Using the Hybrid Model for Credit Scoring (Case Study: Credit Clients of microloans, Bank Refah-Kargeran of Zanjan, Iran)

Journal of Optimization in Industrial Engineering

مقاله 6، دوره 12، شماره 2، مهر 2019، صفحه 65-78   

نوع مقاله: Original Manuscript

شناسه دیجیتال (DOI): 10.22094/joie.2019.574793.1583

نویسندگان

Abdollah Nazari^{* 1}؛ Mohammadreza Mehregan²؛ Reza Tehrani³

¹Department of Management, Alborz College, University of Tehran, Tehran, Iran

²Faculty of Management, University of Tehran, Tehran, Iran

³Faculty of Management, University of Tehran, Tehran, Iran.

چکیده

In any country, commercial banks lay the groundwork for economic growth by collecting national resources and capitals and allocating them to different economic sectors. Optimal allocation of resources is especially important in achieving this goal. Banks with an effective and dynamic system of customer assessment can efficiently allocate their resources to customers regardless of their geographic area. Following[M1]  a linear programming optimization approach, this research employs the UTilités Additives DIScriminantes (UTADIS) model for credit scoring of bank customers. The advantages of the proposed technique are high flexibility, mutual interaction with decision makers, and the ability to update under various macroeconomic conditions. The chosen environment is a branch of Bank Refah Kargaran, one of the popular banks in Iran. According to the experimental results, the proposed technique demonstrates high effectiveness. Also, the results indicate that the initial credit score and age of the applicants are the most influential factors for credit scoring of customers.

کلیدواژه‌ها

Credit Scoring؛ Clustering؛ Data mining؛ UTADIS

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