Three Ways to Enhance Audit Quality with Audit Data Analytics

Why Apply Audit Data Analytics?

Audit data analytics is a hot topic. In fact, there has been a loud call to action recently. That call to action is this. We must transition to applying audit data analytics (ADA) in performing our audit engagements. By applying audit data analytics, it allows those in the profession to enhance audit quality by working more effectively with large data sets. This in turn enhances the quality of the audit for three main reasons.

  1. There will be a stronger understanding of the entity’s operation and associated risks, including the risk of fraud.
  2. Applying audit data analytics will help detect material misstatements by allowing 100% of items in a population to be examined thereby effectively managing sampling risk.
  3. It will improve the communication of those charged with governance of audited entities because visualization dashboards offer an effective way to discuss insights or key matters, which are important in understanding why events may have occurred and the possible implication for control, financial reporting, or governance processes.

Additionally, applying audit data analytics is a giant step towards meeting the objectives of the AICPA RADAR initiative. The desired outcome of RADAR for the auditing profession is improved audit effectiveness through the integration of data analytics and related technologies into everyday practice.

Define Audit Data Analytics

Before we go any further, what exactly is audit data analytics (ADA)? ADAs are defined 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”.(1)

ADAs are similar to CAATs. However, audit data analytics have evolved and now enable auditors to use techniques to visualize the data and use it throughout the entire audit.

Audit Data Analytics Examples

As can be seen in the below chart, there are significant opportunities to use ADAs throughout the entire audit process. Start with risk assessment procedures and go all the way through procedures to help form the overall conclusion. Check out the following three examples.



  • Example 1:  Perform a preliminary “general ledger account balance analysis” as part of the risk assessment of the audit. This will allow you to identify unusual changes, unexpected trends, and risky transactions. It is important for the auditor to define risk transaction scores and have a full audit trail. Another way to accomplish this goal is to visualize key financial statement ratios.  This will help indicate areas where there is a higher risk of material misstatement.
    • Tip: If you can access the client’s general ledger system throughout the year, there is an opportunity for continuous auditing and timely conversations about unusual transactions vs. waiting until the end of the year.
  • Example 2:  Select a “sample for test of controls” and “test of details”. Instead of manually picking your sample items – use technology to create a true random sample! That eliminates any potential auditor bias in the selection process. Many auditors have historically just picked “25”. Now though, using audit data analytics, you can pick a true sample.
  • Example 3:  Use an ADA as part of completing substantive analytical procedures. As defined in AU-C section 520, analytical procedures evaluate financial information through analysis of plausible relationships among both financial and non-financial data. Before you perform the analytical, remember it is critical to develop the expectation of the results so you can compare the results and investigate the difference. One way to accomplish this is by using predictive modeling, such as a regression analysis, to predict amounts for future periods to help identify the potential for material misstatement. This analysis will give you a precise method for forming an opinion. This opinion will then allow you to include a larger number of variables in the analysis.
    • Tip: Consider using the visualization of these trends for more effective conversations with your client. This in turn will help them understand how they can better run their business.

Call to action

In closing, keep in mind that the above are just a few examples of how to use technology to enhance the quality of your audits. There are hundreds of tests available in TeamMate Analytics. The solution’s Test Library comes pre-packaged in customizable modules.  These modules stand ready for your firm to run with guidance to help interpret the results. In addition, coming soon in CCH ProSystem fx Knowledge Coach, there will be a visual indicator added to the substantive audit programs to indicate when (and how) to use TeamMate Analytics to complete a substantive procedure. Wolters Kluwer’s Integrated Audit Approach is continuing to expand to support the evolution of the audit and allow you to challenge your status quo. Learn more about TeamMate Analytics today.

 (1) Byrnes, Paul; Criste, Tom; Stewart, Trevor; and Vasarhelyi, Miklos. “Reimaging Auditing in a Wired World.”



Cathy Rowe

All stories by: Cathy Rowe