Audit evolution in action: Part 2

The auditing profession was already in the midst of transformation, thanks to technological advances and other factors. Then, the COVID-19 pandemic came along and accelerated those changes, further challenging auditors and their view of business as usual. Part 1 was an overview of the audit landscape. In part 2, speakers Carolyn Newman and Jon Cardiello, CPA, share insight into the topic of audit data analytics and how the tools can help to continue the transformation of auditing.

What you’ll learn from this episode:

• An overview of audit data analytics.
• Some of the ways that Cardiello’s firm employs audit data analytics.
• Why some firms might be hesitant to apply an analytics-based approach to auditing.
• The reasons behind Newman saying, “fear not the data.”

Play the episode below or read the edited transcript:

To comment on this episode or to suggest an idea for another episode, contact Neil Amato, a JofA senior editor, at Neil.Amato@aicpa-cima.com.

Transcript:

Neil Amato: This is the Journal of Accountancy podcast, and I’m senior editor Neil Amato. Today’s episode is the second part of a monthly series that focuses on the changing nature of auditing. We’re specifically talking today about how analytics are part of audit transformation. We have two guests: Carolyn Newman, the founder and president of Audimation services in Houston, and Jon Cardiello, a Pittsburgh-based CPA with Schneider Downs, where he is an audit manager and also internally manages the firm’s ADAPT program. That’s an acronym we’ll define in just a bit. Carolyn, first, how would you describe the current landscape of audit data analytics?

Carolyn Newman: Hi, Neil, and thanks for having me on. Audit data analytics is going through an exciting time. There’s a lot of growth and a lot of new things being offered. The tools are just getting more powerful, more able to do the things that auditors want them to do, and I think that the movement recently towards updating the audit evidence standards is going to just really open the floodgates for audit data analytics.

Amato: Let’s talk some about the why behind analytics. And I guess first, what are analytics for those who may not be all that familiar and how can they be used and what’s the value they bring to firms and clients?

Newman: Sure, Neil, analytics are basically analysis of lots of data, an entire population, for example, where you can get the complete set and go through it and find things like anomalies or trends or potential risk areas. How it’s used is by importing the data into the various tools that you would want to use and then running a series of queries; different packages have different ways of doing that. But the whole goal is to make the audit more efficient, more effective. In particular, you can improve audit quality with audit data analytics because you’re not constrained by sampling. You can look at that whole population and know from your analysis how many transactions or records meet a criterion without just trying to project the thing that you find in the evidence.

To me, one of the best uses and benefits of audit analytics is helping you understand the client system. Because once you get your hands on the transactional data and gain an understanding of the flow of data, the profile if you will, of that data, you can plan your audit more effectively and more precisely. So this, to me, points to planning. And everybody knows that the best audits are the ones that are planned well. And so if you can focus what you want to look on because you’ve used audit data analytics to risk assess and identify things to focus on, the auditors can spend their time on that instead of looking and guessing and not being sure.

Amato: Thank you for that, Carolyn. Jon, I mentioned the ADAPT acronym in my intro. Do you want to define what that is and what you do with that at Schneider Downs?

Jon Cardiello: Sure, thanks, Neil, and good to be with you today. ADAPT stands for Automation and Data Analytics Process Team. Essentially, it’s a bunch of words to say we have a dedicated group of people who are focused and who are specialists with different pieces of technology or different softwares that look to implement technology-driven solutions to the audit process. As a member of that, I kind of oversee that group. We have an internal I-ADAPT group that focuses on the audit process specifically, and we have an external analytics base group that focuses more so on meeting client needs.

Amato: I’d say your firm certainly is into analytics given that intro you just gave. But so I’m going to ask you though, what do you think is keeping firms from fully embracing an analytics-based approach to auditing?

Cardiello: Sure. With any new technology or any new process or anything new, people are always a little bit maybe passive to adopting new technology or new items. And there’s always a learning curve associated with that. So as an auditor, whenever I think of analytics, I usually think of high-level ratio analysis of financial results for clients. So, that part of it is not very difficult for firms to adopt because people are already used to thinking about it in that context. I think where it gets more challenging is the deeper levels of analysis as Carolyn alluded to, maybe replacing sampling with a detailed analysis of populations, targeting specific risk factors, whether it be qualitative or quantitative.

A lot of companies are still learning, especially a lot of people in the accounting industry are still learning, how do we use data or how do we coordinate with the folks that oversee the data in order to bring meaning to that data in a financial context? There’s a lot of tried-and-true methods out there, but there’s also a lot that’s new on the horizon. So one the challenges is just working with our clients to decide what is available. I think to what Carolyn alluded to was what are the controls around this data, the concept of data integrity, what’s the flow of data, who touches each piece of the data throughout the process.

And in my experience, usually this is a little bit of a problem-solving exercise, but it’s also in more instances than not, this type of data is available. It’s just a matter of finding it and working together with our clients to do so.

Amato: How is Schneider Downs approaching dynamic auditing and, related to that, how does that navigating the technology kind of tie into people challenges?

Cardiello: Sure, so Schneider Downs takes, obviously, has the ADAPT group that focuses on those issues, and I’d say we usually have an intentional approach to technology-driven solutions. So we’re asking ourselves questions like, “What problems do we have? What takes the most time on our audits? What’s highly repetitive or what requires a lot of data entry? Where’s the risk on these audits?”

That went back to that theme of targeting specific qualitative or quantitative risks and in populations. And then we kind of look at these problems or these areas of opportunity in the audit process as areas where we can develop value-added solutions to the audit process.

Amato: Carolyn, is there anything in Jon’s answer that kind of sparks a response from you?

Newman: Yes, he was talking about the ability to give more insight and more meaningful recommendations to the client. So many times I can remember when I was an auditor, you’ve got that budget, and if you don’t have time, guess what gets left out? It’s the thinking that goes into really useful and insightful commentary and suggestions for the client. And they all expect that. And so to me, a real benefit of audit data analytics is the better insights that you can get and the more time to be able to offer those better suggestions. And that will increase the relevance of every auditor.

Amato: So we’ve touched on just a small part of this topic. Obviously, there’s always more you can say. Go to Jon first, is there anything you’d like to expand on or to add in closing? And then I’ll go to Carolyn.

Cardiello: Sure, Neil. I would just say that Carolyn brought up a good point about the client-facing side of the data analytics as well. A lot of times as auditors we look at how can we use data analytics or process automation to make our audits more efficient. But it also sometimes eases the lift from the client’s standpoint if we’re interfacing more with their data and understanding the data and how the flow of that data, the controls around that data, that might help us alleviate a lot of the paper copies or forms that we’re looking at. Especially today as people are moving into more of a remote environment or as people are enjoying a remote environment, these are some of the tools that we can use to facilitate that type of a transition.

Newman: And I would just say fear not the data. If your firm invests in tools or if they won’t and you encourage them to, play around with that data. Most of them you can’t really mess up the data because it’s a copy. But the more familiar you get with data structures, sources of data, big data, there is audit evidence in some of that big data. But if you’re uneducated or unpracticed, if you will, in getting that data and working with it, you’re not going to be able to add that extra level of either assurance or benefit to your clients.

Amato: Carolyn, Jon, thank you so much for being part of the show today and part of this series on audit transformation.

Cardiello: Thanks, Neil.

Newman: Thank you.