O’ZBEKISTON RAQAMLI EKOTIZIMIDA MOLIYAVIY FIRIBGARLIKNI ANIQLASH: MASHINADA O’QITISH VA MA’LUMOTLARNI BALANSLASH USULLARINI QIYOSIY TAHLIL QILISH
Qabul qilingan: 2026-07-15 15:50:49
Nashr etilgan: 2026-04-18
Annotatsiya
Ushbu maqolada Oʻzbekiston raqamli bank ekotizimida moliyaviy firibgarlik xavfi ortib borayotgani koʻrib chiqilib, bunda oʻgʻirlangan shaxsiy maʼlumotlardan foydalangan holda ruxsatsiz kredit olish muammosiga alohida eʼtibor qaratilmoqda. Qoidalarga asoslangan an’anaviy aniqlash tizimlari ishonchli natijalar bermaydi, ortiqcha yolg’on ishlanmalarni keltirib chiqaradi va tajovuzkorlarning evolyutsion taktikalariga zo’rg’a moslashadi. Random Forest, XGBoost, neyron tarmoqlar va anomaliyalarni aniqlash algoritmlari kabi mashinada o’qitish modellarini joriy etish orqali ma’lumotlarni muvozanatlash usullari (masalan, SMOTE) bilan birgalikda tadqiqot firibgarlikni identifikatsiyalash aniqligini sezilarli darajada oshirishga erishmoqda.
Kalit so'zlar
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