Machine Learning (ML) methods are also becoming more and more important in the insurance industry. But ML is a broad field or even a science in its own right. It is therefore not easy for those interested to know where to start. For this web session series, we have selected three interesting and important facets to shed more light on.

Organised by the EAA - European Actuarial Academy GmbH.

Our web sessions are addressed to interested persons who would like to get a first overview and a selective insight into Machine Learning. We do not require any specific previous knowledge and start from a very basic level.  The web sessions are thematically related. However, they do not build on each other and each can be heard separately.

Technical requirements
Please check with your IT department if your firewall and computer settings support web session participation (the programme GotoTraining/GotoWebinar is used for the web session). Please also make sure that you are joining the web session with a stable internet connection. 

In the first web session “Actuarial Data Science: Innovative Products utilizing AI and Machine Learning opportunities” (Dr Fabian Transchel) we give an overview why and how the new methods and paradigms subsumed as "Actuarial Data Science" will change the business landscape in the insurance industry - and what are the caveats specific to these particular applications. Join in to learn
• the close connection between new methods and new data sources and why just one of them is not enough to turn a profit
• a critical look at (probably?) overhyped concepts and their realistic potential
• why agile development is not a requirement of Data Science, but a consequence

The second web session deals with “Artificial Neural Networks Basics” (Dr Axel Kaiser & Dr Stefan Nörtemann). We would like to give an elementary introduction to the idea, the mathematics and the implementation of artificial neural networks. In addition to the theoretical foundations, we implement artificial neural networks in R and Python as examples and apply them to concrete problems.

In the third web session “Actuarial Data Science: A closer look at Feature Generation from Unstructured Data” (Dr Fabian Transchel) we give an overview of the field of Data Engineering for model development. The selective focus of this particular occasion is to broaden the practitioner's understanding of working with unstructured and contextual data sets from both a programmatic and pragmatic perspective.

Dr Axel Kaiser
is Mathematician & actuary (DAV) at SIGNAL IDUNA Insurance Group in Hamburg, Germany, where he is in charge of ALM and Solvency II in health business. He has been using Computer Science for many years and is a member of DAV’s Actuarial Data Science committee.

Dr Stefan Nörtemann
Mathematician & actuary (DAV) at msg life central europe gmbh in Cologne, Germany. He leads various projects in the context of Risk Management and Insurance Analytics. In addition, he is a lecturer at German Actuarial Academy (DAA) for Computer Science and for Actuarial Data Science and chair of the section Actuarial Data Science of DAV.

Dr Fabian Transchel
is Professor for Data Science at the Harz University of Applied Sciences, Department AI, where his research focus is Insurance and Finance. 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).