Machine Learning Model for Credit Card Fraud Detection- A Comparative Analysis

In today's world, we are on an express train to a cashless society which has led to a tremendous escalation in the use of credit card transactions. But the flipside of this is that fraudulent activities are on the increase; therefore, implementation of a methodical fraud detection system is indispensable to cardholders as well as the card-issuing banks. In this paper, we are going to use different machine learning algorithms like random forest, logistic regression, Support Vector Machine (SVM), and Neural Networks to train a machine learning model based on the given dataset and create a comparative study on the accuracy and different measures of the models being achieved using each of these algorithms. Using the comparative analysis on the F₁ score, we will be able to predict which algorithm is best suited to serve our purpose for the same. Our study concluded that Artificial Neural Network (ANN) performed best with an F₁ score of 0. 91.