The company is also something of a regulatory guinea pig: Upstart was the first company to receive a no-action letter from the Consumer Financial Protection Bureau. The letter essentially stated that the office did not intend to take regulatory action against the company in exchange for detailed information about its loans and operations.
While the bureau didn’t recreate Upstart’s results on its own, it said the company approved 27% more applicants than the traditional model, while the average interest rates they paid were 16% lower. For example, “near prime” customers with FICO scores of 620 to 660 were approved about twice as often, according to company data. Younger and lower-income applicants also fared better.
Upstart, which has also agreed to be monitored by two advocacy groups and an independent auditor, takes into account more than 1,000 data points inside and outside of a consumer’s credit report. It has occasionally tweaked its modeling – it no longer uses a borrower’s average incoming college SAT and ACT scores – but includes the person’s college, field of study, and work history. (Nurses rank well, for example, because they are rarely unemployed, Mr. Girouard said.) The amount borrowers ask for can also be a factor: whether they are looking for more than what the algorithms of Upstart deem appropriate, this can them.
Other companies operate in a similar fashion, although the methods and data they use vary.
TomoCredit, for example, will issue a Mastercard credit card to applicants – even those without a credit score – after being given permission to view their financial accounts; it analyzes more than 50,000 data points, such as monthly income and spending habits, savings accounts and stock portfolios. Within two minutes, consumers are approved for credit ranging from $ 100 to $ 10,000, to be repaid weekly. One-off payments help build users’ traditional credit reports and credit scores.
Zest AI, a Los Angeles-based company that already works with banks, auto lenders, and credit unions, is also working with Freddie Mac, who recently started using the company’s tools to assess people who might not. perfectly match traditional scoring models.
Jay Budzik, chief technology officer of Zest AI, said the company has taken a deep dive into applicants’ credit reports and may incorporate information from a loan application, such as mileage or the potential resale value of a loan. used car. It can also examine the checking accounts of consumers.
“How often are they getting close to zero? Mr. Budzik said. “These items are helpful in creating an additional data point about a consumer that is not on the credit report.”