Tajik, Hojjat, Talebnia, Ghodratollah, Vakilifard, Hamid Reza, Ahmadi, Faegh. (1403). Machine learning support to provide an intelligent credit risk model for banks' real customers. هنرهای کاربردی, 15(4), 23-42. doi: 10.22075/ijnaa.2022.28382.3874
Hojjat Tajik; Ghodratollah Talebnia; Hamid Reza Vakilifard; Faegh Ahmadi. "Machine learning support to provide an intelligent credit risk model for banks' real customers". هنرهای کاربردی, 15, 4, 1403, 23-42. doi: 10.22075/ijnaa.2022.28382.3874
Tajik, Hojjat, Talebnia, Ghodratollah, Vakilifard, Hamid Reza, Ahmadi, Faegh. (1403). 'Machine learning support to provide an intelligent credit risk model for banks' real customers', هنرهای کاربردی, 15(4), pp. 23-42. doi: 10.22075/ijnaa.2022.28382.3874
Tajik, Hojjat, Talebnia, Ghodratollah, Vakilifard, Hamid Reza, Ahmadi, Faegh. Machine learning support to provide an intelligent credit risk model for banks' real customers. هنرهای کاربردی, 1403; 15(4): 23-42. doi: 10.22075/ijnaa.2022.28382.3874

Machine learning support to provide an intelligent credit risk model for banks' real customers

International Journal of Nonlinear Analysis and Applications
مقاله 3، دوره 15، شماره 4، تیر 2024، صفحه 23-42    اصل مقاله (736.35 K)
نوع مقاله: Research Paper
شناسه دیجیتال (DOI): 10.22075/ijnaa.2022.28382.3874
نویسندگان
Hojjat Tajik1؛ Ghodratollah Talebnia* 2؛ Hamid Reza Vakilifard2؛ Faegh Ahmadi3
1Department of Accounting, Qeshm Branch, Islamic Azad University, Qeshm, Iran
2Department of Accounting, Science and Research Branch, Islamic Azad University, Tehran, Iran
3Department of Accounting and Finance, Qeshm Branch, Islamic Azad University, Qeshm, Iran
چکیده
Artificial intelligence plays an important role in the field of personal computers. Right now personal computers are part of our lives, so AI should be used in all everyday tasks. Humans are great thinkers, but machines can be more effective at counting than humans. The machine cannot fully explain different conditions, but it can create a different type of connection between different salient points and features. Either way, there can be many benefits to establishing machine learning computing in our daily lives. Machine learning or machine learning is one of the subsets of artificial intelligence that enables systems to learn and improve automatically without explicit programming, and controlling the credit risk of real bank customers is one of these benefits that can help the monetary and banking system to improve conditions and reduce risk. Therefore, the use of machine learning to create an algorithm to manage credit risks is a topic addressed in this research.
کلیدواژه‌ها
intelligent model؛ credit risk؛ real customers؛ banks؛ machine learning algorithm
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