Ключевые слова
Аннотация
Tezisda tijorat banklarida kredit riskini kechikish yuzaga kelishidan oldin aniqlash uchun sun'iy intellektdan foydalanishning tashkiliy va uslubiy jihatlari yoritiladi.
O'zbekiston bank tizimining ochiq statistikasi va xalqaro ilmiy manbalar asosida erta ogohlantirish tizimining ma'lumot, model, izohlash, validatsiya va boshqaruv bloklaridan iborat amaliy mexanizmi taklif etiladi.
Библиографические ссылки
Ayari H., Guetari R., Kraiem N. Machine learning powered financial credit scoring: a systematic literature review // Artificial Intelligence Review. 2026. Vol. 59. Art. 13. DOI: 10.1007/s10462-025-11416-2.
Basel Committee on Banking Supervision. Principles for the Management of Credit Risk. Basel: Bank for International Settlements, 2025.
Bhatore S., Mohan L., Reddy Y.R. Machine learning techniques for credit risk evaluation: a systematic literature review // Journal of Banking and Financial Technology. 2020. Vol. 4. P. 111-138. DOI: 10.1007/s42786-020-00020-3.
Bussmann N., Giudici P., Marinelli D., Papenbrock J. Explainable Machine Learning in Credit Risk Management // Computational Economics. 2021. Vol. 57. P. 203-216. DOI: 10.1007/s10614-020-10042-0.
Central Bank of the Republic of Uzbekistan. Information on major indicators of commercial banks as of July 1, 2026. Tashkent, 2026. URL: https://cbu.uz/en/statistics/bankstats/4230544/ (accessed: 13.09.2026).
European Banking Authority. Follow-up Report on the Use of Machine Learning for Internal Ratings-Based Models. Paris, 2023.
Hlongwane R., Ramabao K., Mongwe W. A novel framework for enhancing transparency in credit scoring: Leveraging Shapley values for interpretable credit scorecards // PLOS ONE. 2024. Vol. 19(8). e0308718. DOI: 10.1371/journal.pone.0308718.
Lundberg S.M., Lee S.-I. A Unified Approach to Interpreting Model Predictions // Advances in Neural Information Processing Systems. 2017. Vol. 30. P. 4765-4774.
Perez-Cruz F., Prenio J., Restoy F., Yong J. Managing explanations: how regulators can address AI explainability // FSI Occasional Papers. 2025. No. 24. Basel: BIS.
Ribeiro M.T., Singh S., Guestrin C. Why Should I Trust You? Explaining the Predictions of Any Classifier // Proceedings of KDD 2016. P. 1135-1144. DOI: 10.1145/2939672.2939778.