The Effect of AI-Enabled Credit Scoring on Financial Inclusion: Evidence from an Underserved Population of over One Million
Authors: Li, Chunxiao; Wang, Hongchang; Jiang, Songtao; Gu, Bin
Journal: MIS Quarterly (2024)
<jats:p>We studied the effect of a major bank adopting an AI-enabled credit scoring model on financial inclusion as measured by changes to the approval rate, default rate, and utilization level of a personal loan product for an underserved population. The bank serves over 50 million customers and previously used a traditional rule-based model to evaluate the default risk of each loan application. It recently developed an AI model with a higher prediction accuracy of default risk and used the AI model and the traditional model together to assess loan applications for one of its personal loan products. Although the AI model may be more accurate in estimating default risk, little is known about its impact on financial inclusion. We investigated this question using a difference-in-differences approach by comparing changes in financial inclusion of the personal loan product that adopted the AI model to that of a similar personal loan product that did not adopt the AI model. We found that the AI model enhanced financial inclusion for the underserved population by simultaneously increasing the approval rate and reducing the default rate. Further analysis attributed the enhancement in fin…