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:: year 6, Issue 16 (summer 2013) ::
JMBR 2013, 6(16): 27-58 Back to browse issues page
Identifying Influential Factors in Credit Behavior of Real Applicants of Facilities
Khashayar Moghaddam *, Ali Arshadi1, Kianoosh Rezayee
1- Banking Expert
Abstract:   (3396 Views)

Regarding to an increased growth of nonperforming loan plus banks benefits being at risk through the recent years, this study aims to investigate the influential factors in credit behavior of real applicants of retail facilities. Therefore, the researchers identified 35 factors, followed by which they selected 429 credit files to evaluate the effect of these factors on Probability of default applying data mining  techniques such as decision trees (C5, QUEST, CART, CHAID), artificial neural network, Support vector machine, logistic regression and discriminant analysis. The results are indicative of the fact that the artificial neural network has a higher prediction ability compared to other methods. Besides these 35 factors, 12 other indicators (including repayment duration, type of the loan contract, repayment installments number, collateral type, the number of invalid checks before receiving loans, installment amounts, depositing time (short-term deposits), economic sector, gender, job, transaction average through 6 month prior to receiving the loan and the property status) were respectively of highest importance in explaining the creditors behavior. Among the aforementioned factors, only 3 factors (including the property status, gender and Job) were out of bank control. In the end, the regulations resulted from the decision tree were extracted for decision creating (designing a credit evaluation model) in bank.

JEL Classification Codes: E5, E1, C4, C1

Full-Text [PDF 481 kb]   (1963 Downloads)    
Type of Study: Empirical Study |
Received: 2014/08/2 | Accepted: 2014/08/2 | Published: 2014/08/3

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year 6, Issue 16 (summer 2013) Back to browse issues page
فصلنامه پژوهش‌های پولی-بانکی Journal of Monetary & Banking Research
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