Data analytics in internal audit: weighing the benefits

The opportunity to draw insights from data analytics grows every year. This is due to a number of factors, including the simple fact that volumes of data are exploding. Worldwide business data doubles every 1.2 years, according to an estimate from Arizona State University, flowing in from payment systems, billions of smartphones and countless other sources.

At the same time, data storage is increasing while its cost has fallen. Finally, computing power is rising, and data scientists and programmers are developing more sophisticated algorithms to parse and compute that data.

Undoubtedly, this presents a huge opportunity and challenge for organisations. In the era of 'big data', there is an urgency to not only analyse the troves of data being collected, particularly in the very largest corporates, but to draw actionable insights from that analysis.

As organisations come to own more data, there is an opportunity for internal audit to also turn that to its advantage by making it work more efficiently and increasing the breadth and depth of audits, leading to greater assurance coverage.

Microsoft Excel is a powerful tool for analysing datasets and one that internal auditors have been using for years, if not decades. For many internal audit functions, such desktop applications will meet their needs for the foreseeable future.

Audit functions in larger organisations with higher volumes of data, however, may look to more advanced tools as a means for achieving their goals. This is especially true where audit resources are stretched and there is a need to automate processes to focus attention on strategic and emerging risk areas.

Excel is arguably less suited to collaborative work as shared spreadsheets are prone to formula mistakes and user error, which can cause problems with audit trails. Audit-specific applications such as ACL and Teammate solve some of Excel's limitations…