SUN’IY INTELLEKT ASOSIDA KREDIT RISKLARINI BAHOLASHNI TAKOMILLASHTIRISH VA UNING TIJORAT BANKLARI MOLIYAVIY BARQARORLIGIGA TA’SIRI
DOI:
https://doi.org/10.65164/ve1abf57Keywords:
sun’iy intellekt, tijorat banklari, kredit risk, risk-menejment, mashinali o‘qitish, neyron tarmoqlar, raqamli transformatsiya, skoring tizimi, moliyaviy barqarorlik, bank aktivlari sifati, NPL, prediktiv tahlil.Abstract
Mazkur maqolada O‘zbekiston tijorat banklarida sun’iy intellekt texnologiyalari asosida kredit risklarini baholash tizimini takomillashtirish masalalari tadqiq etilgan. Tadqiqotda bank faoliyatida raqamli transformatsiya jarayonlarining jadallashuvi sharoitida kredit risklarini aniq baholashning ahamiyati ilmiy jihatdan asoslangan. Sun’iy intellekt algoritmlari, jumladan mashinali o‘qitish va neyron tarmoqlar asosida ishlovchi modellarning an’anaviy skoring tizimlariga nisbatan ustunliklari tahlil qilingan.
References
1.
Central Bank of the Republic of Uzbekistan (2024) Banking system statistics. Available at: https://cbu.uz/oz/statistics
2.
Ministry of Economy and Finance of the Republic of Uzbekistan (2024) Macroeconomic indicators. Available at: https://www.mf.uz
3.
State Committee of the Republic of Uzbekistan on Statistics (2024) Official statistics data. Available at: https://stat.uz
4.
International Monetary Fund (2023) Global Financial Stability Report. Washington, DC: IMF. Available at: https://www.imf.org
5.
World Bank (2023) World Development Report 2023: Digitalization and Finance. Washington, DC: World Bank. Available at: https://www.worldbank.org
6.
Bank for International Settlements (2018) Sound Practices: Implications of Fintech Developments for Banks and Bank Supervisors. Basel: BIS. Available at: https://www.bis.org
7.
European Central Bank (2023) Financial Stability Review. Frankfurt: ECB.
8.
Federal Reserve System (2023) Financial Stability Report. Washington, DC: Federal Reserve.
