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Study of Hidden Markov Model in credit card fraudulent detection

机译:信用卡欺诈检测中的隐马尔可夫模型研究

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摘要

The most accepted payment mode is credit card for both online and offline in today's world, it provides cashless shopping at every shop in all countries. It will be the most convenient way to do online shopping, paying bills etc. Hence, risks of fraud transaction using credit card has also been increasing. In the existing credit card fraud detection business processing system, fraudulent transaction will be detected after transaction is done. It is difficult to find out fraudulent and regarding loses will be barred by issuing authorities. Hidden Markov Model is the statistical tools for engineer and scientists to solve various problems. In this paper, it is shown that credit card fraud can be detected using Hidden Markov Model during transactions. Hidden Markov Model helps to obtain a high fraud coverage combined with a low false alarm rate.
机译:当今世界上最普遍接受的付款方式是在线和离线信用卡,它在所有国家/地区的每家商店提供无现金购物。这将是最方便的在线购物,付款等方式。因此,使用信用卡进行欺诈交易的风险也在增加。在现有的信用卡欺诈检测业务处理系统中,交易完成后将检测到欺诈交易。很难发现欺诈行为,并且有关损失将被发行机构禁止。隐马尔可夫模型是工程师和科学家用来解决各种问题的统计工具。本文表明,可以在交易过程中使用隐马尔可夫模型检测信用卡欺诈。隐马尔可夫模型有助于获得较高的欺诈覆盖率和较低的误报率。

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