Unlocking the Value of Audit Analytics – Is it all about technology?
I recently spoke at an Institute of Internal Auditors (IIA) General Audit Management Conference on the topic of integrating data analytics in risk based audits and was lucky enough to be asked to present again at a local chapter event in the same week. In fact, I was delighted to participate in an interview on the topic before the conference that appeared on the IIA’s Audit Channel. The presentations at the conference went well and have certainly focused my sights on what auditors think are important in data analytics.
Let’s face it, auditors have been using data analytics in one way or another for over a decade and yet most struggle to maximize the value. We have seen audit departments that have matured over the years and gained tremendous value from using data analytics while others struggle to have a consistently positive impact. Many audit departments also witness a major slump in performance after losing key employees that have become experts. What drives these variations in results?
After having discussions and workshops with a number of customers over the past year, there appears to be consensus on the factors that drive value from using data analytics in an audit department. They include:
- Visionary Leadership
The role of the Chief Audit Executive is to be an advocate for their vision by enrolling key team members to share in the same vision, a topic discussed in our white paper, An Active Fight Against Fraud. The best performing departments have a leader that is very clear of what role data analytics will play in their success.
- A Focus on Stakeholder Satisfaction
Many internal auditors still do not recognize stakeholder needs and how critical it is to manage and satisfy their expectations. With many businesses so invested in analytics there is an expectation for internal audit to do likewise.
- Risk Based Audits
Maximizing the value of the investment in data analytics for internal audit drives a more focused approach based on the organization’s risk framework. Using audit resources optimally by focusing on the areas of greatest need is again consistent with how businesses operate in general and internal audit should follow suite.
- Best Practices and an Obsession with Efficiency
As auditors we document and standardize everything done in an engagement but many do not do the same with data analytics. There are tremendous efficiencies to be gained from sharing, reusing and making analytics repeatable.
- Results Focused Data Analytics
Great auditors always demonstrate superb discipline and validate their findings and the same principle should be adhered to when using analytics during the audit process. Avoiding the “data chase” is critical.
- Commitment to Staff Development
The most effective data analysts are those that demonstrate critical thinking, not those that are best at using software. Gaining value from an investment in people and technology lies in a focus on the contextual use of analytics software.
Over the next few months, I will expand on the various building blocks that enables internal audit to maximize its value from using data analytics and how this brings us closer creating key insights into an organization’s risk and controls environment.
About Andrew Simpson:
Andrew Simpson has close to two decades of experience in the information systems audit and security business; specifically data analytics, interrogation and forensics. He is a regular contributor to various auditing conferences and is acknowledged as an expert on continuous controls monitoring and revenue assurance.