More Than a Score: Using AI to Empower Members Across the Credit Spectrum

June 27, 2023

Alyssa’s car broke down yesterday. She couldn’t get it to start when she took her kids to school, and it was far too expensive to fix. She found a neighbor willing to help her out in the meantime, but she needs a new car.

Liam just graduated high school and decided to open a credit card in his name. He makes minimum wage working at a fast food restaurant near the college he will attend next fall, and wants to build his credit by paying for gas and groceries.

Sonia immigrated to the U.S. several years ago. Despite her professional success, on-time rent payments, and financial stability in her new country, she doesn’t qualify for a mortgage anywhere.

Alyssa, Liam, and Sonia are all thin-file members. Traditional scoring methods typically leave them at an unfair disadvantage, or unable to even be scored.

‍But these members still deserve a fair shot, right? Any credit union leader would tell you they have an imperative to help these members prosper.

According to Zest AI, AI-automated underwriting makes it possible to accurately and fairly assess Alyssa, Liam, Sonia, or most everyone else, for that matter.

With more data and better math, machine learning algorithms can accurately assess thin-file borrowers, leaving your credit union with the necessary confidence and knowledge to lend across the credit spectrum.

‍Knowing who carries a high level of risk, quickly, allows you to devote more attention to the members who truly need it. ‍

Knowledge. Is. Power.

‍The ability to spot high-risk members gives your credit union the ability to intentionally allocate resources where they’re needed most. You instantly know which members need more attention, and in turn, increase automatic approvals and yield.

For example, when using AI-automated underwriting, you discover that Alyssa is less of a risky borrower than traditional scoring models would make it seem. You can confidently provide her with an auto loan without much worry.

You also discover that Sonia is more than qualified for a mortgage when you use AI-automated underwriting to determine her risk, so she confidently starts house hunting knowing your credit union will be there to help finance her new home.

With these loans through your credit union, these two members are now roped into the credit system and can build their credit history when paying off their debts.

On the other hand, you begin to notice that Liam’s credit card balance is trending upward, and he’s starting to see his credit score drop.

Because AI-automated underwriting can automate redundant tasks, loan officers now have more time to focus on Liam. We find out that Liam keeps forgetting when his payments are due, so we set him up with automatic payments. He leaves feeling satisfied and stops missing his payments.

Time for those pivotal moments for financial advice and counseling is a powerful benefit of AI-automated lending. With a 67% resource efficiency gain, loan officers can provide that essential counseling. Think about how many Liams are out there, that could use that extra boost or education from a trusted financial institution. AI helps empower credit unions to do just that by giving them that time as a resource for members in need. ‍

And finally…

Now that Alyssa has an auto loan, she secures a fuel-efficient, reliable, and affordable vehicle so her kids can get to school on time.

Liam has the opportunity to continue building his credit with more financial knowledge and better use of the tools his credit union offers him, setting him up for financial success.

Sonia can finally find the perfect home, start a family, and live her American dream.

Every day, people ask themselves: how am I going to get to work? How can I afford my day-to-day expenses, let alone a home? Credit unions can often be the answer to these very questions — you make a difference.

Make a powerful difference with smart, inclusive, and efficient technology with GoWest Solutions partner, Zest AI.

Posted in GoWest Solutions, Top Headlines.