  This article presents a stochastic framework to quantify the biometric risk
of an insurance portfolio in solvency regimes such as Solvency II or the Swiss
Solvency Test (SST). The main difficulty in this context constitutes in the
proper representation of long term risks in the profit-loss distribution over a
one year horizon. This will be resolved by using least-squares Monte Carlo
methods to quantify the impact of new experience on the annual re-valuation of
the portfolio. Therefore our stochastic model can be seen as an example for an
internal model, as allowed under Solvency II or the SST. Since our model does
not rely upon nested simulations it is computationally fast and easy to
implement.
