Financial Fraud Detection in Plastic Payment Cards using Isolation Forest Algorithm

Ankaj Kumar, G. S. Mishra, P. Nand, Madhav Singh Chahar, Sonu Kumar Mahto
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引用次数: 2

Abstract

The need for technology has always found space in Financial Transaction as the number of fraud in financial transactions increases day by day. In this research we have proposed a new methodology by using the isolation forest algorithm and local outlier detection algorithm to detect the financial fraud. A standard data set is used in experimentation to classify a transaction occurred is a fraudulent or not. We have used neural networks and machine learning for classification. We have focused on the deployment of anomaly detection algorithms that is Local Outlier Factor and Isolation Forest algorithm (IFA) on financial fraud transactions data.
基于隔离森林算法的塑料支付卡金融欺诈检测
随着金融交易中欺诈的数量日益增加,对技术的需求一直在金融交易中找到空间。在本研究中,我们提出了一种利用隔离森林算法和局部离群点检测算法来检测财务欺诈的新方法。在实验中使用标准数据集来分类发生的交易是欺诈还是不欺诈。我们使用神经网络和机器学习进行分类。我们重点研究了局部离群因子和隔离森林算法(IFA)在金融欺诈交易数据上的异常检测算法的部署。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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