Credit Card Fraud Detection Using Hidden Markov Model .Net Project Report

Introduction to Credit Card Fraud Detection Using Hidden Markov Model .Net Project:

The usage of the Credit Card has been tremendously increased. The fraudulent also increased simultaneously with the Credit Card usage. The Credit Card is used for the online payments and also for the normal purchases.

The Project is based on the model the detection of the frauds during the Credit Card usage by applying Hidden Markov Model (HMM). The principle is to make the HMM known to the Credit Card and the act of the Card holder. The fraud is considered when the HMM does not allow the Credit Card transactions. 

The Existing System 

In an existing system the fraud can not be detected. Fraud is identified after the Credit Card holder complains about the fraudulent. The investigation also takes lot of time to complete. The huge data and information is required for detection of the fraud for all transactions which are maintained in the log. The way of using the Credit Card is difficult. To detect the fraud first the requirement is to get the IP address. 

The Proposed System 

The Proposed System is based on the immediate behavior of the Credit Card holders. It does not require the fraud signatures. The Credit Card transaction is done in a stochastic procedure. 

The general fraud detection system is not able to detect separate transactions. The HMM overcome this problem by detecting the False transactions. 

The hardware system required is Pentium IV 2.4 GHz, 40 GB, hard disk. 256 MB RAM. 

 Download  Credit Card Fraud Detection Using Hidden Markov Model .Net Project Report .

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