Credit Card Fraud Detection with Machine Learning and Generative AI: A Data-Driven Approach

This case study investigates the application of Data Science, Machine Learning, Artificial Intelligence, and Generative AI to enhance credit card fraud detection. Leveraging Python-based frameworks, the study employs advanced algorithms for predictive modeling, data interpolation, and visualization. The findings highlight improved accuracy in identifying fraudulent transactions, reinforcing the role of AI-driven automation in financial risk assessment. This research emphasizes the transformative potential of AI in fraud prevention and supports data-driven strategies for securing digital financial ecosystems.