These notes are strongly motivated by practitioners who have been seeking for advise in stochastic claims reserving modeling under Solvency 2 and under the Swiss Solvency Test. There have been tremendous developments since the publication of our first book Stochastic Claims Reserving Methods in...

The aim of this contribution is to revisit, clarify and complete the picture of uncertainty estimates in the chain-ladder (CL) claims reserving method. Therefore, we consider the conditional mean square error of prediction (MSEP) of the total prediction uncertainty (using Mack's formula) and the...

Popular yield curve models include affine term structure models. These models are usually based on a fixed set of parameters which is calibrated to the actual financial market conditions. Under changing market conditions also parametrization changes. We discuss how parameters need to be updated...

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...

Machine learning techniques make it feasible to calculate claims reserves on individual claims data. This paper illustrates how these techniques can be used by providing an explicit example in individual claims reserving