Credit Card Fraud Detection System Based on User Based Model with GA and Artificial Immune System

摘要

Modern science and technology has increased incredibly by inventing new applications and inventions. The expertise machinery has been developed in such a way that it keeps in mind, the new discovery would be contented and will be easy to use for the human beings. One of the discoveries of recent technology is the Credit cards. The use of credit cards has increased a lot for the online purchasing and also for regular purchase. Credit card security is major apprehension to protect its misused from the fraudsters. There comes a necessity to identify the frauds before billing action is executed, this intern will avoid the monetary or economic losses to the banks, card owners. Hence, it is necessary to discriminate the genuine transaction and fraudulent transaction. This User model is based on the Artificial Immune System and Genetic Algorithm. This user based model maintains the historical details, problem description and its relative solution to detect a given transaction is normal or fraudulent transaction. Thus, the user based model is an adaptive self-learning based on the historical details of transactions. The alert generated by this model is noticed in advance before billing action is performed. This helps in reducing the massive financial losses to the cardholder and card issuer or the banks.