According to the 2026 AFP Payments Fraud and Control Survey, 75% of finance teams got hit by payments fraud last year. Almost none of them are using AI to stop it. This finding points to a clear need for fraud prevention, which is a set of controls finance teams use to identify suspicious invoices before they’re paid.

Fraud tactics move faster than manual review can keep pace with. AI catches what a person scanning one invoice at a time can’t: the same vendor billed twice under slightly different numbers, a price that’s crept up $2 a case since spring, a bank-detail change that showed up out of nowhere. Only 17% of finance teams are actually using it. 

This gap presents an opportunity for finance teams. By incorporating AI into an accounts payable fraud prevention program, organizations are better equipped to identify risk early on, while there’s still time to take action and prevent unnecessary losses.

What is accounts payable fraud? 

Accounts payable fraud is any deliberate attempt to manipulate a company’s invoice or payment processes for financial gain. AP fraud might involve fraudulent invoices, altered payment details, inflated charges, or other tactics used to deceive a business into paying money it doesn’t actually owe. 

Accounts payable fraud typically falls into one of three categories:

1. Internal fraud: Acts committed by an employee or other “insider.” For example, a finance team member creates a fake vendor and submits invoices for goods that were never ordered or delivered.
2. External fraud: Fraud that originates outside of the organization. For example, a bad actor impersonates a legitimate vendor and sends an email requesting that payments be redirected to the fraudster’s bank account. 
3. Collusive fraud: This results from two or more parties working together, often an insider and an outsider. For example, a vendor might submit inflated invoices, and a finance team member may approve them in exchange for kickbacks. 

While accounts payable fraud schemes vary widely, they all exploit weaknesses in the organization’s processes for validating vendors, invoices, approvals, or payments. 

What are the most common types of AP fraud in 2026? 

Accounts payable fraud can take many forms, but these seven types are especially common in 2026.

1. Fake vendor (billing scheme)

An employee creates a fictitious vendor, then starts submitting invoices for that fake vendor. 

2. Duplicate invoice

This type of fraud happens when an invoice is submitted twice, often with minor differences in the invoice number, amount, or location. 

3. Business email compromise

According to the 2026 AFP Payments Fraud and Control Survey Report, 74% of organizations were affected by business email compromise in 2025, which is up from 63% in 2024. 

Business email compromise is a type of AP fraud where an attacker impersonates a vendor and requests changes to banking details via email.

4. Invoice inflation

A vendor bills at more than the agreed-upon rate or inflates the quantity delivered. For example, a vendor might charge $10 more for a case of tomatoes than the agreed-upon rate. Or, they may charge for 12 cases when only 10 arrive at the receiving dock.

5. Check tampering

According to the AFP report, 58% of organizations reported check fraud, which is the act of altering or forging a check after issuance. In comparison, 30% of organizations reported ACH debit fraud and 25% have been impacted by wire transfer fraud.

While checks are the payment method most vulnerable to fraud, 72% of organizations plan to continue using them for the foreseeable future, with 68% citing vendor requirements as their reason for doing so. 

6. Kickback or collusion

An insider (such as an employee) and an outsider (such as a vendor) work together to pull off an AP fraud scheme. For example, a finance team member may approve inflated invoices from a specific vendor in exchange for kickbacks. 

7. Expense reimbursement fraud

An employee submits approved or false expenses for reimbursement. For example, an employee might submit an expense report for personal spending, or they might submit the same expenses twice. 

Why do manual AP controls miss fraud? 

Reviewing one invoice at a time was a perfectly good system for the volume AP teams used to handle. At 5,000+ invoices a month, the same process is being asked to do a job it was never built for. Even the most diligent AP professionals can’t remember every invoice they’ve processed, notice small changes across thousands of line items, or identify subtle patterns spread across multiple vendors, locations, or months.

Most finance teams are still catching fraud the way they always have: someone reads the invoice. That was fine when a team processed a few hundred invoices a month. It’s not fine at 5,000. The Association of Certified Fraud Examiners puts the annual cost at 5% of revenue lost to fraud industry-wide – money that’s gone by the time anyone spots the pattern.

Human reviews focus on one invoice at a time, which can be effective for spotting obvious errors like an invoice total that’s significantly higher than expected. Fraud doesn’t announce itself. It’s a case of lemons that’s $2 more expensive than it was in March, or an invoice number that’s one digit off from one you already paid. Nobody catches that scanning one PDF at a time.

To spot these minor discrepancies and patterns, organizations must analyze every invoice in the context of everything that came before it. This requires AP teams to continually compare every transaction against historical invoices, contracts, vendor records, vendor behavior, and other data.

While most finance teams have adopted some form of AP automation, just 4% have fully automated the entire process from invoice to payment. So for the vast majority of businesses, manual work is still a major part of the AP workflow. 

