To sustain their mission for the future, many small credit union CEOs are left with two options: expand their field of membership or merge with a larger credit union. Merging has its drawbacks — it can mean losing some of the uniqueness and autonomy that small credit unions have within their communities.

So, some credit unions might decide that expanding their field of membership works best for them. That leaves the credit union with the task of opening its doors to a whole new cast of members, each with their own unique story, background, perhaps a different regionality, and financial needs.

The only problem with these new faces is that they’re… well, new. They don’t have a history with the credit union yet, creating additional risk when it comes to lending.

Without precise and proven decisioning tools, these new members might not receive an accurate decision, or they could be left waiting for days, not knowing if their new credit union will support their financial goals. And when 73 percent of Americans list finances as their number one stressor, it’s crucial that credit unions of all sizes adapt their practices to serve all members with speed and accuracy.

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We need more data!

Even if a credit union approves most of its current members, it still needs to accurately assess new loan applicants. A big barrier to expanding the field of membership is the lack of data surrounding new members, which requires deeper insights to maintain accuracy and efficiency from their very first contact with the credit union. These new members can include protected classes and thin file consumers, further emphasizing the need for accuracy and speed.

AI-automated underwriting uses more data and predictive modeling to dig deep into each applicant, accurately and consistently assessing the likelihood of default despite gaps in credit history. Powerful AI can take a closer look at tradeline data, producing more high-definition insights than national scores. When tradeline data isn’t enough to make an accurate decision, responsible use of alternative data sources can allow the models to dive deeper into financial and public records that may be difficult to find, or not available on an initial credit report.

Furthermore, AI-automated underwriting is just that: automated. New applicants can receive a decision almost immediately, boosting the credit union’s competitiveness and encouraging new members to stay.

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Serving the underserved

Expanding a credit union’s field of membership can also mean welcoming new members from underrepresented communities, who face biased decisioning and systemic barriers to accessing affordable credit. Credit unions’ not-for-profit model and mission of financial inclusion can benefit these communities, but only so long as lenders have the tools to most effectively serve all members. Biased, outdated methods can make it impossible to give underserved communities a fair shot.

To be the most effective at expanding membership into underserved communities, credit unions still need to adopt practices that will increase the accuracy and fairness of each loan decision. Zest AI’s automated underwriting technology can provide credit unions with a 40 percent lift in approvals on average across protected classes, fulfilling the mission of financial inclusion and allowing new members into the fold.

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The best AI is never one-size-fits-all 

Lastly, it’s not just any AI-automated underwriting model that will do. If a credit union is going to expand into new territory and use AI to increase its speed, accuracy, and financial inclusion, its technology partner needs to ensure these tools are accessible, explainable, and compliant. Small credit unions don’t always have the resources to support new technology — that’s where a dedicated partner who can fill in resource gaps and effectively meet small credit unions’ needs will come into play.

‍AI is not a one-size-fits-all solution, just as lending is not a one-loan-fits-all solution. Whether a credit union decides to expand its field of membership or adapt any of its practices to serve more members, the right technology partner can support these goals to strengthen the credit union’s mission.