AN ANALYSIS OF LEADING FOREIGN BANKS’ PRACTICES IN APPLYING ARTIFICIAL- INTELLIGENCE-BASED MANAGEMENT SYSTEMS FOR CREDIT RISK ASSESSMENT AND THE EARLY DETECTION OF PROBLEM LOANS
DOI:
https://doi.org/10.5281/zenodo.22688559Abstract
Artificial-intelligence-based management systems used by the world’s leading commercial banks to assess credit risk and detect problem loans at an early stage are analyzed. The role and potential of Machine Learning, Deep Learning, Big Data Analytics, Explainable AI (XAI), Early Warning Systems (EWS), Behavioral Scoring, Alternative Data, Predictive Analytics, and Graph Analytics technologies in credit risk management are evaluated. Drawing on the experience of leading foreign banks, institutional and practical proposals are developed to improve an AI-based national management model for Uzbekistan’s banking system.Keywords
credit risk, problem loans, NPL, artificial intelligence, Machine Learning, Deep Learning, Early Warning System, Predictive Analytics, bank management, Big Data, scoringReferences
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