What is data analytics when it comes to auditing? data analytics has been a big buzzword in the audit community, yet the term data analytics can seem a little ambiguous and therefore hard to define and understand. Our goal in this article is to cut through the ambiguity and lay out a clear explanation of what data analytics is as it relates to the auditor. But before we do that let’s take a step back and look at some official definitions…
We’ll start first with data analysis so DATA ANALYSIS is defined as a process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information informing conclusions and supporting decision making (Wikipedia, 2021). So essentially data analysis can be anything we do with data to help us understand develop conclusions and support decision making. At the most basic level, we do this when we use tools like Excel when analyzing row and columns of data, we may even summarize the information and create a pivot table or a graph which helps us identify relationships, help draw conclusions and even discover outliers in the data. This brings us to the next definition and that is AUDIT DATA ANALYTICS which is defined as the science and art of discovering and analyzing patterns, identifying anomalies, and extracting other useful information in data underlying or related to the subject matter of an audit through analysis modeling and visualization for planning or performing the audit (wiley.com, 2018). Here the definition specifically mentions extracting information from the data related to planning and performing an audit. In addition, it describes the technique as both a science and art. The definition is provided by the AICPA and is quoted in their guide to data analytics.
Now let’s go back to the term audit data analytics and let’s focus on the word data. The data refer to here is not summary information, the data is the detail, it’s the lowest common denominator the highly granular detail row that is the origin of a transaction. ideally, this is what we want to analyze and test using data analytic software because now we can test 100% of the data. Could you random sample?! you could.. but why go that route when you can test everything!.
Idea is a data analytic tool that helps the auditor extract information from 100% of the data in order to identify anomalies, test for exceptions and analyze the data to better understand the process and the business it drives. The tasks executed in idea help the auditor perform the data analytic. For example if the order wanted to determine if there are any potential ghost vendors that would be a type of data analytic that could produce an exception, the order would join the vendor payments file to the vendor master file match it by vendor number and choose records with no secondary match, records that don’t match to the vendor master. The join feature is the task that would allow the auditor to perform the data analytic that identifies any exceptions that exist in the population.
To summarize audit data analytics is the science and art of discovering things within data the helps an auditor perform throughout the audit. Data analytic tools can look at 100% of the population and the auditor can utilize its features to perform specific data analytics on the population.
Source: Audimation Services