THE ROLE OF ARTIFICIAL INTELLIGENCE IN IMPROVING LOAN CLASSIFICATION AND CREDIT RISK ASSESSMENT

Authors

  • Kinjayev Kattakul

Keywords:

sun’iy intellekt, kredit riski, kredit tasnifi, mashinaviy o‘qitish, kredit skoringi, muammoli kreditlar,

Abstract

 Ushbu tezis kreditlarni tasniflash va kredit riskini baholash jarayonlarida  sun’iy intellekt texnologiyalarining rolini tahlil qiladi. Tadqiqotda mashinaviy o‘qitish,  ansambl modellari, neyron tarmoqlar va izohlanadigan sun’iy intellekt  yondashuvlarining qarz oluvchining to‘lovga layoqatini baholash, muammoli  kreditlarni erta aniqlash hamda kredit portfelini segmentlashdagi imkoniyatlari ko‘rib  chiqiladi. Taklif etilgan konseptual model an’anaviy moliyaviy ko‘rsatkichlarni  tranzaksion va xulq-atvor ma’lumotlari bilan birlashtiradi.

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References

1. Basel Committee on Banking Supervision. (2000). Principles for the management of credit risk. Bank for International Settlements.

2. Basel Committee on Banking Supervision. (2023). Supervisory framework for the use of artificial intelligence and machine learning in financial services: Selected supervisory considerations. Bank for International Settlements.

3. Bazarbash, M. (2019). FinTech in financial inclusion: Machine learning applications in assessing credit risk. IMF Working Paper, 19/109. International Monetary Fund. https://doi.org/10.5089/9781498314428.001

4. European Banking Authority. (2020). Report on big data and advanced analytics. European Banking Authority.

5. inancial Stability Board. (2017). Artificial intelligence and machine learning in financial services: Market developments and financial stability implications. Financial Stability Board

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Published

2026-10-06

How to Cite

THE ROLE OF ARTIFICIAL INTELLIGENCE IN IMPROVING LOAN CLASSIFICATION AND CREDIT RISK ASSESSMENT. (2026). INTERNATIONAL CONFERENCE ON INTERDISCIPLINARY SCIENCE, 3(8), 364-369. https://www.universalconference.us/index.php/icms/article/view/7831