Why adjust for one-time changes in ratemaking?
So data is most representative of future policy period being priced.
Types of effects of one-time changes
Direct – direct and obvious impacts to premiums, losses, or expenses, all else being equal
Indirect – due to changes in human behavior
Why direct effects of coverage INCREASES are difficult to quantify
Historical losses may have been capped a the lower level of coverage (or coverage may not have existed)
3 ways to calculate direct effect of coverage change on LOSSES
2 methods to on-level premiums
Parallelogram method adv/disadv
A: Quicker to calculate than extension of exposures D: Assumes policies are written evenly over period. Aggregate on-level factors produced may not be appropriate for class level ratemaking
Ways to correct for uneven writings in parallelogram method
2. Aggregate historical data by rate level
Parallelogram assumption for losses
Losses are uniformly distributed over the period being used
Two ways a benefit change can apply to losses