Using Data Analytics to Identify Errors, Waste and Abuse

Using Data Analytics to Identify Errors, Waste and Abuse

Apr 12, 2018

Mistakes happen in organizations of all sizes and types. Unfortunately, so does fraud. Not identifying mistakes can be expensive, while missing abuse can be even more costly. Data analytics offers organizations an efficient and effective way to monitor what’s occurring so they can spot concerns before they cause problems.

Mistakenly thought of as only for big business, data analytics procedures can provide organizations of all sizes and in all industries with a financial sleuthing tool to identify errors and red-flag potential weaknesses in internal controls. They can also provide insight into patterns and trends while uncovering opportunities for greater efficiencies.

Shining a Spotlight on Potential Problems

By highlighting potential gaps in processes, procedures, training or internal controls, data analytics can help you understand more about your organization’s activity. Performing data analysis can provide insight into potential problem areas and irregularities and help you identify missing information, duplicate information, information in incorrect formats or incorrect or improper activity.

Organizations create and retain significant amounts of data in the normal course of day-to-day operations. Data analytics takes advantage of this existing store of information. Today’s powerful analytics tools allow organizations to use 100 percent of available information. Traditional control activities rely on samples of data and, frequently, small sample sizes when compared to the total amount of data. Analyzing the entire population of available data makes it much more likely you’ll be able to identify errors or anomalies.

Data analytics is also an effective method for identifying ineffective or broken processes. For instance, analyzing all payments can quickly identify those to vendors for which no taxpayer identification number (TIN) is on file and that could either lead to compliance failures with IRS 1099 reporting or reflect weaknesses in vendor-authorization procedures.

Similarly, analyzing the payee for all disbursements is far more likely to identify a once-monthly payment to a credit card vendor that the organization doesn’t have an authorized credit card account with than relying on a random sample to identify the single unauthorized monthly payment.

Data analytics also allows you to identify issues such as gaps in check sequences, frequency of payments to vendors, spikes in activity, unexpected vendors or unusual journal entries that would not be readily identifiable from typical accounting reports or records.

Flexible and Efficient With Minimal Impact on the Organization

Data analytics can, and should, not only be customized to the particular industry or type of organization, but also take into consideration how an organization operates. The data you’re analyzing — and the analysis you’re performing on the data — should reflect the risks for your organization.

For instance, data relating to vendors, employees and disbursements is commonly analyzed by organizations in a variety of industries. We would not be surprised to see a manufacturer perform analysis on inventory and receivables data. However, a nonprofit organization providing services to its constituency would likely have no use for analyzing inventory and receivables, but they could be expected to analyze data related to cash deposits, costs per constituent served or cost allocations among programs. Data analytics offers not only flexibility among organizations, but also the flexibility to adapt to changes that occur within organizations over time.

This flexibility is realized with nominal impact to the organization. Since the information you’ll analyze is created in the normal course of operations, no special effort is required to create the data pool. Once the data retained by the organization is identified, it can be extracted for use with no interruption to normal day-to-day operations.

Easily Repeatable for Ongoing Monitoring and Control

Once you have determined the data available, risks to your organization and relevant tests, it’s easy to replicate the analysis on a periodic basis. Analytics can be embedded in the culture and control environment to provide ongoing monitoring of processes and controls.

Errors identified through data analytics can be used to improve or modify existing processes or identify gaps in staff training. Identified waste can be quickly corrected and provide immediate financial benefits. Stopping abuse detected by data analytics can allow prompt corrective action for wrongdoers and improve the prospects for recovery by the organization. With specific problems identified by data analysis, you can take appropriate corrective action, protect your organization and improve your financial reporting.

If you have questions about how your organization can leverage data analytics to resolve vulnerabilities and uncover efficiencies, contact Wipfli.


Marc Courey
Director – Fraud and Forensic Services
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