Statistical analysis provides a risk assessment of nuclear safety based on historical data. We use classical probabilistic models from risk theory to analyze data on nuclear power accidents from 1952 to 2011. Findings are that the severities of nuclear power accidents should be modeled with an...

Various stochastic models have been proposed to estimate mortality rates. In this paper we illustrate how machine learning techniques allow us to analyze the quality of such mortality models. In addition, we present how these techniques can be used for differentiating the different causes of...

The chain-ladder method is one of the most popular claims reserving techniques. The aim of this study is to back-test the chain-ladder method. Therefore, we use a stochastic scenario generator which allows us to simulate arbitrarily many upper claims reserving triangles of similar...

The main idea of this paper is to embed a classical actuarial regression model into a neural network architecture. This nesting allows us to learn model structure beyond the classical actuarial regression model if we use as starting point of the neural network calibration exactly the classical...

The Lee-Carter model is a basic approach to forecasting mortality rates of a single population. Although extensions of the Lee-Carter model to forecasting rates for multiple populations have recently been proposed, the structure of these extended models is hard to justify and the models are...

The aim of this project is to analyse high-frequency GPS location data (second per second) of individual car drivers (and trips). We extract feature information about speeds, acceleration, braking and changes of direction from this high-frequency GPS location data. Time series of this feature...

Generalized linear models have the important property of providing unbiased estimates on a portfolio level. This implies that generalized linear models manage to provide accurate prices on a portfolio level. On the other hand, neural networks may provide very accurate prices on an individual...

The paid-incurred chain (PIC) reserving method is a claims reserving method in general insurance that allows to combine claims payments and incurred losses information in a mathematical consistent way. The main criticism on the original Bayesian log-normal PIC model presented in Merz-Wuthrich...

The Munich chain-ladder reserving method was introduced on an axiomatic basis. We analyze these axioms and we define a modified Munich chain-ladder reserving method which is based on an explicit stochastic model. This stochastic model then allows to consider claims prediction and prediction...

We give a rigorous definition of best-estimate reserves for insurance liabilities in a general multiperiod financial market setting. In this general multiperiod financial market setting we describe payoff spaces and optimal dynamic hedging strategies. Based on this optimal dynamic hedging...