Your Ask Joey ™ Answer

What are the 5 steps to audit data analytics (ADA)?

Universal CPA Review has included audit data analytics in the platform and has lecture videos, study guides, and multiple choice questions on the blueprint topic. The materials are located in the Audit section, specifically chapter 3 module 7. Start a 7-day trial here.

The AICPA has outlined 5 key steps to using audit data analytics (explained in more detail below). The visual below is your mental map to help you truly understand these topics. Every time you see a question or simulation on audit data analytics, you’ll have your mental map to guide you.

Audit Data Analytics and Baking a Cake???

The video below will take you through the 5 steps of audit data analytics and how to bake a cake. By the end of this ~16 min video, you will have the knowledge necessary to nail this topic on the audit exam.

AICPA 5 Steps to Audit Data Analytics

According to the AICPA, audit data analytics (ADAs) are techniques that help auditors leverage current technologies and move toward a more data-driven approach to planning or performing an audit. While audit data analytic techniques are often applied to external audits, they can be applied to internal audit engagements as well. The 5-step approach includes:

Step 1) Plan the Audit Data Analytics

The audit team should brainstorm where and when to apply audit data analytics within the audit engagement. This will consider the nature, extent, and timing (“NET”) of the audit engagement and whether consideration will be made during the risk assessment phase or when performing test of internal controls and/or substantive test of details.

Step 2) Access and prepare the data for the audit data analytics (ADA)

The audit team will subsequently identify the data and determine its original source to verify that it is in a usable format. Furthermore, the auditor will prepare the data for the analytical tools, a process known as data transformation. The data may need to be cleansed and/or normalized. Cleansed will help improve the quality of the information, while normalized eliminates duplicate data. Cleaning may be altering the date format to be more usable while normalizing is more about making similar items are treated the same even if there are slight differences in the values.

Step 3) Consider the relevance and reliability of the data used

In order to consider the overall relevance and reliability of data used within the audit data analytics, the auditor must first understand how the data was entered (e.g., system or manual entry). In addition, they must understand the data’s original source (e.g., internally or externally generated data) and whether the data is the original data or if it has been manipulated by the audit team (or anybody else) prior to the auditor receiving it. Finally, the auditor must assess the quality of the data received. 

Step 4) Perform the ADA

Once the auditor has performed the audit data analytics, they must subsequently analyze the results. If the initial results of the ADA indicate that aspects of its design or performance need to be revised, make appropriate revisions and reperform the ADA. If the auditor concludes that the ADA has been properly designed and performed, and the ADA has identified items that warrant further auditor considerations, plan and perform additional procedures on those items consistent with achieving the purpose and specific objectives of the ADA.

Step 5) Evaluate the results and come to conclusion on ADA’s overall effectiveness

Once the audit data analytics (ADA) has been performed, the auditor must assess the results and come to an appropriate conclusion.


Back To All Questions

You might also be interested in...

  • What is audit data analytics (ADA)?

    According to the AICPA, “Audit data analytics (ADAs) are a technique that can help you leverage current technologies and move toward a more data-driven approach to planning or performing an audit”. This is basically saying that if you utilize the data and analytics tools that are currently on the market, then you’ll be able to better analyze data and spot anomalies in the data (i.e. potential misstatements or issues with the internal control environment). The most common tools available on the market include Alteryx, Tableau, Power BI, and Python. Some of the larger public accounting firms have designed their own data analytics tools. The biggest benefit of audit data analytics is that audit sampling doesn’t need to be used because we can audit the entire population (yeah that is right, the entire population). So if the company has 1,000,000 sales transactions, we can test the full 1,000,000 rather than the 100 transaction that we “haphazardly” selected. Now I know we have painted a beautiful sunset when it comes to data analytics in an audit, but the main issue is that most clients still don’t have quality data. To effectively use data analytics in an audit, the client needs to provide high quality data. That means that its accurate in the system, the data is complete, and it includes the necessary fields to be effectively used for audit procedures. Now, don’t assume that you’ll work less hours in busy season. Technology and data analytics in audit will allow audit teams and accountants to work smarter and more efficiently.

  • July 2021 Changes to The CPA Exam: Everything You Need to Know

    Change is right around the corner! The talk of the (CPA) town is that changes are upon us and they are coming quickly. While this is not an overhaul in the way that CPA evolution will be in 2024, there are changes that are being made to all four sections (FAR, REG, AUD, and BEC) that all candidates should consider. Look, I am not trying to give you a complete panic attack, nor am I saying you need to scream into a pillow, okay, just hear me out! Just because there is change, it doesn’t necessarily mean that change is bad . So, let’s unpack the major changes going on and then we’ll let you decide if, in this case, change is good or bad. We’ve created a video for you that is meant to be educational and informative, but also lighthearted and provide some reassurance that you will be ready and that there is no reason to panic! So what are the changes for FAR? Let’s start by talking about the elephant in the room and discuss changes being made to the Financial Accounting & Reporting (FAR) exam. Everybody is naturally terrified of the big bad FAR exam, and that’s because there is naturally SO MUCH content that needs to be understood. However, I am here to tell you, FAR became a whole lot less scary! Changes made to the FAR exam only consist of content being removed, and namely, the removal of International Financial Reporting Standards (IFRS). All I can say is, I wish I didn’t have to take a FAR exam that included IFRS, so this is certainly something that should be celebrated. So what are the changes for REG (Regulation tax)? Like FAR, content is only being removed from the REG exam. This is also a big one because a lot of people struggle with understanding alternative minimum tax (AMT) as well as incorporating how much time should be allocated to certain areas like tax-exempt income, and federal securities registration within business law. Good news here, you no longer have to worry about any of these three. So what are the changes to AUD (audit)? Now, the audit exam is a different story, because unlike FAR and REG, audit is one of the four exam sections that has not only some content is being removed, but some topics are getting added. This is one of the two areas (in addition to BEC – see below) that will have an added emphasis on data analytics and information technology. Stay tuned. We are still learning to what extent the AICPA plans to include this in post July tests. So what are the changes in BEC (Business Environment Concepts)? Finally, the BEC exam will have both some content getting added and a little bit of content getting removed. Similar to Audit, BEC will primarily have an increased emphasis on data analytics and information technology content, but from a “I am running the business” perspective. Below is the official PDF that was released from the AICPA with the July 2021 exam changes. Final thoughts and our plan to update the materials on the Universal platform? Look, you can sit around and overthink this all you want, but the reality is, that kind of behavior really is unnecessary. The AICPA does this all the time, the exams are ALWAYS changing. The way the blueprint changes always seems like a whole lot of important words. At the end of the day, like all other things CPA related, there is a mental map and a systematic approach that can be built in your brain to ensure that you’re ready for anything they throw your way! To those of you who are Universal CPA students, we are working towards updating our platform with added material by Mid May and will have removal of content completed by June 30th. If you’re looking for some additional guidance about how to prepare for the CPA exam or what order you should schedule your exams, reach out to us!

  • What are predictive analytics?

    Predictive analytics use statistical techniques and forecasting models to predict possible future outcomes. There are a variety of approaches and techniques, but they can be grouped at a high-level into regression techniques and machine learning techniques. Many business are starting to rely on predictive analytics to identify patterns in historical and transactional data to understand where risks and opportunities are present. If used properly, predictive analytics can be used to predict the future and help companies minimize risk while capitalizing on opportunities. Basically any industry or business can use predictive analytics to minimize future risk and capitalize on potential opportunities. Predictive analytics are used in social networking, child protection, pharmaceuticals, healthcare, mobility, insurance, sports (including fantasy sports), business management, and marketing.