Use of "Data Analytics" to Detect or Prevent Purchasing Fraud
In our July 2018 WNDE newsletter, we discussed the detection and prevention of purchasing fraud. Special computer software is available that can perform “data analytics” on a large computer database of purchasing and vendor transactions, in order to identify unusual or suspicious transactions. Examples of data analytics that could be used to investigate possible purchasing fraud are noted below.
• Review of all vendors with PO Boxes (searching for phony vendors)
• Comparison of all vendor addresses and phone numbers with employee addresses and phone numbers (searching for fictitious vendors set up by employees)
• Listing of all invoices without purchase orders
• Listing of all purchase transactions where the invoice cost is greater than the approved purchase order
• Listing of all revisions to the Vendor Master File
• Listing of all new vendors added to the Vendor Master File
• Listing of invoice payments to vendors not on the Vendor Master File
• Listing of all purchase orders over the entity’s approved limit
• Listing of all payments to one vendor (by date or dollar amount)
• Listing of all vendors with similar or sound alike names
• Listing of all payments with duplicate invoice numbers or same dollar amount (i.e. searching for duplicate payments)
• Listing of employees who approved both the purchase orders and invoices for a transaction
At WNDE, we utilize data mining and extraction software, as well as artificial intelligence software to aid in our analysis for assessing risk in our attestation engagements. The ability to utilize current technologies to analyze large amounts of data has greatly enhanced the overall audit process and helps uncover areas of fraud risk that are occurring within businesses.