Unnatural Selection -Chapter 20 & Sept 2019 Paper A Q8(iv)

Hi - thanks for all the interesting questions!

I agree that the definition of 'selection' is not straightforward, and there are lots of different ways in which that term can be used - as indicated in the course notes.

It might be easiest to think about it as the division of 'lives' into groups that exhibit differences in key risk characteristics, such as mortality & morbidity.

 

The rating factors that the insurer chooses will relate to class selection. Class selection means that the differences in risk characteristic (eg mortality) arise due to something that permanently impacts experience. For example, for a term assurance contract, one rating factor would be age, because you would always expect mortality to vary by age. So the insurer will consider class selection effects when choosing appropriate rating factors. The insurer may also use underwriting to gain more information about the individual in order to assess their risk level - this would be an example of temporary initial selection (see next question).

 

Temporary initial selection means that the differences in risk characteristic reflect the amount of time that has passed since an event. A good example of such an event would be underwriting. An individual who was underwritten six months ago would be expected to have a lighter mortality / morbidity than an identical individual who was underwritten three years ago.

Individuals choosing to purchase insurance would be expected to have a different level of mortality / morbidity risk than the general population for many reasons, for example:

• might be more affluent than average, hence able to afford insurance - class selection
• might be more likely to be married and have dependants - class selection
• might undergo underwriting - temporary initial selection
• might be attempting to anti-select against the insurer - adverse selection

 

I think what this is getting at is that if we just say that regions X and Y have different levels of mortality, we aren't properly describing the underlying selection processes. Person X doesn't have a higher level of mortality just because they live in region X; moving between the regions wouldn't make any difference per se. What we are actually seeing is the impact of different mixes of occupation or housing quality etc between those regions, and that is what is driving the differences.

 

Probably partly because in September 2019 we didn't have the same pandemic experience that we now have! Back then, time selection fundamentally referred to gradual mortality / morbidity improvements over calendar time due to things such as medical advances etc, as you mention - and that would not have been a concern for term assurance business.

There aren't many marks available for this question part, so we should focus on key relevant types of selection. Bear in mind that the line above that question part refers to the team raising 'concerns around selection', so we need to think about what might generate such concerns. The pandemic is not something that the insurer has any control over, so it would not necessarily generate the same level of internal 'concern' as other selective effects might. For example, it should be concerned if there is a high level of adverse selection from policyholders (perhaps indicating that its underwriting process is not good enough), or perhaps the temporary initial selection effect from underwriting is not in line with what it was expecting (similarly a need to review its underwriting process). Perhaps it isn't understanding the risk differences correctly (spurious selection), or perhaps it needs to reconsider its target market (class selection).

 

Yes - it is just something that acts to cause a difference in one of the risk characteristics.

 

CP1 also covers morbidity selection, which is very similar to mortality. And yes, the concept can relate to other examples too, as you indicate.

 

Yes it is a bit messy isn't it!

It's reasonably easy to see that climate and other aspects of geography such as living on a tectonic plate faultline / at the base of an active volcano could have a direct causal impact on mortality rates.

Regions will have lots of other factors that differ between them which directly cause mortality / morbidity differences, such as the number of hospitals etc.

So I think what the Core Reading and the question that you reference are getting at is that it's rather lazy just to say 'region X has greater mortality than region X' and leave it at that. Identifying and analysing the causal factors that generate those differences would lead to a more accurate grasp of the actual selective processes.