Igniting Change in Credit Unions ft. Julie Esser

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TL;DR:

• Credit unions need AI adoption, but they must first define the problems AI will solve, rather than just experimenting.
• Fintechs and credit unions must align on values, regulatory needs, and the member experience to build sustainable partnerships.
• CUSOs allow smaller credit unions to pool resources and access fintech capabilities they couldn’t afford alone.
• Data is critical for AI adoption; credit unions must clean and organize their data to maximize AI’s value.
• Effective AI strategy for credit unions means aligning tech with member-driven outcomes and operational readiness.

Before we dive into the key takeaways from this episode, be sure to catch the full episode here:

Meet Julie - Founder of Ignite FI

Julie Esser is the founder of Ignite FI, a firm that helps credit unions and fintechs navigate partnerships for innovation. With over four decades of experience in the credit union space, Julie has worked both inside the system and as an advocate for fintech integration.

Her expertise lies in bridging the gap between traditional credit union values and the agility of fintech solutions. At Ignite FI, Julie’s work focuses on matching credit unions with the right fintechs, building sustainable collaborations, and helping institutions define the outcomes they want to achieve with emerging technologies like AI and blockchain.

Julie’s passion for the cooperative mission of credit unions drives her to ensure that technology supports, rather than overrides, the member-first approach that defines the industry.

The Key to Credit Union Success: Defining the Problem Before Tech

Julie emphasizes the importance of understanding the problem at hand before diving into tech adoption. “Credit unions are dabbling in AI, but they haven’t yet defined the specific problems they’re trying to solve,” she explains.

Without a clear focus, technology risks becoming a solution looking for a problem. Julie encourages credit unions to step back and consider their most pressing issues first. Once these are identified, the right tech—like AI or blockchain—can be deployed to solve them.

“Once credit unions experience AI in context,” she says, “the wheels will start churning on how it can help solve their challenges.” Without this foundational approach, tech will remain disconnected from real needs.

How AI and Fintech Can Align on Member-Centric Solutions

Julie describes the delicate balance required between fintech innovation and credit union values.

“Fintechs create solutions from the outside looking in, but they must understand credit union values, member trust, and regulatory constraints,” — Julie Esser

The best partnerships emerge when fintechs align their technology with the cooperative mission of credit unions. This includes respecting governance, compliance, and the long-term member experience.

“You need a partner, not just a software vendor when it comes to AI.” — Ankur Patel

“A good fintech fit means shared values and a long-term partnership,” Julie explains. It’s not just about selling products but creating sustainable solutions that enhance the member experience while preserving trust. Julie advocates for deep collaboration where both sides share responsibility for the end result.

Scaling Through CUSOs: Collaboration is Key

Julie highlights the power of CUSOs (Credit Union Service Organizations) to help smaller credit unions scale by sharing resources. “CUSOs allow credit unions to pool resources, reducing costs, sharing talent, and gaining access to fintech capabilities that would be otherwise out of reach,” she explains.

This model gives smaller institutions the leverage to adopt modern fintech solutions while spreading risk and reducing individual investment costs. CUSOs serve as bridges, connecting smaller credit unions with the resources and technologies they need to remain competitive.

Julie emphasizes that collaboration is essential, particularly when scaling fintech adoption across multiple credit unions. “We’ve seen great success when credit unions collaborate through CUSOs,” she adds.

The Data Challenge: Organizing Credit Union Information for AI

“Data is the second most important asset next to money.” — Julie Esser

Julie emphasizes that organizing and leveraging data is key to successful AI adoption.

Credit unions often face messy data systems that lack structure and integration, creating barriers for AI tools to function effectively. Julie argues that before any technology can be leveraged, credit unions must clean and organize their data.

Without this preparation, AI tools will suffer from poor input, leading to suboptimal results. “Garbage in, garbage out,” she warns. Once data is organized and ready, AI can begin to provide real value. The first step, she believes, is educating credit unions on the importance of proper data governance to ensure AI’s success.

Building a Long-Term AI Strategy in Credit Unions

Julie emphasizes that adopting AI is not about deploying a quick fix but about building a long-term strategy. “AI can’t just be a shiny tool,” she notes. “It must align with the credit union’s mission and solve real, member-driven problems.”

Julie advocates for a thoughtful, strategic approach where credit unions first define the outcomes they wish to achieve. Once those outcomes are clear, AI can be used as a tool to reach them. She adds that success in AI adoption requires a continuous learning process.

“It’s about building strategy first, then tech,” she says, urging credit unions to avoid rushing into technology without a clear understanding of the desired impact.

Would you like to learn more about AI in credit unions? Check out this episode on how FORUM credit union uses our AI ft. Chris Ferguson.