Join us in our upcoming webinar titled: 
Machine learning applications to non-life pricing and underwriting

DATE: 31 January 2024
Time: 09:00 AM (EDT) 15:00 PM (CET)

Predictive modelling in insurance is performed for many years by actuaries with the help of statistical models (e.g. Generalized Linear Models - GLM).

Machine learning (ML) techniques are now more and more popular in the insurance industry and have a lot of applications (pricing, reserving, claims management, underwriting).
In this webinar, we focus on the application of machine learning techniques to non-life pricing and underwriting.

After presenting some useful machine learning techniques for actuaries (focusing on tree-based models: Gradient Boosting Machine, Random Forest and Explainable Boosting Machine), we analyze their potential applications for pricing as well as for other underwriting activities (profitability analysis, competition analysis, portfolio management). We also discuss the concepts of direct and indirect discrimination and fairness in pricing.

Xavier Maréchal | Speaker 
Xavier Maréchal is the CEO and one of the founders of Reacfin, a spin-off of the UCLouvain (Belgium) active in actuarial science, quantitative finance and data science. Xavier is an engineer (applied mathematics), an actuary (fellow of the Institute of Actuaries in Belgium) and holds a Master in Management Science. Xavier is working for 20 years mainly in non-life and heath insurance (pricing, reserving, DFA models) with a specific interest in data science for a few years. Xavier regularly gives training on these topics for Reacfin's clients or for actuarial associations across Europe (and even further).

George Symeonidis | Moderator
George Symeonidis is the Vice-Chair & President-Elect of the International Association of Consulting Actuaries (IACA). He has been a member of the European Commission Aging Working Group since 2009. He is a fully qualified Actuary and a Doctor in Economics of Insurance.
For almost 20 years, George works in the insurance industry and respective regulatory authorities, with 14 years of experience working in management roles. His expertise lies in blending technical and managerial skills, using his solid foundation in mathematics and analytics along and his applied doctorate in economics of insurance and long-term actuarial projection models. George has contributed to significant pension reforms across a range of small and large pension systems. He also trains new generations of actuaries by giving university lectures in relevant courses. His main areas of interest are risk management, pension economics and public finances.