Duplicate Payment Testing | Maillie LLP

Duplicate Payment Testing

Most organizations are reactive when it comes to fraud; however, there are some things an organization can do to be as proactive as possible in identifying and quickly addressing potential fraud risks.  Many frauds can be detected in a timely manner by “drilling down” into the financial data to analyze suspicious transactions.  Specialized data analytics software can be used to discover indicators of fraud. 

Maillie LLP utilizes IDEA™ data analysis software, a powerful data mining tool used to perform data analysis quickly, by importing, analyzing and reviewing a variety of data.

Duplicate Payment Testing

A duplicate payment occurs when a single vendor invoice is paid multiple times, resulting in over-expenditure.  This can occur as a result of simple processing errors or as a result of fraud. If you are lucky, the vendor will contact you and refund your overpayment, but in many cases these errors go unnoticed, or in cases of fraud, the vendor may be colluding with one of your employees or may not even exist at all.

Duplicate payment testing is accomplished by asking the software to identify instances of payment where a combination of the same vendor, invoice number, invoice date, payment amount, purchase order number, and/or invoice item description were used within the disbursements register. Since many accounting software systems prevent duplicate field entry and because these fields can be modified by the humans entering them, tests can be expanded to identify instances where some of these fields are “close” but not an exact match.  This type of comparison for items that are “close” is often referred to as fuzzy matching.  For instance, the payments listed below could still be an indicator of duplicate payment despite them having slightly different amounts and a modified invoice number.  They would not be identified in an exact match duplicate test, but may be identified using a fuzzy matching test.



Invoice No.

Invoice Date









When running duplicate tests on large volumes of payment data, duplicate testing programs can employ a fairly sophisticated measure of “closeness” in order to better tailor test results and reduce investigative and follow up time.  This measure of “closeness” is called the Levenshtein distance, which is defined as the number of single character differences between two sets of data.  For example, the Levenshtein distance between invoice number “105654” and “105654X” is one, and the distance between transposed numbers such as “$12,250” and “$12,520” is two.  Measuring “closeness” in this fashion allows the investigator to narrow down the fuzzy matching test results and identify those that are most likely to be instances of actual duplicates.

Duplicate payment testing should always be run in conjunction with a test for duplicate vendors, since some fraud schemes consist of duplicating a vendor in the system, often by slightly modifying the name of an existing vendor.  Invoices can then be submitted twice under each vendor number, and the second payment is diverted without alerting the legitimate vendor.  Our next newsletter will focus on methods of vendor testing designed to identify potential fraudulent vendors within the purchasing system.

It’s important to remember that a duplicate or anomalous transaction is not always an instance of fraud.  There are often legitimate business reasons for transactions to be duplicated or to deviate from established patterns.  Identifying and investigating unusual transactions can, however, significantly increase the chances of detecting fraud early.

Maillie LLP can help you use data analytics, including duplicate payment and duplicate vendor testing, to analyze your financial data for potential red flag indicators of fraud.  Contact us today for more information.

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