In this course you study statistical techniques that can be applied in non-life insurance. We explore Generalized Linear Models for determining insurance prices. Also, we take a look at IBNR models for predicting future payments on claims regarding events that have occurred in the past but are not yet (fully) known to the insurer. Another topic is credibility theory to predict future claims. Apart from the theory, we study and practice the implementation of the techniques using the programming language R.

The course will cover the basics of information theory, including information asymmetry, moral hazard and adverse selection and the basics of behavioural insurance and finance.

This course provides an in-depth treatment of the principles of (quantitative) risk management for insurers and pensions. The course focuses first on the joint measurement, modelling and allocation of financial and insurance risks. Next, the course treats the design of risk mitigation strategies and of asset allocation strategies from a long-term perspective.

In this course you learn the basic principles of asset pricing and risk mitigation on a market-consistent basis. The course provides an introduction to mathematical techniques which can be used in complete markets such as those for equity and interest derivatives, but it also considers incomplete markets.

In this course, elements of probability theory, stochastic processes and stochastic calculus are discussed to the extent that it is relevant in the analysis of financial derivatives. The emphasis is on the mathematical concepts and techniques, and to a lesser extent on their application in pricing and hedging derivatives.

In this hands-on seminar you will learn about the practical implementation of an Asset Liability Management (ALM) study focusing on the match between investment policies and liabilities. The cases involve theoretical aspects such as asset dynamics and liability modelling, numerical aspects like Monte Carlo simulation as well as practical communication and team working skills.

The Master’s thesis is the final requirement for your graduation. It is your chance to dive deep into a topic that you are enthusiastic about. A professor in your field of choice (track) will supervise and support you in writing your thesis. After a successful defence of your thesis and completion of the courses, you will be awarded the title Master of Science (MSc).