Most credit unions don’t need more tech – they need AI that supports a holistic, human member experience across every channel. Here’s how to build it.
Why Member Experience Is Your Real Competitive Edge
Credit unions aren’t losing members because their rates are a quarter point higher or lower. They’re losing them because the experience feels confusing, inconsistent, or just forgettable.
Here’s the thing about member experience: it’s already happening, whether you manage it or not. Every interaction – the mobile app, the call center queue, the branch visit, the loan decision time – tells your members who you are.
Taylor Wells from On The Mark Strategies says it plainly:
“A great member experience is going to be holistic and involve everyone.”
That’s exactly where AI for credit unions becomes powerful. Not as a shiny technology project, but as a way to design and scale a consistent, human-centered experience across every channel.
This post builds on ideas from Taylor’s work with credit unions and connects them to the AI tools that are finally mature enough to support true member-centric banking.
You’ll see how to:
- Turn scattered interactions into one connected experience
- Use AI to actually understand your members, not just market to them
- Close the gap between front office and back office
- Align people, processes, brand, and AI so they all work in the same direction
Start With Strategy, Not Software
The best AI projects in credit unions don’t start with a chatbot or a fraud tool. They start with a clear view of the member experience you want to create.
Taylor’s team at On The Mark Strategies does something old-school before anything tech-related: data collection, demographic work, and cross-functional workshops to map the current and ideal member journey.
That’s the right order.
Define the member experience before you automate it
If you drop AI on top of a broken process, you just get faster frustration. Before you deploy any AI member service tools, you should be able to answer in one sentence:
“What does a great member experience look like for our field of membership?”
A few strategic questions to work through first:
- Who are our core member segments (by age, life stage, behavior, not just products)?
- What moments matter most to them? (first account, first car, first home, financial stress, retirement planning)
- Where are we currently making them wait, repeat themselves, or guess what to do next?
Run multi-day workshops with frontline, back-office, IT, and marketing in the same room. Map:
- What members are trying to do
- What they experience now (across branch, call center, digital, and loan processes)
- What an ideal, frictionless version would feel like
Then – and only then – ask: Where can AI help us deliver this consistently?
That’s how AI becomes strategic instead of tactical.
Use AI To Truly Know Your Members, Not Just Target Them
Taylor talks about starting with data and demographics to understand the current member experience. AI simply takes that same idea and scales it.
From scattered data to member-level insight
Most credit unions already have:
- Core transaction data
- Online and mobile usage data
- Contact center notes
- Loan application and decisioning data
- Marketing campaign responses
The problem isn’t data scarcity. The problem is that it lives in silos and no one has time to manually connect it.
AI-supported analytics can:
- Cluster members into behavioral segments (e.g., fee-sensitive, credit builders, digital-first, financially stressed)
- Predict churn risk based on patterns like declining balances, fewer logins, or stopped direct deposit
- Detect life events from transaction patterns (new baby, new job, relocation) that call for proactive outreach
- Personalize offers in ways that are actually helpful (e.g., pre-approved small-dollar credit for overdraft-prone members, not random cross-sell spam)
This matters because a “member-centric” experience isn’t just a friendlier tone. It’s relevant timing plus relevant help.
Practical AI use cases that feel human, not robotic
Here are a few ways credit unions are using AI right now to build better member experiences:
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Smart member service automation
AI assistants handle routine questions instantly (balances, card controls, branch hours, simple loan status) while routing complex issues to humans with context attached. Members spend less time on hold, and staff spend more time on meaningful conversations. -
AI-guided financial wellness
Instead of generic budgeting tips, the system analyzes real member behavior and sends tailored nudges: “You’ve paid $240 in overdraft fees this year. Here’s a low-cost line of credit that would’ve saved you $180.” -
Risk-aware lending decisions
AI-assisted loan models can incorporate more data points more quickly, especially for thin-file or non-traditional applicants, while still staying within fair lending constraints. The result: faster decisions and more approvals for the right members. -
Proactive fraud alerts that make sense
AI fraud models can dramatically reduce false positives by understanding individual member patterns instead of using crude rules like “any foreign transaction is suspicious.” That’s a direct hit on member frustration.
None of this replaces your people. It amplifies them.
Fix The Front-Office / Back-Office Disconnect With Shared Data
Taylor calls out a familiar problem: the gap between front and back-office employees. Frontline staff promise one thing; operations and lending deliver something different or slower. Members feel the inconsistency.
AI by itself won’t fix culture, but it can expose the friction and give teams a shared source of truth.
Where the disconnect usually shows up
Credit unions see this breakdown in places like:
- Loan timelines that vary wildly depending on which branch you visit
- Call center staff who can’t see what’s happening with back-office processes
- Marketing campaigns that push products operations aren’t ready to support
When you start instrumenting these processes with data and simple AI analytics, patterns appear:
- Average time-to-approval by product, channel, and employee group
- Top three member complaints by process step
- Where applications stall and why
Now you can walk into a workshop and say, “Members applying online for auto loans wait 47% longer than in-branch applicants, and they call us 1.8 times on average to ask for updates.”
