Incorporating Data Analytics Into Your Internal Controls

December 20, 2018

Incorporating Data Analytics Into Your Internal Controls

By: Michael Dovi, MBA

The evolution of technology has demanded that organizations more deeply understand the businesses they operate but has also allowed management to gain this understanding with greater ease and efficiency than ever before. This shift in the business environment is fueled by the countless new products that become available each day that offer leaders the ability to develop more accurate feedback on the performance of their companies, operate more efficiently and discover information that they didn’t know they ever needed. At the core of these products is the vast category of data analytics tools.

Data analytics is the process of inspecting and manipulating data to discover useful information needed to draw conclusions and support decision making. Not so simple is the process of deciding how to go about this examination and choosing the tools to accomplish this.

The right place to start when selecting data analytics tools is with identifying your organization’s desired end result and looking at how you can benefit the most from the outcome of the tests these tools can perform. For example, one area we see data analytics being valuable and underutilized in is risk management. What areas of your organization are most susceptible to fraud or error? What functions of your business rely more on human involvement and less on automation? What internal controls would benefit from further testing?

The importance of proper internal controls has come to the forefront of the accounting and auditing profession in recent years, and the systemic lackluster implementation of effective controls within organizations has become an epidemic. Data analytics tools can help prevent your organization from falling behind the curve in this area. When looking at these tools, there  are two key categories of testing that all organizations can start using today: analytical tools and internal control testing.


These are tools that are simple to execute and provide valuable, immediate feedback. This can include year over year variances, ratio analyses, accounts receivable/payable aging schedules, depreciation/amortization calculations and more. You’re probably thinking that your accounting software can do all of this already, but data analytic tools allow you to customize tests and dive deeper into understanding your organization beyond the accounting software. For example, let’s say you want to know how many of your employees are between the ages of 50-65 or how many live beyond 10 miles of your organization or what percentage of your donors pay using credit cards vs. cash. These are simple tests for any data analytics tool that can create new insights for your business that were not as easily available before and can be utilized for a wide variety of applications.


For both management and external auditors, internal control testing can be incredibly tedious. Automating some of this process can prove to be very valuable for both parties. As mentioned earlier, data analytics are great for increasing the quality, efficiency and capabilities of testing – this is especially true with internal control testing. Journal entry and cash disbursement testing are two subsections of internal control testing that benefit the most from data analytics, and there  are some new tests that may be useful for management to use to test the organization’s internal controls.

Data analytic software can extract journal entries that would be deemed unusual under various chosen criteria. Some of these criteria can include the following: 

  • Entries posted on a weekend or federal holiday
  • Entries posted outside of normal business hours
  • Missing journal entry numbers in the sequential listing
  • Entries posted and approved by the same employee
  • Entries matching specific, unusual words, such as “mistake, plug or error”

The available tests go on and on, but the goal is to identify specific data points that may require additional investigation. For the organization, this provides a way to continuously monitor the quality of the general ledger and fix entries that were done incorrectly, as well as identify sources of possible fraud.

Cash disbursement testing is equally as valuable and, in many ways, can be more effective at finding unusual transactions. Again, organizations can identify criteria that would flag a check or wire transfer as being unusual during the course of normal business operations. These criteria are often repeated from the above journal entry testing criteria, and with cash disbursement testing, you can also incorporate the use of the vendor and employee listings. A great test for any organization is to compare the addresses of your vendors to the addresses of your employees. This is a proven assessment that has uncovered fraud in the past: an employee creates a vendor in the accounts payable system with their home address and cuts unauthorized checks to this vendor. While this scenario should never get through a properly designed internal control matrix, this extra test would detect this if it were to occur.

Data analytics can also be used to clean up these employee/vendor listings, which will help prevent fraud or errors from happening in the future. A simple extraction can find all duplicate vendors in the listing, which can then be deleted from the accounts payable system. In a time where data dumps are becoming immense, having the ability to make the data more accurate is critical to the testing results. Extracting a list of all employees that have the same address as another employee can also be a valuable test for management.


While there are thousands of data analytics tools available, there are three that can fulfill the needs of most organizations:

The most user friendly and the lowest cost option is TeamMate Analytics (TMA) by Wolters Kluwer. This program is installed as an Excel add-in, is as easy to use as Excel itself and has more than 150 powerful Computer Aided Audit Tools (CAATS) that will be up to the task to handle the needs of a large portion of organizations. The limitation of TMA is that it only works with Excel files.

For data sets larger than the capacity of Excel, there is IDEA by Caseware. IDEA has all of the functions of TMA and more, but the main advantage is that  this program can handle larger sets of data and from sources other than Excel. However, with this functionality increase comes a steeper learning curve and more skills required to operate.

At the top of our list for data analytics software is  Ai Auditor from Mindbridge Analytics. This software utilizes artificial intelligence and is seamlessly  integrated into your financial software to provide real time feedback and predictive analysis. It is a very advanced, highly intelligent software and, as such, it is better suited to more complex organizations.


Do not let the fancy name fool you - data analytics tools can be easy-to-use and reasonably priced. Often, no extravagant software is required. Now that the importance of using these tools is clear, the next step is finding an option that works best for your organization’s specific needs. The above options are a great place to start your research—and there is no doubt  that the value of immediate and accurate feedback paired with the ability to make on-demand decisions will help business leaders proactively manage the risk and exposure of their organization.

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