Due to the high level of growth in each number of transactions done using credit card has led to high rise in fraudulent activities. Fraud is one of the major issues related to credit card business, since each individual do more of offline or online purchase of product via internet there is need to developed a secured approach of detecting if the credit card been used is a fraudulent transaction or not. Pattern involves in the fraud detection has to be re-analyze to change from reactive approach to a proactive approach. In this paper, our objectives are to detect at least 95% of fraudulent activities using machine learning to deployed anomaly detection system such as logistic regression, k-nearest neighbor and support vector machine algorithm.
Credit Card, Fraud Detection, Machine Learning, Logistic Regression, K-Nearest Neighbor, Support Vector Machine Algorithm
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