Internal auditors are seeing increased value from leveraging data analytics for internal controls evaluation, fraud detection and compliance monitoring, according to a new report.
The report, released Friday by the Institute of Internal Auditors’ Internal Audit Foundation and Top 10 Firm Grant Thornton, surveyed 186 chief audit executives and directors in North America and found 94% of internal audit teams have prioritized analytics through dedicated analytic resources and/or training, while 85% reported that analytics and automation add value across all sizes of internal audit teams.
They see opportunities to increase value through continuous auditing, data-driven board reporting, broader risk sensing and reduced IT vulnerability. As the usage of data analytics increases, so does the perceived value.
The most common use of data analytics by internal audit was for evaluating internal controls (67%). Other uses cited by the respondents included trend analysis (57%), data visualization (53%), fraud detection (52%), compliance monitoring (51%), risk assessment (49%), operational performance (42%) and Sarbanes-Oxley compliance (42%).
When asked for the three areas where data analytics provided the most value, chief audit executives focused on evaluation of internal controls, fraud detection and compliance monitoring.
“Fraud detection, while a more traditional domain of analytic processes, is also high value because it solves the ‘what am I missing?’ or the ‘needle in the haystack’ problem,” said the report. “Fraudulent transactions may be hard to prevent or detect without analytic algorithms assessing high volumes of data with targeted anomaly and risk detection.”
Many of the chief audit executives who responded to the survey pointed out that trend analysis and continuous auditing allow them to identify and address issues on more of a real-time basis, while also enabling them to recognize emerging risks.
For about one-third (34%) of survey respondents, there’s a dedicated team for internal audit data analytics, while another 33% have staff members with formal data analytics training, but no dedicated team. Another 27% of the respondents said they provide training in analytics to staff when needed. Only 6% said they completely lack staff with data analytics skills.
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