19.Data

Question 1

Personal data

Answer 1

Information allowing individual to be identified, either on its own or in combination with other info

Question 2

Sensitive personal data

Answer 2

Info which disclosure to others without consent can cause high level of distress/damage

Question 3

Circumstances under which sensitive personal data can be processed

Answer 3

Explicit consent given
Required by law for employment purposes
Protect vital interests of individual/individual/another person
Needed for administration of justice/legal proceedings

Question 4

Characteristics of big data

Answer 4

• Large data sets
• Brought together from different sources
• Can be analysed quickly

Question 5

Big data consideration

Answer 5

• May be exessive/irrelvant

Question 6

Data governance

Answer 6

Overall management of availability, usability, integrity and security of data employed in organisation

Question 7

Data governance risks

Answer 7

• Legal and regulatory non-compliance
• Can’t rely on data to make decisions
• Reputational issues
• Additional costs from fines etc

Question 8

Data risks

Answer 8

• Inaccuracte/incomplete
• Not sufficiently relevant for intended purpose
• Not reflect future experience
• Chosen data groups not optimal
• Not available in appropriate form for intended purpose
• Not credible due to insufficient volume, particularly due to estimation of extreme outsomes

Question 9

Reasons why data may not reflect future

Answer 9

• Past abnormal events
• Once-off impacts
• Future trends not sufficiently reflected
• Changes in way past data was recorded
• Significant random fluctuations
• Changes in balance of any homogeneous groups
• Heterogeneity with group to which assumptions relate
• Not up to date
• Other changes e.g. medical, social and economic

Question 10

Algorithmic decision making

Answer 10

Automated trading involving buying/selling of financial securities electronically to capitalize on price discrepancies for same stock/assets in different markets

Question 11

Data requirements

Answer 11

Must be controlled through single, integrated system

Question 12

Advantages of keeping data in a single system

Answer 12

• Reduced chance of corruption
• Reduced chance of inconsistent treatment of information
• Better control over who may change or enter info
• Easier access to info
• No need for reconciliation between systems

Question 13

Sources of data

Answer 13

Public data
    - Publsihed accounts
    - Overseas data
    - National statistics
    - Industry data
Internal data
Reinsurer
Industry-wide collection schemes

Question 14

Reasons why data from industry collection schemes may not be comparable

Answer 14

• Operate in different geo/socio-economic sectors of the market
• Non-identical policies sold
• Non-identical sales methods
• Different practices e.g. underwriting
• Differences in nature of data stored
• Differences in coding used to code for risk factors

Question 15

Other problems with data from industry wide collection schemes

Answer 15

• Data may be less detailed/flexible
• Data may be out of date
• Data quality may be poor
• Not all companies contribute, therefore not representative of whole market

Question 16

Checks on data

Answer 16

• Past data can help verify current data
• Accounting data is useful to help verify income and outgo + value of assets
• Data on individual assets could be checked and verify:
- Existence of assets
- Allowed to be held for valuation purposes
- If valuation is restricted by legislation/regulation

Question 17

Assertions to check quality of data

Answer 17

• Reconciliations of member/policy #s
• Reconciliations of benefits + premiums
• Reconciliation of beneficial owner and custodian records where assets are owned by 3rd party.
• Records picked at random spot checks
• Consistency between contribution and benefit levels with accounts
• Consistency between average sum assured + premium for each class, and when compared with previous investigations
• Consistency of asset income data and accounts
• Consistency between start and end period shareholdings
• Full deed audit for certain assets e.g. property
• Validity of dates
• Movement of data against accounts

Question 18

Lack of ideal data

Answer 18

• Insufficient volume to provide credible result
• Data may not be captured at a sufficiently detailed level
• Actuary may only have summarised data …
• … this is not suitable for all valuation purposes

Question 19

Sources of poor quality data

Answer 19

• Poor management control of data/verification process

* Poor data system design

Question 20

Mechanisms that can be used to ensure good quality data

Answer 20

1. Proposal form
2. Claim form
3. Input of data onto system
4. Other

Question 21

Proposal form

Answer 21

Must be designed to:
 Collect data at appropriate level, incl data not currently used but may be needed in future
 Clear and unambiguous to give correct information
 Have inputs be as quantitative as possible

Question 22

Claim form

Answer 22

Must be clear and unambiguous and must link to proposal form so cross-checking can be done

Question 23

Input of data onto system

Answer 23

 Inputs must be in same order as in proposal form so person inputting info doesn’t need to interpret info
 Staff inputting info must be well trained
 Financial incentives for accuracy
 System must have validation checks, e.g. checks on
- blank entry fields
- sensible entry values e.g. sensible bounds on ages and sum assureds
 Insurer may send policyholder key info for verification

Question 24

Other features of good data system

Answer 24

 System must be capable of storing info, so that historical data can be used for future pricing exercises
 System must be robust and flexibles
 Secure- many can view but not many can amend
 At regular intervals, checks of movement analyses must be carried out and checks of changes in policy details, e.g. how sum assured is changing from year to year

Question 25

Use of proposal form to assess claims

Answer 25

* Cross-check against claims info at time of claim to check validity of form * Can also check endorsements (changes to policy)

Question 26

Good quality data

Answer 26

- Accurate - Complete - Up-to-date - At sufficient level as required - Consistent with past data