基于人工神经网络和自组织映射的信用卡欺诈预测与检测

E. Saraswathi, Prateek P. Kulkarni, Momin Nawaf Khalil, Shishir Chandra Nigam
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引用次数: 3

摘要

在过去的二十年里,信用卡业务增长迅速。公司和机构正在转向各种在线服务,其目的是让他们的客户具有高效力和可访问性。这一演变是朝着视野的效力、可及性和可盈利性迈出的一大步。然而,它也有一些缺点。这些智能服务最近容易出现重大的安全相关漏洞。通过卡开展业务取决于这样一个事实,即卡和用户都不需要出现在交易点。因此,商家不可能检查持卡人是否真实。近年来,公司的损失主要是由于信用卡诈骗和欺诈者不断获得新的方法来进行非法活动。正如我们所知,人工神经网络在训练得当的情况下具有像人类大脑一样工作的能力。我们还实现了SOM的准确性目的。在本文中,我们讨论了网络的性能和它们的精度。
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Credit Card Fraud Prediction And Detection using Artificial Neural Network And Self-Organizing Maps
The credit card business has increased speedily over the last two decades. Corporations and establishments are moving towards various online services, which aims to permit their customers with high potency and accessibility. The evolution is a huge step towards potency, accessibility and profitableness of view. Nevertheless, it additionally has some downsides. These smart services are recently prone to significant security related vulnerabilities. Developing business through card depends on the fact that neither the card nor the user needs to be present at the point of transaction. Thus, it is impossible for merchandiser to check weather the cardholder is real or not. Companies’ loss in recent times are majorly due to the credit card fraud and the fraudsters who ceaselessly obtain new ways to commit the unlawful activities. As we know that Artificial Neural Network has the ability to work as a human brain when trained properly. We have also implemented SOM for accuracy purpose. In this paper, we discuss about the performance of the network and their accuracy.
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