Data and decisions

The Data and Decisions theme delivers cutting-edge solutions to complex mathematical and computational challenges in actuarial science and finance, leveraging expertise in optimisation, machine learning, probability and statistics. We work closely with industry partners to translate advanced research into impactful, data-driven decision-making tools and technologies.

General insurance

General insurance provides financial protection against a wide range of risks, including property, liability, and emerging threats. Our research tackles key challenges in this domain, such as optimising reinsurance strategies, ratemaking and reserving, as well as managing capital and solvency under uncertainty.

At its core, our work is driven by the theme of risk in insurance, with a growing emphasis on climate-related risks and cyber risk. We develop and apply advanced statistical and machine learning techniques, including deep learning and spatial-temporal modelling, to capture complex dependencies and deliver robust, data-driven solutions for the insurance industry.

Life insurance and pensions

Life insurance and pensions offer financial security to individuals and their dependents. Our research concerns both design and management, and the many financial aspects inherent in them. More recently, the effect of climate change and the transition to Net Zero is of research interest to us.

We have world-leading expertise on pension scheme design and management, for both private and state systems. This include automatic balance mechanisms, mixed pension scheme, redistribution, as well as the impact of climate change on retirement.

Additionally, our researchers have undertaken work for the Swedish Social Insurance Agency and the Spanish Ministry of Labour and Immigration.

Mortality modelling

Our world-leading mortality modelling group is led by Andrew Cairns. He developed the internationally renowned Cairns-Blake-Dowd family of stochastic mortality models. These models are used extensively in the life and pensions industry, both in the UK and internationally.

The team has developed the Longevity Index for England (LIFE) and the associated open-access LIFE App, to assess of socio-economic differences in mortality, longevity and morbidity.

More recent socio-economic modelling extends to include cause-of-death. This data shows that mortality inequalities are very wide for some causes and almost absent for others. These data give insight into the underlying drivers of mortality and mortality inequalities, such as smoking prevalence.

Financial mathematics and engineering

Financial mathematics concerns the modelling and analysis of financial markets and instruments using mathematical tools. Applications of our research are in pricing and risk management of energy derivatives, and complex options, such as real options. Theoretical research is also done in the analysis of stochastic systems and their applications.

Financial engineering focuses on the design and building of financial products and systems. The design of efficient algorithms for high-dimensional nonlinear dynamic models, underpinned by deep learning, is one focus. Another is time-inconsistent control and its applications in behavioural finance and economics.

Epidemiology

Epidemiology is the study of how diseases and health-related conditions spread and affect populations. Endemic infection modelling, using stochastic models, is one area of interest. Another is the effects of population heterogeneities, with particular focus on veterinary applications, including Salmonella in dairy cattle and pigs. Bayesian statistical inference in the context of infectious disease models is another area of interest.