KREDIT SKORING TIZIMLARIDA SUN’IY INTELLEKT VA MASHINAVIY O‘QITISH TEXNOLOGIYALARINI QO‘LLASHNING ZAMONAVIY YONDASHUVLARI

Feruza Nabiyeva

GREEN ECONOMY AND DEVELOPMENT, 2026, vol. 4, 698-701

Abstract: Bank tizimida kredit skoring jarayonlarini sun’iy intellekt va mashinaviy o‘qitish texnologiyalari asosidatakomillashtirishning zamonaviy yondashuvlari tadqiq etilgan. Kredit skoring modellarining an’anaviy statistik usullardanmashinaviy va chuqur o‘qitish modellariga evolyutsiyasi, ularning qarz oluvchilar defoltini prognozlash imkoniyatlari hamdavaqt davomida prognozlar barqarorligini ta’minlash masalalari yoritilgan. Shuningdek, kredit skoring samaradorliginioshirishda Particle Swarm Optimization (PSO) algoritmi asosida xususiyatlarni tanlash va modellarni optimallashtirishimkoniyatlari tahlil qilingan. Tadqiqot natijalari sun’iy intellekt texnologiyalaridan foydalanish kredit skoring modellariningprognozlash aniqligi, barqarorligi va shaffofligini oshirish, shuningdek, banklarda kredit riskini baholash jarayonlarinitakomillashtirish uchun muhim imkoniyatlar yaratishini ko‘rsatadi

Keywords: kredit skoring; sun’iy intellekt; mashinaviy o‘qitish; kredit riski; defolt ehtimoli; Particle Swarm Optimization (PSO); prognozlash aniqligi; model barqarorligi. (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:teu:ged000:v:4:y:2026:id:12275

DOI: 10.5281/zenodo.22689373

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