From transforming member experiences to building a culture of information literacy, data has become a catalyst for innovation at credit unions. New use cases are constantly emerging for organizations willing to explore them, and artificial intelligence will only increase their value.

In a PaymentsJournal Podcast, Jeremiah Lotz, Senior Vice President of Experience Design and Enterprise Data at Velera, and Christopher Miller, Lead Analyst of Emerging Payments at Javelin Strategy & Research, explored how credit unions are collecting and leveraging data to improve efficiency and better serve their members. 

Forward-thinking credit unions view their data not just as a resource, but as a strategic asset—a goldmine of insights into both members and the business itself. While many credit unions have already invested heavily in data, unlocking its full potential requires clarity on what the organization hopes to achieve. The first step is understanding how the institution intends to put that data to work.

“Look at what the data is saying, and how will it help us make decisions, as opposed to just for historical information,” said Lotz. “Once the organization recognizes that there’s an opportunity to use the data to make decisions or drive intelligence, that’s a sign of a mature level of adoption.”

A key driver is executive alignment at the C-suite level, ensuring that the credit union can use its data to grow, engage and retain membership, and ultimately inform decisions. The next step is empowering data teams to suggest use cases, regardless of the division they work in. When non-technical staff can articulate business needs that data can address, it reflects a culture that is ready to move forward.

“It’s a way to be able to say, ‘I have a problem’ or ‘I have an opportunity that maybe data could help me with,’ versus expecting people to say, ‘Hey, I think you’ve got data. Let me see these three fields and see if it does anything for me,’” Lotz said.

Credit unions are learning that consumer data isn’t just numbers—it’s a roadmap to a better member experience. By analyzing individual patterns, institutions can spot potential financial challenges or opportunities before they happen. Using predictive insights in this way transforms interactions, moving beyond reactive service to experiences that delight members.

“It doesn’t always have to be super aggressive,” said Lotz. “It can be more about putting something in front of them that might help in a situation, if they so choose.”

At the same time, members expect their data to be used responsibly—but they often worry about privacy. Credit unions can address these concerns by clearly communicating how data usage benefits members, showing that it’s designed to make their financial lives easier and more personalized.  

“Whether it’s coupons I receive or recommendations when I’m shopping online, we know this data collection exists,” said Lotz. “It would be nice to understand that my financial institution is going to use it in a way that’s going to help me, that’s going to protect me or maybe give me opportunities by predicting my behavior.”

Predicting when a member might need a product is just the beginning. Data can also streamline everyday interactions. Instead of asking members to fill out forms, a credit union can provide pre-populated applications or automatically update existing accounts. These anticipatory actions reduce friction and create a tangible, member-first experience that sets the institution apart.

“I have a mortgage with a credit union and it is quite possible for that credit union to predict that each year I need to provide proof that I have homeowners insurance,” said Miller. “This is not a magical data-derived prediction. It’s literally in the system.”

“But to the extent that the credit union would be able to anticipate that this is a need—some document has to be provided and returned. The institution has to take that action proactively, rather than dumping it on me to follow up with. You have the opportunity to turn what might be transactional interactions into wow moments.”

Data literacy isn’t just about understanding the data—it’s about understanding what lies behind it and how the organization can leverage it. That starts with conversations between data and business teams, which require a shared language across the organization.

“By having that conversation at every level, you’re giving the opportunity for the people who understand the data to start talking with the individuals in the business units and the operations teams,” said Lotz. “Once they start talking about some common problems that they’re facing, they can start to look at data as an asset.”

Identifying ambassadors for the data practice is helpful—individuals who understand how data connects not only to their regular work but also to new opportunities. Considering how to disseminate and distribute data is an important part of bringing non-technical employees into the process. When leadership can put actionable, accessible information into everyone’s hands, it fosters a fully data-literate organization from top to bottom, rather than concentrating knowledge in the hands of a few specialists.

Artificial intelligence has the remarkable ability to uncover patterns and insights within vast amounts of data, but it’s important not to put the cart before the horse. AI should inform and enhance decision-making, not dictate how data is used.

“We have to focus on understanding governance before glamour sometimes,” said Lotz. “We’ve got to make sure we’re focused on responsible enablement of AI. We’re focused on data quality, model transparency and ethical use. Those are non-negotiable things when it comes to AI.”

When applied thoughtfully, AI can power a range of purpose-driven use cases that support members’ well-being. From fraud prevention and personalized experiences to credit risk insights and financial wellness tools, AI works best when it’s focused on initiatives that make sense and deliver real value to members.

“One of the things that a mature governance structure can do is communicate the fact that organizations have to deal with technology like this with urgency,” said Miller. “But it is not an emergency. If we don’t deploy the new tool next week, that is not the end of the world. It is better to do it correctly and in a sustainable, stable method that results in continuous new improvements than it is to get something out there immediately today.

“There’s an opportunity to harness the energy that can come from throughout an organization, with appropriate attitudes toward doing things that are sustainable and lead to long-run change,” he said. “When you have a group of individuals who understand the technology can then start a conversation within the organization, that’s a great opportunity.”