An Unintended Consequence of Full Population Testing on Auditors’ Professional Skepticism

The emergence of data analytics allows auditors to test entire populations of data drawn from clients’ information systems, rather than relying solely on sampling methods. While full population testing increases the sufficiency – or quantity – of evidence examined, it typically relies heavily on client-internal data. Therefore, auditors must remain skeptical when subsequent, more appropriate evidence from external sources contradicts a client’s financial reporting. In an experiment, we find that auditors using full population testing, compared to sample testing, are less likely to subsequently exercise skeptical actions when an external, industry growth trend reveals a fraud red flag. We do not find that this unintended consequence is exacerbated when full population testing results are visualized (versus tabulated), a typical format used for presenting data analytic tests in practice.

Main Takeaways

• Auditors using full population testing, compared to sample testing, are less likely to exercise skeptical actions when subsequently confronted with a fraud red flag revealed by an external industry growth trend.
• Auditors using full population testing, compared to sample testing, overestimate their evaluation of the appropriateness of client-internal evidence. Presenting the testing results in a visualized compared to tabulated form does not exacerbate the negative effect of full population testing on auditors’ skeptical actions.