@inproceedings{bdcd20da9d3b42c4a7175c27eba5f9ab,
title = "Leveling the Field: Equitable Interest Rates for Unsecured Personal Loans",
abstract = "Interest rates of unsecured personal loans should ideally be based on borrowers' credit risk, free from biases and inconsistencies. In practice, however, interest rates often exhibit distortions that violate this principle. This paper proposes a novel method for determining interest rates that ensures all borrowers have access to credit at rates commensurate with their repayment risk. Utilizing a comprehensive dataset from LendingClub, a major online lending platform, we demonstrate that our method reduces the interest rate gap between borrowers with different credit scores by 38.7\% and eliminates biases against African American borrowers. Loans also maintain their average return on investment across different borrower groups under the new interest rates. Our evaluation employs counterfactual loan outcomes constructed through survival analysis. Our findings highlight the potential for loan providers to enhance fairness, expand credit access, and simplify the investment process for lenders by adopting a more equitable interest rate determination methodology.",
keywords = "counterfactual, fairness, fintech, Interest rates, survival analysis",
author = "Gopal, \{Ram D.\} and Xiao Qiao and Strub, \{Moris S.\} and Zonghao Yang",
note = "Publisher Copyright: {\textcopyright} 2024 International Conference on Information Systems. All Rights Reserved.; 45th International Conference on Information Systems, ICIS 2024 ; Conference date: 15-12-2024 Through 18-12-2024",
year = "2024",
language = "English",
series = "45th International Conference on Information Systems, ICIS 2024",
booktitle = "45th International Conference on Information Systems, ICIS 2024",
}