TruStage Discovery2024 Coverage: How Credit Unions Can Safely Approach AI Strategy

Lydia Wedlock, writer for The Credit Union Connection

Credit union leaders got an in-depth look into artificial intelligence and its growing role in the credit union industry during the TruStage Discovery2024 Conference. The Embracing AI panel was moderated by Filene Fellow and Finance Professor at DePaul University Lamont Black. The panel also featured Chief Strategy Officer at Municipal Credit Union George Chacon, CEO of SAVVI AI Maya Mikhailov, and VP/Chief Data Officer at BCU John Sahagian.

Principles of AI

AI is a technology that is still growing and evolving, and it’s easy to get scared and defensive when it comes to using it. In the case of BCU, the leadership decided to establish a committee to be on both offense and defense when creating their AI strategy. As Sahagian explained:

“We're still trying to understand the risks and the applications and such, but we need to make sure that we set some principles out of the gate to tie back to, first of all, to acknowledge what's going on. There are risks and responsibilities associated with this, so let's make sure that our shared values as an organization are reflected in how we're using AI.”

Those principles start by putting the member first. By keeping the members' needs front of mind, credit unions can better guide an AI strategy and how it will directly affect the membership, Sahagian said.

Taking Ownership of AI

At Municipal CU, Chacon said, “We tossed around the question of where AI should live within the organization for a while. And where we landed was that it would live in strategy with the chief strategy officer, myself.”

He continued, “There are a couple of things we think we can accomplish by doing that. First, I own the vision and strategy for AI at MCU, but it also involves developing a roadmap for use cases in the next one to three years.

“More importantly, assembling a diverse team that can see that roadmap through, and also bringing outside expertise to augment some of the internal expertise we already have. At the center of the organization with strategy is, for us, it's, you know, it's a good place to have it working alongside all the business units. We envision AI living at MCU as an accelerant, as an enabler of strategy, which is centered around the member.

Machine Learning and Generative AI

If you’ve ever had a product recommended to you while online shopping or seen similar shows to one you’ve been bingeing in the feed of your preferred streaming app, that’s machine learning, a type of AI at work, Mikhailov illustrated. It’s the algorithms learning about you and what you like.

“Credit unions can also apply this kind of machine learning to figuring out what their members need most,” she said. “A couple of examples include informing members of services they might be looking into and getting ahead of a loan potentially moving away from the credit union.”

When those needs are identified, generative AI can get the process rolling. It can help get the information that members are looking for faster and more efficiently. This can give credit union staff more time to focus on assisting members in getting what they need and solving the more significant problems.

CUs’ Data Vault

When credit unions are looking to grow, they may not realize they already have an essential tool at their disposal: data. As Mikhailov put it:

“It's amazing when we start talking to folks at credit unions about deposits. I said, ‘You already have the data you need in your member transaction history. You're already looking at this wealth of information that's being funneled at you every single day about what your members are doing. And now, you can start finding signals in that noise.’

“What are the signs that a member may churn, and how can you get folks ahead of it, not just churn next month, churn six months from now? How can you find those members that are most likely at risk and start building back that relationship with them or finding out why they're at risk?”

The wealth of data credit unions already have from members using their services daily can tell you what services they use most and if a problem needs to be addressed. Once you have a question that needs an answer, credit unions can use the data to find the answer.

The idea of embracing AI may seem a little scary at first, but if credit unions take the time to implement a member-centric AI strategy, they can help stay ahead of the curve and better provide services for their members.