Today, half of finance teams are managing more than 5,000 invoices per month, often from dozens of vendors across multiple locations. Under these circumstances, it becomes more difficult for finance teams to review every invoice closely enough to catch potential fraud.

How does AI detect accounts payable fraud? 

AI detects accounts payable fraud by analyzing invoice, vendor, payment, and approval data to identify anomalies and patterns that may suggest suspicious activity. Unlike manual reviews that look at one invoice at a time, AI can compare each transaction against historical invoices, contracted prices, vendor records, and approval behavior to identify potential fraud before an invoice is approved, and paid.

AI helps detect accounts payable fraud in four key ways.

1. Pattern recognition across historical invoices

Oftentimes, duplicate invoices aren’t exact duplicates. A fraudulent invoice might have a slightly different invoice number, date, or description, which can easily sneak past controls that were built to find exact matches. 

AI can compare multiple invoice factors against historical records, including vendor, amount, date, PO number, and line-item composition. Catching subtle patterns manually would require AP staff to search through past transactions and notice the similarities. Automated pattern recognition, on the other hand, can identify a potential duplicate as soon as the invoice enters the AP workflow.  

2. Line-item validation against contracted prices

An invoice might have the correct vendor information and a total that aligns with what the business typically pays the vendor. But there could still be an incorrect or inflated price for a specific item. Header-level validation is likely to overlook discrepancies. 

AI can validate each line item of each invoice against POs, contracted prices, and other pricing data to flag variances. Without AI, an AP professional would need to cross-reference each line against the corresponding PO or pricing agreement, an effort that’s unsustainable when a lean team is managing thousands of invoices and SKUs. 

3. Vendor master and bank detail verification 

Changes to vendor payment details can be a sign of business email compromise, which is one of the most common forms of accounts payable fraud. It could be a fraudster impersonating a legitimate supplier and requesting that payments be sent to a different account. 

AI can compare remit-to and bank details against existing vendor records. Any changes that don’t align with vendor records can trigger independent verification through a trusted contact method. Without these automated checks in place, AP staff would need to recognize any changes to remit-to and bank details and manually confirm with the vendor that every request is legitimate. 

4. Approval and behavioral anomaly detection 

Fraud often appears through subtle patterns that aren’t obvious when AP teams are reviewing one invoice at a time. For example, invoices for a particular vendor may consistently fall just below approval thresholds. Or, a single employee might approve an unusually high portion of a particular vendor’s invoices. 

AI flags it when one person approves an outsized share of a single vendor’s invoices, or when a vendor’s charges consistently land just under the approval threshold. Instead of expecting finance teams to notice patterns across thousands of invoices, AI can flag unusual activity that requires human judgment before payment is made. As AI continues to evolve, agentic workflows can take this even further by using context and predefined rules to determine how transactions should move through the payment process.

What’s the difference between AP fraud detection and prevention? 

AP fraud detection identifies potentially suspicious activity, while AP fraud prevention stops that activity before money leaves the business. When potential fraud is identified early in the process, finance teams have a better opportunity to investigate the issue and prevent a fraudulent payment from being made. 

Fraud can be detected at any point in the AP process. For example, a fake vendor could be identified during vendor onboarding, while a duplicate invoice may be flagged during initial invoice capture. A suspicious change to banking details, on the other hand, might be caught during a pre-payment review.

In some cases, finance teams don’t spot fraud until after payment has been made. For example, they might notice fraud during bank reconciliation, an audit, or when a legitimate vendor reaches out to see why their invoice hasn’t been paid yet. 

Once payment has been made, the focus shifts to recovery. The business may need to work with its bank, pursue a credit or clawback, investigate how the fraudulent payment was missed, and determine whether any other transactions were affected.

Effective accounts payable fraud prevention incorporates controls throughout the entire AP process. This allows teams to identify suspicious signals as early as possible, when there’s still time to prevent fraud. This approach also provides extra layers of protection in case fraud signals are missed at some point in the process. 

What are the most common red flags of AP fraud?

Some common warning signs of accounts payable fraud include unexpected changes to vendor information, duplicate or unusual invoices, unexplained price increases, and suspicious approval patterns. None of these red flags are a guarantee that fraud occurred, however, they do alert AP teams that there’s something suspicious that should be reviewed further before an invoice is approved and paid.

Finance teams should pay particular attention to these 9 accounts payable fraud warning signs. 

Unexpected changes to vendor banking details 

Any request to change payment details, should be independently verified before payment goes out, especially if the request comes via email. 

Duplicate (or near-duplicate) invoices

Invoices with matching amounts, dates, POs, or line items may mean the business has been charged twice for the same thing. 

Unusual invoice numbering

Changes in numbering patterns or numbers that are only slightly different from previously submitted invoices may warrant further investigation.

