Articles
| Open Access | ARTIFICIAL INTELLIGENCE DRIVEN FINANCIAL RISK PREDICTION AND FRAUD DETECTION IN MODERN BANKING SYSTEMS
Kimsanova Gulsanam , Andijon state universitety faculty of law and Economics First-year student of AccountingAbstract
Artificial Intelligence (AI) has become a transformative force in modern banking, particularly in financial risk prediction and fraud detection. This paper reviews the applications of machine learning (ML), deep learning (DL), and advanced techniques such as XGBoost, neural networks, and ensemble models in identifying risks and fraudulent activities in real time. AI systems significantly improve detection accuracy, reduce false positives, and enable predictive risk management, often outperforming traditional rule-based approaches. However, challenges related to model explainability, data privacy, bias, and regulatory compliance persist. The review synthesizes recent literature and highlights both achievements and future directions.
Keywords
Artificial Intelligence, financial risk prediction, fraud detection, banking systems, machine learning, predictive analytics, explainable AI, credit risk.
References
Yang, H. . A Review of Artificial Intelligence for Financial Fraud Detection.
IBM. AI Fraud Detection in Banking (2025–2026 insights).
Various empirical studies and bank case reports
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This work is licensed under a Creative Commons Attribution 4.0 International License.