Classification of Bank Customers by Data Mining: a Case Study of Mellat Bank branches in Shiraz
Publish place: International Journal of Management, Accounting and Economics (IJMAE)، Vol: 3، Issue: 8
Publish Year: 1395
نوع سند: مقاله ژورنالی
زبان: English
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شناسه ملی سند علمی:
JR_IJMAE-3-8_006
تاریخ نمایه سازی: 7 اسفند 1395
Abstract:
This research predicts through studying significant factors in customer relationship management and applying data mining in bank. Financial institutions and other firms in competitive market need to follow proper understanding of customer behavior. Customers’ data are analyzed to identify specific opportunities and investment, to classify and predict the behaviors; further, data are eventually used for decision-making. Therefore, data mining as knowledge exploring (discovery) approach plays a significant role through a variety of algorithms. This study classifies bank customers by using decision tree algorithm. Three decision tree models including ID3, C4.5, and CART were applied for classifying and finally for prediction. Results of simple sampling method and k-fold cross validation show that forecast accuracy of C4.5 decision tree using simple sampling was higher than other models. Thus, predicting customers’ behavior through C4.5 decision tree was considered the ideal prediction for bank.
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Authors
Dariush Farid
Associate Professor, Faculty of Economics, Management and Accounting, University of Yazd, Yazd, Iran
Hojjatollah Sadeghi
Associate Professor, Faculty of Economics, Management and Accounting, University of Yazd, Yazd, Iran
Elaha Hajigol
Industrial PhD, University of Yazd, Yazd, Iran
Nadiya Zrmehr Parirooy
Master of Business Administration Financial trends Yazd University, Yazd, Iran