Not only upcoming regulation plays a role - fairness of treatment lies at the core of insurance in the first place. In the age of Machine Learning and Artificial Intelligence, analysis and, potentially, remedy, of direct and indirect discrimination in insurance decision making - most notably pricing - has become a more pronounced problem due to increased public interest. But in stark contrast to, say, chatbots or personal assistance systems, there are structural aspects preventing companies from creating and maintaining products that are comprehensively fair in all the relevant facets.

Participants are expected to have knowledge about Actuarial Basics such as pricing models. Basic knowledge about the usage and potential of Machine Learning / Artificial Intelligence in the insurance context might prove helpful.

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

The purpose of this session is to introduce relevant concepts of pricing and discrimination therein as well as an overview of discrimination-reducing concepts from the literature. We will then draft some toy models, including generation of synthetic data with particular properties. Afterward, we will review limits and possibilities toward enabling (some kind of) less-discriminatory pricing.

Kindly take note: This session is intended as information seminar; no legal counselling will take place.

The language of the web session will be English.

Prof Dr Fabian Transchel
Fabian is a professor for Data Science at the Harz University of Applied Sciences, Department AI, where his research focus is Insurance and Finance, most notably motor telematics and pricing. He is active in the development of the new Actuarial Data Science subjects at the German Actuarial Association (DAV) and a lecturer for the German Actuarial Academy (DAA) and the European Actuarial Academy (EAA).