C38: Monitoring Flashcards
(13 cards)
Reasons for monitoring experience
- To update assumptions as to future experience
- To monitor any adverse trends in experience so as to take corrective actions
- To provide management information
Monitoring experience is a fundamental part of the Actuarial Control Cycle
Data required for monitoring experience
- A reasonable volume of stable, consistent data, from which future experience and trends can be deduced
- Data divided into homogeneous(risk) groups, subject to there being a sufficient quantity of data in each group to give credible results
- Data required on both the risk event and the exposed to risk – consistency between the two is essential
Explain why having heterogeneous data in a single group is a problem.
The problem with grouping together heterogeneous data into single cells for analysis is that we would not be able to tell whether a change in some observed variable was genuine or just the result of having a different mix of business within the cell.
How demographic assumptions such as mortality, morbidity and withdrawal are monitored?
These are called statistical factors
For each age band , calculate :
1. (number of deaths / number exposed to risk of death)
2. Compare results with existing assumptions (often a standard table) to identify differences
3. Compare results with other relevant standard tables to determine if these results would provide a better fit to the data
Examples of homogenous groups for mortality expereince
Mortality experience of an insurer might be analysed
by:
1. product type
2. age
3. gender
3. duration from entry
4. smoker / non-smoker status
5. accepted on normal terms or special (eg medically-rated) terms
6. sales channel
7. target market
8. occupation.
List economic factors for which experience is analysed
How is the experience analysed?
Economic factors include:
1. Interest rates
2. Investment returns
3. Expense inflation
4. Salary growth.
For these the analysis is simply a comparison between the actual returns and those assumed.
The effect of the difference between actual and expected can be calculated by re-running the expected experience model using the actual economic experience items.
List practical calculation difficulties in calculating actual investment return
The calculation of the actual return may present some practical calculation difficulties, for example allowing accurately for:
1. Timing of cashflows in or out
2. Investment income received or accrued over the period being analysed
3. Investment expenses
4. Tax.
Key points when analysing data for expense inflation
The actual level of expense inflation would need to be determined by
1. Removing from the expense analysis any costs that were included only in the previous or current data,
2. Considering the change in unit costs rather than overall totals (in order to remove the impact on total expenses from volume changes).
Explain how the data might be subdivided when analysing expenses.
The main items of expense for a financial provider are:
1. salaries and salary-related expenses
2. property costs (rent, property taxes, heating, lighting and cleaning)
3. computer costs
4. investment costs (investment department, stamp duty, commission, custodian, etc).
In order to analyse these expenses, the provider will look to subdivide them into:
1. fixed / variable
2. direct / indirect
3. initial, renewal, termination and investment expenses
4. product with which they are associated
5. whether they are proportional to the:
– number of contracts
– amount of the claim (or benefits)
– amount of the premiums (or contributions)
– amount of funds under management.
List two components of salary growth assumption and how they can be analysed
Salaries increase in two ways:
1. general ‘across the board’ inflation-related (or ‘cost of living’) increases
2. individual promotional increases.
When considering salary-related benefits, it would be common to make separate assumptions for each element. When analysing experience, care must be taken to extract the elements separately.
Describe the considerations in using the results of experience analysis in future assumptions
Caution with results of monitoring experience
- Period under investigation may not have been typical
- results may not be representative of future experience
- Experience (data) under investigation may be affected by:
1. Abnormal events
2. Significant random fluctuations
3. Economic cycles
4. Trends in experience, e.g. mortality
5. Heterogeneity in the data used and the group to which it will apply
Necessary to adjust for these factors:
- Consider purpose of assumption
- Adjustment needed to allow for data and modelling risks
- create margins in assumptions for uncertainty
Factors that should be taken into account in using the results of experience study to decide future assumptions
- Purpose for which assumptions will be used.
- Significance of a particular assumption to the overall result
- Relationships / consistency between the assumptions
- Needs of the client
- Legislative or regulatory constraints
- Margins in assumptions vs risk discount rate
- Time horizons over which assumptions will apply
- Credibility of results and hence need for margins.
Summary of the monitoring process
Monitoring investigations typically involve the following stages:
1. Division of data into suitable groups that are homogeneous by risk – need to consider:
– the volume of data in each cell (its credibility)
– the risk factors for the investigation (eg age, gender)
– changes that have occurred that will reduce the relevance of old data
- Identification of any past trends, cycles and anomalies and random variation in the past data
- Using the results to revise models and assumptions used – need to consider:
– the purpose, and hence the need for accuracy and
margins for prudence
– allowance for future trends
– likely differences in future experience from past experience.
