We analyse four stochastic claims reserving methods in terms of their capability to estimate reserve risk and how successful they are at predicting distributions and VaRs of claim developments in particular. Both actual data and hypothetical claim triangles support our results. The...

Fundamental stock analysts covering the insurance industry may be overly influenced by infrequent large scale catastrophes, such as unusually strong hurricanes. It is important for these analysts to be able to put catastrophes in financial perspective in order to set an appropriate fair value on...

The pricing of life insurance products depends critically on the ability to model and forecast three core stochastic drivers. Firstly, the ability to accurately forecast expected mortality rates by age group for a given population in order to construct estimates of the life expectancy required...

We show that classical insurance models based on some compound distributions can well predict information leakage by cyber incidents with reducing the computational cost thanks to the model’s simplicity. We use the negative binomial distribution, a renewal process and a Hawkes process as the...

Stochastic mortality models seek to forecast future mortality rates; thus, it is apparent that the objective variable should be the mortality rate expressed in the original scale. However, the performance of stochastic mortality models-in terms, that is, of their goodness-of-fit and prediction...