Invoicing is the bedrock of supply chains. When handled correctly, it links goods delivered to payments made, ensuring that suppliers are paid on time and buyers can keep production lines running.
But that same process can also become a point of weakness. Errors and fraud in invoicing can drain liquidity, undermine trust and, as recent corporate headlines attest, even accelerate collapse.
Double invoicing, where the same goods or services are billed twice, may pose one of the most damaging and recently visible examples. Sometimes it’s accidental, the by-product of re-submissions or duplicate data entry. Other times, it’s deliberate. Either way, it represents a point of vulnerability and loss of control that leads to overpayments, delayed reconciliations and friction between buyers and suppliers.
Manual and fragmented accounts payable (AP) and receivable (AR) workflows make these problems worse. Many firms still depend on emailed PDFs and spreadsheets that must be keyed into separate systems. That creates blind spots where duplicates can pass unnoticed or where bad actors can slip in doctored invoices. PYMNTS has reported that manual AP processes remain one of the biggest risk vectors for invoice fraud and vendor impersonation attacks, as finance departments struggle to reconcile across disconnected systems.
Two recent bankruptcies show how these weaknesses can metastasize. First Brands, a major auto parts supplier, relied heavily on invoice factoring, selling invoices to financiers for short-term liquidity. During its Chapter 11 proceedings, investigators alleged that some receivables had been sold more than once, meaning the same invoices were effectively pledged to multiple buyers. According to court filings and contemporaneous coverage, payments that should have gone to factoring partners were instead retained internally, as reported by outlets such as Reuters. It was, in effect, a high-stakes version of double invoicing, with millions in play.
A second case, Tricolor Holdings, involved a subprime auto lender that combined vehicle sales, financing, and receivables into a tightly integrated operation. While its collapse stemmed largely from credit performance, analysts noted that weak reconciliation between billing, collections and asset flows made it difficult to track payments accurately, raising the risk of errors and duplicated entries across business lines.
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The Benefits of Automation and AI
Those cautionary tales have intensified focus on automation and artificial intelligence (AI)-driven verification. According to PYMNTS Intelligence, 63% of CFOs cite delays from manual AP workflows as a recurring problem, but AI and automation are increasingly helping to close that gap by flagging anomalies and streamlining approval routes.
A growing set of platforms is embedding AI to detect duplication or fraud before money moves. Routable, for instance, recently introduced an AI agent to its AP platform that scans for duplicate invoice entries, inconsistent vendor identifiers and abnormal values before processing payments. Similarly, a PYMNTS report, “AI Gives Accounts Payable a Seat at the Strategy Table,” describes how machine-learning models are improving invoice matching, enabling AP teams to shift from reactive oversight to proactive risk prevention.
Artificial intelligence in this context does not mean handing decisions entirely to machines. It refers to models that learn from invoice histories, vendor behavior and transaction metadata to identify patterns that deviate from norms. Traditional systems check invoice numbers, amounts and vendor names; AI-enabled engines go further, recognizing “near-duplicates” with slight spelling changes or date shifts. They can also apply anomaly scoring to detect when an invoice’s value is significantly higher than the historical average for a supplier, or when multiple invoices arrive within an unusual time window.
OCR (optical character recognition) and machine learning have improved data capture from PDFs, scans and images, turning unstructured invoices into structured records for automated comparison. Generative AI tools are also being tested to manage exception handling by reviewing supporting documents and recommending human review paths, though final authorization still rests with finance staff.
On the AR side, similar logic applies. PYMNTS Intelligence recently found that 77% of CFOs report measurable improvements in invoice tracking after deploying AR automation, with 85% saying it helps catch discrepancies before they delay payment. By standardizing receivable data and matching it dynamically against sales records, firms reduce the odds that duplicate or misapplied invoices linger undetected.
Automated systems must still enforce three-way matching among purchase orders, receipts and invoices; segregate duties so that no individual can create and approve the same invoice; and ensure consistent data integration across ERP, procurement and treasury systems. When those foundations are in place, AI and automation act as amplifiers, making it possible to flag duplicates before they become overpayments.
Double invoicing may sound like an accounting nuisance, but as the First Brands and Tricolor episodes show, it can snowball into a liquidity crisis when trust and verification are lacking. For firms that trade on tight margins and complex supplier networks, the combination of AI-enhanced detection and automated validation is fast becoming a competitive necessity.
