AI-Powered Payment Strategies For Member-Centric CUs

Most credit unions saw the same thing during the pandemic: payments changed faster in 18 months than they had in the previous decade. Matt Good from Elan Advisory Services puts a number on part of it—about 45% of Americans moved to contactless payments. That’s not a blip. That’s a permanent reset of member expectations.

Here’s the thing about payments: they’re no longer just plumbing in the background. For credit unions that care about member-centric banking, payments are where trust, data, and daily engagement all collide. And now, AI sits right in the middle of that collision.

This post builds on insights from Matt Good’s conversation on The CUInsight Network and connects them to something very practical: how AI can help credit unions modernize payment solutions, rewards, and member communication without losing their relationship-driven DNA.

From Contactless To Context-Aware: The New Payment Baseline

Contactless is now table stakes. The competitive advantage comes from how smart those payments are.

Member behavior since the pandemic is clear:

• More digital transactions (card-not-present, mobile wallets, subscriptions)
• Less patience for friction or delays
• Higher expectations for rewards that fit real life, not generic categories

If you try to manage all that with manual processes and static product designs, you’re always reacting. AI flips that dynamic.

How AI Changes The Payment Equation

AI in payments for credit unions isn’t about fancy tech for its own sake. It’s about three concrete capabilities:

1. Prediction – Who’s likely to adopt contactless? Who’s at risk of attrition? Which members would respond to a new streaming rewards offer?
2. Personalization – Which reward categories should each member see? What credit line feels right based on behavior, not just a FICO band?
3. Protection – Which transactions look normal for this member and which scream fraud?

When you combine those, you get what I’d call context-aware payments: every swipe, tap, or tokenized transaction is processed with an understanding of the member behind it, not just the merchant code in front of it.

AI-Driven Rewards: From Generic Points To Real-World Value

Matt Good calls out something every CU leader has felt: rewards programs have shifted hard since the pandemic. Travel points suddenly weren’t useful. Groceries, delivery, streaming, and everyday digital services became the new “luxury.”

Most credit unions responded with category tweaks—more cash back on groceries, streaming, gas. Helpful, yes. But AI lets you go much further.

What An AI-Powered Rewards Program Looks Like

A genuinely member-centric rewards program powered by AI typically includes:

• Dynamic categories: The system automatically surfaces the most relevant categories (e.g., streaming, grocery, rideshare) for each member based on their spend history and similar cohorts.
• Smart bonus offers: Instead of blasting a “5% back on gas” promo to everyone, AI identifies which members:
  • Actually spend on gas
  • Are most likely to shift more volume to your card
  • Are at risk of switching to another issuer
• Lifecycle-based rewards: A younger member might get boosted rewards on subscriptions and ride-share; a growing family might see elevated rewards on groceries, wholesale clubs, and child-related spend.

This matters because relevance is what turns rewards from a cost center into a loyalty engine.

Practical Steps For Credit Unions

You don’t need a massive data science team to start using AI in rewards. Most CUs can work in phases:

1. Phase 1 – Data Readiness

   • Consolidate debit, credit, and digital wallet transaction data where it can be analyzed together.
   • Clean member profiles (contact info, age, household, preferred channels).

2. Phase 2 – AI Insights

   • Use an AI analytics platform (or a partner’s tools) to cluster members by spend behavior.
   • Identify patterns: heavy grocery shoppers, frequent streamers, subscription addicts, small-business spenders.

3. Phase 3 – Targeted Offers

   • Launch 1–2 tailored rewards campaigns per segment.
   • Measure:
     • Spend shift to your card
     • Active card usage days per month
     • Member satisfaction (survey or NPS by segment)

4. Phase 4 – Ongoing Optimization

   • Feed campaign results back into the AI model.
   • Let the system refine which offers actually move behavior.

If you’re not experimenting with this level of AI-driven reward design by 2026, larger banks and fintechs will own the day-to-day payments relationship with your members.

AI + Payments = Real-Time Fraud Detection Members Can Feel

The more contactless and card-not-present transactions your members make, the more exposed they feel to fraud. And they’re right—fraud patterns have become more complex, especially around:

• Subscription trial scams
• Merchant takeovers
• Digital wallet token abuse
• Account takeover through phishing and social engineering

Traditional rules-based fraud systems are blunt instruments. They trigger too many false positives, decline legitimate transactions, and frustrate members.

AI-driven fraud detection, on the other hand, learns each member’s unique behavior and flags anomalies in real time.

