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PreprintCited by 11FinTech, Crowdfunding, Digital FinanceDecision-Making and Behavioral EconomicsNames, Identity, and Discrimination Research

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How Costly are Cultural Biases? Evidence from FinTech

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D'Acunto, Francesco, Ghosh, Pulak, Rossi, Alberto G.·2022·SSRN Electronic Journal
DOI 10.2139/ssrn.4147353
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Abstract

We study the nature and effects of cultural biases in choice under risk and uncertainty by comparing peer-to-peer loans the same individuals (lenders) make alone and after observing robo-advised suggestions. When unassisted, lenders are more likely to choose co-ethnic borrowers, facing 8% higher defaults and 7.3pp lower returns. Robo-advising does not affect diversification but reduces lending to high-risk co-ethnic borrowers. Lenders in locations with high inter-ethnic animus drive the results, even when borrowers reside elsewhere. Biased beliefs explain these results better than a conscious taste for discrimination: lenders barely override robo-advised matches to ethnicities they discriminated against when unassisted.

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Metadata

Authors
D'Acunto, F., Ghosh, P., & Rossi, A. G.
Affiliations
  • Indian Institute of Management Bangalore (IN)
  • Georgetown University (US)
ORCID
Venue
SSRN Electronic Journal
Publisher
Elsevier BV
Published
2022
ISSN
1556-5068 (ISSN-L)
DOI
10.2139/ssrn.4147353
OpenAlex
W4285144040
Cited by
11
References
1
Citations by year
2026: 1 · 2025: 2 · 2024: 2 · 2023: 4
Type
posted content
Language
en
Open access
Locations
  • SSRN Electronic Journal (acceptedVersion)
  • Publication Server of Goethe University Frankfurt am Main (Goethe University Frankfurt) (submittedVersion)
Funders
Deutsche Forschungsgemeinschaft (FOR 2774)
Topics
  • Social Sciences › Business, Management and Accounting › Management Information Systems › FinTech, Crowdfunding, Digital Finance
  • Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
  • Social Sciences › Sociology and Political Science › Names, Identity, and Discrimination Research
Keywords
cultural bias, peer-to-peer lending, robo-advising, ethnic discrimination, loan default, biased beliefs, diversification, fintech

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D'Acunto, F., Ghosh, P., & Rossi, A. G. (2022). How Costly are Cultural Biases? Evidence from FinTech. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4147353