A.7 Insurer Performance & Profit Flashcards
Fundamental Insurance Equation
Standard Economic Formula:
Price = Cost + Profit
Fundamental Insurance Equation:
Premium = (Losses + LAE + UW Expenses) + UW Profit
Total Profit for an Insurer
Total Profit = UW Profit + Net Investment Income
Ultimate Loss definition and components
Ultimate Loss: The final amount required to close and settle a claim or group of claims.
Ultimate losses have 3 components:
- Reported Losses, which equals paid losses + case reserves.
- Incurred But Not Reported (IBNR) Reserve: This is the amount estimated to ultimately settle claims that have occurred, but have not yet been reported to the insurer.
- Incurred But Not Enough Reported (IBNER) Reserve: This is an estimate of the development of the Reported Losses for claims that have been reported to the insurer.
Reason that fundamental insurance equation should
be balanced at both aggregate and individual levels
Aggregate balance ensures that the insurer stands to make its overall target UW profit.
Individual balance ensures that rates are fair for different customers. For example, a higher risk insured should pay higher premiums than a lower risk insured.
Three main objectives in aggregating data by time
- Accurately matching premiums and exposures to losses.
- Using the most recent data available.
- Minimizing the cost of data collection and retrieval.
Calendar year definition with advantages and
disadvantages
This method considers all policies and loss transactions during the year. The main advantage of using calendar year data is that there is no development, so results are final immediately after the year is over. Calendar year data is also readily available since it is required for financial
reporting. The main disadvantage of using calendar year data is that it provides a poor match in timing between premiums/exposures and losses.
Calendar/Accident year definition with advantages
and disadvantages
This method combines calendar year premium and exposure data with accident year claims data. This is the most commonly used method in ratemaking and reserving analyses. This method presents a better match in timing of premiums/exposures and losses than calendar year. However, future development must be estimated since accident year losses can develop over time.
Using accident year loss data is also preferable when you want to isolate major claim events such as catastrophes.
Accident year definition with advantages and
disadvantages
This is a slight modification of calendar/accident year, with the only difference being that premium audits taking place after the calendar year is over are incorporated into the premium and exposure data. As a result, the premium and exposure data is subject to development and must be estimated in addition to the loss data. However, it does provide a truer match of premiums/exposures to losses than calendar/accident year.
Policy year definition with advantages and
disadvantages
This method considers all premiums, exposures, and losses from policies with effective dates during the year. The main advantage of using policy year data is that it provides a true match between premiums/exposures and losses. The main
disadvantage is that policy year data takes longer to develop than accident year data. Reinsurers also use Underwriting Year, which is similar to policy year but it is based on the year that the reinsurance policy became effective.
Using policy year data is also preferable when you want to isolate policy or underwriting changes, such as a change in policy limits or deductibles being written.
Report year definition with advantages and
disadvantages
This method groups loss data based on the date that claims are reported. This is used primarily for claims-made policies, which provide coverage based on the date the claim is reported instead of the accident date. An advantage of report year data is that the number of claims is known at the end
of the year. A disadvantage is that report year is useful in estimating IBNER, but not as useful in estimating IBNR.
Using report year data is also preferable when you want to isolate changes in claims practices, such as case reserving adequacy.
4 things to review for dataset reliability
-Consistency with financial statement data: How close is the match?
-Consistency with data from prior analyses: How close is the match?
-Data reasonableness: Do values make sense?
-Data definitions: Do you know what each data field
represents?
Types of external data sources
- Statistical plans: These plans aggregate data across companies and produce analyses or rates that companies can use. Examples are NCCI and ISO.
- Other aggregated industry data: An example is the Fast Track Monitoring system, which creates reports on industry level loss trends.
- Competitor rate filings & manuals: These may be obtained from public records at state insurance departments. These can be used by an insurer in setting their own rates.
- Other 3rd party data: This might include economic or geo-demographic data. For example, Consumer Price Indices (CPIs) for things like medical costs can be used to better understand inflation in an insurer’s own loss data.
Why caution should be taken in using external data
When using external data, significant caution needs to be taken in understanding whether the data is relevant or comparable for the insurer. Data may be different for different insurance companies because of differences in products offered, coverage definitions, underwriting criteria, expense levels, claims practices, claims coding, mix of business, etc.
Frequency formula and use
Frequency = Number of Claims/Number of Exposures
The most common scenario is to use earned exposures in the denominator and reported or ultimate claim counts in the numerator.
Changes in frequency can help identify trends in claims occurrence and insurance utilization as well as measure the effectiveness of underwriting changes. As an example, during periods of significantly high gas prices, frequency tends to
decrease for most personal auto coverages as people drive less and thus get into less accidents.
Severity formula and use
Severity = Losses/Number of Claims
Severity is often calculated many different ways in practice, and the differences may help build an understanding of changes in the loss portfolio. Furthermore, ALAE may or may not be included in severity measures with Losses.
Changes in inflation or claims handling procedures may show up as changes in claim severity over time.
