actual habits.
Traditional outsourced card programs often gave credit unions scale but not intelligence. The portfolio sat in someone else’s system, and insights came back as a quarterly Excel report.
That doesn’t work anymore.
An AI-first credit card partnership should give you:
- Data access: granular, near real-time transaction data you can feed into your own analytics or AI tools
- Configurable models: fraud, risk, and marketing models tuned to your member base, not a generic national average
- Brand-safe experiences: your app, your messaging, your voice—backed by your partner’s infrastructure
This is where providers like Elan Credit Card are repositioning: not just as processors, but as growth partners that bring both operational scale and digital, API-driven flexibility.
2. The “blueprint” of a modern AI-enabled card partnership
A solid partnership isn’t just a contract and a conversion schedule. It’s a blueprint for how your credit union will:
- Acquire the right cardholders
- Reduce fraud and losses
- Deepen primary relationships
- Modernize member experience over time
From what Aaron Melnarik describes, there are a few building blocks that show up in successful programs.
2.1 AI across the card lifecycle
A practical way to think about AI in credit card programs is by lifecycle stage:
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Acquisition
- Pre-screen models that use internal and external data to predict approval odds and response likelihood
- Next-best-offer engines that suggest the right card or promo based on transaction and product history
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Underwriting & line management
- Machine learning credit decisioning that considers more than just FICO and debt-to-income
- Dynamic line management that increases or decreases lines based on behavior, not just time-based campaigns
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Fraud & risk management
- Real-time anomaly detection across channels (card present, e-commerce, digital wallets)
- Adaptive authentication that steps up verification only when risk spikes, preserving a smooth member experience
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Engagement & retention
- Personalized rewards nudges: category bonus suggestions tied to actual spending patterns
- Proactive outreach for at-risk accounts before spend or satisfaction drops
The best partners don’t just say “we have AI.” They show how those models impact approval rates, fraud loss per $1,000 in spend, and active card usage month by month.
2.2 APIs and mobile: where AI meets the member
Aaron mentions using APIs to revamp mobile apps. That’s not a technical side note—that’s where member-centric banking either works or doesn’t.
Modern card APIs can power:
- Card controls (on/off, travel notices, merchant/category blocking)
- Real-time alerts and notifications
- Dispute initiation and tracking
- Reward balance and redemption
When you layer AI on top, the experience gets smarter:
- Intelligent notifications (only what’s relevant, timed for when members usually check their phone)
- Context-aware card controls (e.g., prompts to enable travel mode based on location patterns)
- Predictive cash flow insights (flagging when upcoming card payments might stress a member’s budget)
A strong partnership gives your credit union access to these capabilities through APIs, so your own digital team (or your digital banking provider) can keep everything inside your branded app.
3. Member-centric AI: what it looks like in practice
AI for credit unions can either feel invasive or incredibly supportive. The difference is how you design around the member.
Here’s what good looks like in an AI-enabled card program.
3.1 Hyper-relevant offers, not spam
Member-centric AI respects attention.
Instead of blasting the same “0% balance transfer” offer to everyone, smart CUs:
- Use transaction and product data to find members actually paying interest elsewhere
- Score likelihood of response and ability to benefit (e.g., debt consolidation, not just rate chasing)
- Deliver offers through the channels members actually respond to (in-app, email, SMS, in-branch)
Result: fewer messages, better results, more trust.
3.2 Fraud protection that doesn’t annoy members
We’ve all had that card decline while traveling or making an unusual purchase. Members hate it, and staff spend time resolving it.
AI-driven fraud systems reduce that friction by:
- Learning each member’s normal transaction patterns
- Flagging real anomalies like impossible geolocation patterns or bot-driven e-commerce attempts
- Adapting over time as behavior changes
When you align with a partner that’s investing heavily in these models, your members get fewer false positives, faster alerts when it matters, and a stronger sense of safety.
3.3 Financial wellness baked into the card
Cards are often seen as the “spending” product, while financial wellness lives in separate tools or content hubs. That’s a missed opportunity.
