2018 Audit Team Trends with Deniz Appelbaum

June 6, 2018

Earlier this year we chatted with a panel of experts in the audit industry to gather their opinions on what we should expect to see in audit trends throughout 2018. Here is what Deniz Appelbaum, MBA, PhD and Assistant Professor of Accounting and Finance at Montclair State University had to say.

Q: If you could build the ideal audit team for your industry, how many auditors would you have on your team?

Deniz: In my opinion, the ideal audit team should have an audit partner, a manager or someone who is coordinating audits and a few auditors who are industry experts in their particular domain for that type of business. The latter would also act more or less like data scientists and be pulling data from the various information systems and conducting data analysis.

Q: What would be the specific skillset of each team member?

Deniz: All members of the audit team would have an accounting and/or audit background. They would also need to have also have the ability to work the data, which includes knowing how to extract it, or at least code an automated process that could actually extract the data, normalize it and prepare it for analysis.

Ideally there would be at least one team member who would have obtained certifications in certain audit software, or have gone through university and done data analytics coursework. In addition, they should have knowledge of other types of coding languages such as Python, and have some familiarity with Blockchain, artificial intelligence and other new technologies.

Q: How do you think the audit teams of 2017 and 2018 will differ?

Deniz: Sadly, I feel that the audit profession is really, really far behind in the business world currently. They’re very saddled and nervous about the PCAOB (Public Company Accounting Oversight Board) regulations, which don’t discourage the use of data analytics but also don’t encourage it. There is some basic use of analytics in the engagement, mainly for extraction and some general ledger testing, but it’s very basic.

Going forward, there are some encouraging things. For example, the PCAOB has recently mandated that in future a critical audit matters discussion and other facts must be included in the audit opinion. They’re seeking information about the audit itself, such as any issues the auditor experienced during the engagement, or anything that was of note. This will be a great way to provide more information on the opinion side.

Those on the client side of the audit profession, though, are going to demand more information and value from the engagement. They also want the engagement to be more efficient because of technology they have employed in their own companies. They won’t be as tolerant if their auditor is still employing small manual samples from large datasets. Sixty sample transactions from a large dataset doesn’t make any sense. True value comes from representing the entire dataset. So I see that there might be a reduced usage of sampling initially, with more auditors testing 100 percent of the transactions, but there will also be more pressure to reduce false-positives in the resulting dataset.

The problem, however, is that audits present two conflicting issues: efficiency and effectiveness. ‘Efficient’ ought to be like testing minimal amounts of transactions and doing just the bare necessity to form an audit opinion. ‘Effective’ would be testing everything. Because of IDEA and other types of technology now, we can officially test 100 percent of the transactions and be effective as well. We’ll see a slight shift in the audit engagement next year, with more use of IDEA and other types of tools beyond what they’re currently used for.

Q: How do you think changes in the 2017 audit landscape will affect audit teams in 2018? (e.g., at the time of our discussion, PwC was in court because a regulator was attempting to hold the company liable for losses arising after PwC failed to detect fraud at a bank that later collapsed.)

Deniz: This is the first in a long time that auditors have been brought to court over audit failures. While it relates to technology, it’s more about auditor judgement—or perhaps it is negligence, or that they’ve been working for these clients for a long time and got comfortable.

But the PCOAB is starting to examine the use of more data analytics in the audit engagement because on the advisory side of firms they’re very innovative and progressive. They’re jumping on Blockchain, artificial intelligence in audit, etc. They’re even looking at continuous auditing and continuous monitoring. But the engagement side has been very conservative. The benefits of analytics will take over this part of the audit as well because the clients are going to demand it from their auditors. Clients are producing 100 percent analysis of their own transactions; auditors should have access to the same volume of data and be able to conduct their own analytics on it. I believe that right now we’re on the cusp of a big surge or change in the audit engagement.

Q: What role do you foresee data analytics playing in the audit teams of 2018?

Deniz: Data analytics will play an increasingly important role in audit teams, mainly because auditors cannot function effectively and efficiently in an increasingly technically sophisticated environment without doing so. They have no choice. They cannot be proficient or be sure of accuracy in the audit if they are not deploying more audit analytics, specifically tools like IDEA or other types of audit automation software.

The big challenge will be training and educating current auditors and accountants, as well as future auditors. Auditors who have been in the profession for a while may have difficulty in adjusting to the changes.

For incoming auditors or those studying to be auditors, there’s some catching up that has to be made in education and coursework. Data analytics training really should be offered in the underlying coursework at the undergraduate level, not just in Master’s programs. For example, in my Fundamental Audits class, the students are using IDEA and Tableau and are learning to use data analytics in audits. They can personalize and understand the concepts better with IDEA as opposed to just an abstract concept they’re taught in class with case studies that are qualitative and judgmental in nature rather than hardcore, basic analytics. My students have told me they’ve gone to second and third-level interviews with firms, and they’re the only candidates who have had experience with data analytics. It puts them way ahead of their competition.

To learn what our other industry experts had to say about these questions, download your copy of the full 2018 Audit Team Trends Report now


About Anu Sood:

Anu Sood is the Director of Product and Corporate Marketing at CaseWare Analytics and is responsible for the company’s global marketing strategy. Prior to CaseWare Analytics, Anu worked in various roles in the high-tech industry and her accomplishments range from writing software for telephone switches to launching a new global satellite communication service. Anu has extensive experience in strategic marketing, corporate communications, demand generation, content marketing, product management, product marketing and technology development. 

Connect:    Anu Sood 

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