Modelling and Quantifying Climate and Cyber Risks
Announcement from the SAA organiser:
In the context of climate change, severe weather, climate and water events are becoming more intense and frequent. Similarly, cyber threats’ frequency is increasing. Moreover, in a world which is becoming more populated, complex and interconnected, the impacts of climate and cyber events are growing. Therefore, for risk managers and insurers, an accurate quantitative assessment of corresponding risks is more important than ever for appropriate decision-making processes.
Extreme-value theory offers a proper statistical framework to model impactful events as those described above, so knowing at least the basics in this field is an asset for actuaries. Furthermore, for the applications mentioned above and many others, dependence plays a critical role. For instance, extreme rainfall will have a much bigger impact if it affects a whole catchment rather than just a locality, and so knowing to which extent rainfall can be extreme at several locations at the same is crucial. Thus, the main tools allowing a proper quantification and modelling of dependence should be known by actuaries. Understanding the potential limitations of the employed models as well as the consequences of their misuse in concrete cases is also important.
This Summer School of the Swiss Association of Actuaries 2023 will have a particular focus on climate and cyber risks and the statistical models and tools required for their proper assessment. The lectures will be supplemented by several practical sessions where the participants will apply the learned statistical techniques to concrete climate and cyber datasets using the R programming language.
Throughout the Summer School, the following topics will be considered:
- Risk measurement, reporting and monitoring.
- Extreme-value theory (univariate, multivariate, and spatial).
- Dependence measures, multivariate models and copulas.
- Climate change.
- Climate risk.
- Cyber risk.
Upon completion of that course the participants will:
- Understand and master techniques from a general methodological toolkit.
- Be able to apply them for measuring risk in several fields of quantitative risk management.
- Have a precise idea of the modelling challenges associated with climate and cyber risks.
- Be able to use risk management tools available in the R statistical programming language.
Required prerequisites are an intermediate level knowledge of probability and statistics and basic programming skills.
Valérie Chavez-Demoulin:
Valérie Chavez-Demoulin is full Professor of Statistics at the Faculty of Business and Economics, University of Lausanne. She holds a master’s degree in Mathematics from EPFL and a PhD in Mathematics (specialization in Statistics) from the same institution. She obtained a grant for a postdoctoral position in collaboration with the Swiss Federal Institute for Snow and Avalanche Research in Davos. She has been a research fellow at the Department of Mathematics (D-Math) at ETH, Zurich and later on an Invited Professor at the D-Math, ETH, Zurich for a sabbatical leave. Aside from her research, she has been the quantitative risk manager for a Hedge Fund. Valérie is an elected member of ISI (The International Statistical Institute) and an elected member of the European Regional Committee (ERC) of the Bernoulli Society for Mathematical Statistics and Probability. Her domain of expertise is extreme value theory and in particular, the statistical modeling of univariate or multivariate extremes events. Some of her work concerns risk assessment for non-stationary or covariate-dependent time series, attempting to capture the influence of different types of dependence when estimating risks. She has written more than 50 articles in peer reviewed international journals and is co-author of a book entitled “Risk Revealed: Cautionary Tales, Understanding and Communication”, with Paul Embrechts and Marius Hofert, Cambridge University Press, to appear in 2023.
Erwan Koch:
Erwan Koch is currently Bernoulli Instructor in Statistics at EPFL. He holds a diploma in Engineering from Ecole Centrale de Paris, a master’s degree in Applied Mathematics and Climatology from the same school, as well as a master’s degree in Actuarial Science from Université Paris Dauphine. Erwan Koch’s research has so far mainly focused on spatial extreme-value statistics, spatial risk measures theory, and their applications to extreme weather risks. He is also passionate about the real-time observation/monitoring/prediction of severe weather events and the understanding of their physical drivers, and would like to be increasingly active in these areas. Appropriately combine physics, statistics and actuarial science to improve the forecast of severe weather events and of their impacts is a goal he plans to tackle in the coming years.
Matthias Scherer:
Matthias Scherer is professor for Risk and Insurance at TUM. His research interests comprise the pricing and risk management of insurance contracts and financial derivatives, probability theory, statistics, and efficient numerical tools. He is particularly interested in dependence concepts / copula models and multivariate financial problems. He holds a Diploma in “Wirtschaftsmathematik” from Ulm University and a Master’s degree in “Mathematics” from Syracuse University. In his dissertation, he constructed a multivariate default model. He joined TUM in 2007, where he first coordinated the elite graduate program “Finance and Information Management” and then became a professor for Financial Mathematics in 2010. Prof. Scherer is a member of the board of the DGVFM and member of the advisory councils of FIRM and RiskNet.