AI-enabled credit card experiences can:
- Detect early signs of financial stress (rising utilization, missed payments, increasing cash advances)
- Surface personalized budgeting tips, payment plans, or counseling referrals in-app
- Offer just-in-time messages: “If you pay $40 more this month, you’ll be debt-free 3 months sooner.”
This is where the AI for Credit Unions: Member-Centric Banking vision becomes very real: the same data that powers revenue growth can also power financial resilience—if you choose to use it that way.
4. Building and maintaining the right partnership
Technology is only half the story. The other half is the relationship—something Aaron Melnarik emphasizes repeatedly in his work with credit unions.
A strong credit card partnership in 2025 looks like this:
- Shared strategy – Your partner understands your field of membership, growth goals, and risk appetite. You’re not just another portfolio in their book.
- Transparent performance data – You see performance dashboards, test results, and AI model impacts, not just summary reports.
- Ongoing training – Frontline staff and lenders know how to explain card features, AI-driven decisions, and fraud protections in plain language.
- Co-created roadmaps – You’re involved in prioritizing which APIs, features, and AI use cases roll out next for your members.
4.1 Questions to ask potential (or current) partners
If you’re evaluating partners like Elan Credit Card or reviewing an existing relationship, here are direct questions worth asking:
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Data & AI
- How do you use AI in underwriting, fraud, and marketing today for credit unions?
- What performance improvements have you seen in the last 12–24 months (approval rate, fraud loss, active use)?
- What data can our CU access in near real time, and how can we use it in our own analytics tools?
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APIs & digital experience
- Which card features are available via API for our mobile and online banking platforms?
- How do you support co-development or integration efforts with our existing vendors?
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Governance & member impact
- How do you monitor AI bias and fairness in your decisioning and fraud models?
- Can we override or adjust strategies to align with our member-centric philosophy?
When a partner is truly confident in their blueprint, they’ll welcome these questions.
5. Practical next steps for CU leaders in 2025
If you’re responsible for payments, lending, or overall strategy, here’s how to turn all of this into action over the next 6–12 months.
5.1 Audit your current card program through an AI lens
Create a simple scorecard across these areas (1–5 scale):
- Data accessibility and timeliness
- AI use in underwriting and line management
- Fraud detection sophistication and false-positive rate
- Member-facing digital card features (apps, alerts, controls)
- Personalization of offers and communications
Anything at 3 or below is a candidate for either partner enhancement or internal investment.
5.2 Build a joint roadmap with your partner
Sit down with your card partner and:
- Share your scorecard and member feedback
- Identify 2–3 high-impact AI or digital initiatives (e.g., enhanced fraud models, new APIs for your app, personalized campaigns)
- Agree on metrics: approvals, active rate, digital engagement, member satisfaction, fraud losses
- Set quarterly check-ins to review progress and refine models
5.3 Invest in staff understanding, not just tech
AI feels opaque to many staff and members. Clear explanations build trust.
Ask your partner to provide:
- Training on how AI is used in decisions and fraud monitoring
- Simple talking points your frontline can use with members
- Scenarios where staff can override or escalate when something “doesn’t feel right”
The goal isn’t to turn your team into data scientists. It’s to make sure they can confidently stand behind the tools you’re using.
Where AI-powered partnerships go next
Credit card programs have always been important for growth. The difference in 2025 is how much AI, APIs, and data now determine whether that growth feels aligned with your mission—or not.
Partners like Elan Credit Card are shifting from being pure processors to being strategic collaborators, bringing a “blueprint for what works” and the infrastructure to back it up. The opportunity for credit unions is to match that with a clear vision of member-centric banking: fraud tools that protect without frustrating, offers that truly help, and financial wellness features that sit right inside the products members use every day.
If your card program doesn’t feel like a real-time, data-driven engine for member value yet, this is the moment to change that. Ask harder questions, push for AI that serves people first, and expect more from your partnerships.
Because the credit unions that win the next decade won’t be the ones with the flashiest rewards. They’ll be the ones whose technology quietly proves—card by card—that they know their members and have their back.