Bayesian Statistics for Audit Sampling
Highlighting the implementation of #bayesian statistics as an important direction for the improvement in audit quality and effectiveness
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Today, I want to highlight the important work being carried out by the Statistical Auditing Group at Nyenrode Business University. This group has been developing a sampling methodology that introduces Bayesian statistics into audit practice—offering auditors the potential to increase efficiency without compromising quality.
To be clear, I’m not advocating for Bayesian statistics over frequentist methods on a theoretical level. I’m not looking to enter into academic debates or take sides. But from a practical standpoint, the Bayesian approach to sampling often enables auditors to test fewer items while still maintaining—or even improving—audit quality, compared to traditional frequentist approaches.
A key contribution in this area is the work of Dr. Koen Derks, who published Bayesian Benefits for Auditing: A Proposal to Innovate Audit Methodology. The book provides valuable insight into the methodology and makes a compelling case for its adoption. It’s a must-read for anyone in the audit profession.
This video is a pretty accurate capture of how I was reading this book:
For those interested in applying this methodology, there is a dedicated tool available:
“JASP for Audit (also known as the Audit module) is an add-on module for JASP that streamlines the process of statistical auditing. The Audit module offers a wide range of functionalities, including (but not limited to) planning, executing, evaluating, and documenting statistical audit samples. Specifically, it comprises analysis tools for determining sample sizes, selecting items using standard audit sampling methodology, and inferring the population misstatement based on the sample data or the summary statistics of the sample. Furthermore, the Audit module also includes tools for data auditing. The module provides Bayesian equivalents of most analyses, enabling users to incorporate pre-existing audit information into the statistical procedure. In all analyses, the Audit module provides comprehensive explanatory text that assists the auditor in understanding, documenting and communicating the statistical results.”
You can find a software package that allows to apply Bayesian statistics to practical audit tasks here: JaspAudit Github.