Faculty of Actuarial Science and Insurance Research Seminars - George Tzougas

Abstract
This talk presents a regression framework for multivariate claim frequencies that accounts for overdispersion arising from unobserved heterogeneity and for dependencies between claim types that can be positive or negative. The focus is on multivariate count models in which Poisson components are linked through continuous latent effects with continuous marginals combined via copulas. This structure allows flexible dependence modelling and remains identifiable under mild regularity conditions. Estimation is carried out using a Monte Carlo Expectation–Maximization algorithm, which treats the latent variables as missing data and enables maximum likelihood inference when the joint distribution is intractable. A case study on the Wisconsin Local Government Property Insurance Fund shows that the proposed approach captures dependence patterns well and improves predictive performance compared to existing benchmarks. Diagnostic analyses further support the adequacy of the fit. The results highlight the importance of allowing both dispersion and dependen

Bio - George Tzougas
George Tzougas is an Associate Professor in the Department of Actuarial Mathematics and Statistics at Heriot-Watt University in Edinburgh, UK, and serves as the Academic Director of the Scottish Financial Risk Academy (SFRA). His research lies at the intersection of applied and computational statistics and statistical machine learning, with applications in insurance and, more recently, in computational finance. His work has been published in leading journals, including the Journal of the Royal Statistical Society (Series A & C), Journal of Computational and Graphical Statistics, Insurance: Mathematics and Economics, North American Actuarial Journal, ASTIN Bulletin, Scandinavian Actuarial Journal, Annals of Actuarial Science, European Actuarial Journal and Statistical Inference for Stochastic Processes among others. George’s recent research focuses on developing statistical machine learning models to evaluate the impact of climate hazards on non-life insurance portfolios and to advance the study of green finance. As Academic Director of the SFRA, he collaborates closely with industry partners to promote expertise in climate-related risk and has organized numerous events at Panmure House in Edinburgh. In 2026, he will serve as lead organizer of the international workshop “AI in Risk Assessment and Mitigation”, to be held in Edinburgh. The event aims to foster collaboration between academics and practitioners on how AI, statistics, and related methods can be applied to understand and manage societal risks, particularly those arising from climate change. He has received several distinctions for his research, including two Best Paper Awards from the Institute and Faculty of Actuaries (IFoA, 2021) and the SCOR Actuarial Award (2023).

Faculty Events | Website | View More Events

Contact the organizers