ch3 doubts

  1. One of the advantage of RY aggregation is that RY is appropriate when there’s a change in social or legal climate that causes severity to be correlated with reported date more than accident date. [Fall 2016_Q16_part(b) ]. A similar advantage is given for AY aggregation too. Please explain.
  2. How is case reserving strength a consideration in determining data groupings for analysis?
  3. Why reinsurers and self-insurers generally use PY/UY aggregation? Any intuitive explanation?


Thanks

Keshav

Comments

  • edited January 2021
    1. The answer in the examiner's report is unclear. It does seem like they are listing the same advantage for both report year and accident year aggregation methods. For the AY aggregation method, they should have specified that this is an advantage only if the social/legal change is tied to accident date. That is not typically considered an advantage of AY data however. I probably would not have included that as an advantage of AY data aggregation if I were answering the question.
    2. Case reserving strength might be a consideration in determining data groupings because of homogeneity considerations. If we knew that coverage A has a case reserve strength of 80% and coverage B has a case reserve strength of 90%, but coverage B is growing more rapidly than coverage A, it might not be a good idea to group these 2 coverages for reserving purposes.
    3. SELF-INSURERS: They only have 1 policy, their own, and it just makes more sense to keep track of the data by policy. Then when that policy "expires", they just start fresh and begin collecting data on the new policy. Everything is simple because it's kept separate. That doesn't work as well for something auto insurance which is (almost) always aggregated by AY. REINSURERS: Part of it is probably just accepted industry practice but also because attachment points (that's when the reinsurer's liability begins) are very important. A reinsurer may write policies at a certain attachment point for a given year. Then the following year, they may change this attachment point. It's cleaner if all policies with the same attachment point are grouped together into the same PY rows in a triangle. (If AY aggregation was used, then rows in the triangle would have claims at a mixture of attachment points.)
    1. I did not exactly understand the increased correlation with RY when social/legal climate changes in the first place (and thus, why RY aggregation is advantageous then?), let alone AY for the time being.
    2. So, if the growth of both coverage A and B would had been stable, we might had at least considered combining their data based on similar case reserving strengths?
  • edited January 2021
    1. Oh ok, I see. An example where RY aggregation is good because of a change in legal climate is this: Suppose a jurisdiction passes a law on Jan 1 that requires auto insurers to increase medical benefits by 10% on all newly reported claims, regardless of when the accident occurred. RY aggregation would ensure that all claims at the higher benefit level are grouped together in the triangle from that point forward. (And all claims reported before Jan 1 are grouped together in prior rows of the triangle.) This would not be true for AY aggregation because claims at different benefit levels may then be mixed together.
    2. Yes, if the growth had been the same for coverage A and B you might consider grouping them. This is discussed in more detail in chapter 7 of Friedland in the section on changing mix of business. There is an example and video explaining this when you get to that chapter.


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