This article examines the forecasting of bank financial risks and the development of an early warning system using artificial intelligence. It discusses the use of financial, transactional, and macroeconomic data to identify credit, liquidity, market, and operational risks. A conceptual model is proposed for generating green, yellow, and red signals based on risk probability and expected losses. The importance of model explainability, human oversight, and regular validation is also substantiated.
| Mualliflar | Xolmatov, Suxrob, Холматов , Сухроб, Xolmatov , Suxrob |
|---|---|
| Jurnal | Иқтисодий тараққиёт ва таҳлил |
| Nashr sanasi | 2026-07-31 |
| Jild | 4 |
| Son | 7 |
| Betlar | 191-198 |
| Til | O‘zbek |
| DOI | 10.60078/2992-877x-2026-vol4-iss7-pp191-198 |
DOI: 10.60078/2992-877x-2026-vol4-iss7-pp191-198 · Maqolaning asl sahifasi
artificial intelligence, banking risks, financial risks, forecasting, early warning system, credit risk, liquidity risk, risk management, искусственный интеллект, банковские риски, финансовые риски, прогнозирование, система раннего предупреждения, кредитный риск, риск ликвидности, риск-менеджмент, sun’iy intellekt, bank risklari, moliyaviy risklar, prognozlash, erta ogohlantirish tizimi, kredit riski, likvidlik riski, risk-menejment
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