B.2 Large Events & Anomalies

Question 1

Shock loss Examples

Answer 1

Examples of shock losses could be a major auto accident
involving multiple claimants for auto insurance, a total
loss on a large home for homeowners insurance, or a
permanent disability injury of a young worker for workers’
compensation insurance.

Question 2

Why shock loss definition might vary by insurer

Answer 2

One reason is related to the size of the book of business. For example, a $1,000,000 loss would have a very large impact on the profitability of a book of business with $10,000,000 in annual premium, but less of an impact on a book of business with $1,000,000,000 in annual premium.

Question 3

What happens to future losses when you don’t

smooth out shock losses or catastrophe losses

Answer 3

If you don’t adjust for shock losses or catastrophes in your historical loss data, you will overestimate future losses when these events are in your dataset, and underestimate future losses when the events do not occur in your dataset.

Question 4

Ways to adjust data for shock losses

Answer 4

1. Cap losses at basic limits
2. Cap losses and apply an excess loss loading
3. Remove ground-up shock losses and apply a shock loss loading

Question 5

Common choices for a level to cap shock losses

Answer 5

-An arbitrary amount: Such as $1,000,000.
-A percentile of the size of loss distribution: For example,
sort all claims in increasing order by size, and cap all losses at the 99th percentile loss amount.
- Loss as a percent of the insured value: This is most
common in homeowners or commercial property insurance. For example, you might cap all losses at 98% of the insured value, so if a home was insured for $500k, you would cap any losses for that home at $490k.

Question 6

Goal in deciding number of years to use for excess

loss load or non-modeled catastrophe load

Answer 6

Balancing the stability of the long-term average and its

responsiveness to changes.

Question 7

Ways to account for changes in severity for excess loss

loads

Answer 7

1. Using a cap level based on the future policy period cost levels, and trending historical losses to this cost level. You then calculate the ratio of trended excess losses to non-excess trended losses.
2. Indexing the cap level to reflect the changing cost levels, so the cap level varies for each year.

Question 8

Why catastrophe loads are often split into modeled

and non-modeled components

Answer 8

Non-modeled catastrophe losses are frequent enough that a long term average provides enough data for a reliable estimate.

Catastrophe models are used to estimate losses from events like earthquakes or hurricanes, where even a longer term average doesn’t have enough data to provide a reliable estimate.

Question 9

Some non-pricing measures to mitigate catastrophe

exposure for an insurer

Answer 9

Restricting writings in high risk areas, requiring higher

deductibles in high risk areas, and purchasing reinsurance.