When should Python be used for audit sampling instead of full-population testing?

author: AcadiFi Team

Answer:

Use sampling when the audit objective requires item-level evidence that cannot be fully automated, or when the population is too complex for a reliable full-population rule. Python can help select random samples, stratified samples, or targeted high-risk items, but the method must be documented.

The workpaper should show the population, exclusions, sample size rationale, selection method, and seed or logic used to reproduce the sample. If analytics also identify exceptions, separate the exception population from the sample population so the conclusion is clear.

Full-population testing is powerful when the criteria are objective and data is reliable. Sampling is still useful when judgment, inspection, or qualitative evidence is needed.