Detecting Credit Card Frauds Using Different Machine Learning Algorithms

Abstract

The main focus of this research paper is to analyze the savings fraud credit card’s identification in current era. Based on transaction the savings account fraud credit cards’ detection is identified. Both online and offline savings fraud things are happening in online and offline transactions of accounts in the real world.  But day by day the rate of happening of frauds are increased in an exponential manner.  In order to detect the frauds in an online transaction a quite a number of techniques have been used in current era. Based on this, an exhaustive survey has been done and conclusion made. By considering the survey, we have proposed different machine learning algorithms for detecting the transactions fraudulent and the accuracy trusted records or transactions. We have used random forest, decision tree, SVM, Gaussian NBLogistic algorithms to  find credit card fruds. The consequences acquired from processing the dataset provides the maximum accuracy as amble of above 90%.