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Journal of Finance Vol. 79 No. 2 2024

Lender Automation and Racial Disparities in Credit Access

Sabrina T. Howell1; Theresa Kuchler2,3,4,5,6; DAVID SNITKOF2,3,4,5,6; Johannes Stroebel2,3,4,5,6; Jun Wong2,3,4,5,7,6

1 New York University · 2 Northeastern University · 3 United States Department of State · 4 University of Georgia · 5 Cornell University · 6 Arizona State University · 7 Issues Research

Abstract

Process automation reduces racial disparities in credit access by enabling smaller loans, broadening banks' geographic reach, and removing human biases from decision making. We document these findings in the context of the Paycheck Protection Program (PPP), where private lenders faced no credit risk but decided which firms to serve. Black‐owned firms obtained PPP loans primarily from automated fintech lenders, especially in areas with high racial animus. After traditional banks automated their loan processing procedures, their PPP lending to Black‐owned firms increased. Our findings cannot be fully explained by racial differences in loan application behaviors, preexisting banking relationships, firm performance, or fraud rates.

DOI
10.1111/jofi.13303
Volume
79
Issue
2
Pages
1457-1512
Language
en
Sources
bibtex:phds-export.bib openalex crossref

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