Evaluation of Naïve Bayes and Voting Classifier Algorithm for Credit Card Fraud Detection
T. Vairam, S. Sarathambekai, S Bhavadharani, A Kavi Dharshini, N Nithya Sri, Tarika Sen · 2022 8th International Conference on Advanced Computing and Communication Systems (ICACCS) · 2022
In this new generation, each and everything is done online and most of the time the payment is performed via the internet using net banking or a credit card. Debit card and credit card plays a major part in day-to- day life. The total amount of money transfers through online has a great amount of growth. Fraudulent transactions have escalated as E-commerce continues to expand at a rapid pace. Therefore banks, financial institutions and many other companies offer credit card fraud detection applications with more demand, and it adds more value to the applications. To reduce the transactions that are fraud, Credit Card Fraud Detection that employ Machine Learning Techniques comes to the rescue, which is a data investigation procedure carried out by a Data Science team, with the model generated providing the greatest outcomes in stopping fraudulent transactions.