2023 Summer School for Actuaries

The insurance industry is changing – it is particularly affected by (and yet can particularly benefit from) digitalization and automatization. Artificial intelligence makes it possible to improve and accelerate many processes in risk management, marketing and claim settlement. This workshop will provide insight into algorithms for a better prediction and reservation in life and non-life actuarial mathematics.

The course starts with „Generalized Linear Models“ (GLMs), but then introduces more flexible regression models such as „Regression Trees“, „Random Forests“ and „Gradient Boosting“.
In the second half of the course, neural networks and deep learning algorithms are discussed. The aim is to present a kind of „toolbox“ of algorithms, together with various applications in insurance. Exercises and application examples are presented in the programming language «R».

The course is based on the classic: G. James, D. Witten, T. Hastie and R. Tibshirani: An Introduction to Statistical Learning; with Applications in R (2nd edition, 2021) as well as various books in the field of «Actuarial Data Science».


Prof. Dr. Peter Hieber

Peter Hieber has been professor (tenure-track) of Acturial Sciences at the Université de Lausanne (HEC Lausanne, Switzerland) since 2021 and is member of the German and Swiss Association of Actuaries. His research and teaching interests lie particularly in the areas of Life and Pension Insurance Mathematics and Actuarial Data Science. After completing his doctorate in Financial Mathematics at the Technical University of Munich, he habilitated in 2022 at the Department of Acturial Sciences at the University of Ulm (Germany). Together with José Garrido (Montreal) and Sascha Günther, he taught at the Summer School „Machine Learning in Insurance“ of the Swiss Association of Actuaries (saa-iss.ch).

Sascha Günther, PhD Cand.

Sascha Günther is a PhD student at the Department of Actuarial Sciences at the Université de Lausanne (HEC Lausanne, Switzerland) and works as the assistant of Prof. Peter Hieber.
He graduated with a Master’s degree in Mathematics in Business and Economics from the Technical University of Dresden (Germany). His research focuses on Variable Annuities and the application of Machine Learning in Insurance.

Organizing Commitee

Univ.-Prof. DI Dr. Michaela Szölgyenyi

Michaela Szölgyenyi is full-professor for Stochastic Processes at the University of Klagenfurt (AAU). Her research interests focus on numerical methods and analysis of stochastic differential equations and their applications in machine learning, energy markets, and financial- and insurance mathematics.
After completing her doctorate at the Johannes Kepler University Linz, she was a post-doc researcher at the Vienna University of Economics and Business. After that, funded by an AXA Research Fund grant, she was a post-doc researcher at ETH Zurich’s Seminar of Applied Mathematics and associated to the RiskLab Switzerland.
Currently, she is head of the Department of Statistics and coordinator of the FWF doc.funds doctoral school Modeling – Analysis – Optimization.

DI Dr. Jürgen Hartinger

Jürgen Hartinger has been a member of the board at Kärntner Landesversicherung (KLV) since 2014.
After completing his doctorate at TU Graz with the focus on actuarial and financial mathematics, he served as a research scientist at RICAM (ÖAW).
When joining the KLV in 2006, he headed the actuarial office. His duties included the implementation of quantitative methods in enterprise risk management and Solvency II.

Further information

Language of instruction: English

Date and time: May 3rd (9 am) until May 5th (1 pm)

Place: University of Klagenfurt, room Z.1.08 / Z.1.09

Registration fee: € 1.350,- (incl. VAT, catering and Conference Dinner)

Register here!

If you have further questions, please do not hesitate to contact us at via e-mail or phone!