Machine Learning and Artificial Intelligence in Credit Risk Management in Banking: A Literature Review


Ankita Srivastava
ICFAI University Dehradun, India
Aishwarya Kumar
Department of Management, ICFAI University, Rajawala Road, Selaqui, Central hope town -248197, Uttarakhand, India


This paper traces these developments and algorithms through a review of the available literature and focuses to analyze and evaluate machine learning techniques and usage of artificial intelligence in the context of credit risk in banks. The paper also focuses on exploring the potential areas for further research. The review has shown that the application of machine learning and artificial intelligence in credit risk management of the banks has been explored; however, different parameters are still unexplored in case of credit risk prediction analysis. Deep learning and Artificial Neural networks are the crucial fixtures in the banking industry, giving way to infinite possibilities and opportunities to transform the traditional banking system. A large number of areas remain in credit risk management and analysis could extensively get benefit from the study of how machine learning and artificial intelligence can be applied to address certain problems.

January 16, 2020