Credit Card Fraud Detection Using Machine Lea...

Credit Card Fraud Detection Using Machine Learning

Author Name : Pranay Singhal, Sarthak Bhatia, Dr. Sunil Maggu, Vibhor Sharma

ABSTRACT

In today’s world, due to rapid increase of technology many countries in the world are encouraging cashless transactions. Credit cards are the easiest and fastest mode of payment both in offline as well as in online transactions. So, credit cards are becoming a more popular mode of transaction in modern day life. It also increases the incidents of credit card frauds. People and companies face a huge amount of loss of money due to this increasing case of fraud transactions. This also affects liability of the bank systems and service providers. That is why it becomes very important to detect fraud transactions and avoid financial loss. As we step into the digital world, cybersecurity becomes a crucial part of our lives. When it comes to security in digital life, the main problem is finding abnormal activity. Such problems can be solved with the help of Data Science and its importance, along with machine learning, cannot be overlooked. This project aims to demonstratethe simulation of a dataset using machine learning with the problem of credit card fraud detection. The fraud detection problem involves simulating past card transactions with those that turned out to be a scam. The model is then used to determine if a new transaction is fraudulent or not. Our goal is to identify maximum number of fraudulent transactions with minimal misclassifications.

Keywords— Credit Card Fraud, Logistic Regression, Machine Learning, Decision Tree, Dataset