Credit Card Fraud Detection Using Support Vector Machine

Abstract

Credit card fraud has without hesitation an expression of criminal deception. Fraud identification seems to be a complicated problem that requires a significant amount of skill until throwing algorithms regarding machine learning into it. However, it is an implementation for both the better of machine learning as well as artificial intelligence, ensuring that perhaps the funds of both the customer seems to be secure and therefore not manipulated. The whole research article addressed an effective system of identifying fraud depending on machine learning methodologies, with such a feedback system. Its feedback process relates to enhancing the classifier's detection rate as well as effectiveness. The state of art approaches failed to detect the frauds through credit card transactions. Thus, to solve these drawbacks, the proposed system is implemented with the Support vector machine (SVM) classification to detect the frauds. The simulation results show that the proposed method gives the better classification accuracy compared to the state of art approaches.