Fraud Detection in Financial Transactions Using Credit Card: A Machine Learning Model

Dr Rakesh Kumar Pathak, Priyanshu Gaurav, Vaibhav Kumar, Aditya Raj
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Abstract

Fraud in any financial transactions causes severe loss to both customer as well as the seller. The loss is not confined to financial loss only but it also causes severe dent to the confidence of the customer especially related to shopping platform and the payment instrument used. Nowadays a substantial part of buying and selling of goods and services are taking place using various e commerce platforms. Many customer use credit card as payment instrument. During the payment process, users do exposes the credit card credentials to the payment platform. These payment platforms are vulnerable to fishing and hacking attackers and the payment instrument remains highly susceptible to fraudulent activities. There are two approaches to dealing with this problem. The first step is to identify the fraudulent activities and second step is to prevent any such attempt of fraud. This paper proposes a model based on machine learning algorithms to identify fraudulent attempts by analyzing credit card transactions data set and proposes methods of preventing such fraud activities. The paper also presents the accuracy of this AI model in identifying and preventing fraudulent and mischievous activities.
信用卡金融交易中的欺诈检测:机器学习模型
任何金融交易中的欺诈行为都会给客户和卖家造成严重损失。这种损失不仅限于经济损失,还会严重打击客户的信心,尤其是对购物平台和所用支付工具的信心。如今,很大一部分商品和服务的买卖都是通过各种电子商务平台进行的。许多客户使用信用卡作为支付工具。在支付过程中,用户会将信用卡凭证暴露给支付平台。这些支付平台很容易受到钓鱼和黑客攻击,支付工具仍然极易受到欺诈活动的影响。有两种方法可以解决这个问题。第一步是识别欺诈活动,第二步是防止任何此类欺诈企图。本文提出了一个基于机器学习算法的模型,通过分析信用卡交易数据集来识别欺诈企图,并提出了预防此类欺诈活动的方法。本文还介绍了该人工智能模型在识别和预防欺诈和恶作剧活动方面的准确性。
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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