In today’s rapidly evolving financial landscape, it’s crucial for credit unions to look ahead at the strategies and innovations needed to future-proof their lending practices to continue to serve their communities for years to come. It’s no longer a game of wait and see with the acceleration of digital expectations and the need to be agile in quickly changing economic conditions.

As financial cooperatives, the core purpose of credit unions is to make loans and foster growth in the community. While the ongoing surges in interest rates have indeed presented challenges such as margin compression and expense control, it’s still important for all credit unions–especially the smaller ones–to investigate deeper investments in tools that allow them to lend confidently, and better navigate volatility.

In 2020 I gave a virtual presentation to the NYCUA titled, “Marketing in the New Normal.” This was peak COVID time, and as you can imagine, the credit union industry was all a bit shell shocked.

My opening slide was designed as a poll and asked this question: How many of these things did your credit union already have in place prior to the shut down?

• Electronic signatures
• Remote deposit capture
• Voice banking
• AI enabled chatbots
• CRM system

Not a single credit union could answer yes to all five. Looking at that list now, it’s table stakes. Today we find ourselves in yet another unfamiliar situation with anxiety around a looming recession while we watch rising inflation and interest rates.

According to a July 2023 FinRegLab white paper titled, Explainability & Fairness in Machine Learning for Credit Underwriting, “The coming years could offer the most fundamental reset of lending practices in several decades.”

In order to remain competitive and inclusive, credit unions need to embrace innovation and adopt new, more advanced approaches to evaluating creditworthiness. It’s time to move beyond the traditional model of determining credit worthiness, and acknowledge it is inherently biased, and doesn’t serve the members or create a durable lending business. Machine learning (ML) provides a path forward with its ability to provide deeper and more accurate insights, addressing the inadequacies of the old industry standards.

The March 2023 CUNA report revealed there are 4,712 credit unions in the U.S. Of those, almost 3,000 are under $100M in assets. And we know that this army of financial cooperatives are serving some of the smallest communities with the greatest financial need.

To ensure that this group of smaller credit unions survives and thrives for years to come depends a lot on how they lean into and educate themselves on machine learning innovation, and how ML providers are doing their due diligence in policy and compliance as well. Whether, and to what extent these new systems prioritize responsible, fair, and inclusive use of machine learning models and secondary tools will ultimately depend not just on technology issues, but on business and policy decisions.

The hope is that small credit unions will embrace this change and lead the way in fairer and smarter lending to support their members and community now and in the future.

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Denise Wymore – Manager, Corporate Philanthropy

Denise Wymore is an inductee to America’s Credit Union Museum and a cheerleader for passion and commitment. Currently, she is the Marketing Manager for Small Credit Union Initiatives at Zest AI and is proud to be a credit union lifer who started her career as a teller.