AI-Powered Protection For Underserved Members

Most credit unions say they serve the underserved. Very few can prove it with data.

Here’s the thing about member-centric banking: if your protection products, outreach, and pricing are designed around the top 10–20% of income earners, you’re not member-centric. You’re premium-centric. The middle-market households that credit unions were created to support? They’re still exposed, underinsured, and one emergency away from serious financial stress.

That’s why I like how TruStage frames its work with credit unions as noble and relentlessly focused on the underserved. And it’s exactly where AI for credit unions becomes more than a buzzword. Used well, AI gives you the scale, personalization, and insight to actually serve these members, not just market to them.

This post builds on ideas from Joe Boan, SVP Head of Sales Distribution at TruStage, and connects them to practical ways AI can help credit unions bring protection and financial wellness to the middle market in 2025.

Why the Underserved Middle Market Is Your Biggest Missed Opportunity

The fastest way for a credit union to grow in a sustainable way is to solve real problems for the middle market: working families, gig workers, first-time homebuyers, and members who don’t think of themselves as “insurance people.”

TruStage is clear about this. Their business is 100% focused on credit unions and their members, with a specific emphasis on underserved, middle-income consumers. Instead of designing products for the wealthiest slice of the market and hoping everyone else fits, they do the opposite: build for middle-market realities.

For most credit unions, those realities look like this:

• Members with inconsistent income or gig work
• Limited emergency savings (often < $1,000)
• High exposure to income shocks (job loss, illness, unexpected expenses)
• Very low uptake of traditional life and protection products

The gap is massive. Many members need simple, affordable protection more than complex wealth products.

And here’s the key: AI, used properly, makes it much easier to identify who’s exposed, when to talk to them, and how to present protection in a way that feels helpful rather than pushy.

How AI Turns Protection Products Into Member Service, Not Sales

AI in credit unions isn’t just for fraud and chatbots. It can quietly power a more humane, member-first approach to protection—exactly what TruStage is trying to achieve with its partners.

1. Smarter Segmentation: Finding the Quietly At-Risk Members

Most credit unions segment by age, product, and maybe balance. That’s a start, but it misses nuance.

AI-based segmentation models can analyze patterns like:

• Income volatility and frequency of overdrafts
• Debt-to-income trends over time
• Life events inferred from behavior (marriage, new child, new mortgage, new car)
• Digital engagement signals (what content members read, what tools they use)

From there, you can identify micro-segments such as:

• “New parents with under $500 in savings and no life insurance”
• “Single-income households with rising credit card utilization”
• “Members 50+ supporting adult children and aging parents”

These aren’t just marketing segments. They’re risk realities. When TruStage talks about being tailored to the middle market, this is where AI can operationalize that philosophy day-to-day.

2. Timing and Context: Reaching Members When It Matters

Protection conversations land best when they’re connected to a real moment, not a generic campaign.

AI can watch for event-based triggers like:

• A new auto loan booking → suggest payment protection
• First mortgage closing → surface mortgage protection or life insurance options
• Major deposit from a new employer → prompt for income protection education

Instead of a random “Do you want life insurance?” email, members receive timely, contextual messages like:

“You’ve just taken on a new auto loan. Here’s how many members use affordable protection to keep their families safe if something unexpected happens.”

That’s not aggressive cross-selling. That’s responsible member care, and it aligns with TruStage’s mission and the cooperative DNA of credit unions.

3. Product Fit: AI-Guided Recommendations, Not One-Size-Fits-All

Most members don’t buy protection products for two reasons:

1. They’re overwhelmed by jargon.
2. They assume it’s too expensive.

An AI-powered financial wellness assistant can stop that pattern. Here’s how:

• Ask a few plain-language questions about household, income, and obligations.
• Run those through rules + machine learning models informed by partners like TruStage.
• Recommend one or two right-sized protection options at realistic coverage levels.

You’re not pitching the member a giant, abstract policy. You’re saying:

“Based on your current situation, most members like you start with this basic coverage. Here’s what it costs per month in your case.”

That simplicity is exactly what middle-market households respond to.

Where TruStage’s Approach and AI Naturally Fit Together

Joe Boan has seen the industry from just about every angle: brokerage, direct-to-consumer, and now distribution for credit unions. The throughline in his perspective is clear: protection products should serve real people, not just balance sheets.

When you map that mindset onto AI, you get a practical roadmap.

