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Statistical and Spending Behavior based Fraud Detection of Card-based Payment System

机译:基于统计和支出行为的基于卡的支付系统欺诈检测

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The occurrence of credit and debit card fraud has been a growing issue in the past years, not least due to the increased prevalence of card payments. This results in billions of dollars of lost revenue every year. The fraud preventative measures still show room for improvement. In this paper, we present an alternative fraud detection technique in the form of a rudimentary fraud detection system that utilizes consumer spending behavior. Three attributes of a transaction, namely time, amount, and geographical location, were used as a basis to build a consumer profile. Data for these attributes would be collected from each transaction made by the cardholder and would be used to calculate various statistical values pertaining to their spending patterns, which is used to calculate the probability of fraud. Experimental results show that the aspect of consumer spending behavior can be quantified and used to accurately calculate various probability values related to transactions and possibility of fraud.
机译:在过去几年中,信用卡和借记卡欺诈的发生已成为一个日益严重的问题,这尤其是由于卡支付的普及率越来越高。这导致每年数十亿美元的收入损失。预防欺诈措施仍显示出改进的空间。在本文中,我们以利用消费者支出行为的基本欺诈检测系统的形式提出了另一种欺诈检测技术。交易的三个属性,即时间,金额和地理位置,被用作建立消费者档案的基础。这些属性的数据将从持卡人进行的每笔交易中收集,并用于计算与他们的支出方式有关的各种统计值,该统计值用于计算欺诈的可能性。实验结果表明,可以量化消费者支出行为的方面,并用于准确计算与交易和欺诈可能性有关的各种概率值。

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