Chapter 19: Data Flashcards

1
Q

Personal data

A

Relates to information in respect to an individual where the individual can be identified, or where data, combined with other information can be used to identify the individual.

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2
Q

Eight conditions covering the processing of personal information by individuals and companies in South Africa

Which ACT covers this

A

I nformation quality - Data completeness, accuracy and updates to be ensured by the holder of the data.
O penness - Documentation to be maintained on all processing operations and maintaining transparency on data use
S ecurity safeguards - Integrity and confidentiality of personal data must be secured and all processing done only by authorised operator. Notification to be done on security compromise.

A ccountability - The party responsible for processing the data is also responsible for compliance with POPIA - not just the collector
P urpose specification - Personal information must be collected for a specific purpose. Record keeping to be destroyed when personal data is no longer relevant or authorised to be held.
P rocessing limitation - Information must be processed in a fair, lawful and relevant manner, after consent is given by the data subject.

Further processing limitation - Further processing must be compatible with inital collection purpose.
Data subject partcipation - The data subject may request confirmation of personal data held and request correction or deletion of any inaccurate, misleading or outdated information held.

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3
Q

When is personal data considered sensitive

A

When its disclosure can cause damage or distress to the individual - subject to stricter regualtion than regular personal data

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4
Q

Competition legislation

A

Limits ways in which data may be put to use. Usually prohibits:
* Sharing of data to particpate in price collusions.
* Monopolies - imposing unfair trading terms such as exclusivity.

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5
Q

Big data

A
  • Very large data sets
  • Data brought together from different sources
  • Data that can be analysed quickly - such as in real time.
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6
Q

Big data analytics

A

The process of analysing the large data sets to uncover patterns, trends, correlations and other details that can be used to inform decision-making within an organisation.

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7
Q

Data governance

A

Describes the overall management of the availability, usability, intergrity and security of the data employed in an organisation

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8
Q

Data governace policy

A

Documented set of guidelines for ensuring the proper management of the organisation’s data

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9
Q

What will a data governance policy set out guidelines with respect to ?

A
  • The specific roles and responsibilities of individuals in the organisation with regards to data.
  • How an organisation will capture, analyse and process data.
  • Issues with respect to data privacy and security.
  • The controls that will be put in place 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.
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10
Q

Possible risks that an actuary faces when dealing with data.

A
  • A ppropriate form - Data may not be in the form appropriate for the purposes required.
  • L ack of confidence in the available data
  • F uture experience -even if there were enough data to estimate the future in normal situations, it might not be enough to estimate the future experience in adverse situations.
  • A vailable data may have omissions or errors - leading to erronous results or conclusions.
  • S pecific form - The collected data may have been for a specific purpose, and cannot be used for a different purpose.
  • H istorical data may not be a good reflection of future experience.
  • I nsufficient historical data to credibly estimate the extent of a risk or etimate the lielihood of occurence of that risk in future.
  • H omogeneous groups - There are risks when trying to group data into homogenous groups - having small groups, and resulting data not being homogenous
  • I ndustry data - Where there is insufficient data, industry data may be used, at the risk of the industry data not being a good proxy for estimating the risk.
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10
Q

Algorithmic trading

A

A form of automated trading that involves buying or selling of financial securities electronically to capitalise on price discrepencies for the same stock or assetin different markets.

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11
Q

Why should data for an organisation be integrated into one system

A
  • C orruption - Reduced chance of existing data being corrupted.
  • R econcilliation - Time will not need to be spent reconciling data from different systems
  • A ccess - Information will be easier to access
  • I nconsistency = Reduced chance of inconsistent treatment of information.
  • C ontrol - Better chance of controlling who can enter and amend information.
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12
Q

Data sources

A
  • Publicly available data
  • Internal data
  • External sources
  • Industry-wide data collection schemes
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13
Q

Sources of data quality issues

A
  • Poor management control of data recording or its verification process
  • Poor design of the data systems
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14
Q

Checks on data

A
  • Reconcilliations of member/policy numbers
  • Reconcilliations of benefits and premiums
  • Movement data against accounts
  • Validity of dates
  • Consistency of benefit level with the accounts
  • Consistency between avaerage sum assured and premium for each class, and when compared to previous investigations
  • Consistency of asset income data and accounts
  • Full deed audit for certain assets.
  • Records picked at random for spot checks
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