Definition
AU-C 500 lists three ways to select items for testing: select all items, select specific items, or use audit sampling. Full-population testing is the first. Analytics tools let an auditor run a test, such as matching every invoice to a receiving record or recalculating every depreciation entry, across the whole population. When it can be done, sampling risk is not a concern for that test.
Why it matters in an audit or review
Examining all items is more efficient when data is electronic and the test can be coded. The limit is data quality. The auditor still needs evidence that the data extract is complete and accurate, as AU-C 500 requires for information produced by the entity. Exceptions found still need investigation by the auditor.
Example
Illustrative: a client has 48,000 sales orders. The auditor tests all of them for shipping date later than invoice date, and 312 items fail. After review, 40 relate to period-end and are tested for cutoff.
Common mistakes
- Skipping completeness checks on the extract.
- Treating a clean full-population test as covering all assertions. It covers only the attribute tested.
Sources
- AICPA, AU-C Section 500, Audit Evidence, selecting items for testing and information used as audit evidence
- AICPA, AU-C Section 330, Performing Audit Procedures in Response to Assessed Risks and Evaluating the Audit Evidence Obtained
Definitions paraphrase AICPA and FASB guidance; read the standard itself before relying on a requirement. Example figures are illustrative. This page is guidance, not professional advice. Report an error