The rapidly progressing digitalization leads to enormous amounts of data which can be used to enhance the core processes of the insurance industry. An important precondition to derive the right decisions from the data is to increase the knowledge on statistical methods.

Organised by the EAA - European Actuarial Academy GmbH in cooperation with the Österreichische Förderungsgesellschaft der Versicherungsmathematik GmbH (ÖFdV GmbH).

Participants should have basic previous knowledge in stochastics and probability theory. No specific statistical knowledge is required.

During this seminar, you will not need a laptop.

Dr Fabian Winter
Fabian joined the Munich Re Group in 2009 and is responsible for analytics within Munich Health globally. Within this role, he has led a significant number of analytics projects and supported primary insurance companies in the strategical and operational tasks all over the world. He holds a PhD in Politics and Statistics from the University of Heidelberg, Germany. This Doctoral Thesis was performed after he obtained a Diploma in Statistics from the Institute for Statistics in Munich, Germany.

Levent Alkaya
Levent Alkaya joined Munich Re in March 2015 and is working as a data scientist in the reinsurance development department which consults Munich Re’s business units by developing analytical solutions across the whole Reinsurance Group. Since then he has participated in a significant number of data analytics projects. He holds a Master of Science in Statistics from the Ludwig Maximilian University of Munich, Germany.

Andreas Bayerstadler
Andreas Bayerstadler joined Munich Re in 2010 and is working as a statistical consultant in Munich Health. He is part of the Business Analytics team which develops analytical solutions and strategies for primary insurance companies. He has been involved in a significant number of client projects. He holds a Diploma in Statistics from the Ludwig-Maximilians-University in Munich, Germany. Currently, he is working on his PhD thesis on modern statistical methods in worldwide health insurance.