FraudMiner: a novel credit card fraud detection model based on frequent itemset mining.

K R Seeja,Masoumeh Zareapoor

doi:10.1155/2014/252797

Abstract

This paper proposes an intelligent credit card fraud detection model for detecting fraud from highly imbalanced and anonymous credit card transaction datasets. The class imbalance problem is handled by finding legal as well as fraud transaction patterns for each customer by using frequent itemset mining. A matching algorithm is also proposed to find to which pattern (legal or fraud) the incoming transaction of a particular customer is closer and a decision is made accordingly. In order to handle the anonymous nature of the data, no preference is given to any of the attributes and each attribute is considered equally for finding the patterns. The performance evaluation of the proposed model is done on UCSD Data Mining Contest 2009 Dataset (anonymous and imbalanced) and it is found that the proposed model has very high fraud detection rate, balanced classification rate, Matthews correlation coefficient, and very less false alarm rate than other state-of-the-art classifiers.

Highlights

With the advent of communications techniques, e-commerce as well as online payment transactions are increasing day by day
Input: Legal Pattern Database LPD, Fraud Pattern Database FPD, Incoming Transaction T, Number of costumers “n”, Number of attributes “k”, matching percentage “mp” Output: 0 or 1 Assumption: (1) First attribute of each record in pattern databases and incoming transaction is Customer ID (2) If an attribute is missing in the frequent itemset we considered it as invalid
The performance of the proposed classifier is evaluated in terms of 4 classification metrics relevant to credit card fraud detection—fraud detection rate, false alarm rate, balanced classification rate, and Matthews correlation coefficient

Summary

Introduction

With the advent of communications techniques, e-commerce as well as online payment transactions are increasing day by day. Along with this financial frauds associated with these transactions are intensifying which result in loss of billions of dollars every year globally. Among the various financial frauds, credit card fraud is the most old, common, and dangerous one due to its widespread usage because of the convenience it offers to the customer. According to Kount, one of the top five fraud detection consultants revealed by http://www.topcreditcardprocessors.com in the month of August 2013, 40% of the total financial fraud is related to credit card and the loss of amount due to credit card fraud worldwide is $5.55 billion. In real case, 99% of the transactions are legal while only 1% of them are fraud [3]

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