Credit Card Fraud Detection using Machine Learning and Deep Learning Techniques
Mohammed Azhan, Shazli Meraj
Abstract
In general, fraudulent activities are always intended to cause financial detriment to the second party. With the aggrandizement of digital money in various countries, the fraudulent activities will be even more increased. Credit card companies and Banks lose billions to such fraudulent activities every year, where it accounts to a huge part of their revenue and affects the jobs of various employees. The proposed research work discusses more about the different fraudulent activities associated with credit cards. While all of them cannot be dealt simultaneously, this research work discusses how Machine Learning and Neural Networks can be used to determine the potential fraudsters by referring to their previous mistakes and details of previous fraudsters. Machine Learning algorithms such as Multinomial Naive Bayes, Random Forest Regression, Logistic Regression, Support Vector Machine and a basic Neural Network are also used.