Internal Audit and Big Data
What exactly is “Big Data?” Big data is the term used to describe the massive portfolio of data that is growing exponentially. Big data includes data that is unstructured & machine-generated, as well as data that resides outside of corporate boundaries. Analytics is the process of analysing data with the objective of drawing meaningful conclusions. Big Data analytics (BDA) means that unstructured data can now be mined.
Major organizations are making significant investments to unlock the potential of Big Data. One area where we see significant potential is in the transformation of the audit. Recent technology advancements in big data & analytics are providing an opportunity to rethink the way in which an audit is executed. The transformed audit will expand beyond sample-based testing to include analysis of entire populations of audit-relevant data (transaction activity & master data from key business processes), using intelligent analytics to deliver a higher quality of audit evidence & more relevant business insights.
Since big data works with automation processes, AI & ML, larger volumes of higher velocity data can be processed efficiently, and so, auditors can gain valuable information & insights in a shorter period of time.
One of the main things the internal auditors do, is to perform a thorough risk assessment of the organisation they are auditing. With the help of BDA, internal auditors can analyse any data either from inside or outside of the organization. The BDA can help internal auditors to better assess the risks within or outside the organization, & help reach more precise findings.
However, the value of integrating big data & analytics into the audit will only be realized when used by auditors to influence the scope, nature & extent of the audit. This will require them to develop new skills focused on knowing what questions to ask of the data, & the ability to use analytics output to produce audit evidence, draw audit conclusions & derive meaningful business insights.