THE AI SHIELD: DETECTING FINANCIAL CRIMES IN REAL-TIME

ABSTRACT As the number of digital transactions surges, so does financial fraud, revealing the shortcomings of traditional rule-based detection systems. Artificial Intelligence, with its ability to analyze real-time data and learn from patterns, has emerged as a powerful method for detecting and mitigating fraud. This paper discusses techniques driven by AI, including anomaly detection and predictive analytics, delves into challenges that need to be addressed (e.g., privacy and adversarial attacks), and highlights the current state of real-world applications across banking, insurance, stock trading, and e-commerce. Finally, we discuss future directions for enhancing AI's role in fraud detection.. Keywords: Anomaly Detection, Artificial Intelligence (AI), Blockchain Security, Deep Learning (DL), Financial Fraud Detection, Machine Learning (ML), Predictive Analytics, Supervised Learning, Unsupervised Learning.