It’s no secret that internal audit is being pulled in several different directions these days and that the demands on the function are greater than they have ever been. A partial solution to the mounting workload has been available for years now, but audit shops have been slow to embrace it. Is it time to give automation and advanced data analysis a closer look?
Corporate internal audit departments are stretched thin. The endless string of attacks on corporate networks and the data they hold have caused companies to enlist internal audit to ensure that proper cyber-security controls are in place to protect data. Information security audits are now occupying a larger portion of internal audit’s resources. Meanwhile, at many global companies supply chain risks are increasing and internal audit is playing a larger role there too.
Still, recent accounting problems at companies like Toshiba and others serve as reminders that the traditional demands on internal audit aren’t going away either. In fact, the Securities and Exchange Commission has said it is providing greater scrutiny to accounting and financial fraud, and the numbers of cases involving financial reporting problems are on the rise once again.
While all of these areas are placing greater demands on audit, few companies are devoting more resources to the audit function. According to a 2015 survey by The Institute of Internal Auditors (IIA), half of those surveyed said internal audit budgets would remain the same and 9 percent expect budgets to decline in the coming year. Even if companies wanted to beef up internal audit, several surveys point to a talent gap, indicating that an army of well-equipped internal audit reserves isn’t going to show up anytime soon.
Nor are internal audit shops levering technology to help them do their jobs better, at least not the majority of them. According to a survey of more than 800 audit executives and staffers conducted last year by Protiviti, a business consulting and internal audit firm, improving data analysis technologies and techniques ranked as the top area where the most improvement was needed.
These respondents realize that internal audit, like nearly every other profession, needs to embrace the latest technology and use data analytics to more quickly find the red flags and other problems so they can use their valuable time investigating the problem spots and less time fishing for them in the vast oceans of data their companies are now collecting and storing.
Professional associations are realizing the need too. The AICPA recently joined forces with Rutgers Business School to form a data analytics research initiative to examine ways that data analytics can improve audits. The AICPA’s task force on data analytics is also working on developing standards for audit data, as well as a framework that maps innovative data analytic procedures to traditional audit objectives.
These initiatives could go a long way in helping companies adopt automation and technology to improve the audit function. Computer-assisted audit tools (CAATs) and data analysis tools aren’t going to magically evaporate the piling internal audit workload, but they could lighten the load. They could also free audit resources to tackle the many emerging issues internal auditors will encounter this year.