Chapter 30: Data

Question 1

What are the main uses of policy and claims data?

Answer 1

• Administration
• Accounting
• Statutory returns
• Setting investment strategy
• Financial control
• Management information
• Risk Management
• Setting provisions
• Experience statistics and analyses
• Pricing
• Marketing

Ideally, all of these functions should be controlled through one integrated data system.

Question 2

What are the main sources of data?

Answer 2

• published company accounts
• regulatory returns
• internal experience investigations
• industry data, including actuarial tables
• national statistics
• data from reinsurers

Question 3

Why might data be of poor quality or quantity?

Answer 3

• Poor management control

- Poor design of data systems

Question 4

How can good quality data from the proposal and claim forms be ensured?

Answer 4

• well-designed and unambiguous questions that are in the same order that they will be processed on the administration system.
• It is important that the result of any underwriting is captured;
• and for general insurance, that the rating factors can all be separately identified.

The policy data should be used to check the validity of the claims data and vice versa.

Question 5

What are the data issues for employee benefit schemes?

Answer 5

• The actuary may not have full control over the data, and so validation is particularly important
• Additionally, the data might not be sufficiently detailed to provide all the information that is financially significant to the valuation

Question 6

What are the sources of data that are useful in checking the current data from the scheme?

Answer 6

• Data from the previous valuation, for reconciliation with the current data
• Accounting data for checks on assets, benefit outgo and contribution income.
• A full listing of the assets held to check whether they are permitted.

Question 7

What are the problems with using summarised data?

Answer 7

The reliability of the valuation will be reduced as full validation of the data is impossible.
Changes in the mix of the members may remain unidentified.
Summarised data is not useful for valuing individual options and guarantees.

Question 8

Some countries have industry-wide data collection schemes.

What is this useful for?

Answer 8

Industry-wide data can be used

• to increase the credibility of a country’s own data, or
• for providing a comparison of a country’s own data against that of competitors.

Question 9

Industry-wide data might not be directly comparable.

Why is this?

Answer 9

There will be differences in

• target markets
• geographical or socio-economic areas of operation
• policy conditions
• risk and rating factors used
• underwriting and claims settlement
• ways of storing data

In addition,

• industry data may be less detailed or flexible than internal data.
• It may be out of date,
• not everyone contributes,
• the quality may be dubious.

Question 10

4 Categories of checks to be carried out on data

Answer 10

• Reconciliations
• Cross checks
• Reasonableness checks
• Spot checks

Question 11

3 Reconciliation checks on data

Answer 11

Include:

• reconciling the total number of members or policies and changes in membership or policies using previous data and movement data
• reconciling the total benefit amounts and premiums and changes in them using previous data and movement data.
• reconciling shareholdings at the start and end of the period adjusted for sales and purchases and bonus issues.

Question 12

4 Cross checks on data

Answer 12

• checking movement data against accounting data, e.g. benefit payments
• checking membership data against accounting data, e.g. contributions
• checking asset data against accounting data, e.g. investment return.
• checking asset ownership records against the custodian’s records

Question 13

Reasonableness checks on data

Answer 13

• Checking the average sum assured or premium looks sensible for the class of business, and against previous data.
• Checking for unusual values or missing data.

Question 14

Spot checks on data

Answer 14

• Checking individual members or policy records.
• Checking that individual assets or liabilities exist on a given date.
• Carrying out a full deed audit for certain assets, e.g. property title deeds
• Checking that the correct value for an asset or liability is being recorded.

Question 15

Main aim of risk classification

Answer 15

To obtain homogeneous data

Question 16

Why is it important to have homogeneous data?

Answer 16

So that the experience in each group of risks is more stable, enabling the data to be used for projection purposes.

Question 17

What is the main practical problem of risk classification?

Answer 17

It may result in too little data in a group for a credible analysis.

Question 18

Spot check

Answer 18

Eg for lapse rates, check a policy to determine when it lapsed and check against when last premium was received

Question 19

Cross checks

Answer 19

• Check data against other sources
o Eg check accounting data vs data used to administer contracts
• Check for consistency between claims and exposed to risk data

Question 20

Reasonableness checks

Answer 20

• Check whether rates consistent with what was expected
• Check is rates reasonable compared to previous rates
• The drivers of rates should be analysed
o Consider how rates differ by SA, prem size, entry year, dist channel, calandar year etc
o Will help to explain any differences vs industry data
• Ensure no clustering of dates (claim/ lapse) – may suggest system error
• Consider rate measure – unweighted or weighted by eg prem size
• Check changes in business mix

Question 21

Reconciliations

Answer 21

• Reconcile latest results with previous results, eg for lapse data:
o Num pol in force at end of period= num at start + num new pol – num exits
• Could carried out for each product class and year
• Check results of an analysis of surplus