SUN’IY INTELLEKT YORDAMIDA MOLIYAVIY XAVFLARNI ANIQLASH VA BOSHQARISH: ALGORITM, SAMARADORLIK VA O‘ZBEKISTON MOLIYA SEKTORI UCHUN TATBIQ MODELI
DOI:
https://doi.org/10.65164/2qb9fy18Keywords:
sun'iy intellekt, moliyaviy xavf, risk menejment, mashinali o'qitish, chuqur o'qitish, kredit riski, firibgarlik aniqlash, bozor riski, fintech, raqamli iqtisodiyot, XGBoost, LSTM, O'zbekiston.Abstract
Ushbu maqolada sun'iy intellekt (AI) texnologiyalarining moliyaviy xavflarni aniqlash va boshqarishdagi ilmiy-amaliy ahamiyati kompleks tarzda tahlil qilinadi. Mashinali o'qitish (machine learning), chuqur o'qitish (deep learning) va tabiiy tilni qayta ishlash (NLP) algoritmlarining kredit riski, bozor riski, firibgarlik riski va likvidlik riski kabi asosiy moliyaviy xavf turlarini aniqlashdagi samaradorligi ko'rib chiqiladi. Tadqiqot natijalariga ko'ra, AI asosidagi risk tizimlari an'anaviy uslublarga qaraganda firibgarlikni aniqlash aniqligini 95–99% darajasiga, kredit skoringni esa 88–96% darajasiga yetkazish imkonini beradi. JP Morgan, Visa, Mastercard va Markaziy banklar tajribasi asosida qiyosiy tahlil o'tkazilgan. O'zbekiston moliya sektori uchun to'rt bosqichli AI risk menejment integratsion modeli taklif etiladi.
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