Fintech for the Poor: Financial Intermediation Without Discrimination*

Predatory lending and the subprime crisis

Prasanna Tantri

Review of Finance, 2021, vol. 25, issue 2, 561-593

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.

Keywords: Machine Learning; Discrimination (search for similar items in EconPapers)
JEL-codes: G21 G23 G51 (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (11)

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