Following on from last week’s blog about the Financial Reporting Council publication on professional judgement, today we look at the final three biases mentioned in Professional Judgement Guidance. Awareness of these factors allows auditors to make more objective professional judgements and maintain a higher overall quality of work.

The Financial Reporting Council publication looks at six biases (taken from International Standard on Auditing (Ireland) 220 (Revised December 2021), ‘Quality Management for an Audit of Financial Statements’, paragraph A35 which states that the six biases set out here are not intended to be a complete list of all biases that could affect audit judgements, just an illustrative list of some that might be especially relevant.

The last three biases alert auditors to be aware of:

  1. Groupthink: a tendency to think or make decisions as a group that discourages creativity or individual responsibility.
  2. Overconfidence: a tendency to overestimate one’s own ability to make accurate assessments of risk or other judgements or decisions.
  3. Automation bias: a tendency to favor output generated from automated systems, even when human reasoning or contradictory information raises questions as to whether such output is reliable or fit for purpose.

The following example given in the publication helps illustrate how these types of bias affect professional judgement.

Example: A trainee auditor is using automated tools, specifically audit data analytics, in the identification of high-risk journal entries. She uses the program’s default selection parameters, without tailoring them based on the entity and its environment. The generated selection of “high-risk” journal entries includes several items categorised as such due to having been posted at the weekend by members of the finance team.

The trainee auditor knows from her prior work on the audit that the finance team often works weekends, especially at month-end, and thus she ought not to take the output of the analytic at face value. However, the trainee auditor places a lot of weight on the fact that a specialised piece of software deemed the journal entries unusual, and plans to perform further procedures over all of these journal entries. This is an example of automation bias, because she relies on the system output without considering whether her wider understanding might imply it is not fit for purpose.

Finally, the FRC publication encourages auditors to cultivate qualities to proactively support effective professional judgement, especially self-awareness, perceptiveness, listening skills, and willingness to consult with others.

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