Internal auditors with data analytics experience are becoming the rock stars of the profession. Not only are they in high demand among leading companies and can earn a premium over internal auditors without data analytics capabilities, but they are also gaining greater influence in internal audit departments that are eager to infuse their audits with more analytics.
It’s taken a long time—using data analytics in internal audit dates back at least 30 years, say some experts—and companies cover the spectrum in terms of their data analytics sophistication, but some companies are moving up the maturity curve.
Most use the approach as an alternative to sampling. Others are using data analytics to create automated monitoring systems that act as an “always-on” check of such internal auditing mainstays as auditing travel and expense reporting or accounts payable for fraud, abuse, or other problems. This application sometimes referred to as “continuous auditing,” relies heavily on analytics. Leading-edge companies apply data analytics to nearly every audit they do and even to when determining what audit projects to undertake.
To carry out these initiatives, many companies are desperate to hire more data analytics experts, but the market is competitive, particularly for those with internal audit backgrounds. An analysis conducted by CareerBuilder last year found that job postings searching for a “data analyst” numbered more than 800,000 in the 12 months from September 2015 to August 2016, while the active candidates who were searching for data analyst jobs numbered only about 125,000 during that same period. That’s greater than a 6-to-1 ratio!
According to Anthony Thornburg, president of recruitment firm General Ledger Resources, internal auditors with data analytics experience are in high demand and can earn a 20 percent premium over those who don’t have such experience. “Leading-edge internal audit shops are moving toward using more data analytics and automation to drive down cost and improve efficiency,” says Thornburg.
Candidates who know they can earn a premium by acquiring data analytics skills are looking to boost their capabilities. While you can’t learn the skill overnight, most experts we talked to say someone who is driven can become proficient in as little as 6 to 12 months. So, where to begin?
Start Small and Build Up
Jumping into the deep waters of analytics can seem daunting, but it doesn’t have to be. Yves Froude, a data analytics expert at the World Bank, says the best way to get started is to start small. “It usually starts out of personal frustration over something you want to test, but that can't be done with the normal means. That gives them the drive,” he says. His advice is to find a data-rich environment, such as supplier lists or accounts payable, and start playing with the data.
You might start, for example, by trying to answer a question such as: “Did anyone post a journal entry over the weekend?” or, “Do any of my vendors share the same mailing address as any of my employees?” Next, think of how to work with the data to isolate the answer.
“Analytics is not as technical as you may think. The concept is to use data analysis to obtain answers to your business questions so that you can make informed decisions rather than a rough guess or based on speculation,” says Alex Fung, practice manager at ACL, a provider of analytics software.
Another good starting point is putting concepts first and the tools second. For example, learning about such statistical methods as regression analysis, variance, and correlation. “A lot of people want to go out and learn the tools first, but then they don’t know how to apply them. You need to learn the basic concepts first,” says Steve Biskie, managing director of High Water Advisors, a GRC and audit advisory firm that specializes in data analytics, and a senior MISTI data analytics training instructor.
Don’t underestimate free resources that can be found online. “There are innumerable tutorials online that are only a Google away to find out how to solve a specific technical problem, such as the SQL command for checking if a date is a weekend or weekday,” says Andrew Clark, IT auditor and data scientist at Astec Industries, and a keynote speaker at MISTI’s upcoming ITAC Conference. Khan Academy is one such online resource that offers several tutorials in statistical analysis.
Push for Answers, Demonstrate Results
One obstacle to learning is how thinly stretched most audit departments are. They simply don’t have the bandwidth to let internal auditors experiment with analytics. “You might need to start that experimentation on your own time or by staying late,” says Biskie. He also advises volunteering for a project that could expose you to using basic analytics.
Others might stumble on analytics as a solution to a problem an internal auditor needs to solve. “You have to start asking about what the data might be able to tell you. Maybe it’s a problem that’s been keeping you up at night,” says Froude. From there, he says, you look for greater opportunities.
For internal auditors that are trying to build their skills with common data analytics tools, focus on areas where you have easy access to data, in a process you understand well, and that is common enough that you can borrow ideas from similar projects in other companies, says Biskie. Some examples are travel and expense reporting, PCards, and accounts payable.
You could also start a small project using data analytics to add value to audits. According to Fung, the two most important aspects to getting buy-in from decision-makers are proof of value and return on investment. For example: “If you suspect there is revenue leak in AP payments, which most of the time there is, use tools even like Excel to establish a case that using data analysis helps you find problems and investing in proper tools can help find more money even easier,” says Fung.
Biskie agrees that you can build trust by addressing a pain point with data analytics. Easily automated areas are good candidates, such as selecting a sample every quarter for Sarbanes-Oxley testing. "You want to look for areas where the current process isn't enjoyable, such as where an auditor has to spend hours consolidating reports into a single Excel spreadsheet before analysis can begin, or where the use of data could allow them to see things they hadn't seen before and therefore ask better questions when planning the audit," says Biskie.
Training and Certification
Once you have a taste for analytics and understand the basics, training can be a great way to open doors to more powerful tools, such as ACL or Structured Query Language (SQL), a database language.
In fact, two-thirds of those who responded to an Institute of Internal Auditors’ 2017 Pulse of Internal Audit study say that their staff needs more training in data mining and analytics. “Training in data mining and analytics builds competencies and instills self-confidence in internal auditors,” the report’s authors wrote.
Other tools to learn include IDEA, Python, and SAS. “At some point, you are probably going to need some training to build on your foundation and realize what else can be done with analytics,” says Froude. Webinars and conferences are also great places to build on data analytics skills.
With knowledge of specific tools in hand, analysts can also get advanced training on successfully applying analytics in certain ways. There are courses, for example, on using analytics to search for fraud, or more generally in internal audits.
Certifications can be a good way to demonstrate proficiency in certain tools and capabilities. ACL, for example, offers the ACL Certified Data Analyst (ACDA) credential. Also, consider Certified Analytics Professional (CAP) and the Associate Certified Analytics Professional, aimed more at entry-level analytics professionals.
If you want to completely immerse yourself in the field, pursue an advanced degree. That’s where the data analytics journey led Astec’s Clark. “It started when I wanted to understand how databases work and how to extract insights from them. One thing led to another and I went to graduate school for Data Science,” he says.
Pursuing data analytics might start as a curiosity or as a necessity to solving an internal audit problem but it can change your career and your organization for the better. “It’s like learning how to swim,” says Froude. “You just have to jump in.” Be careful, he warns: “It can easily become a lifelong journey.”
Joseph McCafferty is Editor & Publisher of Internal Audit 360°