Information Matrix

A particular leitmotif of 2010 is productivity — getting more work done with the time and resources available.  Often this is about controlling costs, but in the insurance sector in the European Union it is also about adapting to scarcity of resources: with Solvency II looming, there is strong Europe-wide demand for actuarial expertise.

In an earlier blog I wrote about how stochastic volatility in run-off increases with age. This applies when you exactly know (or think you know) the current and future mortality rates.

Insurers and reinsurers throughout the EU are facing up to the implementation of Solvency II, a radical overhaul of regulatory standards for insurance business.  Recently we explored how much Solvency II demands stochastic models. 

Solvency II is a major overhaul of the reserving rules for insurers throughout the European Union.  An important consideration for annuity writers is how it will relate to longevity trend risk.

In my previous post I illustrated the effects of over-dispersion in population data. Of course, an actuary could quite properly ask: why use ONS data?

In an earlier post we discussed how a survival model was directly equivalent to assuming future lifetime was a random variable.  One consequence of this is that survival models make it quick and simple to simulate a policyholder's future lifetime for the purposes of ICAs and Solvency II.

When investigating risk in an annuity portfolio, a key task is to simulate the future lifetime for each annuitant.  Survival models make this particularly easy, as covered in an earlier posting on simulating lifetimes.

Stochastic projections of future mortality are increasingly used not just to set future best-estimates, but also to inform on stress tests such as for ICAs in the UK.