Cars

AI in auto lending lowers risks, speeds up process, reduces bias

Estimating a car buyer’s income is not always easy, especially when the buyer is a gig worker who might not be including commission in their total pay. In addition, lenders each have different policies on how to calculate income. Discrepancies can occur if one lender looks at two pay stubs vs. three, or if a lender looks at pay stubs from a 60-day time frame vs. 30 days. Calculating income using bank statements, especially when data is input incorrectly from the start, creates different outcomes.

“Whenever you have AI and you see so many different data points, so many different variations of a W-2 pay stub — you become more effective on how to calculate that income with the minimal amount of risk,” Gonzalez said. “You open up the opportunity [for funding] to a market that maybe historically had underrepresented their income.”

Low-income consumers are most at risk for bias. Informed.IQ data shows auto loan borrowers from the low-income segment are underrepresented about 43 percent of the time.

Informed.IQ has portals where dealers and consumers upload documents and receive real-time feedback on how income is calculated to provide transparency. This process tells customers which deals and vehicles fit their qualifications, Gonzalez said.

Bias in calculating income for car buyers can result in troubling situations.

If a buyer’s income is overrepresented to a lender by just $5,000, that can impact the interest rate and terms. Once the income error is discovered, the consumer would no longer qualify for the loan and the dealer might have to claw it back. If the customer drove the car off the lot and the dealer can’t find another lender to fund the loan, they have to tell the customer to consider another car.

“When you walk out of the dealership, you think your loan’s closed, you’ve done all the good things, you’ve signed the paperwork. But in reality that loan is not funded,” Gonzalez said. F&I managers “would have to go and search for another lending organization to provide this loan. So they’re calling all their friends in the credit unions or anywhere they can and saying, ‘Hey, what can you do for me?’ ”

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