Over the last decade, data analytics has helped many internal audit organizations greatly improve the quality, depth, and coverage of their work all while keeping operating costs relatively flat.
Analytics can be utilized during the planning process by assessing risk within the financial statement analysis, during testing to identify exceptions, and internal control gaps, to assist the audit team’s direction during field work.
Further, continuous auditing and monitoring can be used to automatically test user access reviews, journal entry authorization, the propriety of expense reimbursements, and out of period adjustments, amongst other audit tests.
While audit analytics has dramatically improved, its use by internal audit functions has lagged. There are several reasons for this, however, from working with our clients at The Cadence Group, we have noticed there are two main obstacles that impede companies as they look to implement analytics into their internal audits:
First, internal audit departments struggle to obtain, access, or understand the data needed to perform their work. To this, our recommendation is to start with data they’re comfortable with, data you understand, and have worked with before. It starts with the data; know what you need to perform your audits, know what you’re auditing, and align with the departments within your organization to assist you in harvesting data.
Second, and often more challenging, they strain to harness the data and develop effective visualizations and tests to improve their audit processes. However, we have seen internal audit departments flourish by utilizing the power of Domo to establish auditing and continuous monitoring routines.
The below roadmap has worked quite well for clients interesting in implementing analytics within their audits and how to get there:
Year 1 – define the analytics goals within the Internal Audit department and set your foundation: Identify and train staff with an interest in analytics, obtain data to analyze, and develop Domo cards and pages. As this is early in the analytics program lifecycle, execute a handful of pilot programs to show value, build momentum and confidence.
Year 2 – leveraging the previous year’s successful tests, identify additional opportunities to fully embed data analytics within Internal Audit. Define the foundation for governance over Internal Audit data.
Year 3 and beyond – fully embed data analytics, broadening Internal Audit’s reach within the organization.
Incorporating data analytics into internal audit doesn’t happen overnight, it’s a process. By following the above several of The Cadence Group’s clients have made remarkable progress in harnessing the benefits of implementing analytics into their audits and evolving towards continuous auditing.