The economic model of insurance is based on mutualization. Roughly speaking, this consists in considering that the good results of the majority of the insureds compensate for the losses linked to the claims of a minority. Mathematically, it is based on the law of large numbers and the central limit theorem. But new risks, on a large scale, such as cyber, climatic or epidemiological risks, can challenge this model. On the one hand, the scale of the associated disasters, which takes us away from the hypotheses of the central limit theorem, and on the other hand, the statistical ignorance of the phenomena considered, which makes their anticipation and coverage complicated. The question of the (mathematical) insurability of these risks is clearly raised.

Organised by the EAA – European Actuarial Academy GmbH.

The web session is open to all interested persons with basic knowledge on property and casualty insurance.

Real-life examples will be presented on R. Attendees are encouraged to install R on their laptop, as the exercises will be done in this programming language (*). One can install R from https://www.r-project.org. As the editor we’ll be using ‘RStudio’, which can be installed from https://www.rstudio.com.

Technical Requirements
Please check with your IT department if your firewall and computer settings support web session participation (the programme Zoom will be used for this online training). Please also make sure that you are joining the web session with a stable internet connection.

The objective of this course is to understand and master the mathematical and statistical tools necessary for the analysis of extreme risks. We will present the main mathematical issues related to the study of these extreme risks and show how mathematical modeling and the relevant use of the (often scarce) data available can be used to build management solutions for this type of risk.

The language of the web session will be English.

Maud THOMAS
Maud Thomas is an assistant professor in Statistics and Actuarial Sciences at Sorbonne Université (formally Université Pierre et Marie, Paris VI) since 2016. She is co-chair of the Actuarial Master Degree of ISUP. She is a board member of the French Institute of Actuaries. Her research topics cover statistic methods and machine learning applied to actuarial sciences and, in particular, extreme value theory and their application to risk analysis and risk management in various sectors (natural disasters, public health, insurance applications…).