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.
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Learn more about the speakers
Thomas Holmes is currently the Head of US Actuarial Data Science at Akur8. Before Akur8, he worked for several years at Allstate, spending time as an analyst for commercial auto and then as a lead modeler on Allstate’s property modeling team. During his time as an actuary, he has worked with GLMs, GLMnets, and GBMs. He received his Fellowship from the Casualty Actuarial Society in 2019.
Max Martinelli joined Akur8 as an Actuarial Data Scientist in 2023. He works with clients to ensure they get the most out of Akur8's transparent machine learning software. This ranges from actuarial modeling advice to collaborating on how an insurer can get the most out of their data. Before this, Max worked in various actuarial and data science roles at Allstate for nearly 8 years. He has worked on auto, property and specialty lines with a broad scope of projects. These ranged from traditional actuarial indications to price optimization to cutting-edge high-fidelity telematics models. His work spanned from production grade models to rapid research models to further Allstate's pricing sophistication with extensive use of GLMs, GLMnets, GBMs and Bayesian GLMs.
