Credit Card Fraud Detection

Credit card fraud detection aims to identify fraudulent transactions amidst a vast volume of legitimate ones, minimizing financial losses and enhancing security. Current research heavily emphasizes advanced machine learning techniques, including deep learning models (like transformers and graph neural networks), to improve accuracy and efficiency, often addressing challenges like imbalanced datasets and concept drift through methods such as SMOTE and adversarial training. These advancements are crucial for financial institutions, impacting both their operational costs and the security of their customers' funds, while also driving innovation in areas like privacy-preserving techniques and the use of alternative data sources.