Part 7

Question 1

Requirements of a good model:

Answer 1

• The model being used must be valid, rigorous well documented.
• The model should reflect the risk profile of the business being modelled
• Allow for all significant features of the business being modelled
• Have appropriate input parameters and parameter values
• Be communicable and the output varifiable
• Not be overly complex or time consuming to run
• Be capable of development and refinement
• Be capable of being implemented in a range of ways

Question 2

Steps for developing a Deterministic Model:

Answer 2

• Specify the purpose of the investigation
• Collect, group and modify data
• Choose the form of the model
• Identifying its parameters and variables
• Ascribe values to the parameters using past experience and appropriate estimation techniques
• Construct a model based on the expected cashflows
• Check that the goodness of fit is acceptable. This can be done by running a past year and comparing the model with the actual results
• Attempt to fit a different model if the first choice does not fit well
• Run the model using selected values of the variables and using estimates of the values in the future
• Run the model several times to assess the sensitivity of the results to different parameter values

Question 3

Steps for developing a Stochastic Model:

Answer 3

• Specify the purpose of the investigation
• Collect, group and modify data
• Choose a suitable density function for each of the variables to be modelled stochastically
• Specify correlation between variables
• Ascribe values to the variables that are not being modelled stochastically
• Construct a model based on the expected cashflows
• Check that goodness of fit is acceptable. This can be done by running a past year and comparing the model with the actual results
• Attempt a different model if the first model does not fit well
• Run the model many times, each time using a random sample from the chosen density function(s)
• Produce a summary of the results that shows the distribution of the modelled results after many simulations have been run

Question 4

Assertions to be examined:

Answer 4

• That a liability or asset exists on a given date
• That a liability is held or an asset is owned on a given date
• That when an event is recorded, the time of the event and the associated income or expenditure are allocated to the correct accounting period
• That data is complete, i.e. there are no unrecorded liabilities, assets or events
• That the appropriate value of an asset or liability has been recorded

Question 5

Checking the assertions:

Answer 5

• Reconciliation of member numbers
• Reconciliation of benefits and premiums
• Movement data against accounts
• Validity of dates
• Consistency of contributions and benefit levels indicated by membership data with the accounts
• Consistency between the average sum assured or premium compared with previous investigation
• Consistency of asset income data and accounts
• Where assets are held by a third party, reconciliation between the beneficial owner’s and the custodian’s records
• Full deed audit for certain assets, eg property
• Consistency between shareholdings at the start and end of the period
• Random spot checks on the records

Question 6

Possible reasons for heterogeneity:

Answer 6

• Companies operate in different geographical or socio-economic sections of the market
• The policies sold by different companies are not identical
• Sales methods are not identical
• The companies will have different practices, eg underwriting, claim settlement
• The nature of the data stored by different companies will not always be the same
• The coding used for the risk factors may vary from organisation to organisation

Question 7

Additional problems with industry wide data

Answer 7

• Data may be less flexible/detailed
• Data may be more out-of-date
• Data quality may be poor
• Not all organisations contribute

Question 8

When setting assumptions it is important to:

Answer 8

• Consider the use to which the assumptions will be put
• Take particular care over the choice of the assumptions that will have the most financial significance
• Achieve consistency between the various assumptions
• Consider any legislative or regulatory constraints
• Consider the needs of the client

Question 9

When using past data, it is necessary to consider how to deal with:

Answer 9

• Abnormal fluctuations
• Changes in experience with time
• Random fluctuations
• Changes in the way in which the data was recorded
• Potential errors in the data
• Changes in the balance of any homogenous groups underlying the data
• Heterogeneity with the group to which the assumptions are to relate

Question 10

Features which make contract design riskier (viewed as an investment)

Answer 10

• Lack of historical data
• High guarantees
• Policyholder options
• Overhead costs
• Complexity of design

Question 11

Premiums or contributions should allow for:

Answer 11

• Theoretical value of benefits to be provided
• Value of the expenses that will be incurred
• Contribution to profit
• Taxation
• Commission (this may be included as an expense)
• Cost of any capital supporting the product
• Margins for contingencies
• Cost of any options and guarantees
• Provisioning basis
• Experience rating
• Investment income
• Reinsurance costs