We assess racial discrimination in mortgage approvals using new data on mortgage

applications. Minority applicants tend to have signicantly lower credit scores, higher

leverage, and are less likely than white applicants to receive algorithmic approval from

race-blind government automated underwriting systems (AUS). Observable applicant-

risk factors explain most of the racial disparities in lender denials. Further, we exploit

the AUS data to show there are risk factors we do not directly observe, and our analysis

indicates that these factors explain at least some of the residual 1-2 percentage point

denial gaps. Overall, we nd that dierential treatment has played a limited role in

generating denial disparities in recent years.