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 to
quantify 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, and
whether the results can be adequately understood by analysts who will need to make decisions based on AI
computation. We use the keywords "artificial intelligence", "machine learning", and "credit risk" in google
scholar. Full text is obtained from Web of Science if unavailable as open-source documents. The consensus is
quite consistent and positive. AI can provide better forecast power, and when used correctly, AI can increase
the 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 complexity
so that more people can learn how to configure, operate, and interpret the AI computation results. This study
is looking for consensus of how AI can help more accurate forecasting of forward-looking credit risk
quantification.