Abstract
Abstract---In the current economic scenario, credit card use has become extremely important. They enable the user to perform transactions of large sums of money without the requirement to carry cash for payments. They have revolutionized the path of making cashless transactions and have made it easy in making payments convenient for the buyer. This digitized form of payment is extremely beneficial but comes with its own set of shortcomings. With constant increase in number of users, credit card frauds are also increasing at a commensurate pace.Billions of dollars of losshaveresulted every year by illegitimate credit card payments. The development of effective and efficient fraud detection models is key to reducing these losses, and more algorithms depend on advanced machine learning methods to help fraud investigators. As the obtainable credit card fraud data is highly imbalanced. In this paper we are overcoming this deficiency by balancing out the data and bringing out the best algorithm that segregates the transaction efficiently.
Published Version
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