THE EFFECTIVENESS OF ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING TECHNOLOGIES IN MANAGING NON-PERFORMING ASSETS IN THE BANKING SYSTEM
Abstract
In the current era of rapid digital transformation in the global financial sector, the integration of advanced technologies—particularly artificial intelligence (AI) systems—into lending processes is becoming increasingly urgent. International experience demonstrates that the use of AI technologies enables banks not only to improve the accuracy of credit risk assessment, but also to significantly enhance the efficiency of asset portfolio monitoring and management. For countries with developing economies, including the Republic of Uzbekistan, these trends are opening up new opportunities to improve banking performance and strengthen the stability of the financial system.
References
Law of the Republic of Uzbekistan “On Banks and Banking Activities” (as amended on July 17, 2023).
Presidential Decree of the Republic of Uzbekistan No. PQ–4707 dated May 12, 2020, “On the Strategy for Reforming the Banking System of the Republic of Uzbekistan for 2020–2025”.
Basel Committee on Banking Supervision. Guidelines on the Management of Non-Performing Exposures and Forbearance. Bank for International Settlements, 2019.
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Abdullayev, F.K. (2023). Application of Machine Learning in Managing the Credit Portfolio of Commercial Banks. Uzbek Journal of International Economics, No. 4, pp. 85–92.
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