CH:19 Data

Question 1

List seven examples of sensitive personal data

Answer 1

• Racial or ethnic origin
• Political opinions
• Religious or other similar beliefs
• Membership in a trade union
• Physical or mental health
• Sexual life
• Convictions, proceedings and criminal acts

Question 2

What risks are associated with the use of data? (9)

QUERIED

Answer 2

• Data contains errors or omissions leading to incorrect conclusions being made
• Insufficient credible data to provide credible results
• There might be enough data to provide credible results but not enough to give a credible estimate of an adverse circumstance, i.e., what occurs in the tails of the distribution
• External sources might not be relevant or appropriate for this circumstance
• Historical data might not be a good representation of the future experience
  – Past abnormal event
  – Significant random fluctuations
  – Future trends not being reflected in past data
  – Change in the way data was recorded
  – Changes in homogenous groups
  – Past data is not up to date
• Difficulties in creating homogenous groups due to
  – Groups being too small to be credible
  – Merging with other groups can cause it not to be homogenous anymore
• Data might not be in the appropriate form
• Data collected for a specific purpose, so it is not appropriate for this purpose
• Lack of confidence in the available data reduce confidence in final conclusion

Q - Quantity (credibility)
U - Up-to-date
E - Errors
R - Relevance (heterogeneity)
I - Incomplete
E - Exceptionals
D - Detail and format

Question 3

List six areas of actuarial work where data would be required

Answer 3

• Setting provisions
• Pricing/setting contributions
• Investment management
• Risk management
• Management information / financial control
• Accounts/ statutory or supervisory reporting
• Experience statistics/analyses
• Marketing

Question 4

What are the 8 conditions of POPIA

Answer 4

1. Accountability- party responsible for processing data is also responsible for compliance with POPIA
2. Processing limitation- information must be processed in a fair, lawful and relevant manner
3. Purpose specification - info collected for specific purpose, record keeping to be destroyed when no longer relevant
4. Further processing limitation - further processing must be compatible with the initial collection purpose
5. information quality - data completeness, accuracy and updates
6. Openness - documentation to be miantained on all processing operations and maintaining transparency on data use
7. Security safeguards - integrity and confidentiality of personal data must be secured
8. Data subject participation - data subject may request confirmation of personal data help and request correction or deletion of any inaccurate, misleading or outdated info held

Question 5

How can assertions be checked on as to the quality of data

11

Answer 5

• reconciliation of members/policy numbers
• reconciliation of benefits and premiums
• movement data against accounts
• validity of dates
• consistency of contributions and benefit levels with accounts
• consistency between average sum assured and premiums for each class
• consistency of asset income data and accounts
• reconciliation of benefial owner and custodian records
• full deed audit for certain assets
• consistency between start and end period shareholdings
• records picked at random for spot checks