Rethinking Exposures - Considerations for Modern, Emerging and Complex Risks
A clearly defined exposure base is essential for actuarial modeling, and its definition has become increasingly complex as risk becomes more complex. Telematics and cyber insurance are examples of this added complexity, and we expect this complexity to grow as coverage becomes more complex. Should a telematics exposure be based on trip count or miles driven? When should an exposure base also be a variable in your predictive model? What about composite exposure bases? How can a more complex exposure base improve your ability to react to environmental or societal changes? We will discuss these questions and more in this session.
Learn more about the speakers
Max Martinelli
Max Martinelli is a Managing Director in the Insurance and Actuarial Advisory Services practice of EY, where he focuses on P&C pricing, actuarial data science, applied AI and external rating. He has over a decade of experience in actuarial and data science roles, primarily in predictive modeling for personal and commercial lines, and a background in machine learning and computational mathematics. A dedicated collaborator with the Casualty Actuarial Society, he co-designed and led the CAS AI Fast Track bootcamp and co-hosts Almost Nowhere, the CAS Institute podcast exploring AI and data science in insurance.
