A BAYES NETWORK ANALYSIS FOR BANKING'S CONSUMER LOAN ALLOCATION

Volkan Sevä°n㇠()
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Volkan Sevä°nã‡: MuÄŸla Sıtkı Koçman Ãœniversitesi Fen Fakültesi, Kötekli Kampüsü, MuÄŸla, Yrd. Doç. Dr.

Eurasian Eononometrics, Statistics and Emprical Economics Journal, 2018, vol. 10, issue 10, 77-84

Abstract: One of the solutions that consumers apply to afford some of their needs is consumer credit. Consumer credits mainly form three groups: Mortgage credits, personal finance credits and vehicle credits. When banks are allocating those credits to their customers they make an evaluation of the customers according to some criteria. At the end of this evaluation they accept or reject the credit demands. This manuscript provides a simultaneous analysis of the variables belonging to the consumer credit customers by means of a Bayesian network. The analysis includes the relationship of the variables with each other and the decision of the bank. According to the analysis it has been detected that banks tend to give the personal finance credit more easily to the all age and occupation groups. The mortgage credit, however, is the most difficult to get. As far as the vehicle credit applications are concerned, age appears to be an important factor to get the credit.

Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:eas:econst:v:10:y:2018:i:10:p:77-84

DOI: 10.17740/eas.stat.2018�V10�06

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