AI in Insurance: Practical Applications, Performance, and Trust

This webinar explores how artificial intelligence is being applied across the insurance value chain to enhance actuarial performance, operational efficiency, and decision-making—while maintaining trust and professionalism. Drawing on real-world examples from a leading health insurer and a global reinsurer, the session highlights practical AI use cases in pricing, underwriting, claims, risk assessment, portfolio management, and health management. It also addresses the critical role of actuaries in governing AI responsibly, managing bias and risk, and ensuring transparency and ethical use. Together, these perspectives demonstrate how trusted, scalable AI can drive meaningful impact in insurance when actuaries remain firmly in the loop.

Increasing Actuarial Performance while building trust with AI

Increasing Actuarial Performance While Building Trust with AI highlights how artificial intelligence—one of the SOA’s top three strategic initiatives for 2026—can enhance actuarial work when applied responsibly. The presentation emphasizes hat actuaries have a long-standing reputation for professionalism and judgment, providing a strong foundation for building trust with AI. It walks through key strategies for using AI effectively, including understanding AI risks, keeping the actuary firmly in the loop, and identifying appropriate use cases. The session also addresses professionalism, bias, and the critical role of education in ensuring AI supports sound, ethical, and transparent decision-making. Ultimately, the presentation positions actuaries as uniquely equipped to lead in high-stakes AI environments where trust truly matters.

AI Application in Ping An Health Insurance

During the presentation, the speaker will outline how AI is being applied across the health insurance value chain at Ping An Health Insurance (PAH) to support the “health insurance + health & wellness services” strategy. It demonstrates AI-enabled use cases in marketing, pricing, underwriting, claims settlement, and end-to-end health management. Through AI agents, multi-modal large models, and integrated data platforms, PAH enhances operational efficiency, personalization, risk management, and customer experience, shifting from passive claims handling to proactive health and risk management while enabling large-scale, personalized health services.

The AI Developments from A Reinsurers's Perspective

As risks grow more complex, actuarial sciences must improve risk assessment and protection, but data access remains a challenge. SCOR's AI Assistant, a generative AI tool, efficiently extracts and structures data from diverse documents with high accuracy, supporting key insurance workflows. This innovation enhances actuarial practices by enabling more precise assessments and better portfolio management, demonstrating the value of scalable AI in insurance and paving the way for future advancements with autonomous AI support.