Yiğit Kültür, Mehmet Ufuk Çağlayan
Intelligent Automation & Soft Computing, Vol.24, No.4, pp. 807-817, 2018, DOI:10.1080/10798587.2017.1342415
Abstract Because credit card fraud costs the banking sector billions of dollars every year, decreasing the losses
incurred from credit card fraud is an important driver for the sector and end-users. In this paper, we
focus on analyzing cardholder spending behavior and propose a novel cardholder behavior model
for detecting credit card fraud. The model is called the Cardholder Behavior Model (CBM). Two focus
points are proposed and evaluated for CBMs. The first focus point is building the behavior model
using single-card transactions versus multi-card transactions. As the second focus point, we introduce
holiday seasons as spending periods that are different… More >
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