AI, Payments & Members: What Credit Unions Miss

Most credit unions now process more digital payments than branch transactions, yet many still treat payment data as an operational byproduct instead of a strategic asset. That’s a missed opportunity.

Here’s the thing about payment trends: they’re not just about which card or mobile wallet wins. They’re a live feed of member behavior. When you combine that with AI, you get something every credit union leader wants: member-centric banking at scale.

Inspired by insights from Tom Pierce, CMO at PSCU, this post connects payment trends—mobile wallets, BNPL, crypto, and even “financial aesthetics”—to practical AI use cases for credit unions that want to stay relevant in 2025 and beyond.

Why Payment Trends Are Your Best Member Intelligence Engine

Payment data is the single richest source of behavioral insight most credit unions already own but underuse.

Every tap, swipe, or digital payment tells you:

• Where a member shops
• How often they spend
• Which channels they prefer (card, wallet, P2P, BNPL)
• Whether they’re under stress or thriving financially

AI turns these raw transactions into patterns:

• Propensity models predict who’s likely to adopt mobile wallets, use BNPL, or churn
• Segmentation models group members by real behavior, not just age or zip code
• Next-best-action engines suggest what to offer a member next—card upgrade, financial coaching, line increase, or fraud check

The reality? It’s simpler than you think to start. Most credit unions already send card files to processors, CUSOs, or providers like PSCU. The gap isn’t data—it’s strategy and execution.

If you’re building a roadmap for AI in your credit union, payment data should be step one, not step five.

Mobile Wallets: From Optional Feature to Baseline Expectation

Mobile wallet adoption has shifted from “early adopters” to everyday behavior, especially for younger members.

Tom Pierce’s research highlights that mobile wallets are now a preferred payment method for younger generations and increasingly used across all age groups. The pandemic accelerated this, and the behavior stuck.

For a member-centric credit union, the question isn’t “Should we support mobile wallets?”—that’s already a yes. The real questions are:

• Are your cards top-of-wallet in Apple Pay, Google Pay, and Samsung Pay?
• Do members even know you support wallets?
• Are you using AI and data to drive activation and ongoing usage?

How AI Can Boost Mobile Wallet Adoption

AI can analyze which members are most likely to add your card to a wallet and then personalize your outreach:

• Identify members who:
  • Transact heavily at contactless merchants
  • Shop at stores where tap-to-pay is the norm
  • Have newer smartphones but no wallet tokenization yet
• Trigger personalized campaigns:
  • In-app prompts: “Add your credit union card to your mobile wallet in 10 seconds.”
  • Targeted emails or SMS when members visit specific merchants
  • Step-by-step tutorials tailored to older or less tech-confident members

Use AI to test and optimize messaging: some segments respond to security benefits, others to convenience, others to rewards. Over time, you’ll see wallet usage grow without blasting the same generic message to everyone.

BNPL, Crypto & New Payment Habits: Risk or Opportunity?

New payment types—especially Buy Now, Pay Later (BNPL) and crypto—aren’t fads for younger members; they’re normal tools.

Pierce points out that emerging payment trends differ sharply by generation:

• Younger members are far more likely to use BNPL and experiment with crypto
• Older generations remain more tied to cards and ACH

Too many credit unions either ignore these trends or treat them as existential threats. That’s a mistake. The better play is to:

1. Understand how members already use these tools
2. Decide where you’ll compete, where you’ll partner, and where you’ll simply monitor

Using AI to Manage BNPL Risk and Experience

BNPL can be both a member-experience opportunity and a credit risk headache. AI helps you stay on the right side of that line.

Practical AI use cases for BNPL:

• Behavioral risk scoring
  • Detect members whose BNPL usage is increasing across multiple providers
  • Flag signs of financial stress before delinquencies hit your books
• Credit line and product recommendations
  • Offer a small-dollar installment product when AI sees repeated BNPL use for essentials (groceries, utilities)
  • Suggest consolidating BNPL balances into a structured personal loan with lower rates
• Member education at the right moment
  • Trigger in-app education when BNPL patterns shift from “occasional convenience” to “debt dependency”

Instead of scolding members for using BNPL, use AI to understand why they’re using it and where your credit union can offer a healthier, more transparent alternative.

Crypto: Monitor, Don’t Panic

Crypto isn’t going to replace checking accounts for mainstream members any time soon, but it’s a signal. Members curious about crypto are often:

• More digitally savvy
• More open to new financial tools
• Good candidates for early adoption of digital experiences

AI can flag crypto-related activity (transfers to known exchanges, patterns in P2P payments) and feed that into your member segmentation. Use that insight to:

• Offer these members advanced digital features first
• Involve them in beta programs for new apps and AI-driven tools
• Target them with content around risk, diversification, and long-term planning

You don’t have to offer crypto to stay relevant. You do need to understand which of your members are living in that world.

