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A Hybrid Approach Using Maximum Entropy and Bayesian Learning for Detecting Delinquency in Financial Industry

机译:利用最大熵和贝叶斯学习的混合方法来检测金融行业的违法行为

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摘要

The use of credit card has increased tremendously in the past tew years because of the boom in the economy which has also resulted in the increase in the credit card fraud cases. Various leading banks and software development companies worldwide are taking serious measures to deal with the gravity of this situation. This paper proposes a framework for credit card fraud detection that will detect frauds using maximum entropy according to the irregular behavior of the customers in various transactions of credit card. The comparative study of above approach with existing approaches is also addressed. Results show the feasibility and validity of each approach.
机译:在过去的几年中,由于经济的繁荣,信用卡的使用已大大增加,这也导致了信用卡欺诈案件的增加。全球各地的多家领先银行和软件开发公司都在采取严肃措施来应对这种情况的严重性。本文提出了一种信用卡欺诈检测的框架,该框架将根据客户在各种信用卡交易中的不规则行为,使用最大熵来检测欺诈。还讨论了上述方法与现有方法的比较研究。结果表明了每种方法的可行性和有效性。

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