Rise of the Machines: The Impact of Automated Underwriting

Mark Jansen, Hieu Quang Nguyen () and Amin Shams ()
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Hieu Quang Nguyen: Department of Applied Finance, Macquarie University, Sydney, New South Wales 2109, Australia
Amin Shams: Department of Finance, Fisher College of Business, The Ohio State University, Columbus, Ohio 43210

Management Science, 2025, vol. 71, issue 2, 955-975

Abstract: Using a randomized experiment in auto lending, we find that algorithmic underwriting outperforms the human underwriting process, resulting in 10.2% higher loan profits and 6.8% lower default rates. The human and machine underwriters show similar performance for low-risk, less complex loans. However, the performance of human underwritten loans largely declines for riskier and more complex loans, whereas the machine performance stays relatively stable across various risk dimensions and loan characteristics. The performance difference is more pronounced at underwriting thresholds with a high potential for agency conflict. These results are consistent with algorithmic underwriting mitigating agency conflicts and humans’ limited capacity for analyzing complex problems.

Keywords: lending; underwriting; FinTech; automation; household finance; agency conflicts (search for similar items in EconPapers)
Date: 2025
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http://dx.doi.org/10.1287/mnsc.2024.4986 (application/pdf)

Related works:
Working Paper: Rise of the Machines: The Impact of Automated Underwriting (2020)
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