In the rst part of the paper we present some classical actuarial models (the collec- tive and individual risk model) and the probability theory behind. A discussion of pros and cons of each approach leads to an alternative approach where the losses on each policy is modelled by an individual compound Poisson process. We estimate this model using generalized linear models (GLM). In the second part we introduce a framework for incorporating empirical claim severity in ation in the severity models. This gives a method for automatic update of the insurance tari . The framework is a generalization a commonly used method of discounting, modelling and in ating (which we denote the DMI framework). A possible modi cation to the DMI framework is proposed, which makes it applicable to frequency models too. We suggest some methods to compare risk models, especially with respect to their performance over time, are suggested. Finally the methods are applied on a real life motor insurance dataset and we nd that the models under the DMI framework are superior to traditional models without in ation adjustments. The reader is expected to have a background in probability theory and have experience with GLM modelling.
|Educations||MSc in Business Administration and Management Science, (Graduate Programme) Final Thesis|
|Number of pages||80|