Credit Card Fraud Detection Based on Deep Neural Network Approach

Khalid Alkhatib, Ahmad Al-Aiad, Mothanna Almahmoud, Omar N. Elayan
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引用次数: 7

Abstract

Currently, the financial companies’ reliance has become on the new technologies and developments, in which these companies provide the customers with various services, electronically. One the most common financial services is the credit cards, where the customers can complete any financial payments using a credit card, such as; Visa card and MasterCard. However, criminals started to find ways to attack customers’ cards for fraud purposes, and that has caused a big issue for both of companies and customers. This work aim to propose a new for credit card fraud detection based on a dataset for customers’ transactions of a well-known company called Vesta, where the utilization of deep learning approaches has achieved a method with efficient performance in identifying transactions that was classified as fraud with 99.1% score of area under ROC curve.
基于深度神经网络的信用卡欺诈检测
目前,金融公司的依赖已经成为新的技术和发展,这些公司为客户提供各种服务,电子化。最常见的金融服务之一是信用卡,客户可以使用信用卡完成任何金融支付,例如;Visa卡和万事达卡。然而,犯罪分子开始想方设法攻击客户的信用卡以达到欺诈目的,这给公司和客户都带来了一个大问题。本工作旨在提出一种新的信用卡欺诈检测方法,该方法基于知名公司Vesta的客户交易数据集,其中利用深度学习方法实现了一种高效性能的方法,可以识别被归类为欺诈的交易,其ROC曲线下面积得分为99.1%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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