We introduce an additive stochastic mortality model which allows joint
modelling and forecasting of underlying death causes. Parameter families for
mortality trends can be chosen freely. As model settings become high
dimensional, Markov chain Monte Carlo (MCMC) is used for parameter estimation.
We then link our proposed model to an extended version of the credit risk model
CreditRisk+. This allows exact risk aggregation via an efficient numerically
stable Panjer recursion algorithm and provides numerous applications in credit,
life insurance and annuity portfolios to derive P\&L distributions.
Furthermore, the model allows exact (without Monte Carlo simulation error)
calculation of risk measures and their sensitivities with respect to model
parameters for P\&L distributions such as value-at-risk and expected shortfall.
Numerous examples, including an application to partial internal models under
Solvency II, using Austrian and Australian data are shown.Comment: 34 pages, 5 figure
