Advanced Machine Learning Techniques for Credit Card Fraud Detection: A Comprehensive Study

Credit card fraud poses a significant threat to the financial sector, resulting in substantial financial losses. This research investigates the application of advanced machine learning techniques to effectively detect fraudulent transactions. By utilizing a publicly available dataset, this study evaluates and compares various algorithms, including Random Forest, Decision Tree, and Artificial Neural Networks (ANN). This research contributes to the advancement of fraud detection technologies by providing valuable insights into the effectiveness of different machine learning algorithms and the critical role of feature engineering. The findings highlight the need for resilient, scalable, and real-time mechanisms to combat evolving fraud strategies.