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Faculty Research

Research outcomes produced by our faculty frequently appear in well-known actuarial journals such as Insurance: Mathematics and Economics, Journal of Risk and Insurance, ASTIN Bulletin: The Journal of the International Actuarial Association, Scandinavian Actuarial Journal, North American Actuarial Journal, and Variance. Our diverse faculty team possesses research expertise in a wide range of areas, including but not limited to:

  • CAT risk modeling and insurance-linked securities: Research in catastrophe (CAT) risk modeling and insurance-linked securities (ILS) within actuarial science focuses on developing advanced models and financial instruments to manage and transfer the financial risks associated with catastrophic events. CAT risk modeling involves the use of sophisticated mathematical and statistical techniques to predict the frequency, severity, and financial impact of catastrophic events such as hurricanes, earthquakes, floods, and other large-scale disasters. Insurance-linked securities are financial instruments that allow insurers and investors to transfer and manage CAT risks. Research in this area focuses on the development, pricing, and risk assessment of ILS.

  • Risk measurement and allocation: This area of study involves developing statistical measures and models to assess the potential impacts of uncertain future events, determining the optimal/sensible allocation of capital, and ensuring regulatory compliance. The insights gained from this research help organizations enhance their risk management strategies, improve financial stability, and make informed decisions that safeguard their long-term viability.

  • Dependence modeling: Dependence modeling research in actuarial science focuses on understanding and quantifying the relationships between different risk factors and events. This research area is crucial because risks in insurance and finance are often interconnected rather than isolated. Dependence modeling uses advanced statistical and mathematical techniques, such as copulas, multivariate distributions, and correlation structures, to capture the complex dependencies between variables.

  • Mortality modeling: Mortality modeling research in actuarial science focuses on developing and refining models that predict mortality rates and trends. This area of study is crucial for accurately assessing life expectancy, setting insurance premiums, and managing pension plans. Researchers in this field use a variety of statistical and mathematical techniques to analyze historical data and forecast future mortality rates.