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, they are also winning plum assignments and 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 sophistication with using data analytics in the internal audit department, but some companies are pushing the boundaries of what they are doing with analytics during audits and moving up the maturity curve.
Most use the approach as an alternative to sampling to analyze entire sets of data to look for red flags, anomalies, indicators of fraud, and outliers. 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 is sometimes referred to as “continuous auditing” and relies heavily on analytics. Leading edge companies, however, are applying data analytics to nearly every audit they do and are also using the approach to determine what audit projects to undertake.
To carry out these initiatives, many companies are desperate to hire more individuals with data analytics skills, but the market is competitive, particularly for those with internal audit backgrounds as well. An analysis conducted by CareerBuilder last year found that jobs postings that were 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. Not bad odds for those with the right skills and experience. Indeed, an Institute of Internal Auditors’ CBOK report listed “data mining and analytics” among the top seven skills that chief audit executives are looking to add to their departments.
Wade Brylow, director of internal audit at Northrop Grumman, is one of them. He says, however, that finding internal auditors with data analytics experience can be difficult. At Northrop Grumman, for example, the internal audit department has had a data analytics position that has gone unfilled for almost two years. "It's very difficult to find candidates who are really good at data analytics," says Brylow. He adds that competition from other industries, particularly financial services firms, is driving salaries higher. "They can afford to pay a little more," he adds.
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, and while it’s not something you are going to pick up overnight, most experts we talked to say someone who is driven and smart can learn the essentials and 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 a 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 whose answer lies somewhere in the data, such as: “Did anyone post a journal entry over the weekend?” or, “Do any of my venders share the same mailing address as any of my employees?” Next, you starting thinking of how to manipulate the data so that you might be able to isolate the answer.
Others endorse this idea of experimentation as a way to get started using analytics. “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 important starting point, advise experts, is to put the concepts first and the tools second. That could mean 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.
Many experts advise those who want to get exposure to data analytics to resist the temptation to start by learning the top software packages. “There are tools like ACL that are purposely built for it, but it doesn't mean you can't start the journey with Excel if you can't access other tools,” says Fung. “Remember that the experience comes from doing it and living in it, not what tools you use to do so.”
Fung’s not the only one to suggest getting started with Excel, which most internal auditors are likely to have some comfort with. “Excel can do quite a lot and is a great place to start,” agrees Froude. For those who don’t have advanced Excel knowledge, there are several free tutorials online, such as YouTube videos on using pivot tables, statistical analysis, and modeling.
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. An online resource that can be a great place to learn about data analytics concepts and statistical analysis is Khan Academy, which offers several tutorials in statistical analysis.
Push for Answers, Demonstrate Results
One of the problems for internal auditors that want to get started in data analytics is that most audit departments are stretched thin and don’t have the bandwidth to let internal auditors experiment with analytics if they aren’t assured of results. “You might need to start that experimentation on your own time or by staying late,” says Biskie. He also advises those who are interested to simply ask to take on a project that could expose them 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 can begin to start looking at what else you can do.
For internal auditors that are trying to build their skills and increase their confidence in using some of the common data analytics tools, early projects should be in areas where they have easy access to data, in a processes they understand well, and that are common enough that internal auditors can easily borrow ideas that have worked well in other companies, says Biskie. Some examples are those are travel and expense reporting, PCards, and accounts payable, which, he says, are common starting points.
Another way to get a foot in the door is to do a small project to prove that data analytics can provide 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 agree that addressing a pain point with data anlytics can help win over non-believers and may be able to get the ball rolling on data analytics in the department. Areas where people are spending time doing things that could be easily automated 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
While training might not be the place to start on the data analytics journey, it’s an essential part of building analytics skills. Once internal auditors have a taste for analytics and understand the basic concepts of how to apply them, training can be a great way to open doors to more powerful tools, such as ACL or Structured Query Language (SQL), a computer language for retrieval and management of data in a database.
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 for data analytics that individuals can pursue training on include IDEA, Python, SAS, and others. “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.
Pursuing certifications can be a good way to demonstrate proficiency in certain tools and data analytics capabilities. ACL, for example, offers the ACL Certified Data Analyst (ACDA) credential. Another certification is the Certified Analytics Professional (CAP), as well as the Associate Certified Analytics Professional, aimed more at entry level analytics professionals.
For individuals that want to completely immerse themselves in the field, there are plenty of advanced degrees available. 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 that’s been keeping you up at night, but it can turn into a specialty that can pay big dividends, both for the professionals that embrace it and the companies they serve. “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.”
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