CIA.MfAD: Sections 6-10

Section 6: Relevant Statistical Concepts

This section is a very brief discussion of statistics as it applies to P&C insurance. It covers:

• when a normal distribution works well (high volume of risks, limited correlation between risks)
• when a normal distribution DOESN'T work well (low volume of risks, high correlation between risks.)

That's about it.

Section 7: Stochastic Techniques

For Section 7, you need to know what a stochastic technique is (produces a loss distribution using simulation) and where it works well (with skewed loss distributions such as catastrophe insurance.)

Section 8: Three P&C Product Examples

• The examples are: TPL (third party liability), GL (general liability), and catastrophe insurance.
• They are compared according to the criteria of skewness, CV (coefficient of variation), and length of settlement pattern.
• The PURPOSE of introducing these examples is that they are used in Section 10 to compare various methods for calculating risk margins.
• Here's a little secret: None of the methods work very well on ANY of these examples!

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Section 9: Quantile Approaches (Stochastic)

This feels like it should be an important section, but it's been only very lightly tested. I found it interesting, but you probably shouldn't spend too much time on it. You definitely need to know the names of the 3 quantile methods:

multiples of SD (standard deviation)

VaR (Value at Risk), also called the percentile method or confidence interval method

TVaR (Tail Value at Risk), also called CTE (Conditional Tail Expectation)

It's less likely you'd be asked for any details of these methods OR to evaluate how well they perform OR what to do in the case of an extreme event like an earthquake. These points are all covered in the Level 3 BattleCards anyway, if you're interested.

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Section 10: Comparison of Risk Margin Methods

This section is quite interesting, but it's probably too detailed to be asked. It compares the 3 methods from Section 9 on both a quantitative & qualitative basis. Surprisingly, none perform particularly well. This highlights the inherent difficulty in assessing risk, and, by implication, setting an appropriate risk margin.

It would be nice to have a general method for coming up with risk margins that satisfies the traits discussed in Section 3; in practice, however, many situations have unique characteristics that must be take into account, above and beyond any generalized methodology.