There has been a distinct surge in the amount of interest and media coverage on the use of data analysis technology in business today. I believe that this increased level of awareness is being driven not so much by new tech capabilities or the marketing efforts of software vendors, but rather by today's business climate and the lessons that are being learned as the economy drags itself out of the recession and realigns itself for growth.
As organizations navigate their way towards prosperity, they're seeking to better manage business risk and gain greater insight into the efficiency of their business processes, compliance requirements and overall corporate governance. After all, you could argue that it was insufficient attention to and management of business risk that led to many of the losses incurred during the recession.
There's increasing pressure on organizations to make better, more informed decisions and to gain greater insights into business risks. That means more pressure on internal audit departments to provide heightened levels of insight into organizational risk.
Many are turning to audit analytics technology to do just that.
The use of audit analytics (i.e., purpose-built data analytics for audit) has been identified by audit industry surveys as a top-five enabling strategic priority. Looking internally at key business processes and the underlying data that reflects the nature of those processes is a natural place to start. Leading internal audit functions are leveraging audit analytics to identify risk, evaluate the effectiveness of internal controls, determine levels of overall compliance, and combat fraud and inefficiencies.
Audit analytics enables organizations to analyze transactional data to obtain fact-based insights into their operations. It helps auditors identify indicators of risk, internal control failures, and non-compliance to internal or external requirements.