Using Internal Controls For Data Analytics

New technologies continually allow organizations to gain a deeper insight into their business processes. They also enable management to gain this insight with greater ease, efficiency, and efficacy than ever before. At the heart of these technologies is a vast category of data analytical tools.

The ability to utilize “big data” and data analytics to attain a competitive advantage and manage strategic plans and operations ranks top among the risk issues for C-suite executives and board members globally.

Analytics are now top priorities for chief audit executives keen on offsetting the mounting workload of internal and external controls off of themselves and their teams.

By leveraging data analytics strategies, businesses can boost their efficiency, improve the quality of their internal controls and evaluation risks, and placate stakeholder scrutiny.

What is Data Analytics?

It’s the process of analyzing raw data and using it to make conclusions about the information therein and support decision making. Today, there is widespread automation of many data analytics processes and techniques into automated algorithms that work over raw data (and analyze it) for human consumption.

Data analytics can reveal metrics and trends that you would otherwise miss in the mass of information you collect. You can then use the analyzed data to optimize processes to increase your business’ overall efficiency.

The Importance of Data Analytics for Internal Controls

Internal controls are critical to achieving organizational objectives. They also help eliminate mistakes and prevent fraud. A 2018 report by the association of Certified Fraud Examiners (ACFE) found that the prominent organizational weaknesses that led to fraud were:

  • A lack of internal controls (formed 30% of cases)
  • Countermanding the existing internal controls system (18%)
  • A lack of effective management review (17%)

Together, the above three weaknesses accounted for 65% of total cases.

Strong internal controls should form the primary focus of any competent management team. However, this challenge requires considerable effort in:

  • Identifying and assessing risks
  • Prioritizing which controls to evaluate for effectiveness
  • Identifying exceptions
  • Drawing conclusions based on the investigation
  • Identifying controls that mitigate risks and evaluating their impact
  • Conducting further tests
  • Investigating exceptions again
  • Developing and implementing a plan to address specific exceptions and prevent future occurrences

As you can see, this traditional approach to ensuring that your internal controls are effective is tedious at best and problematic at worst. Hence, the need for using data analytics tools.

Where to Start

Before selecting the right data analytics tools, start by identifying your organization’s desired goals, and look at how you can benefit from the test outcome that these tools can perform. Here, consider the three internal controls carefully. For instance, one key area of focus that needs data analytics is in risk management, which falls under detective controls.

Some questions to ask include:

  • What areas are most susceptible to error or fraud?
  • What business functions rely more on human involvement instead of automation?
  • Which of your internal controls would benefit from testing?

Data analytics tools can prevent your internal controls from falling behind the curve.

These tools have two key testing categories that all organizations can begin using today.

  1. Analytical Tools

They are simple to execute and provide immediate, valuable feedback, such as year over year variances, accounts receivable and payable aging schedules, ratio analyses, depreciation and amortization calculations, etc. What’s more, these tests can create new business insights otherwise not easily available, which you can utilize for a variety of applications.

Accounting software cannot allow you to customize tests or dive deeper into understanding your business beyond the program.

  1. Internal Controls Testing

Internal control testing is an incredibly tedious process for both management and external auditors. Automating some processes can prove valuable for both parties. Data analytics are great for increasing the efficiency, quality, and capabilities of testing. Some suitable examples include cash disbursement and journal entry testing. You can also use it to clean up employee or vendor listings.

Benefits of Using Data Analytics for Internal Controls

  • It allows for more robust controls. You can test transactions in near real-time, continuously, and neither vacancies nor vacations impact the testing frequency. It also enhances the visibility into internal controls exceptions to make sure that you investigate and remedy each one.
  • You can lower your compliance cost by moving away from manual testing. Instead, you can allocate your staff to other tasks like analysis, remediation, or preventative.
  • Enables faster detection because more testing decreases the risk of non-compliance.
  • It reduces losses. The ACFE found that the median fraud losses were 52% lower, with the presence of proactive data monitoring and analysis controls.
  • The proper implementation of data analytics and monitoring necessitates formal documentation and the standardization of business processes. These business processes are easier to teach and implement in case of staff turnover.

Over to You

Whichever way you look at it, the use of data analytics is paving the future of internal controls and audits whether organizations are ready or not. Now that the essence of these tools is clear, the next logical step is finding a suitable option that works best for your specific needs. Without a doubt, the value of accurate and immediate feedback plus the ability to make on-demand informed decisions would help you proactively manage your organization’s risk and exposure.


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