How Much Does Racial Bias Affect Mortgage Lending? Evidence from Human and Algorithmic Credit Decisions

Deskripsi

We assess racial discrimination in mortgage approvals using confidential data on mortgage applications. Minority applicants tend to have lower credit scores and higher leverage, and are less likely to receive algorithmic approval from race-blind automated underwriting systems (AUS). Observable applicant-risk factors explain most of the racial disparities in lender denials. Further, exploiting the AUS data, we show there are risk factors we do not observe, and these factors at least partially explain the residual 1 to 2 percentage point denial gaps. We conclude that differential treatment plays a more limited role in generating denial disparities than previous research suggests.