ICAEW SE Data ethics and the impact of technology: practice questions with answers

Answer: B. There is no single official list of data ethics principles, but widely accepted principles include transparency, fairness, accountability, privacy and minimising harm (beneficence).

Transparency means being open with people about what data is collected, how it is used, and how decisions that affect them are made, in a form they can understand. Explaining the model and giving reasons for declined applications supports transparency. It also helps people challenge decisions, which links to fairness and accountability. UK GDPR's 'lawfulness, fairness and transparency' principle and its rules on automated decision-making point the same way.

Answer: B. Data ethics goes beyond legal compliance. Widely accepted principles include transparency, fairness, accountability, privacy and minimising harm (beneficence). They are drawn from several sources, not a single official list.

Key points:

- Lawful is not always ethical. A use permitted by UK GDPR may still be unfair, intrusive or harmful.
- Ethical concerns apply to all data, including aggregated or anonymised data, which can still disadvantage groups or be re-identified.
- Consent is one lawful basis, but it does not end the accountant's duty to consider fairness and harm.

For ICAEW members, the fundamental principles (integrity, objectivity, confidentiality and professional behaviour) also apply to the use of data.

Answer: A. Survivorship bias occurs when analysis is based only on the items that have 'survived' a selection process, ignoring those that dropped out. Fund performance studies are a classic case. Funds that closed or merged were often poor performers, so an average of surviving funds overstates typical returns and makes the client's portfolio look worse by comparison.

An accountant challenging the data would ask how the population was selected and whether it includes all funds that existed at the start of the period.

Answer: C. The Code expects professional accountants to have an inquiring mind when applying the conceptual framework. When collecting and assessing data from varied sources, this means considering:

- provenance: who produced the data, how, and for what purpose (including possible bias of the source);
- timeliness and relevance: whether old data still reflects current conditions;
- completeness and accuracy: whether the method and coverage are sound;
- corroboration (triangulation): whether independent sources support the figure.

Ivo should investigate both figures and find independent evidence before building a business case on either.

Answer: A. Having an inquiring mind includes questioning the completeness and reliability of data, even data produced automatically by the organisation's own systems. A system only captures what it is designed to capture. Here, bookings may exclude walk-in customers or one site may use a different process.

Comparing two sources (triangulation) has revealed a discrepancy. Fatima should find out why before relying on either source, and the finding may improve data capture in future. Assuming either source is correct, or dropping the inconvenient data, would risk misleading users and fall short of professional competence and due care.

Answer: B. UK GDPR (with the Data Protection Act 2018) sets seven principles: lawfulness, fairness and transparency; purpose limitation; data minimisation; accuracy; storage limitation; integrity and confidentiality (security); and accountability.

Purpose limitation requires personal data to be collected for specified, explicit and legitimate purposes and not further processed in a manner incompatible with those purposes. Selling warranty data to an insurance broker is a new, unrelated purpose. It would also need a lawful basis, such as consent, and would raise transparency and fairness concerns, because customers would not expect it.