DEVELOPING AN EARLY WARNING SYSTEM FOR LOAN CLASSIFICATION AND CREDIT RISK MANAGEMENT

Authors

  • Kinjayev Kattakul

Keywords:

early warning system, loan classification, credit risk, probability of default, non-performing loans,

Abstract

This thesis examines the development of an early warning system (EWS) for  improving loan classification and credit risk management in commercial banks and  other lending institutions. The proposed framework integrates borrower-level  financial indicators, repayment behaviour, account activity, collateral quality,  sectoral conditions, and macroeconomic signals into a unified risk-monitoring  process. The study emphasizes the transition from periodic, backward-looking loan  review to continuous and forward-looking risk detection. 

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References

1. Altman, E. I. (1968). Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. The Journal of Finance, 23(4), 589–609. https://doi.org/10.1111/j.1540-6261.1968.tb00843.x

2. Basel Committee on Banking Supervision. (2000). Principles for the management of credit risk. Bank for International Settlements.

3. Brown, I., & Mues, C. (2012). An experimental comparison of classification algorithms for imbalanced credit scoring data sets. Expert Systems with Applications, 39(3), 3446–3453. https://doi.org/10.1016/j.eswa.2011.09.033

4. European Banking Authority. (2020). Guidelines on loan origination and monitoring (EBA/GL/2020/06).

5. Hand, D. J., & Henley, W. E. (1997). Statistical classification methods in consumer credit scoring: A review. Journal of the Royal Statistical Society: Series A (Statistics in Society), 985X.1997.00078.x

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Published

2026-10-06

How to Cite

DEVELOPING AN EARLY WARNING SYSTEM FOR LOAN CLASSIFICATION AND CREDIT RISK MANAGEMENT . (2026). INTERNATIONAL CONFERENCE ON ANALYSIS OF MATHEMATICS AND EXACT SCIENCES, 3(3), 71-77. https://www.universalconference.us/index.php/icames/article/view/7830