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Lender Automation and Racial Disparities in Credit Access

Author

Listed:
  • Sabrina T. Howell
  • Theresa Kuchler
  • David Snitkof
  • Johannes Stroebel
  • Jun Wong

Abstract

Process automation reduces racial disparities in credit access through 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), a setting where private lenders faced no credit risk but decided which firms to serve. Black-owned firms primarily obtained PPP loans 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, pre-existing banking relationships, firm performance, or fraud rates.

Suggested Citation

  • Sabrina T. Howell & Theresa Kuchler & David Snitkof & Johannes Stroebel & Jun Wong, 2021. "Lender Automation and Racial Disparities in Credit Access," NBER Working Papers 29364, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:29364
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    More about this item

    JEL classification:

    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G23 - Financial Economics - - Financial Institutions and Services - - - Non-bank Financial Institutions; Financial Instruments; Institutional Investors
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation
    • G41 - Financial Economics - - Behavioral Finance - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making in Financial Markets
    • J15 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Minorities, Races, Indigenous Peoples, and Immigrants; Non-labor Discrimination

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