Personal data
Relates to information i.r.o an individual where the individual can be identified or the data can be combined with other information to identify the individual
Sensitive data includes
Racial or ethnic origin
Political opinions
Religious or other similar beliefs
Sexual orientation
Convictions
Physical or mental health
Members of trade unions
Consequences of non-compliance with relevant data protection laws may lead to
Individuals who commit criminal offences may be prosecuted
Organisations can be fined, go to jail, or be required to compensate the data subjects for damage suffered
Breaching data protection rules could lead to adverse publicity which can lead to significant reputational damage
Fines
Disqualification of company directors
Awards for damages
Data governance
Term used to describe overall management of the availability, usability, integrity and security of data employed in an organisation.
Data governance policy must include:
Roles and responsibilities of individuals in the org with regards to data
How data will be captured, analysed and processed
Issues wrt data security and privacy
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
Risks associated with using data
The data is inaccurate
The data is incomplete
Data is not credible due to being of insufficient volume
Data is not sufficiently relevant to the intended purpose
Past data does not reflect what will happen in future
Chosen data groups are not optimal
Data is not available in a appropriate form for the intended purpose
Lack of confidence in the data
Data might have been collected for a different purpose, making it useless for current purpose
Why past data may not be a good reflection of future experience
Past abnormal events
Significant random fluctuations
Future trends not being reflected sufficiently in past data
Changes in the way which past data was recorded
Changes in the balance of any homogenous groups underlying the data
Past data may not be sufficiently up to data
Uses of data
Administration
Marketing
Premium rating, product pricing, determining contributions
Setting provisions
Experience analysis
Investment
Accounting
Management information
Risk management, including using underwriting and reinsurance
Data Sources
Publicly available data - National statistics
Internal data
Reinsurance data
Industry-wide data collection schemes
Data quality
Problems with data quality and quantity arise from
* Poor management control of data recording or its verification process or
* Poor design of data systems
To maintain good quality data:
*Information source on proposal form should be good - questions asked on forms
*Information from proposal form will be used for several purposes - claims, changes in the plan etc.
* Data from claim form also needs to be good and provides information