How to identify and prevent accounts payable fraud?

The accounts payable department is still one of the most fraud-prone areas within a company. Whether it is internal or external attempts at theft, even with accounts payable fraud prevention controls it can sometimes be tough for companies to detect fraudulent activities.


But there are many ways that organizations can analyze and detect whether fraud has taken place so that strict measures can be put in place to prevent such incidents going forward.

Common accounts payable frauds


1. Invoices

Invoices are the bread and butter for any fraudster to try and manipulate the system to gain money. This can be in the form of duplicate invoices from the same vendor, invoices from a fake vendor, and can sometimes even be similar invoices where one invoice is actually fake.




2. Vendor master file

The database within which all the information your company stores about your vendors to make payments to them is also often a major target by scammers.


You must regularly monitor the vendor master file for a large number of inactive or duplicate suppliers. Someone might try to hack into the system and modify the data in a way that benefits them. 




3. Checks

Approvals can be a tricky mess if it’s easy to forge them. You can prevent such trickery by putting systems in place that allow for double verification by multiple people instead of just one so that you people can spot missing checks and signatures that don’t look right. 




4. Employee behavior

As sad as it is to think about it, sometimes even employees might turn out to be aliased in fraudulent activity alongside external scammers.


To avoid accounts payable fraud risk, your AP processes should be kept transparent and visible to multiple other managers so that there is complete visibility of all transactions taking place.

Ways to identify and prevent accounts payable fraud


1. Duplicate payments

When individuals are aware that a particular vendor has recurring payments each month, they might try to send invoices and try to divert the payment for it into their account.


Regardless of whether someone tries to do this from the inside or outside, it is easy for them to claim that it was done accidentally. Data analytics is an accounts payable fraud detection method that can be used to spot payments with extremely similar details with just a few details being different. 


Suggested read: How can businesses avoid duplicate invoice payments?



2. Unauthorized vendor

Another form of fraud that is prevalent within organizations that have loose controls is when an employee sets up an unauthorized or fake vendor account. They then submit invoices for non-existent or fraudulent goods and try to siphon money in this manner.


One way to spot this fraud is by using data analytics to match employee data such as bank accounts, tax IDs, matching addresses, and telephone numbers with that of any vendor within the company database.




3. Purchases of consumer items

Under this type of fraud, you may notice employees with purchasing permissions misuse their authority to purchase materials or services for personal use.


Data analytics can help you spot this type of fraud by looking for keywords that are often associated with consumer items. You can also look for common consumer item vendors like Amazon and search for certain merchant codes of brands and stores that provide personal goods.  




4. Above average payments per vendor

It is very rare for an increase in the payment amount for vendors who you are in a contract with. If you notice higher than normal due amounts this might be because the vendor has overcharged on invoices.


Unless and until there are new terms and conditions or contract renewals, this type of fraud is easy to spot by seeing the average payment amount that is paid to a vendor each month. 




5. Sequential invoices

Sequential invoice number test analyzes all the invoice numbers from each vendor over a given time frame and indicates the average range between numbers, anything outside these numbers can be seen as unusual and detected as fraud.




6. Benford’s law

Benford’s law is a way to identify numeric amounts that don’t fit expected patterns. If payment volumes each month don’t match the Benford curve, you can probably expect some fraudulent activity to have occurred. 




7. Unauthorized changes to vendor master file

When employees have access to vendor databases, they could fraudulently access a master record and input their own bank account information and change it back to the correct information once they have received the money.


Data analysis can be used to spot frequent changes in records and detect such accounts payable fraud.




8. Round amount invoices

It is not very common for invoice amounts to end in round numbers given that there are tax calculations involved in it. Although a round number payment may not always be a fraud, it is wise to always double-check such payments and their origin closely to detect potential fraud.

Manage your account payables securely with Volopay


Volopay is an all-in-one expense management solution that helps companies make payments, track expenses, manage budgets, and control each element through the platform. This robust system can help you in accounts payable fraud detection and prevention in the following ways:


Approval policies

The first way in which Volopay helps you prevent fraud within the accounts payable department is through our approval workflow feature.


This feature essentially lets you set up custom approval triggers whenever anyone within your organization is trying to make a payment to someone through Volopay’s money transfer system.


This ensures that payments go through 1 or more (up to 5) senior managers who ensure the legitimacy and reasoning of the payment before it is made.

Spend analytics

Each and every transaction that happens on Volopay is recorded instantly in real-time. All this data is easily available to admins to view in the form of concise and insightful analytics to understand spending behavior across the organization and even at an individual level.


This access to data with our sorting and filtering capabilities allows you to spot inconsistencies and detect fraud. 

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