Data Analytics and the Future of Internal Audit
IIARF, Grant Thornton book urges practitioners to embrace data-driven world
ALTAMONTE SPRINGS, Fla. (Feb. 23, 2016) — Imagine the ideal internal audit function, where data is abundant, intimate knowledge of the enterprise allows for continuous monitoring of risks and opportunities, and internal audit leverages the coveted space of trusted strategic partner to the C-suite.
It is all within reach for organizations that can successfully incorporate data analytics fully into their operations, according to Data Analytics, a new book published by The Institute of Internal Auditors Research Foundation (IIARF) and authored by Grant Thornton LLP.
The publication, which will launch at The Institute of Internal Auditors’ (IIA) General Audit Management (GAM) conference March 7-9, in Dallas, Texas, does more than paint a rosy picture of what could be. It provides a roadmap for setting up a strong data analytics program and warns that practitioners who fail to do so may face the risk of becoming obsolete.
The book provides internal auditors with a Data Analytics Framework to help assess their current status and define future actions through a four-step process:
- Envision how data analytics will work for the organization
- Evaluate current capabilities
- Enhance people, process, and technology
- Implement, monitor and evolve the process once in place.
The book’s authors, Grant Thornton’s Warren W. Stippich Jr., CIA, CPA, CRMA; and Bradley J. Preber, CPA/CFF, CGMA, CFE, CCA, surveyed more than 350 chief audit executives, internal audit directors, data analytics managers and other internal audit professionals to benchmark the way data analytics currently is viewed by internal auditors. They found that the majority of organizations (59 percent) did not incorporate data analytics into their functions before 2010 and 20 percent have less than one year of data analytics work experience.
Because the profession clearly is behind the curve, true integration will transform most internal audit functions, according to Stippich and Preber. Organizations that successfully transform will operate in functions where data analytics is the backbone of internal auditing, enabling high-risk items to be automatically flagged and freeing practitioners to focus on high-value areas.
“By letting computers handle the transactional, low-value tasks and engaging staff only on high-risk transactions that require human scrutiny, internal auditors will wield technology to achieve unprecedented levels of efficiency,” according to Data Analytics.
The book also provides abundant case studies derived from interviews with dozens of internal audit leaders who have developed successful data analytics programs. The case studies provide real-world examples of each step outlined in the book, from the rudimentary — defining the data analytics vision — to the advanced — capturing value through data analytics.
Stippich and Preber confidently conclude that history will look back at the current era as an inevitable transition period to widespread data analytics use, with the next generation of internal audit practitioners already primed to thrive in a digital world where technological change is viewed as an enabler rather than an obstacle.
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