Countdown to unisex pricing
In just over one year's time, insurers throughout the European Union will be prohibited from using a person's gender to price insurance risks. This court ruling applies to individual contracts, but not (apparently) to group arrangements.
For insurers it is time to review their pricing bases and systems in good time for December 2012. Gender has been used as a risk factor in insurance for a very long time: the oldest copy of the Journal of the Institute of Actuaries on my bookshelf shows that actuaries were separately calculating mortality tables by gender at least as far back as 1871. As a result, it is quite possible that pricing and quotation systems have some subtle oddities, and these will need to be identified and addressed soon.
In our 2004 paper Financial aspects of longevity risk, Gavin Jones and I identified gender as the second strongest risk factor for annuitant longevity after age. Losing such an important variable is obviously a serious challenge for pricing annuity business, although we note that insurers will still be expected to use gender as a factor for reserving and risk management. If the second most important risk factor is being forbidden by law, it is natural to ask: what risk factors might take its place? Again, insurers will have to look now at their pricing and quotation systems and see what changes have to be made to accommodate these new risk factors.
In the case of individual annuities we have not only purchase price (or annuity level) and postcode, but also client-selected options such as escalation rate and the level of spouse's benefits. These latter two variables are examples of self-signalling as to an annuitant's longevity — only someone who expects to live a long time will be worried about preserving the long-term purchasing power of their annuity. Equally, married males tend to live longer than unmarried ones (marital status doesn't appear to affect female longevity as much). Interestingly, annuitants who pick escalating benefits are more likely to pick spouse's benefits as well, and both of these variables are strongly correlated with pension size and geodemographic group.
It is at this point that a statistical model for annuitant mortality becomes an absolute business must. If you were to rely on a series of two-way comparisons, for example, you would risk double-counting some of the effects on longevity. A statistical model avoids this by simultaneously fitting all the desired risk factors and measuring the effect of each in the presence of the others. Where there are important interactions, such as with age, these can be included as well and formally tested. Conveniently, a set of risk factors can be fitted with and without gender present, thus giving you consistent models for both pricing and internal capital management.
Comments