Billing Schemes in the Professional Services Industry

In previous Our Thoughts On articles, I’ve discussed a case study regarding billing schemes in the professional services industry, and my colleague Andy Trettel has talked about using data analytics to identify check and payment tampering schemes.  In this article, we’ll combine these ideas to provide some common data analytics tests to detect billing schemes.

As a refresher, billing schemes attack a company’s cash disbursements and payables cycle by making false claims for payment from the victim company.  These bogus claims induce the victim company to issue payments for goods or services not actually received.  Fraud perpetrators can accomplish this in a variety of ways:

• Invoicing via shell companies, wherein a fictitious entity is created for the sole purpose of committing fraud
• Invoicing via non-accomplice vendors, wherein fraudsters use invoices in the name of existing vendors to generate fraudulent payments
• Overbilling by falsifying or inflating billing records
• Making personal purchases with company funds, by using company accounts to buy items for themselves, their businesses, their families, etc.

A company should continually monitor relationships with vendors to ensure that vendors are not taking advantage of the relationship with the company and that all vendors are legitimate.  Common data analytics tests to monitor red flags with vendors include:

• Identify vendors with significant increases or decrease inactivity
• Extract vendors with incomplete profiles, especially those with missing telephone number or tax ID numbers
• Review transactions that are just barely under the authorization thresholds

There are various new data analytic tools, besides Excel, to perform these tests that are now available.  We are utilizing several of these tools at Schneider Downs, including:

• Alteryx – a business intelligence platform and data preparation tool that offers data mining and predictive analytics.  It focuses on accessing, preparing, blending and enhancing data, especially from multiple sources in different formats.
• Microsoft Power BI – a business analytics solution with interactive visualization and business intelligence capabilities.  It can connect to hundreds of data sources and convert data into dashboards and reports.
• Tableau – interactive analytics tool to integrate and combine data from multiple sources into visualizations and dashboards, with virtually no programming required.
• IDEA – an analysis tool that quickly analyzes data, guarantees data integrity and accelerates performing data analytics to assess risk, gather evidence and uncover trends.

If you have any questions regarding potential fraud schemes or the use of data analytics to detect fraud, please contact the Business Advisory Group at Schneider Downs.