The Washington Post, November 14, 2018: Are you a minority borrower? You might want to think twice about using an online lender
It’s not just bank loan officers with racial biases who discriminate against black and Latino borrowers. Computer algorithms do, too.
That is the groundbreaking conclusion of University of California at Berkeley researchers who found that algorithmic credit scoring using big data is no better than humans at evening the playing field when it comes to determining home mortgage interest rates.
The disparity results in African Americans and Latinos, together, paying up to a half a billion dollars more in mortgage interest each year, the study found.
The racial disparities could result from algorithms that use machine learning and big data to charge higher interest rates to borrowers who may be less likely to shop around. For example, the algorithms may take into account a borrower’s neighborhood — noting who lives in banking deserts — or other characteristics such as their high school or college. The consumers least likely to comparison shop also happen to be black or Latino.
