Jules Charrington looks at the effect of the Test-Achats gender ruling on rating factors
On 21 December 2012, the Test-Achats ruling came into effect meaning that pricing of insurance products is now bound by the Equality Act. It has long been understood that male and female life expectancies differ and this has been a major factor in pricing annuities. Medically underwritten annuities look at the whole person, their lifestyle and medical conditions included, pricing each client individually without relying on the cross-mortality subsidy used in standard-rate annuities. This would suggest that pricing could be different if gender was an actual marker in the progression of a disease.
To accommodate that, a change would be required in traditional pricing structures, where medical risk factors are 'added' to average life expectancy tables. The question is whether this is really necessary. Current statistics are pointing to the imminent merging of male and female life expectancies, probably as a result of recent cultural shifts, such as the increase in smoking and drinking among women.It may be more productive to look at potential new rating factors as there are many. For example, although we may consider medical advances to lead to increases in life expectancy without detriment, there are treatments that hold their own risks. Methotrexate, a drug widely prescribed for rheumatoid arthritis, is one.
We need to consider the combination of the mortality risks, and this is difficult and complex, especially as it would not be ethical to withhold treatment from one group in order to calculate the different death rates for treated and untreated patients. First, though, there is a definite opportunity to add rating factors by medicines, as the data is easy to obtain, being a question in each condition area on the common quotation form.
Interestingly, it would appear that treatments will also have different effects depending on gender. Sometimes the risks may present in the opposite direction to the disease progression, and research into the potential longevity risk calculation factors allowable with gender-specific pricing resulting is showing where this would potentially be appropriate.
In fact, the rates offered for women should be better than for men, as there are conditions that progress more rapidly towards death in women.
Another area that has been extensively studied is the effect of poverty on mortality. Dr Sheryl Gabram of Emory University School of Medicine and Grady Memorial Hospital in Atlanta, Georgia, conducted a study in 2008. Using men and women from differing socioeconomic groups with breast, prostate and colorectal cancers, she showed a meaningful difference in survival by status.
We already look at wealth as a factor in the pricing of annuity rates, but low socioeconomic status has many other factors that could be used and the data is often available to underwriters and actuaries.
Ideas being considered include the use of the plethora of personal data related to our everyday lives that is out there. Predictive underwriting is already being debated by protection product underwriters, and much of this information could also be useful to annuity underwriters. Potential factors include gym membership, food shopping trends and online computer gaming hours.
We need to keep reviewing the statistics used, as society is no longer the stable, unmoving thing it once was. People move house and change job more often than ever before, rendering the traditional postcode and occupation factors as determinants for socioeconomic status less and less relevant. Recreational drug use is becoming more widespread across all classes and may overtake smoking as a relevant lifestyle risk factor. Gathering information on this, however, is going to be difficult.
Medical advances are continuing apace. No longer are stem cell treatments and bionic body parts the stuff of science fiction. It is an unassailable fact that the world is changing faster than the insurance industry. If we are to maintain acceptable risks on our books, we must adapt in order to survive.