SUN’IY INTELLEKT ASOSIDA KREDIT RISKLARINI BAHOLASH MODELINI ISHLAB CHIQISH
DOI:
https://doi.org/10.5281/zenodo.23008073Abstract
Ushbu maqolada kredit risklarini baholashda sun’iy intellekt va mashinali o‘qitish texnologiyalaridan foydalanish imkoniyatlari tadqiq etilgan. Kredit riskini aniq baholash moliyaviy tashkilotlarning barqarorligi va kredit portfeli sifatini ta’minlashda muhim ahamiyatga ega. Tadqiqotda an’anaviy kredit skoringi yondashuvlarining xususiyatlari hamda zamonaviy mashinali o‘qitish algoritmlarining imkoniyatlari tahlil qilingan. Muallif tomonidan kredit oluvchining moliyaviy holati, kredit tarixi, qarz yuklamasi va to‘lov intizomini hisobga oluvchi sun’iy intellekt asosidagi model taklif etilgan. Modelda ma’lumotlarni tayyorlash, muhim belgilarni tanlash, riskni tasniflash va model natijasini izohlash bosqichlari nazarda tutilgan. Logistic Regression, Decision Tree, Random Forest va Gradient Boosting algoritmlaridan foydalanish imkoniyatlari ko‘rib chiqilgan. Model shaffofligini oshirish uchun Explainable AI yondashuvlarini qo‘llash taklif etilgan. Tadqiqot natijalari sun’iy intellekt asosidagi kredit riskini baholash tizimi kredit qarorlarini ma’lumotlarga asoslangan holda qo‘llab-quvvatlash imkoniyatiga ega ekanligini ko‘rsatadi.Keywords
sun’iy intellekt, kredit riski, kredit skoringi, mashinali o‘qitish, kredit baholash, bank tizimi, moliyaviy texnologiyalar, Explainable AI, Random Forest, Gradient BoostingReferences
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