Adaptive Model for Credit Card Fraud Detection

被引：1

作者：

Sadgali I. ^{[1
]}

Sael N. ^{[1
]}

Benabbou F. ^{[1
]}

机构：

[1] University Hassan II, Casablanca

来源：

International Journal of Interactive Mobile Technologies | 2020年 / 14卷 / 03期

关键词：

Credit Card Fraud; customer profile; Fraud Detection; Machine-Learning; transaction profile;

D O I：

10.3991/ijim.v14i03.11763

中图分类号：

学科分类号：

摘要：

While the flow of banking transactions is increasing, the risk of credit card fraud is becoming greater particularly with the technological revolution that we know, fraudulent are improve and always find new methods to deal with the preventive measures that financial systems set up. Several studies have proposed predictive models for credit card fraud detection based on different machine learning techniques. In this paper, we present an adaptive approach to credit card fraud detection that exploits the performance of the techniques that have given high level of accuracy and consider the type of transaction and the client's profile. Our proposition is a multi-level framework, which encompasses the banking security aspect, the customer profile and the profile of the transaction itself. © 2020, iJIM. All Rights Reserved

引用

页码：54 / 65

页数：11

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