Credit Card Fraud Detection

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Presentation transcript:

Credit Card Fraud Detection

Contents Introduction Problem Definition Proposed Solution Block Diagram Implementation Software and Hardware Requirements Benefits Results and Conclusion

Introduction Online Shopping – one of the largest and fast going trend Mode of payment – credit card, debit card, Net Banking Online payment does not require physical card Major Risk – credit /debit card detail is known to other

Problem Definition Online payment does not require physical card Anyone who know the details of card can make fraud transactions Currently, card holder comes to know only after the fraud transaction is carried out. No mechanism to track the fraud transaction

Proposed Solution A mechanism is developed to determine whether the given transaction is fraud or not The mechanism uses Hidden Markov Model to detect fraud transaction Hidden Markov Model works on the basis of spending habit of user. Classifies user into Low, Medium or High category

Block Diagram User e-Commerce Website Bank FDS

Implementation Project is implemented using following technologies : HTML, CSS, JavaScript, PHP and MySQL HTML and CSS is used for interface designing JavaScript is used for client side validation PHP is used for server side scripting MySQL is used for database

Hardware & Software Req. Online Auction System Hardware Software Windows 2000/ Windows XP/ Windows Vista/ Windows 7 WAMP Macromedia Dreamweaver Pentium Core 2 Duo processor or above I GB RAM 20 GB HDD Router for Internet Connection

Benefits Reduction in number of fraud transaction User can safely use his credit / debit card for online transaction Added layer of security

Results and Conclusion Fraud detection is based on Hidden Markov Model which is learning algorithm, hence not 100% correct It has detected those transaction as fraud where user belongs to low category and high category payment is made or vice versa The mechanism require at least 10 transaction to determine accurately the transaction as fraud or not.

Thank You