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Payment Card Fraud Detection with Data Mining: A Review

机译:带有数据挖掘的支付卡欺诈检测:回顾

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Today, one-fourth of the customers are a victim of online fraud, with 24% directly experienced fraud with online transactions. With about 90% Indian digital service consumers, 50% are comfortable sharing the data with banks while 51 % shares data to avail services. With the advancement of the credit card business, credit card fraud is also increasing. Payment card fraud is causing losses in millions of Rupees for the card industry. It is not only hurting the consumers, but the industry is affected as well by the loss of consumer confidence in the brand. Due to huge property damage brought by fraud to the investors, hundreds of researches have been conducted to prevent and detect this problem using Data mining methods. Data mining is a technique of examining already existing databases to find patterns and extracting useful information for the business. Various systems using techniques like Hidden Markov Method, Neural Networks and Dynamic key generation has been discussed. A system has been proposed using Associative Rule mining, Clustering and Outliers.
机译:如今,四分之一的客户是在线欺诈的受害者,其中24%的在线交易直接经历了欺诈。印度大约有90%的数字服务消费者,其中50%的人愿意与银行共享数据,而51%的人共享数据以使用服务。随着信用卡业务的发展,信用卡欺诈也越来越多。付款卡欺诈给卡行业造成了数百万卢比的损失。它不仅伤害了消费者,而且消费者对品牌的信心丧失也对该行业产生了影响。由于欺诈给投资者带来的巨大财产损失,已经进行了数百项研究,以使用数据挖掘方法来预防和检测此问题。数据挖掘是一种检查现有数据库以查找模式并提取业务有用信息的技术。已经讨论了使用隐马尔可夫方法,神经网络和动态密钥生成等技术的各种系统。已经提出了使用关联规则挖掘,聚类和离群值的系统。

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