PREDICTIVE MACHINE LEARNING MODELS FOR MITIGATING NON-PERFORMING LOANS IN EMERGING BANKING SYSTEMS
This study benchmarks four supervised machine learning classifiers — logistic regression, random forest, gradient boosting, and extreme gradient boosting (XGBoost) — in predicting twelve-month-ahead loan delinquency using a loan-level panel drawn from commercial banks operating in an emerging Central Asian banking system over 2019–2025.