Insurers and pension funds must value liabilities using mortality rates that are appropriate for their portfolio. Current practice is to multiply available projections of population mortality with portfolio-specific factors, which are often determined using Generalised Linear Models. Alternatively, one of the well-known stochastic mortality models can directly be applied to portfolio
data to construct portfolio-specific projections without the use of population data. However, this requires a sufficiently large historical dataset for the portfolio, which is often not available.
We overcome this problem by introducing a model to estimate portfolio-specific mortality simultaneously with population mortality. We use a Bayesian framework, which automatically generates the appropriate weighting of the limited statistical information for a given portfolio and the more extensive information that is available for the whole population. It also allows us to incorporate parameter uncertainty when projecting portfolio-specific mortality rates.
We apply our method to a dataset of assured lives in England & Wales. We find that uncertainty in portfolio-specific factors can be
significant, and that confidence intervals for portfolio-specific mortality projections are slightly wider than those resulting from frequentist projections.

Netspar, Network for Studies on Pensions, Aging and Retirement, is een denktank en kennisnetwerk. Netspar is gericht op een goed geïnformeerd pensioendebat.

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