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Efficient Scalable Multi-Level Classification Scheme for Credit Card Fraud Detection


Dipti D.Patil, Sunita M.Karad, Vijay M.Wadhai, J A Gokhale, Prasad S.Halgaonkar


Vol. 10  No. 8  pp. 123-130


The detection of fraudulent transactions in credit card world is an important application of classification techniques. As human behavior is unpredictable classifying any transaction either as fraud or non-fraud is not acceptable. In all of the previous studies, the transactions were classified in only two levels either fraud or legitimate. An approach where the credit card transactions can be classified in various fraud levels depending on different fraudulent situations mined from the historical behavior of the customers is proposed and implemented. To perform the classification, Efficient Scalable Multilevel Classifier (ESMC) algorithm is developed. Our algorithm is scalable to large dataset and results shows better accuracy than the previous algorithm implemented for credit card fraud detection. The concept of multi-dimensional decision tree is introduced to have better scalability in the field of distributed databases.


Distributed data Mining, Decision Tree, Pruning, Intrusion Detection