MECHANISM FOR IMPLEMENTING ARTIFICIAL INTELLIGENCE TECHNOLOGIES IN THE OPERATIONS OF COMMERCIAL BANKS IN UZBEKISTAN
DOI:
https://doi.org/10.5281/zenodo.17847007Keywords:
artificial intelligence, commercial banks, credit risk, digital transformation, data analysis, risk managementAbstract
This article analyzes the mechanisms for implementing artificial intelligence (AI) technologies in the operations
of commercial banks in Uzbekistan from scientific, theoretical, and practical perspectives. Furthermore, the study focuses
on issues of credit risk assessment, client segmentation, default probability forecasting, and the integration of AI into
decision-making processes within the banking system.
Using a theoretical-analytical approach, the research examines the level, opportunities, and limitations of using artificial
intelligence technologies in the activities of Uzbek commercial banks. Furthermore, the author presents a comparative
analysis with the experience of AI implementation in banking systems within international practice. The article emphasizes
the necessity of establishing institutional and technological prerequisites for the successful integration of artificial
intelligence into the banking system
References
Bhatia, R., & Singh, P. (2022). Machine learning algorithms for credit risk assessment in Indian commercial banks:
Evidence from Random Forest and XGBoost models.
Chu, J., Liu, Y., & Zhang, W. (2020). Deep learning in credit risk modeling: Capturing nonlinear dependencies in
banking data. Journal of Banking & Finance, 118, 105874.
He, J., Lin, Y., & Xu, K. (2022). Hybrid machine learning and econometric models for credit risk prediction in Korean
financial markets. Emerging Markets Review, 51, 100921.
Nowak, P., & Kowalski, R. (2021). Artificial intelligence in credit risk assessment in Polish banks. Journal of Banking
& Finance, 124, 106084.
Zhang, L., & Li, H. (2023). Artificial intelligence in credit risk prediction: Evidence from Chinese commercial banks.
Emerging Markets Review, 50, 101055.
OECD. (2023). Digital transformation of risk management in financial systems: The role of artificial intelligence. OECD
Publishing.
International Monetary Fund (IMF). (2024). Artificial Intelligence and Financial Stability: Policy Considerations for
Emerging Markets. IMF Working Paper WP/24/118.
Bank for International Settlements (BIS). (2023). Artificial intelligence and machine learning in financial services:
Market developments and policy implications. BIS Papers No. 126.
World Bank. (2022). Fintech and AI in banking supervision: A global overview. World Bank Group.
Central Bank of the Republic of Uzbekistan (CBU). (2024). Monetary Policy Guidelines for 2024–2026. https://cbu.uz/
upload/medialibrary/8d2/gdta 2oa6w3jzzlmjs90z0xw67vhfujri/MP-Guidelines-for-2024_2026.pdf
Ministry of Economy and Finance of Uzbekistan. (2023). Digital economy and banking sector development strategy
–2026. Tashkent.
OECD. (2023). AI in the financial sector of developing economies: Challenges and opportunities. OECD Policy Paper
No. 67. https://doi.org/10.1787/aifin-2023-en
IMF. (2024). Republic of Uzbekistan: Financial Sector Assessment Program—Financial System Stability Assessment.
IMF Country Report No. 24/145.
Nazemi, A., & Fabozzi, F. J. (2024). Interpretable machine learning for creditor recovery rates. Journal of Banking &
Finance, 164, 107187.
Emmanuel, I., Sun, Y., & Wang, Z. (2024). A machine learning-based credit risk prediction engine system using a
stacked classifier and filter-based feature selection. Journal of Big Data, 11(1), 23. https://doi.org/10.1186/s40537-
-00882-0
BIS. (2025). Annual Economic Report 2025 — AI and Finance Governance Chapter. Basel: Bank for International
Settlements. https://www.bis.org/publ/ arpdf/ar2025e.htm
World Bank. (2024). Digital banking transformation and risk implications in emerging markets. World Bank Group.
https://documents1.worldbank.org/ curated/en/234421682381626542/pdf/Digital-Banking-Transformation-and-Risk.
Ministry of Economy and Finance of Uzbekistan. (2025). AI-based Financial Technologies Implementation Plan 2025–
Tashkent.