AI can probably tell a prospective customer your checking account fees, current CD rates and mortgage terms, but what does it know about why people choose your institution or why they stay?
It’s a question worth asking as consumers begin using tools like ChatGPT and Gemini to research financial products. Someone looking for a mortgage lender or a new checking account can ask AI to compare options, explain terms and recommend institutions. Much of that conversation will naturally focus on things that are easy to compare, like rates, fees and product features.
For community banks and credit unions that have worked hard to differentiate themselves through relationships, service and local expertise, that’s a concern. If those advantages aren’t reflected in the information AI can find, consumers may never hear about them. And if the only information readily available about your institution is what you offer and what it costs, you’ve effectively handed your differentiation over to the comparison engine.
The big banks have a head start…Again.
The largest financial institutions have spent decades putting their expertise into the public domain. Economic forecasts, small-business research, executive commentary and media coverage have created a substantial body of information about who they are and what they know. That history may give them an advantage as AI tools draw on information from across the web to answer consumer questions.
Meanwhile, a community bank may have a commercial lender who understands the challenges facing local manufacturers better than anyone at a national institution. A credit union may have helped hundreds of first-time homebuyers navigate a difficult housing market. That expertise is real and valuable, but much of it never makes it beyond customer conversations, community events or the occasional LinkedIn post.
Community institutions can’t undo years of big-bank visibility, and they certainly can’t match the volume of content those organizations produce. However, they can do something about how little of their own expertise is visible outside the institution.
We’ve always talked about making intangible brand advantages tangible. AI gives us another reason to take that challenge seriously.
What does AI actually know about your institution?
As bank and credit union marketers, we’re paying attention to answer engine optimization (AEO) and generative engine optimization (GEO). Understandably, much of the conversation is about whether an institution appears in AI-generated recommendations. I’d argue that how you’re described matters just as much.
If AI recommends your credit union because it offers competitive auto loan rates, what happens when another institution offers a better rate? If your community bank shows up in a checking account comparison but there’s no mention of its expertise serving local businesses, are you really getting credit for what makes you different?
It’s worth spending some time asking ChatGPT, Gemini and other AI tools the kinds of questions prospective customers might ask:
- Which banks in [region] have experience financing manufacturing businesses?
- Why would someone choose [institution] over a national competitor?
- What makes [credit union] different from others in [market]?
Look at the answers and the sources behind them. See how your competitors are described. You may find that your institution’s strongest advantages barely register, or that the answers rely on the same generic claims about personal service and community commitment that appear on nearly every bank and credit union website.
AI responses vary by platform and prompt, so this isn’t a definitive measurement exercise, but it can tell you something about whether the story you’re telling about your institution is supported by information others can actually find.
The brand and demand debate just got more complicated
We’ve been having the brand versus demand conversation in financial services for years. And frankly, demand usually wins. When you’re accountable for account openings, loan growth and deposit acquisition, it’s easier to defend dollars tied directly to an application than investments in brand awareness or reputation. Unfortunately, that decision may be catching up with us.
We’ve spent years getting better at promoting products, targeting consumers who are ready to buy and measuring the results. Many of us have not put the same effort into building a public record of what makes our institutions worth choosing.
Much of the expertise that supports a community institution’s brand lives with the people serving customers every day. Yet marketing teams don’t always capture those experiences or turn them into something prospective customers can learn from.
That’s a missed opportunity regardless of what happens with AI search. As more of the research process moves into AI-powered tools, the consequences could become more significant.
Give AI something worth finding
I don’t think the answer is to suddenly produce more content or divert limited budgets into every new AEO tool. Most community institutions don’t have the resources for that, and volume alone won’t solve the problem. Instead, start with one business priority and identify the institutional expertise that supports it.
If growing commercial lending among healthcare practices is a priority, talk to the bankers who work with those clients. Find out what they understand about practice financing that a generalist lender might not, what questions come up repeatedly and what they can share that would help a practice owner make a better decision.
Then turn that knowledge into useful content, informed executive commentary or the basis for a story in a regional business publication. Customer experiences, when they can be shared, can help demonstrate what your institution’s expertise looks like in practice.
The same approach applies to claims about service and relationships. Nearly every financial institution makes them. Far fewer provide specific evidence of what those promises mean for customers.
This is where brand, content and public relations need to work together. The goal is to make your institution’s strengths more visible and credible beyond your own marketing channels. This means explicitly and consistently sharing the impact that your financial institution has on your customers. Over time, that creates a more complete picture of your institution for prospective customers and potentially for the AI tools they use to research their options.
There’s no guarantee that any of this will earn you an AI recommendation. But it gives you a better foundation than hoping a comparison of rates and fees will somehow communicate the value of a relationship.
A different kind of competitive gap
Community banks and credit unions have spent years narrowing the digital convenience gap with larger competitors. Now they may face a new disadvantage, one shaped partly by how much information already exists about the institutions they’re competing against.
You can’t change what the big banks have published over the past 20 years, but you can take a harder look at what your own institution is putting into the world today.
We’ve spent years arguing for a better balance between brand and demand. AI may make that conversation harder to avoid. Because the expertise your institution is known for among existing customers won’t necessarily help you win new ones if nobody outside those relationships knows it exists.