AI + Purpose-Built Products

TruStage designs protection products specifically around credit union members, not generic bank customers. Think:

• Simpler underwriting
• Fewer decision points
• Affordable entry points for middle-income households

AI can amplify that by:

• Matching each member to the least complex option that still improves their resilience
• Surfacing “starter coverage” for members who’ve never bought insurance before
• Identifying when a member is ready to expand coverage as their financial situation improves

The result is a journey, not a one-time sale.

Distribution as Member Education, Not Pressure

Joe talks about seeing the industry as someone who helps individuals directly and as a distribution partner. The lesson: distribution should feel like education plus choice.

AI-powered channels—chat, messaging, in-app prompts—can:

• Explain protection concepts in natural, conversational language
• Give side-by-side comparisons tailored to the member’s income and debts
• Let members “try on” scenarios (e.g., “What happens if I’m out of work for 3 months?”) using simple simulations

When members understand, they buy. And they stay.

Aligning Financial Security With Non-Interest Income

Some credit unions still treat non-interest income from protection products as something to be slightly apologetic about. That’s backwards.

If you’re:

• Offering appropriate, member-fit coverage
• Pricing fairly, especially for the underserved
• Using AI to avoid bias and overselling

…then the income you earn isn’t a side hustle—it’s fuel for your mission.

TruStage’s model is built on that alignment: help members become more financially secure while generating sustainable income for the institution. AI simply helps you do it at scale and with better accuracy.

Practical AI Use Cases Credit Unions Can Launch in 2025

You don’t need a massive data science team to start. Here are realistic, high-impact ways to bring AI into your TruStage-style protection strategy.

1. Member Risk & Protection Gap Scoring

Build or adopt a model that assigns each member a protection gap score based on:

• Household income vs. fixed obligations
• Presence or absence of key protection products
• Age and inferred life stage
• Savings and liquidity signals

Use that score to:

• Prioritize outreach from your team
• Feed targeted, educational journeys in digital channels
• Set up dashboards for frontline staff so they can have better conversations at the branch or in contact centers

2. AI-Assisted Outreach Scripts for Staff

Your frontline and call center teams aren’t actuaries—and they don’t need to be.

Give them AI tools that:

• Summarize a member’s key risks in one simple view
• Suggest 2–3 natural language openers (“Given your new mortgage, a lot of members ask about…”)
• Provide simple explanations of TruStage-style products in plain English

Now your people can sound like seasoned financial guides, even if they’re new. That’s a huge win for consistency and member trust.

3. Digital Journeys for Underserved Segments

Use AI to power member-centric banking journeys that are specific to the underserved:

• A “new to credit” path that pairs credit-builder loans with affordable protection
• A “young family” path that highlights basic life coverage plus savings automation
• A “gig worker” path with income protection, budgeting tools, and micro-savings

Each journey should:

• Educate in short, clear modules
• Offer one simple action at a time
• Respect that the member might be anxious about money

If you’re working with a partner like TruStage, co-design these journeys so product rules and compliance are built-in from day one.

Guardrails: Using AI Responsibly for Underserved Members

AI can absolutely help you serve the underserved—or it can quietly exclude them if you’re careless. You can’t skip guardrails.

Here’s what responsible looks like:

• Bias checks: Regularly test your models to ensure they’re not implicitly penalizing low-income members or protected classes.
• Explainability: Make sure staff can explain, in human language, why a certain protection recommendation was made.
• Opt-in transparency: Tell members when AI is being used to tailor offers, and frame it as a service, not a sales trick.
• Human override: For complex or sensitive situations (health issues, job loss), make it easy to escalate from AI to a human advisor.

Done right, AI becomes an assistant to your cooperative mission, not a replacement for it.

Where This Fits in Your AI for Credit Unions Roadmap

Serving the underserved isn’t a tagline; it’s a series of operational decisions.

TruStage’s model—focused on credit unions, grounded in middle-market realities, and oriented around protection and financial security—pairs naturally with a member-centric AI strategy. When you combine the two, you get:

• Better identification of at-risk, underinsured members
• More relevant and timely protection conversations
• Increased non-interest income that’s directly tied to member resilience
• Stronger loyalty, because members can feel the difference

If you’re mapping your 2025 AI roadmap, don’t stop at fraud detection and chatbots. Put protection for underserved members on the agenda. Talk with your protection partners about how their products and your data can work together. And challenge every AI use case with a simple question:

“Does this make our members more secure, especially the ones who’ve historically been left out?”

Credit unions that can honestly answer “yes” will win the next decade of member trust.