C30 Monitoring Experience Flashcards
List six reasons for monitoring experience as part of the control cycle.
Reasons for monitoring experience (DUMAMI)
1. To develop earned asset shares
2. To update assumptions as to future experience
3. To monitor any trends in experience
4. To monitor actual compared to expected experience and take corrective actions as needed
5. To provide management information to aid business decisions
6. To make more informed decisions about pricing and about adequacy of reserves
List four reasons a life company requires assumptions as to future experience.
Why assumptions are required
1. Model office work – including: (PEFAR)
profitability monitoring
embedded value work
financial projections
asset-liability modelling for setting investment strategy
determination of reinsurance requirements
2. Product pricing
3. Valuations
4. Setting discontinuance terms
Discuss the data required for monitoring experience.
Data required for monitoring experience
Basic requirement is for reasonable volume of stable, consistent data,
from which future experience and trends can be deduced.
Important to agree period over which data will be collected
Data ideally divided into sufficiently homogeneous risk groups, according to relevant risk factors – but must be balanced against credibility of data.
Give a typical example of ‘big data’, and
state three uses of big data for insurance companies.
Big data
Typical example – banks that have insurance subsidiaries that sell
insurance mostly to own customers (‘bancassurers’) amass large volumes of additional data on their insurance customers eg on personal spending habits and travel locations.
Uses:
– better analysis and understanding of risks
– develop more sophisticated and detailed risk classifications, allowing for more accurate (individual) rating and ability to select preferred risks
– through monitoring, may help drive better experience by earlier identification of changes in individual risks, or through being able to intervene and influence customer behaviours.
List four experience investigations an actuary might conduct
Experience investigations
1. Mortality (and other contingencies)
2. Persistency
3. Expenses
4. Investment return
List eight classifications by which the data (both claims and exposed to risk) would ideally be sub-divided for the purpose of analysing the mortality experience.
Sub-division and analysis of mortality experience data (TASD SMS L)
Data would ideally be analysed, where relevant, by:
1. Type of contract
2. Age
3. Sex
4. Duration from entry
5. Smoker / non-smoker status
6. Medical / non-medical status
7. Source of business
8. Location
List ten classifications by which the data (both claims and exposed to risk) would ideally be sub-divided for the purpose of analysing the persistency experience.
Sub-division and analysis of persistency experience data TDS TFS POGA
Data would ideally be analysed by:
1. Type of contract
2. Duration in force
3. Sales method used
- Target market
- Frequency of premium
- Size of premium
- Premium payment method
- Original term of contract
- Gender
- Age
The first three of these are particularly important.
Give three other factors, external to the life company, that may also influence persistency rates.
Other external influences on persistency rates
1. Economic situation
2. Competitive situation of product, eg introduction of more attractive products can have adverse effect
3. Perceived value of the product to the customer
Outline how full withdrawal rates can be determined for each homogeneous group of lives analysed.
Determination of withdrawal rates
For each homogeneous group of lives analysed:
Number of contracts issued in company’s last financial year is divided into corresponding number that survive in-force until first policy anniversary to give first-year persistency rate.
First-year withdrawal rate = 1 – first-year persistency rate.
Deaths and maturities excluded from calculation (if material).
Similar procedure adopted to obtain second-year, third-year, etc withdrawal rates (by looking at number surviving from number of contracts, in each group, that have their first, second, etc policyanniversary in last financial year).
Define what is meant by a direct expense and an overhead expense.
Direct and overhead expenses
Direct expenses – the expenses that can be attributed directly to a product or policy
Overheads – the balance of the expenses, ie those that relate to general management and service departments which are not directly involved in new business or policy maintenance activities.
List the four categories into which the non-commission expenses are split for the purpose of an analysis of expenses.
Categories of non-commission expenses
1. Initial expenses
2. Renewal expenses
3. Termination expenses
4. Investment expenses
State how the initial, renewal and termination expenses can be further split.
Initial, renewal and termination expenses
Can be further split according to whether expense is proportional to:
number of contracts written or in-force
amount of premium written or in-force
amount of benefit written or in-force.
Give two examples of expenses that are not proportional to the number of contracts written or in-force.
Non-proportional expenses
Expenses that aren’t proportional to number of contracts written or in-force include:
1. marketing expenses – may be related to amount of initial commission paid
2. underwriting expenses – mainly related to size of benefit.
Explain how investment expenses are normally treated.
Investment expenses
Normally expressed as percentage of funds under management.
Normally treated as deduction from earned investment return.
Describe the division of expenses into cells.
Division of expenses into cells
Cells may be separated by:
– accounting fund
– each main product line of company.
These may be further sub-divided between regular and single premium business.
Choice of cells will vary across companies depending upon:
– types and volumes of business written
– requirements of analysis.
Cells chosen should not be so small that analysis becomes unreliable.
