GLM pricing

Hi I am a bit unclear about the use of GLM in pricing. I have sat the previous general insurance paper ST3 before, and understand fairly well about the burning cost/freq & severity pricing. I work in Life and have never seen GLM in practice.

For the traditional methods, you choose data -> divide data into homogenious groups-> adjust data for the usual->project data to ultimate position->then add loadings to give the theoretical office premium.

But the outputs of the GLM are the relativities between different rating groups. It doesn't give us the absolute premium rates to charge for the prospective period. Do we then need to use the traditional methods to work out the risk premium for the base(or benchmark) rating group, and then the RPs for the other rating groups will follow from the relativities from the GLM?

Or is it the case that GLM is only used to check on the appropriateness of the rating structure as derived from the traditional methods?

A slightly different question, I read somewhere in the course note that GLM is mainly used in the commercial line of business. So in the exam, if the question is relating to a personal line of business, should I assume that GLM would not be used and I don't need to make any comments on this?

For example, in assignment question X2.6. This question is asking to suggest appropriate checks on the correctness of the risk premium for household contents. The solution does not mention GLM, but I think if GLM can be used in this situation, there are a range of suitable answers can be generated, e.g. the choice of variables, statistical tests of factor significance, model residual checks, etc.

Thank you in advance for anyone's comments

 

Thanks Duncan. Your answer confirms my understanding, i.e. you do need RP for a base group before you apply the relativities to derive the rest of the rating series. I don't think this is very clear in the note.

It is interesting that you say that there might not actually be an individual policy with a relativity of 1 for all factors. How then can the risk premium for this base group be derived without any data?

I would thought you need to define one of the rating groups you have in your data as the base group. For example, for a motor policy, one may pick a female driver age 40-45 driving a vehicle belonging to group 1 with over 20 years' driving experience as the base group. You can then derive RP based on the data relating to policyholders falling into this group using, say, burning cost approach.