That kind of clarity unites teams around the member, not around internal silos.
AI as a neutral referee
AI-driven dashboards and journey analytics give everyone the same view:
- Frontline sees what’s realistically happening in the back office
- Back office sees how process delays show up in member sentiment and attrition
- Leaders see exactly which fixes will improve both experience and cost
From there, you can:
- Redesign workflows so the member’s experience is the primary lens, not departmental convenience
- Use AI to automate status updates (“Your loan is now in underwriting”) instead of forcing members to chase answers
- Build shared KPIs: member satisfaction, time to resolution, and first-contact resolution across all functions
This is where organizational health starts to show up in the numbers Taylor talks about – not as a buzzword, but as fewer complaints, less rework, and better member loyalty.
Hiring, Culture, And AI: Get The Mix Right
Taylor makes a point that I strongly agree with: you can’t fix a broken culture with technology. But you can use AI to support the kind of culture you want.
Hire for attitude, support with AI
He encourages credit unions to look both outside and inside the industry for talent. That’s smart. Some of your best future member experience leaders may come from hospitality, retail, or tech support.
Pair that with AI in a few practical ways:
- AI-assisted training: New hires get scenario-based training powered by real member interactions (sanitized, of course). They learn how the best performers respond, not just the policy manual.
- Knowledge assistants for staff: Give employees instant access to procedures, product details, and compliance guidance via an internal AI assistant. That way, they can focus on the human conversation instead of digging through intranet pages.
- Performance insight that’s actually helpful: Use AI to analyze call transcripts or chat logs for sentiment, empathy, resolution patterns – then coach, not punish. Highlight top performers and what they do differently.
Retention: make it easier to do great work
People don’t leave only because of pay. They leave because the tools are clunky, the processes are chaotic, and members are constantly upset.
AI can improve employee experience, which directly improves member experience:
- Fewer repetitive, low-value tasks
- Clearer workflows and next steps
- Less time spent copying data between systems
If you want your people to “Engage, Educate, Entertain” – Taylor’s three E’s – you have to give them the space and support to do it.
Align Brand, Community, And AI-Driven Strategy
One of Taylor’s smartest points is around community involvement and charitable donations: they only build your brand if they line up with your values and your target members.
AI can make this more precise.
Use data to decide where to show up
Instead of sponsoring every event that asks, analyze:
- Where your highest-value or highest-need members live, work, and shop
- Which schools, nonprofits, or small business groups overlap with those communities
- What financial stress signals you’re seeing in your data (e.g., rising late payments, increased payday loan transactions nearby)
Then focus community involvement on areas where you can measure impact:
- Financial wellness programs in schools where a high percentage of your members’ kids attend
- Support for small business ecosystems where you’re already their primary financial partner
- Targeted debt management or savings programs for neighborhoods showing higher financial strain
Make your AI story part of your brand, not a side project
Members don’t care that you’re “using AI.” They care that:
- Fraud alerts are accurate and timely
- Loan decisions are faster and fairer
- Advice feels tailored, not canned
Frame AI as part of your member-centric promise:
“We use modern tools to protect you, respect your time, and give you advice that fits your life – and we’re always here with real people when you need us.”
That’s how AI, strategy, and brand become one story.
Making Member-Centric AI Real In Your Credit Union
Most credit unions don’t need more vendors or more hype right now. They need a clear, actionable plan to make member-centric AI real.
A practical starting path:
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Run a member experience workshop
Bring cross-functional teams together. Map your current and ideal member journeys. Capture where members get stuck, confused, or annoyed. -
Pick 2–3 high-impact use cases
Good early wins: AI-assisted member support, smarter fraud detection, and personalized financial wellness nudges. -
Align your data
You don’t need perfection. You do need: basic data hygiene, access from your AI tools to core and digital channels, and clear data governance. -
Measure outcomes that matter
Track changes in: member satisfaction, call volume, time-to-decision, fraud losses, and product adoption. Share the results internally. -
Keep people at the center
Train and support staff. Treat AI as a coworker, not a replacement. Reward teams for member outcomes, not just volume.
The credit unions that will thrive over the next decade aren’t the ones with the fanciest tech stack. They’re the ones that connect strategy, culture, and AI around a simple idea: make life easier and more hopeful for your members.
If your team is starting to ask, “How do we actually do that?” – that’s the right question.
Featured Image Prompt
A modern credit union branch interior where staff and members interact, with transparent digital overlays showing AI-powered analytics, member profiles, and financial insights, warm lighting, collaborative atmosphere, clean and professional style, subtle technology elements that feel supportive rather than flashy, 16:9 composition.