OPTIMIZING RISK MANAGEMENT IN DIGITAL BANKS USING AI ALGORITHMS

Mualliflar

  • Feruza Nabieva Researcher, Tashkent State University of Economics Muallif

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https://doi.org/10.5281/zenodo.21278656

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AI, digital banking, risk management, machine learning, credit scoring, fraud detection, regulatory compliance, cybersecurity.

Abstrak

This research presents a comprehensive analysis of the integration and optimization of Artificial Intelligence algorithms within the risk management frameworks of digital banks. As the financial sector moves toward autonomous value units, the limitations of traditional, linear risk assessment methodologies have become pronounced. By leveraging advanced machine learning architectures, including ensemble models, artificial neural networks, and natural language processing, digital banks can significantly enhance their predictive accuracy across credit, market, and operational risk domains.

Iqtiboslar

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Brown, M. (2024). Influence of Artificial Intelligence on Credit Risk Assessment in Banking Sector. Fintech Research Review.

Faisal, S. M., Khan, W., & Ishrat, M. (2025). Al and Financial Risk Management: Transforming Risk Mitigation With Al-Driven Insights and Automation. Advances in Financial Technology.

Josyula, P., et al. (2023). The potential of AI to support financial risk governance. Journal of Economic Research.

Vaithilingam, S. (2022). Privacy and data security in Al-based banking. Journal of Digital Sovereignty.

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Nashr qilingan

2026-07-09

Nashr

Bo'lim

Maqolalar

Iqtibos keltirish tartibi

Feruza, N. (2026). OPTIMIZING RISK MANAGEMENT IN DIGITAL BANKS USING AI ALGORITHMS. Ilm-Fan Va Innovatsiya, 4(65), 104-107. https://doi.org/10.5281/zenodo.21278656
Innovative Academy RSC
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