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Does Automatic Loan Approval Reduce Gender Bias in SME Lending ?

Author

Listed:
  • Arraiz, Irani
  • Bruhn, Miriam
  • Ruiz Ortega, Claudia

Abstract

This paper examines whether automatic credit approval can reduce gender bias in lending to small and medium-sized enterprises. The study team collaborated with a bank in Peru that piloted a new screening tool to generate psychometric credit scores. Applicants who scored above a predefined threshold were automatically offered a loan with a size tied to their score, and those below the threshold were assessed by a loan officer. Using a regression discontinuity design and credit bureau data, the paper compares loan offers and loan sizes of female and male applicants within a narrow window around the automatic approval threshold. The results show that female applicants below the threshold are less likely to take out loans and receive smaller loan amounts than men. However, this gender bias disappears for applicants above the threshold, suggesting that automated screening methods can reduce loan officer discretion and promote gender equity in lending.

Suggested Citation

  • Arraiz, Irani & Bruhn, Miriam & Ruiz Ortega, Claudia, 2026. "Does Automatic Loan Approval Reduce Gender Bias in SME Lending ?," Policy Research Working Paper Series 11361, The World Bank.
  • Handle: RePEc:wbk:wbrwps:11361
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    References listed on IDEAS

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    4. J. Michelle Brock & Ralph De Haas, 2023. "Discriminatory Lending: Evidence from Bankers in the Lab," American Economic Journal: Applied Economics, American Economic Association, vol. 15(2), pages 31-68, April.
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