African-American and Latino borrowers continue to face lending discrimination despite the rise of online applications and algorithms, according to a new study from the University of California, Berkeley.
The study found that both online and face-to-face lenders charge higher interest rates to black and Latino borrowers. Black and Latino borrowers pay 5.6 to 8.6 basis points higher interest on purchase loans than White and Asian ethnicity borrowers do, and three basis points more on refinance loans.
For borrowers, these disparities cost $250 million to $500 million annually. For lenders, this amounts to 11% to 17% higher profits on purchase loans to minorities, based on the industry average 50-basis-point profit on loan issuance.
Adair Morse, a finance professor at UC Berkeley’s Haas School of Business and a study co-author, said the results are consistent with lenders using big data variables and machine learning to infer the extent of competition for customers and price loans accordingly.
Morse calls this phenomenon “algorithmic strategic pricing,” where AI figures out which applicants might do less comparison shopping and accept higher-priced offerings.
“The mode of lending discrimination has shifted from human bias to algorithmic bias,” Morse said. “Even if the people writing the algorithms intend to create a fair system, their programming is having a disparate impact on minority borrowers—in other words, discriminating under the law.”
The researchers said the findings raise legal questions about the rise of statistical discrimination in the fintech era and point to potentially widespread violations of US fair lending laws.