Credit Card Fraud Detection System Using CNN

Abstract

Abstract: This Project is focused on credit card fraud detection in real-world scenarios. Fraud is one of the major ethical issues in the credit card industry. In this era we can see many innovative financial services like ATMs, online banking, etc. Besides, along with the rapid advances of e-commerce, the use of credit cards has become a convenient and necessary part of financial life. A credit card is a payment card supplied to customers as a system of payment. Using a third-person credit card or its information without the knowledge of that person is referred to as credit card fraud. Application and Behavioral fraud are major types of fraud where people are easily tricked and lose their money. The same user may submit multiple applications which may lead to identical fraud. Application fraud takes place when fraudsters apply for new cards from a bank or issuing companies using false or others' information. In this project, we will be applying some supervised and unsupervised algorithms and will classify the credit card dataset. We will use CNN and correlate the data train and get the model's accuracy. Keywords: CCFD, CNN, Logistic Regression, Feature extraction.