As new and emerging technologies continue to flood the marketplace, auditors face a variety of techniques that could potentially transform the traditional financial statement audit, making it more efficient and adding more value. Understanding how these new techniques can be used throughout the audit, under the current auditing standards, is important for firms of all sizes.
In response, the American Institute of CPAs (AICPA) developed a new publication entitled, Guide to Audit Data Analytics. This guide demonstrates how audit data analytics (ADAs) can be applied to the current financial statement audit to gather audit evidence. This guide complements and expands upon the AICPA’s Analytical Procedures guide and will benefit firms of all sizes. From those who may not be familiar with ADAs to those who may use them on a day-to-day basis, this guide has something for every expertise. Our intent is to introduce auditors who may not be familiar with ADAs to basic concepts and illustrative examples of how they might be used in practice. We also offer guidance to those who may be more familiar with how they can be used within the current auditing standards.
Audit data analytics
This guide defines ADAs as: “The science and art of discovering and analyzing patterns, identifying anomalies and extracting other useful information in data underlying or related to the subject matter of an audit through analysis, modeling and visualization for the purpose of planning or performing the audit.” Simply put, ADAs are techniques that can be used to perform a number of audit procedures (i.e., risk assessment, tests of details, substantive analytical procedures and in forming an overall conclusion) to gather audit evidence.
The benefits of using ADAs can include:
Improved understanding of entity’s operations and associated risks, including the risk of fraud
Increased potential for detecting material misstatements
Improved communications with those charged with governance of audited entities
Guide to Audit Data Analytics will help auditors decide whether — and, if so, how — to use ADAs throughout the financial statement audit. The following chapters are included in the guide:
Using ADAs in performing risk assessment procedures and in procedures to assist when forming an overall conclusion
Using ADAs in performing substantive analytical procedures
Using ADAs in performing tests of details
Each chapter includes a separate appendix with various illustrative examples detailing how ADAs can be applied to each phase of the audit.
The following additional appendix also is included:
Matters to consider regarding the reliability of data — The purpose of this appendix is to provide some items to consider when assessing the reliability of data to be used.
We believe that Guide to Audit Data Analytics is a critical first step to understanding what ADAs are and how they can be applied to the audit under the current auditing standards. It is crucial for the profession to move forward and stay abreast of these new techniques.
The AICPA’s Guide to Audit Data Analytics was developed by its Assurance Services Executive Committee (ASEC) and Auditing Standards Board’s (ASB) Audit Data Analytics Guide Working Group.
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