Fintech for the Poor: Financial Intermediation Without Discrimination*

Tantri, P L (2020) Fintech for the Poor: Financial Intermediation Without Discrimination*. Review of Finance, 25 (2). pp. 561-593. ISSN 1572-3097

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Abstract

I ask whether machine learning (ML) algorithms improve the efficiency in lending without compromising on equity in a credit environment where soft information dominates. I obtain loan application-level data from an Indian bank. To overcome the problem of the selective labels, I exploit the incentive-driven within officer difference in leniency within a calendar month. I find that the ML algorithm can lend 60 more at loan officers’ delinquency rate or achieve a 33 lower delinquency rate at loan officers’ approval rate. The efficiency is maintained even when the algorithm is explicitly prevented from discriminating against disadvantaged social classes.

Affiliation: Indian School of Business
ISB Creiators:
ISB Creators
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Tantri, P L
UNSPECIFIED
Item Type: Article
Uncontrolled Keywords: Fintech, Financial Intermediation
Subjects: Finance
Depositing User: Gurusrinivasan K
Date Deposited: 17 May 2021 13:14
Last Modified: 17 May 2021 13:14
URI: https://eprints.exchange.isb.edu/id/eprint/1504
Publisher URL: https://doi.org/10.1093/rof/rfaa039
Publisher OA policy: https://v2.sherpa.ac.uk/id/publication/1390
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