Demystifying AI: A guide to Explainable AI (XAI) Techniques

AI is transforming insurance , from underwriting to claims. However, the complexity of these models often creates a "black box" problem, making it difficult to understand how decisions are reached. This lack of transparency hinders trust, accountability, and the detection of biases. While regulations are emerging to address these concerns, industry-wide adoption of explainable AI is crucial to ensure fairness and ethical AI practices. The goal of Explainable AI is to create AI systems that are transparent and interpretable, so that humans can understand how the model works and why it is making certain decisions. Download the whitepaper to know more about Explainable AI and why there’s a need to ensure transparency in AI models.