This research explores how enterprise risk management (ERM) can be modernized to combat the rising financial threat of insurance fraud. By integrating artificial intelligence and machine learning into traditional frameworks like Basel II, insurers can shift from reactive investigations to proactive prevention. The author emphasizes the use of data analytics and Principal Component Analysis (PCA) to simplify complex claims data into clear, actionable risk categories. These advanced visualization techniques, such as confidence ellipses and heat maps, allow executives to identify fraudulent patterns and anomalies more efficiently. Ultimately, the paper provides a data‑driven roadmap for casualty insurers to strengthen their operational resilience while maintaining regulatory compliance.