In short
Audit data analytics is the analysis of patterns, anomalies and other information in the data behind an audit area, using modeling and visualization, to plan or perform the audit.
Key takeaways
- They can examine 100% of a population, for example every journal entry or every sales transaction.
- Items flagged need follow-up; a large number of exceptions may point to a control deficiency or a problem with the test.
- The auditor must evaluate whether the underlying data is accurate and complete.
Where it's tested
AUD: Analytical Procedures — study notes, a five-minute revision sheet and practice questions.
Practise: 3 questions
Question 1 of 3 · 0 answered
At which stages of the audit are analytical procedures REQUIRED?