A Novel Approach in Credit Card Fraud Detection System Using Machine Learning Techniques

With the rapid expansion of daily life, the use of credit cards for online purchases is steadily increasing and credit card fraud is on the rise. Nowadays, in the social distancing environment, due to covid-1, 9online shopping has become important. Credit card credentials are used to make online payments, and then deduct money which does not involve any contact and makes people’s life difficult. Because of this, finding the most effective method of detecting scams in online systems is essential. To prevent customers from being charged for goods they have not purchased, credit card companies must be able to identify fraudulent credit card transactions. Therefore, there are several theories either completed or proceeding to detect these kinds of frauds. This study is an approach to identify non-legitimate transactions using semi-supervised machine learning models by explaining how to deal with imbalanced datasets, using a wide variety of models to better understand which ones work better.