What Strong AI Fraud Protection Looks Like

A member-centric credit union using AI for fraud detection can:

• Spot unusual patterns within seconds (new merchant type, foreign IP, weird time-of-day behavior)
• Approve more legitimate transactions while reducing false declines
• Trigger intelligent step-up verification (push notification or SMS) only when necessary

You know it’s working when members say things like:

“My CU caught a weird charge within minutes and made it easy to confirm it on my phone.”

That’s not just fraud prevention. That’s a trust moment.

Integrating AI Fraud With Your Member Experience

Here’s where many institutions get it wrong: they bolt on AI fraud tools but don’t adapt the member experience around them. A better approach:

• Align fraud alerts with digital channels
  Make sure alerts flow through your mobile app, SMS, and email in a consistent, plain-language way.

• Feed fraud insights into your member 360
  When a member calls, your staff should see recent fraud events and resolution history.

• Use conversational AI to triage
  A simple AI assistant inside digital banking can:

  • Confirm if a transaction is recognized
  • Temporarily freeze a card
  • Start a dispute process

This lets your human staff focus on complex cases and emotional conversations, not routine verification.

Smarter Member Communication: AI As Your Always-On Education Layer

Matt Good emphasizes constant communication about rewards and benefits. He’s right. Most members don’t know half of what their card or account actually offers.

AI can turn that communication gap into an engagement advantage.

From Generic Emails To Contextual Nudges

Instead of monthly blasts that most people ignore, AI can drive individualized, timely messages, such as:

• “You spent $120 on streaming this month. Turning on your CU card’s streaming rewards could earn you $X back next month.”
• “You’ve used tap-to-pay at groceries five times this month. Add your card to your mobile wallet for faster checkout.”
• “You’re close to a higher rewards tier based on last month’s spend. Here’s how to reach it.”

These aren’t gimmicks. They:

• Educate members about benefits in the context of their actual behavior
• Increase primacy of your card or account
• Reinforce your role as a financial partner, not just a transaction processor

AI-Powered Member Service For Payments Questions

Payment questions clog call centers, especially during holidays and travel season:

• “Why was my card declined?”
• “Is this subscription charge legitimate?”
• “How do I set up contactless or a digital wallet?”

An AI assistant trained on your payment products, policies, and transaction codes can handle the bulk of these front-line questions.

The best setups I’ve seen:

• Let the AI answer directly inside digital banking and your mobile app
• Escalate to a human with full context (member question + AI summary + relevant transactions)
• Use insights from those conversations to refine your knowledge base and product design

That’s member-centric AI in action: less friction for the member, less strain on your staff, better data for the organization.

Making AI In Payments Realistic For Mid-Sized Credit Unions

Most credit unions don’t have a data lab or an AI research team. The good news: you don’t need one to get real value.

Here’s a pragmatic roadmap:

1. Start With One High-Impact Use Case

For most CUs, I’d prioritize in this order:

1. AI fraud detection – Protect members and reduce losses
2. AI-powered member communications – More effective, personalized engagement
3. AI-driven rewards optimization – Improve card usage and loyalty

Pick one, define a success metric (fraud loss reduction, card usage lift, or reduced call volume), and execute.

2. Choose Partners Who Understand Credit Unions

Vendors like Elan Advisory Services exist for a reason: they bring scale, analytics, and payments expertise you don’t need to build alone.

When evaluating partners, ask:

• How do you handle data privacy and explainability of AI decisions?
• Can you show results specifically for member-owned institutions, not just big banks?
• How easily does your solution integrate with our core and digital banking providers?

If a partner can’t explain their AI in plain language to your board, they’re probably the wrong fit.

3. Keep Your Mission Front And Center

AI should amplify your member-centric mission, not dilute it. Use that as your filter:

• Does this AI solution help us understand members better?
• Does it make life easier, safer, or more rewarding for them?
• Does it free up staff to have more meaningful, human conversations?

If the answer’s no, it’s just tech for tech’s sake.

Where AI, Payments, And Member-Centric Banking Converge

Payments are the most frequent interaction most members have with their credit union. That makes them the perfect proving ground for AI-driven, member-centric banking.

The institutions that will win over the next few years will:

• Treat contactless and digital payments as a data-rich relationship channel
• Use AI to power relevant rewards, timely fraud protection, and smart communication
• Lean on partners where it makes sense, while staying crystal clear about their mission

Matt Good’s comment resonates here: tough times reveal leaders. The rapid transformation of payments has been tough. The leaders are the credit unions that read member behavior honestly, adopt AI thoughtfully, and refuse to give up their relationship edge.

If your payment strategy still feels rooted in pre-pandemic habits, now’s the moment to rethink it. Start with one AI-powered use case, measure the impact, and build from there. Your members are already living in a contactless, always-on world. The question is whether their credit union feels like it belongs there, too.