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IJSTR >> Volume 7 - Issue 7, July 2018 Edition

International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616

Credit Card Fraud Detection System In Nigeria Banks Using Adaptive Data Mining And Intelligent Agents: A Review

[Full Text]



Amanze, B.C., Onukwugha, C.G



Fraud Transaction, Data Mining, Intelligent Agents, Credit Card, Spending Pattern.



The growth in electronic transactions has resulted in a greater demand for fast and accurate user identification and authentication. Conventional method of identification based on possession of pin and password are not all together reliable. Higher acceptability and convenience of credit card for purchases has not only given personal comfort to customers but also attracted a large number of attackers. As a result, credit card payment systems must be supported by efficient fraud detection capability for minimizing unwanted activities by fraudster’s. Most of the well-known algorithms for fraud detection are based on supervised training. Every cardholder has a certain shopping behaviour, which establishes an activity profile for him. Existing fraud detection systems try to capture behavioural patterns as rules which are static. This becomes ineffective when cardholder develops new patterns. This paper aimed at developing credit card fraud detection system for banking industries in Nigeria using adaptive data mining and intelligent agents that could combines evidences from current as well as past behaviour and to determine the suspicious level of each incoming transaction. The statistics of fraud in Nigeria is discussed. In this paper, a system model for credit card fraud is discussed and designed.



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