Do Algorithms Discriminate Against African Americans in Lending?

Jérémie Bertrand and Laurent Weill
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Jérémie Bertrand: IESEG

Working Papers of LaRGE Research Center from Laboratoire de Recherche en Gestion et Economie (LaRGE), Université de Strasbourg

Abstract: We investigate whether discrimination against African Americans occurs in peer-to-peer lending. We consider data from a large peer-to-peer lender that uses algorithms and no face-to face interview to decide loan approval and conditions. Using data from 3.6 million loan applications and 817,000 granted loans for 2016 and 2017, we perform regressions of loan acceptance and loan conditions on the percentage of African Americans by 3-digit zip area. We observe evidence of discrimination in peer-to-peer lending. African Americans have a greater chance to have their loan applications rejected, pay higher loan rates, and obtain loans with shorter maturity. Discrimination is more pronounced after the election of Trump.

Keywords: discrimination; Fintech; peer-to-peer lending; loans. (search for similar items in EconPapers)
JEL-codes: G21 J15 (search for similar items in EconPapers)
Date: 2019
New Economics Papers: this item is included in nep-ban, nep-pay and nep-ure
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Journal Article: Do algorithms discriminate against African Americans in lending? (2021)
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Persistent link: https://EconPapers.repec.org/RePEc:lar:wpaper:2019-04

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