AI in Credit Unions: Unraveling the Good, the Bad, and the Risk-Free
A credit union's reason to use AI in 2024
Mid-November, I hosted a webinar looking ahead at 2024 and the economic uncertainty that another new year is bringing for lenders big and small. I asked our attendees — made up of leaders from across the credit union industry — how they felt about next year's prospects, and 56% of them responded that they thought 2023's trends would persist. A third of attendees said they believed things would get more challenging. Not a lot of room for optimism, but with the struggles that the financial services industry has faced in the last 12 months it's better to prepare for another rocky year instead of doing nothing and hoping for the best.
When it comes to what those leaders' most significant concerns for 2024, they responded that these were the top issues they saw: 42% accelerating delinquencies & charge offs, 35% lack of liquidity, 14% customer acquisition & share-of-wallet, 5% fraud increasing, 2% antiquated tech, and 2% talent acquisition.
The Good, the Bad, and the Ugly
Much like a classic spaghetti western film, we had our heroes and villains for the year, but also an anti-hero was established.
The US GDP rose at an unexpected 4.9% in the third quarter of 2023, and the unemployment rate has stayed relatively stable throughout the year. Interest rates are still high, and the savings people built up during the pandemic started dwindling. Consumer delinquency rose 54% in two years. Inflation is dropping, though the effects of this are still to be seen, with prices on staple goods still high throughout the country.
2024 is shaping up to be a unique macro environment. But there are some steps credit unions can take this year strategically: Increase automation to capture efficiency gains, proactively manage portfolio and incoming credit risk, and prepare for growth in the future.
Embrace automation, become more efficient
Let's look at the high-level benefits of automating your loan decisions: you experience a more frictionless experience, gain operational efficiencies, increase booking rates, see more consistent underwriting decisions, and improve your members' experiences through these efforts. But these high-level benefits aren't the only ones you'll see in adding AI to your lending decisions.
Would you believe me if I told you that risk-free automation is possible for your organization? Well, believe it or not, powerful AI models using the latest in technology actually do allow for risk-free automation. It's generally easy to automate in the top and bottom tiers. But those middle and lower credit tiers can't be automated when they're not able to be accurately risk-ranked. Machine learning algorithms have proven to be more accurate in calculating risk across the credit spectrum, meaning using AI in your underwriting enables both automation and better risk management.
Manage risk proactively
As fraudsters themselves are adopting AI, fraud solutions must incorporate AI, too. Currently, most credit unions are solving fraud with a very hands-on approach. But with over two-thirds of global banking leaders predicting an increase in fraud in 2023 and 69 percent of credit unions reporting first-party fraud issues, that manual process won't be fast enough to compete and likely can't accurately predict that first-party fraud. However, AI can help credit unions minimize credit and fraud risk at the time of application. A fraud model can detect those patterns quickly without becoming overactive in screening, which leads to high false positives. Applying AI to your anti-fraud practices helps your organization lower risk and move more rapidly to help members in need.
Get ready to grow down the road
Plenty of business decisions are made with instant or quick ROI in mind. Which AI certainly brings — but there are also benefits down the road that remain to be seen.
When your organization grows in its use of AI technology:
● More applicants can be instantly and accurately approved instead of being manually approved
● You can eliminate instant decisioning rules that are redundant against the model insights
● Underwriters' jobs are repurposed for high-value tasks like cross-selling, collections, member service, etc.
● Policies can be updated and optimized to match today's reality
● Your credit union is more prepared to respond rapidly to changing economic conditions
● Modifying credit decisioning rules & criteria becomes more straightforward as you gain expertise, meaning you can streamline the process for credit policy changes
When utilizing AI to its greatest potential, your organization gains the opportunity to compete with larger organizations and online banking options. You're reducing costs and improving your members' experience all in one go.
About Author:
Adam Kleinman – Head of Strategy and Client Success
Adam Kleinman is a business development manager at Zest AI. He has spent his entire career working with the financial services industry and has an MBA from the University of Chicago Booth School of Business with a concentration in econometrics and statistics. He is a self-proclaimed fitness nerd and enjoys reading, traveling, and CrossFit.