A Review Study of AI Methods for Credit Default Prediction

Research using empirical and analytical approaches from the field of artificial intelligence (AI) has found credit default to be a fascinating issue. The article shows a systematic literature review of the last decade's worth of work on using artificial intelligence for credit default prediction. The key subjects of this study are discussed in this paper's overview, including credit default prediction, machine learning, feature selection, classification performance, computational time, and single, hybrid and ensemble classifiers for credit default prediction. The review study sheds a lot of insight on the ways in which AI techniques have helped the banking industry. Finally, we use the results on literature to suggest many avenues for future study, including developing topics and approaches.