Fraud detection has become an important issue to be explored. Fraud detection involves identifying fraud as quickly as possible once it has been perpetrated. Fraud is often a dynamic and challenging problem in Credit card lending business. Credit card fraud can be broadly classified into behavioral and application fraud, with behavioral fraud being the more prominent of the two. Supervised Modeling/Segmentation techniques are commonly used in fraud detection to distinguish risky transactions from non-risky transactions. In this paper I address the problem faced due to stolen or fake credit card which is a behavioral type of credit card fraud. To deal with this problem I used Data mining approach which is a classification method and neural network classifier for building my model. The model uses two dataset which is synthesized one for training the network and the other one is for testing. Feed forward back propagation neural network algorithm is used for building my model.

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Credit card Fraud Detection (CCFD) Neural network