Determination of the Bank's Customer Risk Profile: Data Mining Applications
In this study, the clients who applied to a bank branch for loan were analyzed through data mining. The study was composed of the information such as amounts of loans received by personal and SME clients working with the bank branch, installment numbers, number of delays in loan installments, payments available in other banks and number of banks to which they are in debt between 2010 and 2013. The client risk profile was examined through Classification and Regression Tree (CART) analysis, one of the decision tree classification methods. At the end of the study, 5 different types of customers have been determined on the decision tree. The classification of these types of customers has been created with the rating of those posing a risk for the bank branch and the customers have been classified according to the risk ratings.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1126381Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 751
 F. Bryan, and S. Merlin, “CRM in Financial Services: A Practical Guide to Making Customer Relationship Management Work”, Kogan Page Limited, Milford, Ct, USA, 2002.
 Peppard, J., 2000, “Customer Relationship Management (CRM) in Financial Services”, European Management Journal, Vol. 18, No. 3, pp. 312–327.
 M.A. Evcim, “Segmentasyon ve Müşteri Prototipleri”, CRM Institute Turkey, CRM Atölye Çalışmaları, (CD), 2004.
 T. Oktay, “Kurumsal Destek Sistemleri”, Yöneticinin E-iş Rehberi, Mayıs, (6), 4-9, 2002.
 B.M Thuarisingham, “Web Data Mining and Applications in Business Intelligence and Counter Terrorism”, CRC Press LLC, Boca Raton, FL, USA. 2003.
 O. Akgobek, and F. Cakiri, Akademik Bilişim’09 - XI. Akademik Bilişim Konferansı Bildirileri, Harran Üniversitesi, Şanlıurfa 11-13 Şubat, 2009.
 N. Ata, E. Özkök, and U. Karabey, “Survival Data Mining: An Application to Credit Card Holders” Sigma Mühendislik ve Fen Bilimleri Dergisi, Cilt 26, No 1,33-42, 2008.
 R. Nijskens, and W. Wagner, “Credit Risk Transfer Activities and Systemic Risk: How Banks Became Less Risky Individually, But Posed Greater Risks to The Financial System at The Same Time”, Journal of Banking and Finance, 35, 1391–1398, 2011.
 R.A. Cole, “The Importance of Relationships to The Availability of Credit”, Journal of Banking and Finance, 22, 959-977, 1998.
 A.S. Albayrak, and Ş.K Yılmaz, “Veri Madenciliği: Karar Ağacı Algoritmaları ve İMKB Verileri Üzerine Bir Uygulama”, S.D.Ü. İktisadi ve İdari Bilimler Fakültesi Dergisi, Cilt 14, No 1, 31-52, 2009.
 U. Altunöz, “Bankaların Finansal Başarısızlıklarının Diskriminant Analizi ve Yapay Sinir Ağları Çerçevesinde Tahmini”, Sakarya Üniversitesi İktisat Dergisi, 2(4), 1-21, 2013.
 L F. M.iou, “Fraudulent Financial Reporting Detection and Business Failure Prediction Models: A Comparison”, Managerial Auditing Journal, 23(7), 650-662, 2008.
 A.S. Albayrak, and R. Akbulut, “Sermaye Yapısını Belirleyen Faktörler: İMKB Sanayi ve Hizmet Sektörlerinde İşlem Gören İşletmeler Üzerine Bir İnceleme”, Dumlupınar Üniversitesi Sosyal Bilimler Dergisi, 22, 2008.
 Y. Ma, “Data Warehousing, OLAP and Data Mining: An Integrated Strategy for Use at FAA”, Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, http://www.citeseer.ist.psu.edu/ma98data.html, 1998.
 C. Bounsaythip, and R. R. Esa, “Overview of Data Mining for Customer Behavior Modeling”, VTT Information Technology Research Report, Version:1, s. 1-53. 2001.