Chapter 30: Data Flashcards
Main uses of data
F - financial control I - investment R - risk management E - experience analyses S - statutory returns P - premium rating, A - accounting and administration C - determining contributions E - experience statistics
P - product costing,
I - management information
M - marketing
P - setting provisions
2 Main sources of data
- publicly available data
- internal data
Poor data can be due to… (2)
- poor management control of data recording or its verification processes
- poor design of the data systems
The actuary’s data quality assertions will regularly be checked by looking at (11)
(headings are artificial) RECONCILIATIONS - of member numbers - of benefits and premiums - of beneficial owner and custodian records where assets are owned by a 3rd party - movement data against accounts
CONSISTENCY
- of contribution and benefit levels with the accounts
- of average sum assured or premium compared with previous investigation
- of asset income data and accounts
- between start and end period shareholdings
OTHER
- validity of dates
- full deed audit for certain assets (eg property)
- records picked at random for spot checks.
Issues causing heterogeneous data in industry-wide data collection schemes
- companies operate in different geographical or socio-economic sections of the market.
- the policies sold by different companies are not identical
- sale methods are not identical
- 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
4 Additional problems with large data collection schemes
- data may be less detailed / flexible
- data may be more out-of-date
- data quality may be poor
- not all organisations contribute
Assertions to be examined
- 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
- the data is complete (ie there are no unrecorded liabilities, assets or events)
- that the appropriate value of an asset or liability has been recorded.
4 Causes for the lack of ideal data
- Data have not been captured at a sufficiently detailed level.
- There may be insufficient data to provide a credible result.
- Poor systems
- Practically difficult / impossible to capture good data
Main aim of risk classification
To obtain homogeneous data.
The reduction of heterogeneity within the data for a group of risks makes the experience in each group more stable and characteristic of that group, and enables the data to be used more appropriately for projection purposes.
3 Primary Uses for Data
- Strategic decision making
- Day-to-day Running
- Monitoring
Uses for data: Day-to-day running
- Administration
- Investment
- Setting provisions (in financial statements)
- Marketing
Uses for data: Monitoring
- Premium rating & (benefit scheme) funding
- Internal management
- Experience statistics
- Financial Control
- Accounting (Financial Statements & Tax returns)
- Statutory returns
What do we mean by “good quality data”
- Complete
- Necessary level of detail
- Accurate
- Up-to-date
- Audit trail (crutial)
Checks on data:
Checks
• Detailed Audit • Reasonability Checks: ---- Averages ---- Impossible values ---- Outliers ---- Consistency over time ---- Check Asset data vs Liability data • Spot checks ---- Particularly on the "big ticket" items ---- random
Checks on data:
Valuations
Assets:
- At the start of the period
- Movements during the period
- At the end of the period
Liabilities:
- At the start of the period
- Movements during the period
- At the end of the period
