A case for data analytics
The numbers call for improvement, our panelists agreed. The right approach, they concurred, is to set up a continuous transaction monitoring program fortified with analytics that identify non-compliance across a wide range of high-risk categories. The application of behavioral science can further help identify patterns of non-compliance and catch repeat offenders. Finally, there should be a single source of truth to view all information through easy-to-access dashboards.
Such well-conceived data analytics can go far to resolve a wide array of issues, said Jenitha, who advises auditors to perform a fraud risk assessment that addresses vulnerabilities before breaches occur. Additionally, not only does more sophisticated analytics help management make better decisions, IIA standards recommend their use. Analytics track trends and patterns – such as weekend spend and duplicate or repetitive payments – that teams might otherwise miss.
Our panelists discussed cases in which successful pattern analysis flagged unusual entertainment spend with an external attendee, identified a gap in the employee separation process by tracking sudden spikes in spending, and exposed employees who were claiming fraudulent expenses suspiciously just short of the threshold defined by policy.