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A data mining based system for credit-card fraud detection in e-tail

机译:基于数据挖掘的电子尾巴信用卡欺诈检测系统

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Credit-card fraud leads to billions of dollars in losses for online merchants. With the development of machine learning algorithms, researchers have been finding increasingly sophisticated ways to detect fraud, but practical implementations are rarely reported. We describe the development and deployment of a fraud detection system in a large e-tail merchant. The paper explores the combination of manual and automatic classification, gives insights into the complete development process and compares different machine learning methods. The paper can thus help researchers and practitioners to design and implement data mining based systems for fraud detection or similar problems. This project has contributed not only with an automatic system, but also with insights to the fraud analysts for improving their manual revision process, which resulted in an overall superior performance.(C) 2017 Elsevier B.V. All rights reserved.
机译:信用卡欺诈给在线商家造成数十亿美元的损失。随着机器学习算法的发展,研究人员已经发现了越来越复杂的检测欺诈的方法,但是很少有实际实现的报道。我们描述了大型电子商务零售商中欺诈检测系统的开发和部署。本文探索了手动和自动分类的结合,对完整的开发过程有深入的了解,并比较了不同的机器学习方法。因此,本文可以帮助研究人员和从业人员设计和实现用于欺诈检测或类似问题的基于数据挖掘的系统。 (C)2017 Elsevier B.V.保留所有权利。该项目不仅为自动系统做出了贡献,而且还为欺诈分析师提供了有关改进其人工修订流程的见解,从而带来了总体上的卓越性能。(C)2017 Elsevier B.V.保留所有权利。

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