Lender Automation and Racial Disparities in Credit Access

Sabrina T. Howell, Theresa Kuchler, David Snitkof, Johannes Stroebel and Jun Wong

No 29364, NBER Working Papers from National Bureau of Economic Research, Inc

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.

JEL-codes: G21 G23 G28 G41 J15 (search for similar items in EconPapers)
Date: 2021-10
New Economics Papers: this item is included in nep-ban and nep-cfn
Note: CF PE PR
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Published as SABRINA T. HOWELL & THERESA KUCHLER & DAVID SNITKOF & JOHANNES STROEBEL & JUN WONG, 2024. "Lender Automation and Racial Disparities in Credit Access," The Journal of Finance, vol 79(2), pages 1457-1512.

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Journal Article: Lender Automation and Racial Disparities in Credit Access (2024)
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