Actuarial science is an interdisciplinary research area that focuses on the quantification, assessment and managing of risks and uncertainty arising from insurance and financial industries.
There are many ways of classifying research topics in actuarial science, one of which is based on areas of practice in the actuarial profession, such as
- Life and annuities
- Property and casualty
- Pension and retirement planning
- Finance and investment
- Enterprise risk management
However, as a scientific discipline, actuarial science is more broadly defined and extends beyond traditional boundaries of areas of actuarial practice. Researchers are at the forefront of expanding actuarial knowledge and developing cutting edge analytical and statistical techniques in a wide range of topics, including predictive modeling, asset and liability management, dependency modeling, etc.
Housed in the Department of Mathematics, known for its world-renowned probabilists, the Illinois Actuarial Science Program is a unique place for the coalescence of world-class mathematical education and actuarial research.
Our actuarial faculty members are actively involved in a wide range of research projects, many of which are sponsored by the Society of Actuaries and the Actuarial Foundation. The actuarial science group also leads the Computational Risk Management Research Lab, which provides a channel for faculty and students to work with practitioners and to explore analytics on emerging technical problems from insurance and financial industries.
Klara Buysse – perform and analyse quantitative studies in the domain of risk management (Solvency II regulation (European Economic Capital); Market Consistent Valuation; New Business Valuation; Liability Adequacy Test; IFRS 17). Create an actuarial platform in order to calculate these quantitative studies.
Alfred Chong – optimal insurance and reinsurance designs, premium principles and risk measures, indifference pricing and valuation, stochastic control and backward stochastic differential equations, optimal investment and forward performance preferences.
Daniel Linders – aggregating risks, basket option pricing, pricing of contingent claims combining insurance and financial risks, quantitative aspects of sustainable pension design.
Runhuan Feng – quantitative risk management, applied stochastic processes, equity-linked insurance, asset and liability management, nested stochastic modeling, exotic option pricing.
Shu Li – applied stochastic processes, quantitative risk Management, risk theory.
Ying Wang – optimization problems in insurance and finance, risk measures, quantitative risk management.
Our actuarial science faculty members also collaborate on both educational and research projects with faculty members in Departments of Statistics, Industrial Systems and Enterprise Engineering, and Finance.
Faculty in Related Areas
Alexandra Chronopoulou (ISE) – financial engineering, stochastic modeling and simulation, stochastic systems with long memory, statistical inference for stochastic processes.
Donald W. Davis (Finance) – insurance, insurance risk management, insurer financials.
Georgios Fellouris (Statistics) – sequential hypothesis testing, decision making under communication constraints, educational measurement and cognitive assessment, epidemic detection.
Liming Feng (ISE) – quantitative finance, Stochastic Modeling and Operations Research
Bo Li (statistics) – spatio-temporal modeling, Bayesian hierarchical modeling, copula methods, large data analysis in climatology, atmospheric and environmental science, time series data analysis
Xiaofeng Shao (Statistics) – econometrics, functional data analysis, resampling methods, spatial statistics, time series, applications in atmospheric science, economics, finance and neuroscience
Renming Song (Mathematics) – stochastic analysis, Markov processes, branching processes and potential theory.
Richard Sowers (Mathematics and ISE) – interaction of randomness and dynamics in various applied problems
Alexey G. Stepanov (Statistics) – stochastic processes, financial modeling, actuarial analysis