Credit card programs are the fastest path for credit unions to apply AI to fraud, lending, and member experience—if you treat them as platforms, not products.
Most credit unions are sitting on an asset they’re not fully using: the data running through their credit card portfolio.
Every authorization, every dispute, every tap at a gas pump is a signal about member needs, risks, and opportunities. The difference between a stagnant card program and a growth engine in 2025 is how well you turn those signals into action with AI and smart partnerships.
That’s the thread running through Aaron Melnarik’s work at Elan Credit Card and his conversation on The CUInsight Network: a blueprint for credit card partnerships that actually grow the credit union, not just add another product. In this post, I’ll connect that blueprint to AI for credit unions and show how modern card programs can become the core of member‑centric banking.
If you’re thinking about how to compete on digital experience, fraud protection, and personalized offers without a Fortune 100 tech budget, this is for you.
From Product to Platform: Why Credit Cards Matter More in the AI Era
A modern credit card program is no longer just an interchange and rewards machine; it’s a data and engagement platform that feeds your entire AI strategy.
Here’s why that matters:
- Card transactions are often the most frequent touchpoint you have with members
- They generate real-time, high-volume data perfect for AI models
- They intersect directly with fraud, lending, and financial wellness—all core CU priorities
Elan’s approach, as Aaron describes, is to bring a blueprint of what works to each new partner. The smart move is to extend that mindset: treat your card program as the anchor for AI-driven, member-centric banking.
How a card program feeds AI for credit unions
When your card program is integrated into your core and digital channels via APIs, you can:
- Train fraud detection models on live transaction patterns
- Enhance loan decisioning with behavioral spend data
- Fuel member service automation with context-rich insights
- Drive financial wellness tools that react to real-life spending
The reality? You don’t need to build this from scratch. You do need a partner and operating model that treats credit cards as strategic, not tactical.
A Blueprint for Member-Centric, AI-Ready Partnerships
Aaron talks about delivering a blueprint for partnerships that consistently work. For credit union leaders, that blueprint should include three non-negotiables: alignment, enablement, and data access.
1. Strategic alignment: growth, risk, and member value
A good card partnership doesn’t start with rewards tiers; it starts with strategy. You should be crystal clear on:
- What growth means for your CU (deposits, active users, total spend, interchange)
- How much credit risk and portfolio management you want to own
- What member experience you refuse to compromise on
The best partners are honest about trade-offs. Outsourcing portfolio management, for example, can free you to focus on digital experience, AI-driven insights, and member relationships. Keeping it in-house might give you more control but demand capabilities you don’t have staff for.
I’ve found that the most successful CUs in 2025 treat card programs as joint ventures: shared goals, shared data, shared responsibility for member satisfaction.
2. Enablement: training, change management, and culture
Aaron highlights ongoing training and support as a core part of Elan’s model. That’s not a nice-to-have; it’s the difference between:
- An AI-enhanced card program staff barely understand
- A front line that confidently explains fraud alerts, digital wallets, and new credit tools
For an AI-forward credit card program, you should expect:
- Training on AI features: fraud alerts, virtual cards, credit line automation
- Playbooks for contact center and branch staff: how to talk about AI with members, handle concerns, and highlight benefits
- Regular reviews of performance metrics: activation rates, fraud losses, digital engagement, member feedback
Most AI projects fail quietly in the gap between “we bought the tech” and “our people know how to use it.” Aaron’s focus on training is exactly how you close that gap.
3. Data and APIs: the foundation for AI
Aaron mentions using APIs to revamp mobile apps. This is where AI for credit unions gets real.
At minimum, your card partner and tech stack should provide:
- Real-time access to card balances, transactions, and alerts
- Secure APIs that your digital banking provider can consume
- Clear data-sharing agreements that allow you to run internal analytics and AI models
When card data flows into your data warehouse or analytics platform, you can:
- Identify at-risk members before they churn
- Spot patterns of card-not-present fraud faster
- Build Next Best Action models for cross-sell and financial wellness outreach
No APIs, no AI. It’s that simple.
Where AI Adds Real Value in Credit Card Programs
AI in credit card programs is not about flashy chatbots. It’s about concrete, measurable improvements in fraud, lending, service, and member well-being.
Smarter fraud detection that members actually trust
Card fraud is personal. When you get it wrong, members remember.
AI-driven fraud detection can:
- Analyze thousands of transaction attributes in milliseconds
- Learn each member’s unique spending profile
- Reduce false positives while catching more real fraud
Here’s the nuance: if your partner implements AI fraud models but your front line can’t explain why a transaction was declined, members experience it as random punishment, not protection.
