Evaluation of Data Mining Classification Techniques and Performances to Banking Customers Credit Scoring

سال انتشار: 1390
محل انتشار: پنجمین کنفرانس بین المللی پیشرفت های علوم و تکنولوژی
کد COI اختصاصی: SASTECH05_130
زبان مقاله: انگلیسی
تعداد مشاهده: 1244

نویسندگان

Master Student of Islamic Azad University, Zanjan

MS Computer Engineering – Iran university of Science and Technology

چکیده

The clarity of the information about Iran’s banking system is increased at the result of the globalization of trade and the growing economy of the country’s economy and this is playing a significant role in the process of the banks in primary customer. Such a system which assist the banks in reaching their goals will require diversity ground. This system have some problems in Iran’s banking system due to the lack of comprehensive data bank of bank’s customer that these problems will be reveled in the payment facility to customers or presentation long-term programs about the amount of the facilities that will paid in the future and also this can’t considered as a guarantee for receipt of claims. Thus the lack of the full validation and scoring customers in Iranian banks with the aim of transparency and competition in the banking system is one of the main reasons for increased bank demand.There are many data mining techniques for predicting and validation of bank’s customers, that the most famous techniques is considered in this article which included: support vector machines, genetic programming, denotative analysis, logical regression, C4.5, Bagging, Boosting.

کلیدواژه ها

Banking facilities, Data mining, Validation

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