Credit risk management: a comparative study of ML techniques applied to credit scoring

Adil Oualid, Abdderrahim Hansali and Lahcen Moumoun

International Journal of Management Practice, 2024, vol. 17, issue 5, 509-521

Abstract: Banks are concerned with controlling and managing credit risk - particularly the risk prudently required by central banks. Consequently, banks are constantly developing models to consider, analyse and predict risk. Credit risk assessment and prediction come in the form of models that calculate scores regarding a business' potential vulnerability. This is done using financial data and a method of calculation. The objective of our work is to study the various AI techniques of credit scoring, and their interests as a powerful tool to predict the creditworthiness of borrowers.

Keywords: credit risk; credit scoring; machine learning; supervised ML; unsupervised ML. (search for similar items in EconPapers)
Date: 2024
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