Fisher.AggExcess: Difference between revisions
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# How much does the insurer pay before hitting its policy limits? | # How much does the insurer pay before hitting its policy limits? | ||
# How much is the insured responsible for above the policy limits? | # How much is the insured responsible for above the policy limits? | ||
===Key Definitions and Notation=== | |||
Let ''A'' be a random variable for the actual loss experience and <math>E=E[A]</math> be the expected losses. The <span style="color:red;">'''entry ratio'''</span> is the ratio of actual to expected losses, and is written as <math>r=\frac{A}{E}</span>. It may equivalently be defined as the ratio of actual loss ratio to expected loss ratio. | |||
We may view the entry ratio as a random variable. Similarly sized policies having the same entry ratio and coverage should behave similarly. It's common practice to estimate aggregate excess losses based on the entry ratio. | |||
==Pop Quiz Answers== | ==Pop Quiz Answers== |
Revision as of 02:13, 9 April 2020
Reading: Fisher, G. et al, "Individual Risk Study Note," CAS Study Note, Version 3, October 2019. Chapter 3. Section 1
Synopsis: To follow...
Study Tips
...your insights... To follow...
Estimated study time: x mins, or y hrs, or n1-n2 days, or 1 week,... (not including subsequent review time)
BattleTable
Based on past exams, the main things you need to know (in rough order of importance) are:
- fact A...
- fact B...
reference part (a) part (b) part (c) part (d) E (2018.Spring #1) E (2018.Spring #1) E (2018.Spring #1) E (2018.Spring #1) E (2018.Spring #1) E (2018.Spring #1) E (2018.Spring #1) E (2018.Spring #1)
In Plain English!
When modelling an insurance contract you need to know who pays and how much they pay out. Risk sharing at an aggregate level makes it challenging to determine overall coverage responsibilities. A familiar example (to US students at least) of aggregate loss cost coverage is health insurance. An insured has a deductible, a co-payment (another type of deductible), and a maximum annual out of pocket amount (the aggregate limit for your deductible and co-pay).
Let's look at the following example from the text. Suppose we have a Commercial General Liability large deductible policy with a per-occurrence deductible of $100,000 and an aggregate limit on the deductible of $500,000. The claim payment pattern for this policy may look like:
Date | (1) Dollars of loss on claims that are each less than $100k |
(2) Number of claims over $100k |
(3) Dollars of loss on claims over $100k |
(4) Deductible |
(5) Insurance payment |
(6) Insured's cost so far this year |
Q1 | $132,500 | 0 | 0 | $132,500 | 0 | $132,500 |
Q2 | $93,000 | 2 | $350,000 | $293,000 | $150,000 | $425,500 |
Q3 | $105,000 | 0 | 0 | $74,500 | $30,500 | $500,000 |
Q4 | $122,500 | 1 | $150,000 | 0 | $272,500 | $500,000 |
The main thing to do is to keep track of the cumulative deductible amount (6) in relation to the aggregate limit. Claims below the per-occurrence limit are covered by the insured's deductible unless the aggregate deductible is reached. Claims above the per-occurrence limit have the insurer cover the difference between the claim and the per-occurrence deductible. If a claim would cause the aggregate deductible to be exceeded, then the insured is only responsible for the amount up to the aggregate deductible.
Put differently, (4) = min( (1) + (2)*[Per-occurrence deductible] , [Aggregate deductible] - [Prior row (6)]). Then (5) = (1) + (3) - (4).
Here's a practice problem for you to try. Insert Fisher.AggDed1 PDF.
Question: What are three key questions which help price an insurance contract?
- Solution:
- How much does the insured pay before the insurer is responsible?
- How much does the insurer pay before hitting its policy limits?
- How much is the insured responsible for above the policy limits?
Key Definitions and Notation
Let A be a random variable for the actual loss experience and [math]E=E[A][/math] be the expected losses. The entry ratio is the ratio of actual to expected losses, and is written as <math>r=\frac{A}{E}. It may equivalently be defined as the ratio of actual loss ratio to expected loss ratio.
We may view the entry ratio as a random variable. Similarly sized policies having the same entry ratio and coverage should behave similarly. It's common practice to estimate aggregate excess losses based on the entry ratio.