RIVOJLANGAN MAMLAKATLARDA KREDIT PORTFELI MONITORINGINING OPTIMAL MEXANIZMLARI
DOI:
https://doi.org/10.5281/zenodo.20825055Ключевые слова:
kredit portfeli monitoringi, BCBS 239, IFRS 9, kutilayotgan kredit zarari (ECL), PD, LGD, EAD, sun’iy intellekt (AI), Watchlist, kovenant nazorati, geospatial analytics, ESG, DORA, AI Act, eskalatsiya, fire sales, model riskiАннотация
Ushbu ilmiy maqolada rivojlangan mamlakatlar bank amaliyotida kredit portfelini monitoring qilishning optimal mexanizmlari
atroflicha tahlil qilingan. Tadqiqotda kredit riskining bir necha turlari — individual (avtonom) risk, portfel riski, konsentratsiya
riski, mamlakat va suveren riski, kontragent kredit riski, model riski, likvidlikni transformatsiyalash riski hamda reputatsion risk
— tasniflangan va ularning monitoring uslublari ko‘rib chiqilgan. Maqolada zamonaviy monitoring tizimining uch qatlamli raqamli
arxitekturasi — ma’lumotlar yig‘ish, signallarni shakllantirish va prioritetlash, boshqaruv va harakat — atroflicha o‘rganilgan. Bundan
tashqari, sun’iy intellektga asoslangan kuzatuv (AI-assisted surveillance), Watchlist boshqaruvi, kovenant buzilishi ish jarayonlari,
garov mulkini geofazoviy tahlil qilish (geospatial analytics), kunlik tezkor xabar berish (intraday alerting), Open Banking API integratsiyasi
va ESG omillarini hisobga olish kabi yangi vositalar atroflicha tahlil qilingan. AQSH va Yevropa Ittifoqi tajribasining qiyosiy
tahlili shuni ko‘rsatadiki, AQSH modeli tez eskalatsiya va rezident-inspektor amaliyotiga, YeI modeli esa BCBS 239, IFRS 9, DORA
va AI Act talablariga muvofiq institutsional ma’lumotlar intizomiga asoslanadi. Tadqiqotda “yong‘in sotuvlari” (fire sales) sharoitida
garov qiymati boshlang‘ich baholashga nisbatan 30–50% gacha pasayishi mumkinligi aniqlangan
Библиографические ссылки
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Manba: xalqaro regulyativ hujjatlar va ilg‘or bank amaliyotlari asosida muallif ishlanmasi.
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