Amounts just below approval thresholds

When invoice totals for a specific vendor regularly fall just below the threshold where additional approvals are required, it may be an attempt to get around controls.

Unexpected line-item price increases

Prices that don’t match contracted rates or gradually creep up over time may signal invoice inflation. 

Suspicious approval patterns

If one employee consistently approves a large portion of a specific vendor’s invoices, collusion may be at play. 

Vendor spend that unexpectedly increases

An uptick in payments without a corresponding increase in purchasing volume is an anomaly worth investigation. 

New vendors with limited documentation or history

Missing information, limited history, or a remit address that matches that of an employee can all be signs of a fake vendor. 

Round-dollar invoices

When invoice totals for a particular vendor are frequently even amounts, it’s worth reviewing, especially if there are other suspicious vendor or invoice details. 

How do businesses build an AP fraud prevention program? 

An effective AP fraud prevention program combines strong internal processes with technology that can identify risk throughout the accounts payable workflow. No single control will catch every type of AP fraud, so finance teams need a multilayered approach that covers vendor onboarding, invoice validation, approvals, and payment.

Here are eight key steps to take to build a multilayered AP fraud prevention program that identifies issues as early as possible. These steps incorporate both process and technology, with many requiring a combination of the two. 

1. Segregate of duties (process)

Divide the different parts of the AP process amongst multiple team members, including invoice entry, approvals, and payment. Segregating duties makes it harder for an employee to initiate, approve, and complete a fraudulent transaction without oversight. 

2. Maintain an up-to-date vendor master (process)  

Regularly review vendor records for duplicates, inactive vendors, missing information, and unexpected changes to contact or payment details. When vendor records are outdated, it’s difficult to confirm whether requested changes are legitimate. 

3. Independently verify bank account change requests (process) 

Confirm any requests to change payment information through a trusted contact method in the vendor master. Don’t just rely on the contact information in the change request. 

4. Match invoices against supporting records (technology and process)

Use three-way matching to compare invoices against purchase orders and receiving data before approval and payment.

5. Use positive pay for checks (technology) 

Send issued-check data to the bank, including check numbers, amounts, and payee names. Checks that don’t match this data will be flagged before they clear.

6. Automate duplicate detection (technology) 

Use technology that compares every invoice against historical transactions and uses multiple data points to identify duplicates, including vendor names, invoice numbers, and totals. 

7. Help staff focus on true exceptions (Technology + process) 

When suspicious invoices are automatically flagged, AP teams can focus their attention where it’s needed, rather than manually reviewing every single invoice. 

8. Maintain a complete audit trail (Technology) 

Automatically capture invoice, approval, vendor change, and payment activities so finance teams can easily investigate suspicious transactions and understand how they moved through the AP process. 

No single control catches everything; that’s the point of layering them. Get these eight in place, and you’ve got a program that flags risk at every stage, from onboarding a new vendor to the moment a check clears

How does Ottimate catch AP fraud before payment? 

Ottimate helps finance teams identify potential AP fraud before money leaves the business with a combination of automated controls throughout the AP process. Rather than relying on AP staff to review each transaction, Ottimate analyzes each invoice in context to identify discrepancies and patterns that warrant further review. 

Ottimate uses four primary controls to catch AP fraud before payment. 

Duplicate detection
Ottimate analyzes invoice data to identify potential duplicates, even when invoices aren’t exact matches. This helps teams catch near duplicates that would otherwise fly under the radar and get approved and paid.

Item validation
Discrepancies often hide in line items. Ottimate compares invoice line items against contracted pricing to identify issues that are easy to miss during header-level reviews. 

PO line pairing
Ottimate automatically matches invoice line items with the corresponding purchase order. This helps teams identify discrepancies in pricing, quantities, or other details before invoices are approved. 

AI-powered invoice processing
Ottimate uses AI for processes such as GL coding and approval routing. This helps teams surface exceptions and route invoices to the right reviewers at the right time. 

Lean finance teams don’t have the bandwidth to diligently review every line item of every invoice. Ottimate’s controls allow finance teams to focus on the true exceptions and potentially suspicious activity that requires human judgment. Potential issues are identified early on, when teams still have time to investigate and resolve them before payment is made.

Ottimate’s capabilities allow finance teams to focus on true exceptions and suspicious activity, rather than manually reviewing every invoice that comes through. Potential issues are surfaced  early on, when teams still have the chance to investigate and resolve them before payment is made.

It’s time to prioritize accounts payable fraud prevention

Fraud tactics keep getting harder to catch. The gap is that only 17% of finance teams are using AI to catch them; everyone else is still betting on a person noticing.

When risks are identified early on, finance teams have a better chance of investigating and taking action before payment is made.  With the right combination of technology, processes, and human oversight, AP fraud detection can become effective AP fraud prevention.