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Detecting Frauds Using Customer Behavior Trend Analysis and Known Scenarios

عنوان مقاله: Detecting Frauds Using Customer Behavior Trend Analysis and Known Scenarios
شناسه ملی مقاله: JR_IJIEPR-29-1_007
منتشر شده در شماره 1 دوره 29 فصل در سال 1397
مشخصات نویسندگان مقاله:

Abdollah eshghi - Industrial and systems engineering , Tarbiat Modares University
mehrdad kargari - Indust rial and systems engineering , Tarbiat m odares University

خلاصه مقاله:
The present paper proposes a fraud detection method in which user behaviors are m odelled th ough using two main components known as abnormal trend analysis component and sce nario -based component. The extent of deviation of a transction from customers’ normal behavior is estimated u sing fuzzy membership functions. The results of applyi ng all mem bership fu nctions on a transaction will then be infused, and a fin l risk is de termined as for decidin g whether to block the arrived tr ansaction orthe basis ptimized threshold f or the val e of the f inal risk is not. An estimated in order to strike a balance betw en fraud d etection rate of such problems is Although the assessment and alar m rate. useful in application m ethod is sh own to be complicated, this according to several measures and metrics.

کلمات کلیدی:
fraud detection,user profiles,fuzzy membership function,trend analysis ,scenario

صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/794492/