As organizations scale their use of machine learning and generative AI, the cost of model failure grows. CSAA Insurance Group built an Independent Model Validation (IMV) team to evaluate models across multiple risk dimensions: bias, fairness, robustness, explainability, and real-world impact. In this session, Aaron will share how CSAA operationalized scalable model validation across supervised models, large language models, and vendor-built systems. You’ll hear real examples of model flaws they’ve caught and how they balance rigor with innovation. Model validation isn’t a gate, it’s how machine learning becomes safe, fair, and launch-ready.