Artificial Intelligence in Credit Risk: A Literature Review

Abstract

This study aimed to address the needs of using artificial intelligence (AI) by investors and industry players toquantify credit risk in a more forward-looking view instead of the traditional non-forward-looking methods.This is a literature review of nine studies on how applications of AI used to provide better forecast power, andwhether the results can be adequately understood by analysts who will need to make decisions based on AIcomputation. We use the keywords "artificial intelligence", "machine learning", and "credit risk" in googlescholar. Full text is obtained from Web of Science if unavailable as open-source documents. The consensus isquite consistent and positive. AI can provide better forecast power, and when used correctly, AI can increasethe acceptance for less privileged people to access credit, which is good for the overall economy. However,several key challenges remain to make this technology affordable, especially on how to reduce the complexityso that more people can learn how to configure, operate, and interpret the AI computation results. This studyis looking for consensus of how AI can help more accurate forecasting of forward-looking credit riskquantification.