19. Data Flashcards

1
Q

What is personal data

A
  • information that relates to an individual which would allow that individual to be identified,
  • or where the data combined with other information could allow the individual to be identified
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2
Q

Examples of what might be considered as personal data

4

A
  • racial or ethnic origin
  • political opinions
  • religious or other similar beliefs
  • membership of trade unions
  • physical or mental health condition
  • sexual orientation
  • convictions, proceedings and criminal acts
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3
Q

What are the conditions of POPIA relating to personal data

8

A
  • Accountability
  • Processing limitation
  • Purpose specification
  • Further processing limitation
  • Information quality
  • Openness
  • Security safeguards
  • Data subject participation
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4
Q

Examples of competition legislation

A
  • Anti-competitive agreements => small number of companies sharing data
  • Abuse of dominant market position
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5
Q

What are the characteristics of big data

3

A
  • Very large data sets
  • Data brought together from different sources
  • Data which can be analysed very quickly e.g real time analysis
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6
Q

What is data governance?

A
  • The overall management of the availability, usability, integrity and security of data employed in an organisation
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7
Q

Data governance policy will set out guidelines with regards to what?

5

A

ICHES

  • Issues with respect to data security and piracy
  • Controls to ensure that the required data standards are applied
  • How the adequacy of the controls will be monitored on an ongoing basis with respect to data usability, accessibility, integrity and security
  • How an organisation will capture, analyse and proces data
  • Ensuring that the relavant legal and regulatory requirements in relation to data management are met by the organisation
  • Specific roles and responsibilites of individuals in the organisation wrt data
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8
Q

What are the risks relating data governance inadequacy and/or failure

A
  • Legal and regulatory non-compliance
  • Inability to rely on data for decision-making
  • Reputational issues
  • Incurring additional costs (e.g. fines and legal costs)
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9
Q

What are the risks relating to using data

7

A

N3 CLIP
* Not credible
* Not sufficiently relevant to the intended purpose
* Not available in an appropriate form for the intended purpose
* Chosen data groups are not optimal
* Lack of confidence in the data leads to a lack of confidence in the results
* Inaccurate or incomplete data
* Past data do not reflect what will happen in the future

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10
Q

Outline the key issues and risks arising in relation to the use of algorithmic tools, particularly for trading.

A

Key issues

  • decisions that are unfairly biased
  • the algorithm not performing as expected.

Risks
* errors in the algorithm or data used to parameterise the model, leading to losses
* the algorithm not operating properly in adverse conditions
* in very turbulent conditions, trading in individual stocks or markets may be suspended before the algorithmic trade can be completed
* possible impacts on the financial system

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11
Q

What is the overriding principle in relation to all the different uses of data?

A
  • There should be one single integrated data system so that the data used for different applications is consistent
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12
Q

What are the main sources of data

A

TRAINERS
* Tables
* Reinsurers
* Abroad (data from overseas contracts)
* Industry data
* National statistics
* Experience investigations on the existing contract
* Regulatory reports and company accounts
* Similar contracts

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13
Q

What two main factors cause data to be of poor quality and quantity

A
  • Poor management control of data recording and checking
  • Poor design data systems
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14
Q

How can good quality data be ensured from an insurance proposal and claims form?

A
  • Questions clear and not ambiguous
  • Questions with quantitative or tick-box answers if possible
  • Questions in the same order as in systems for quick processing
  • Ask the policyholder to verify a copy of the key information
  • All rating factors must be readily identifiable
  • Underwriting results should be added to the proposal form
  • Forms designed in a way that info can easily analysed and cross-checks made between the two sources
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15
Q

Why is it important, at the time of the claim, to have access to the information given on the proposal form

A
  • To check the validity of the claim
  • To update policy information
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16
Q

What is the key problem with data for employee benefit schemes?

A
  • Actuary does not have full control over the data, as it is provided by the sponsor
  • Consequently, poor data quality or summarized data
17
Q

What are the sources of data for valuation of a benefit scheme

A
  • Membership data (sufficiently detailed) on individuals who are currently receiving benefits and those who are entitled to benefits in the future
  • Data from previous valuation for reconciliation with current data and validation
  • Accounting data for information on asset values, benefit outgo and contribution income, to help check other sources of data or in setting assumptions
  • A full listing of the actual assets held
18
Q

Give examples of reconciliations and cross-checks that can be performed on data

6

A
  • Comparing total members/policies and changes using prior and movement data.
  • Matching total benefits and premiums with previous and movement data.
  • Cross-checking movement data with accounting records (e.g., benefit payments).
  • Validating membership data against accounting records (e.g., contributions).
  • Ensuring asset data aligns with accounting records (e.g., investment income).
  • Reconciling third-party-held assets between owner and custodian records.
19
Q

Give examples of reasonableness and other checks that can be performed on data

4

A
  • Verify that the average sum assured or premium is reasonable and consistent for the business class.
  • Compare the average sum assured or premium with historical data.
  • Identify unusual values, impossible dates, or missing records.
  • Conduct spot checks on individual records (members, policies, or assets).
20
Q

Outline three problems with using summarised data

A
  • Valuation reliability decreases due to limited data validation.
  • Summarised data may overlook key differences in benefit structures.
  • Summarised data cannot be used to value options and guarantees.
  • Suitable only if users acknowledge potential inaccuracies.