Doesn’t it seem that the term “data-driven” is getting tossed around quite a bit these days? You’re probably even seeing and hearing the term “data-driven audits”. So, what does “data-driven audit” mean? The answer seems to mean a lot of different things to a lot of different people. The good news is that they may all be right. However, when we talk about auditing and data, for most people the first thing that comes to mind is performing specific audit tests during fieldwork.
Using data to perform specific tests and analysis during fieldwork can provide a great deal of value to your audit. Additionally, by analyzing 100% of a data set we can report, with confidence, that we have performed a thorough review as opposed to data sampling. Analyzing 100% of your data provides greater assurance and reduced risk and some tests cannot be performed through sampling. Using a tool like TeamMate Analytics which is designed to do the kinds of analysis that auditors need to perform can make looking at 100% of the data faster than manually going through a sample.
Most likely when you get to this level of fieldwork, you have already decided what you are going to look for as a part of your audit. However, when considering risk-based auditing, we should start by identifying our riskiest areas of the business, and then determine the audits to be performed based on those risks. Our challenges, as auditors, is that often the direction that comes from this is fairly high level and our audit budget and time permitted don’t allow us to perform a detailed audit of all areas of the risk. So, the question becomes where and how should we focus our time and resources?
The good news is, in a data-driven audit, you can use data to help make this decision. Often, we look at key indicators where our risk analysis has taken us. Reviewing year over year, quarter over quarter or even month over month numbers of key indicators can give us insights into potential problems or areas of risk. For instance, are costs increasing in a certain area? Are there more (or fewer) transactions in the latest period than there have been in prior periods? Unanticipated changes like these can help us determine areas where we want to dig deeper, gather more detail, and perform more tests.
Certainly, there are other ways to use data in a data-driven audit, but in our experience, these seem to be most common and advantageous to audit teams. So how will you take advantage of your data-driven audit? Give us a call to discuss how TeamMate Analytics can improve your data-driven audit.
