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

Author

Listed:
  • Adil Oualid
  • Abdderrahim Hansali
  • Lahcen Moumoun

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.

Suggested Citation

  • Adil Oualid & Abdderrahim Hansali & Lahcen Moumoun, 2024. "Credit risk management: a comparative study of ML techniques applied to credit scoring," International Journal of Management Practice, Inderscience Enterprises Ltd, vol. 17(5), pages 509-521.
    • Handle: RePEc:ids:ijmpra:v:17:y:2024:i:5:p:509-521
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