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Lender Automation and Racial Disparities in Credit Access

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  • SABRINA T. HOWELL
  • THERESA KUCHLER
  • DAVID SNITKOF
  • JOHANNES STROEBEL
  • JUN WONG

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.

Suggested Citation

  • Sabrina T. Howell & Theresa Kuchler & David Snitkof & Johannes Stroebel & Jun Wong, 2024. "Lender Automation and Racial Disparities in Credit Access," Journal of Finance, American Finance Association, vol. 79(2), pages 1457-1512, April.
    • Handle: RePEc:bla:jfinan:v:79:y:2024:i:2:p:1457-1512
    DOI: 10.1111/jofi.13303
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