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The insurance industry has long relied on modeling as a fundamental means to drive decisions on products, pricing and markets as well as to determine capital requirements and provisions. This content focuses on applying quantitative modeling at the intersection of economics and risk management, by quantifying risk exposures, prioritizing targets for risk transfer, and maximizing alignment between insurance programs and risk reduction. Areas of focus includes bespoke risk assessment models that serve as the basis of tail-risk mitigation programs such as political risk insurance; machine-learning models quantifying the relationship between a community’s insurance protection gap and the speed of its recovery post-extreme weather events; and the development of analytical frameworks and indices to quantify and forecast the granular impact of GDP and inflation metrics on individual P&C lines underlying growth, replacement costs and performance


Dr. Michel Léonard, PhD, CBE
Chief Economist and Data Scientist
Insurance Information Institute

Dr. Michel Léonard, CBE, is the Insurance Information Institute’s Chief Economist and Data Scientist. In this role, he is responsible for providing analysis and insight on industry economics and business performance, as well as other forward-looking, data driven insurance insights.

Michel brings more than twenty years of insurance experience to Triple-I, including senior and leadership positions as Chief Economist for Trade Credit and Political Risk at Aon; Chief Economist at Jardine Lloyd Thompson; Chief Economist and Data Scientist at Alliant; and Chief Data Scientist at MaKro LLC. In these roles, he worked closely with underwriters, brokers and risk managers to model risk exposures for property-casualty and specialty lines such as credit, political risk, business interruption and cyber.

Michel also currently serves as adjunct faculty at New York University’s Economics Department. Previous academic appointments include Adjunct Faculty in NYU’s Center for Data Science and Adjunct Faculty at Columbia University’s Data Science Institute and Statistics Department. He was the recipient of a grant from the Spencer Educational Foundation to develop a course in data analytics for insurance. In these capacities, Michel provides a key link between the Triple-I, its Non-Resident Scholars and academia.

Michel holds a Bachelors of Arts from McGill University, a Masters of Theological Studies from Harvard University, and a Masters of Arts and Doctorate of Philosophy in Political Economy from the University of Virginia, focusing on qualitative and quantitative risk modeling. He is a member of the Insurance Research Council Advisory Board.