Financial Aesthetics: Why Design Now Matters for Trust

Tom Pierce mentions “financial aesthetics” as an emerging theme—and he’s right to. Members don’t just compare your credit union to other financial institutions anymore. They compare your app experience to the apps they use daily.

Here’s the uncomfortable truth:

If your mobile banking looks and feels dated, members assume your services and technology are dated too. That’s a trust problem, not just a branding issue.

Where AI Enhances the Member Experience

AI won’t design your brand identity, but it will make your digital experience feel smarter and more personal:

• Contextual interfaces
  • Show the most relevant actions based on time of day, location, and behavior (e.g., “Pay upcoming bill” or “Review unusual transaction”)
• Personalized financial wellness views
  • Instead of static dashboards, use AI to highlight what matters this week: “You’re on track to pay down your card 2 months early” or “Spending is 18% higher than usual in restaurants.”
• AI-powered chat and guidance
  • Integrated virtual assistants that actually understand transaction context: “What was this $47 charge?” “Can I afford to increase my car payment by $50?”

The aesthetic shift isn’t just about pretty screens. It’s about experiences that feel intuitive and responsive—and AI is what makes that possible without hiring an army of UX designers and analysts.

Generational Differences Matter—But Data Matters More

Pierce underscores differences across generations in payment preferences: younger members favor digital wallets and new payment types, older members stick closer to cards and traditional channels.

That’s useful, but I’ll be blunt: if you stop at generational generalizations, you’ll design for stereotypes instead of people.

The better approach is “behavior-first, age-second.”

Use AI to Build Behavior-Based Segments

Instead of saying “Millennials like X, Boomers like Y,” use AI to cluster members based on:

• Digital engagement (app logins, wallet usage, P2P payments)
• Credit usage and repayment patterns
• Channel preferences (branch, call center, mobile, web)
• Financial resilience (savings rate, bounced payments, BNPL usage)

You’ll discover:

• Some 65-year-olds behave like your most digital-native 25-year-olds
• Some 30-year-olds behave like traditional branch loyalists

Design experiences, communications, and product offers for those segments. Age still matters—it affects life stage and needs—but behavior should drive your AI models and your strategy.

Turning Payment Trends into an AI Roadmap for Your CU

Most credit unions don’t need more theory; they need a clear starting point. Here’s a practical roadmap to use payment trends and AI in a member-centric way.

1. Start With One High-Impact Use Case

Pick one of these and commit:

• Mobile wallet activation model
  • Goal: increase tokenized cards and wallet spend
• BNPL risk and wellness model
  • Goal: identify at-risk members and offer better alternatives
• Digital engagement segmentation
  • Goal: tailor contact strategies and product offers

You don’t need a full-blown internal data science team to do this. Many CUSOs, processors, and AI vendors already support these capabilities. Your job is to prioritize.

2. Connect AI Outputs to Real Member Experiences

An AI model is useless if it just sits in a dashboard. Tie the outputs directly to:

• Campaign rules in your marketing automation platform
• Offers and prompts in your mobile and online banking
• Scripts and alerts for your contact center and branch staff

For example:

• If AI predicts high likelihood of wallet adoption → trigger an in-app prompt and a follow-up email
• If AI flags BNPL stress → schedule a financial wellness outreach or in-app message with options

3. Measure What Members Actually Feel

Don’t just track model accuracy. Track member outcomes:

• Wallet activation and ongoing usage
• Reduced delinquency or overdraft for at-risk members
• Net Promoter Score or satisfaction for segments you target

Ask members directly in your app or via short surveys: “Was this suggestion helpful?” Use that feedback to refine models, not just marketing copy.

Where This Fits in Your AI for Credit Unions Strategy

Payment trends aren’t a side project—they’re the backbone of member-centric AI for credit unions.

If you’re building or refining your AI roadmap, payment data should fuel:

• Fraud detection that adapts to new payment types
• Loan decisioning that understands real spending and resilience
• Member service automation that knows transaction context
• Financial wellness tools that respond to how members actually spend and borrow

The credit unions that will grow in the next five years aren’t necessarily the ones with the most branches or the flashiest app. They’ll be the ones that treat every payment as a conversation starter—then use AI to respond with intelligence and empathy.

Your members are already telling you who they are with every tap, swipe, and click. The question now is whether your institution is ready to listen.