18 - Data

Question 1

What are the 8 basic principles in the UK Data Protection Act for personal data?

Answer 1

• Must be fairly & lawfully processed
• Be processed according to individual’s rights under the Act
• Be processed securely
• Obtained and processed for specified purposes
• Be adequate, relevant and not excessive for purposes concerned
• Not be kept longer than necessary for purposes concerned
• Be accurate & up to date
• Must not be transferred to a country/territory outside the European Economic Area unless that country ensures an adequate level of protection

Question 2

What is data governance?

Answer 2

Used to describe the overall management of the availability, usability, integrity & security of the data employed in an organization.

Question 3

What does data governance policy set out?

Answer 3

• How organisations capture, analyse & process data
• Issues wrt data privacy & security
• Roles/responsibilities of company individuals wrt data
• Mechanism through which regulatory/legal requirements wrt data management are met
  o Controls to be put in place to ensure required data standards are applied
  o Ongoing monitoring methods for adequacy of controls wrt managing data security, availability, integrity & usability (data governance)

Question 4

Organisations without adequate data governance procedures can be exposed to risks relating to:

Answer 4

• legal and regulatory non-compliance
• inability to rely on data for decision making
• reputational issues (leads to loss of business)
• incurring additional costs

Question 5

Possible risks/problems we might face with using data:

Answer 5

• Inaccurate/Incomplete data
• Insufficient data removes credibility of risk estimates, particularly for the estimation of extreme outcomes
• Data is not sufficiently relevant to the intended purpose
• Data is not in the appropriate form for intended purpose
• Where external data is used, there is risk of it not being a good enough proxy for risk being assessed
• Historical data might not be accurate reflection of the future experience
• When actuary attempts to group data into homogeneous groups:
  o Individual groups are too small for credible analysis
  o Risk that combined groups are heterogeneous

Question 6

Why might historical insurance data not accurately reflect the future?

Answer 6

• Past abnormal events
• Significant random fluctuations
• Future trends not reflected sufficiently in past data
• Change in the underlying mix of homogeneous groups
• Heterogeneity in the group to which assumptions are to relate
• Changes in the way past data was recorded
• Past data may not be sufficiently up to date
• External environment changes eg. medical, social, economic etc.

Question 7

Main uses of data

Answer 7

F - financial control
I - investment
R - risk management
E - experience analysis
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

Question 8

Advantages of data being controlled by a single integrated system:

Answer 8

• Easier access to information, no need to collate information
• No need to reconcile information from different systems
• Less chance of inconsistent treatment of information b/w different products or over time.
• Easier to place controls on who can amend/enter data
• Less prone to corruption

Question 9

Problems with data quality & quantity can be a result of:

Answer 9

• Poor management of data recording or its verification processes
• Poor management of data systems
• Not enough data collected yet to perform analysis

Question 10

Qualities of good proposal & claims forms:

Answer 10

Well designed proposal/claim forms contain unambiguous questions to ensure correct answers are collected from policyholders.

• Ideally the info. should be quantitative in nature (for rating factors)
• Use of tick boxes

The information on both the proposal and claim forms should be easy to enter into the system.

The system must be able to link across proposal and claims records.

Question 11

How are proposal forms used when assessing claims?

Answer 11

• Cross-checking claims information (from claim forms) w proposal form to assess validity of claims

Question 12

Ideal qualities of data from sponsors of a benefit scheme are that data should be:

Answer 12

• Consistent with previous data
• Complete, ie no omissions
• Accurate
• Up-to-date
• At the level of detail requested

Question 13

Data is required from the sponsors of benefit schemes wrt :

Answer 13

All data that is probably financially significant wrt timing/amount of benefits for:

• Individuals entitled to receive benefits in the future (active & deferred members)
• Individuals currently receiving benefits (current pensioners)

Question 14

Methods of verifying data:

Answer 14

• Using accounts (Bal. Sheet & Inc. Stat.) to verify asset valuations / claims experience data (past data)
• Asset data used to place reliable value on assets wrt legislation & regulation

Question 15

Assertions to be examined when using data: (5)

Answer 15

• 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 the appropriate value of an asset or liability has been recorded.
• 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)

Question 16

How to check the actuary’s assertions about data quality using past accounts:

Answer 16

Using previous data and movement data, do RECONCILIATIONS of:

• total number of members/policies (m/p) and their changes
• benefit amounts and premiums and their changes
• where assets are held by 3rd party, reconciliation b/w beneficial owner’s and custodian’s records

CONSISTENCY between:

• contribution and benefit levels with the accounts and membership data
• average sum assured or premium compared with their values in the previous investigation
• investment income implied by asset data and corresponding totals in the accounts
• between start and end period shareholdings

OTHER

• validity of data entries eg. DOBs, retirement ages etc.
• full deed audit for certain assets (eg property)
• records picked at random for spot checks.

Question 17

Institutions’ main reasons for their lack of ideal data:

Answer 17

• Practically difficult/impossible to capture good data
• Poor data systems
• Poor management of data recording and verification processes
• Insufficient volume of data
• Insufficient detail within the data

Question 18

Issues causing heterogeneous data in industry-wide data collection schemes

Answer 18

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

Question 19

4 Additional problems with large data collection schemes

Answer 19

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

Question 20

All sources of data

Answer 20

T - Tables
R - Reinsurers
A - Abroad
I - Industry
N - National Statistics
E - Experience from own contracts
R - Regulatory Reports & Company Accounts
S - Similar Contracts

Question 21

Main aim of risk classification in data:

Answer 21

-To obtain homogeneous data.
-The reduction of heterogeneity within the data for a group of risks so:
o The experience in each group more stable and
characteristic of that group (no distortions)
o Enables the data to be used more appropriately for
projection purposes.