Credit Card Fraud Detectionusing Random Forest and XGBoost

Abstract

Protecting consumers and financial institutions from credit card fraud is a top priority. As we increasingly rely on digital payments, the need for effective fraud detection systems has become more urgent than ever. It isimportant to ensure the safety of people's financial assets. Traditional methods of fraud detection are being replaced by machine learning, which is like a intelligent tool that can analyze vast amounts of data and spot patterns that might seem invisible to the human eye.Using machine learning, we can directly detect suspicious transactions and prevent fraud before it happens. This abstract proposes a System uses Random Forest and XGBoost - that are really good at identifying potential fraud cases. While these methods are highly effective, there's always room for improvement. Future breakthroughs could include combining different models, monitoring transactions in realtime, and using more advanced neural networks to improve detection accuracy and response time.