A strong partnership model means:
- Shared fraud reporting and dashboards
- Scripts and training for staff when members call upset about declines
- Member-friendly controls in the app: travel notes, spending limits, instant freeze
This is member-centric AI: powerful in the background, transparent and controllable up front.
Better loan decisioning from real behavior, not just bureau scores
Credit unions have always prided themselves on relationship-based lending. AI can support that philosophy instead of replacing it.
With rich card data feeding your lending models, you can:
- See income and spending stability patterns over time
- Identify responsible card use that may not be obvious from a credit report
- Offer pre-approved lines or balance transfer offers that feel thoughtful, not pushy
The best setups allow you to pair AI-driven scores with human overrides for edge cases and deep relationships. That’s how you keep your values intact while still moving faster than large banks.
Member service automation that feels human
Member-centric automation doesn’t start with, “Let’s add a chatbot.” It starts with, “Where are members getting stuck?”
Credit card programs are full of these moments:
- “Why was my card declined?”
- “What’s this merchant name? I don’t recognize it.”
- “Can I increase my limit for this one purchase?”
AI-driven member service for cards can:
- Pre-answer these questions in your app with contextual explanations
- Use conversational AI to complete tasks: dispute a charge, request a new card, set controls
- Hand off smoothly to a human with full context when needed
The key is tight integration between your card platform, CRM, and digital channels. That’s where partners that bring a tested blueprint have an edge—they’ve already solved the plumbing.
Financial wellness tools based on real spending
If you’re serious about member-centric banking, your card program should be a pillar of your financial wellness strategy.
AI models can:
- Categorize spending accurately without member effort
- Flag emerging risks: rising BNPL use, frequent overdrafts, growing card balances
- Trigger proactive nudges: payment reminders, pay-down plans, or coaching sessions
The difference between “creepy” and “caring” is consent and clarity. Be open about what data you use, how AI works, and how members can control it. Partner with providers who respect that line.
Executing the Blueprint: Practical Steps for CU Leaders
Turning these ideas into reality doesn’t require a moonshot project. It does require focus and the right questions for your partners.
1. Audit your current credit card experience
Start with what members feel today:
- How easy is it to activate a card, add to a mobile wallet, and set controls?
- How clear are fraud alerts and dispute processes?
- How well is your card experience integrated into your mobile app?
Run this audit like a member: sign up, use the card, lose it (on purpose), and resolve an issue. Document every friction point.
2. Clarify your AI priorities
You don’t need AI everywhere at once. For most credit unions, the highest-impact priorities are:
- Fraud detection and member-friendly controls
- Smarter targeting for pre-approvals and line management
- Digital self-service for common card questions
Pick 1–2 to focus on in the next 12 months. Use those to guide partner conversations.
3. Ask partners specific, non-generic questions
When you talk with a card provider or fintech, skip the buzzwords and ask:
- How do your APIs integrate with a typical CU tech stack like ours?
- What AI models are you actually using, and how do they improve fraud, approvals, or experience?
- What training and ongoing support do you provide to our staff?
- How do you share data with us so we can run our own analytics and AI?
You’re looking for concrete answers, not vague assurances.
4. Build a cross-functional “card+AI” squad
Don’t run this as a pure IT or pure lending project. Bring together:
- Card program owner
- Digital banking lead
- Risk/fraud leader
- Contact center manager
- Data/analytics or IT representative
Give this group a simple mandate: improve the member credit card experience while increasing portfolio growth and reducing avoidable losses. Review progress monthly.
Where This Fits in Your AI for Credit Unions Journey
AI for credit unions can feel abstract until you tie it to something concrete. A member swiping (or tapping) a card is about as concrete as it gets.
A well-designed partnership like the one Aaron Melnarik describes—strong training, API-driven tech, and a clear blueprint—becomes the practical way to:
- Turn raw transaction data into smarter fraud defense
- Turn daily spending into more accurate credit decisions
- Turn member frustrations into automated, thoughtful experiences
If you’re building a member-centric banking strategy, your credit card program is one of the best places to start applying AI at scale while staying true to cooperative values.
The next step is straightforward: assess where your current card program stands against this blueprint, identify the AI-powered capabilities that matter most for your members, and push your partners—and your own team—to meet that bar.
The credit unions that win the next few years won’t be the ones with the flashiest tech stack. They’ll be the ones who use tools like AI and strong partnerships to quietly make members’ financial lives feel easier, safer, and more personal every single day.