Abstract 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 F_1 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 F_1 score of 0.91.

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[23] Uqaili I. and Ahsan S., “Machine Learning Based Prediction of Complex Bugs in Source Code,” The International Arab Journal of Information Technology, vol. 17, no. 1, pp. 26-37, 2020. Pratyush Sharma has a bachelor's degree in Computer Science with specialization in Business Analytics and Optimization from UPES, Dehradun. He is currently working in the IT industry as a software engineer. He has keen interest in application/full stack development and machine learning. Souradeep Banerjee has a bachelor's degree in Computer science with specialization in cloud computing and virtualization from UPES Dehradun. He is currently working the IT industry as a software developer engineer. Devyanshi Tiwari has a Bachelor's Degree in Cloud Computing and Virtualization Technology. Her research interests include machine learning, DevOps. She is currently working as a Software Engineer. Jagdish Chandra Patni working as Associate Professor at School of Computer Science, UPES Dehradun India. He did his Ph.D. in the area of High Performance computing in 2016. He did M. Tech. and B. Tech. respectively in the year 2009 and 2004.His areas of research are Database Systems, High Performance computing, Software Engineering, Machine Learning. He has published more than 50 research articles 5 books/book chapters. He is Guest Editor/Reviewer of various referred International journals. He has delivered 15 Keynote/Guest speech in India and abroad.