Cursed with Knowledge? Strategic Risks of AI-Powered Monitoring

54 Pages Posted: 15 May 2024 Last revised: 3 Jan 2025

See all articles by Xuyuanda Qi

Xuyuanda Qi

NYU Shanghai

Yang Yi

University of Rochester - Simon Business School

Date Written: September 15, 2022

Abstract

Why are some financial institutions slow to adopt artificial intelligence (AI) despite its decreasing costs, while others are quick to embrace it? This paper develops a theoretical framework to understand the tradeoff between using AI for better borrower evaluation and maintaining strict financial discipline. Although AI improves the ability to assess borrower quality during refinancing, it can also encourage financiers to refinance initially speculative borrowers, thus exacerbating adverse selection in initial lending. To avoid these risks, some institutions may optimally choose not to adopt AI. Our model predicts that lower AI costs drive adoption only when this adverse selection is not severe. Moreover, AI adoption is most beneficial for institutions with a moderate-quality lending pool. These results help explain the strategic dynamics of AI adoption in lending and investment monitoring.

Keywords: Artificial Intelligence, Investment Monitoring, Strategic Information Acquisition, Soft Budget Constraint

JEL Classification: D82, G21, G23, G24, O32, O33

Suggested Citation

Qi, Xuyuanda and Yi, Yang, Cursed with Knowledge? Strategic Risks of AI-Powered Monitoring (September 15, 2022). Available at SSRN: https://ssrn.com/abstract=4828253 or http://dx.doi.org/10.2139/ssrn.4828253

Xuyuanda Qi (Contact Author)

NYU Shanghai ( email )

567 West Yangsi Road
PUDONG
Shanghai, Shanghai 200126
China

Yang Yi

University of Rochester - Simon Business School ( email )

Rochester, NY 14627
United States

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