AI Could Increase Minority Homeownership
NEW YORK – According to a recent study from the National Bureau of Economic Research, the use of algorithms for online mortgage lending can reduce discrimination against certain groups, including minorities.
The study found that in-person mortgage lenders typically reject minority applicants at a rate 6% higher than non-minority members with comparable economic backgrounds. However, when the application was online and used an algorithm to make the decision, the acceptance and rejection rates were the same.
But even with artificial intelligence (AI) helping minority borrowers get approval online, they still pay more under algorithmic lending. In 2017, $2.25 trillion of the $13 trillion of outstanding household debt in the United States was associated with minority households.
Disparities in homeownership rates are cited as a leading cause of a racial wealth gap, and several studies have found that the median white family holds more than 10 times the wealth of the median African American family. McKinsey projects that the U.S. economy could net between $1.1 trillion and $1.5 trillion by 2028 if it closed the racial wealth gap.
According to the U.S. Census Bureau, black homeownership recently dropped to its lowest level of 40% and has been steadily declining since its 2004 peak. It’s possible that AI could help reverse this trend. Researchers calculate that up to 1.3 million minority applicants were rejected for a mortgage from 2009 to 2015 that would have been accepted if loan officers had not discriminated.
Mortgage platforms like Better.com say they’ve had a five-fold increase in Hispanic and African American borrowers between the ages of 30 and 40 over the last year.
Source: Forbes (12/30/19) Hale, Kori
© Copyright 2020 INFORMATION INC., Bethesda, MD (301) 215-4688