Internal Audit: Using process discovery to test for process variations

Are your process narratives and SME interviews still effective?  How does your internal audit function consume the volumes of big data and complex business processes produced from today’s technologies?  Is your internal audit team’s skill set staying ahead of your enterprise digital transformation?

With the rapid pace of enterprise digital transformation, increases in data volumes and complexity of systems and business processes, it is imperative that internal audit functions and skillsets stay ahead of this trend.  In fact, PwC’s 2019 State of the Internal Audit Profession Study identified six habits to enable a more “digitally fit risk function”.   Of these, three key areas include enabling an organization to act on risks in real time, upskill talent, and finding the right fit for emerging technologies.  These are all possibilities now, read on… 

Getting to process flow visualization with volumes of data…no problem 

Imagine dropping into your business processes and tracking them through to a process visualization, like following a trail of data breadcrumbs to a well-baked remarkable end result.  This can be achieved through process mining (process discovery).    

Process discovery leverages techniques found in data mining, process management and analysis to extract information readily available in enterprise systems’ event logs to discover, monitor and optimize business processes.  This helps complement the internal audit function allowing them to understand, visualize and analyze workflows and risks across business processes such as Procure To Pay and Quote To Cash as well as drill down into revenue management scenarios such as revenue leakage and billing.  Furthermore, process discovery spotlights areas of risk or deficiency by comparing actual visualized processes and more importantly, process variations against the standards originally set by the enterprise. 

What do you do with Implicit or Inferred Processes? 

Oftentimes, business processes and decisions sit outside of structured systems.  What happens then? For example, how does an auditor assess the risk in legal contracts, embedded excel calculations and macros, and supplier purchase orders – these are all part of a business process but the data or decisions are not always captured by an ERP.  Advances in machine learning and natural language understanding (NLU) have helped businesses take traditionally unstructured data and transform it into structured data.  This in turn, allows internal audit functions to effectively understand and analyze these implicit processes for risk and compliance. 

AI-enabled process discovery and unstructured data discovery are technologies available today to any internal audit function looking to stay ahead of their enterprise’s digital transformation programs.   Live Objects can provide the process understanding coupled with the much-needed agility for internal audit functions to proactively expand their scope of testing (for completeness), properly assess for deviations and anomalies in business processes (by following the data), as well as monitor (in real time) any material variations in workflows and approvals, from the standard operating procedures, in an unbiased data-driven approach.

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