Credit Card Fraud Detection using Machine Learning: A Study
  As the world is rapidly moving towards digitization and money transactions
are becoming cashless, the use of credit cards has rapidly increased. The fraud
activities associated with it have also been increasing which leads to a huge
loss to the financial institutions. Therefore, we need to analyze and detect
the fraudulent transaction from the non-fraudulent ones. In this paper, we
present a comprehensive review of various methods used to detect credit card
fraud. These methodologies include Hidden Markov Model, Decision Trees,
Logistic Regression, Support Vector Machines (SVM), Genetic algorithm, Neural
Networks, Random Forests, Bayesian Belief Network. A comprehensive analysis of
various techniques is presented. We conclude the paper with the pros and cons
of the same as stated in the respective papers.
