Payment fraud has become routine enough that finance teams can no longer manage the risk with periodic training and careful email habits. New data from the Yooz 2026 Payment Fraud Readiness Report, based on a survey of 750 U.S. finance, accounting, and accounts payable professionals, finds that 70% of finance professionals say their organization experienced a payment fraud attempt in the past two years — or could not rule one out. That figure alone should change how finance leaders think about their exposure and the processes they rely on to manage it.

The financial toll is rising as well. Among organizations that experienced a known fraud attempt, 28% lost money. Of those incidents, 39% produced losses of $50,000 or more. These events are occurring across finance functions of all sizes, and manual processes are a common thread running through many of them, which makes the structure of AP operations increasingly important as payment workflows grow more complex.

Manual Processes Are Losing More Money to Fraud

The most consequential finding in the Yooz report concerns the relationship between accounts payable (AP) process design and fraud outcomes. Organizations with mostly manual AP processes lost money in 42% of known fraud attempts, compared with 30% among highly automated teams and 22% among organizations using a combination of automated and manual processes.

The data shows that manual AP workflows create the conditions in which fraud can thrive. Human review bottlenecks, inconsistent verification steps, limited real-time visibility into payment activity, and approval chains that rely on individual judgment all increase the odds of a successful fraud attempt. In a manual process, a person must catch fraudulent invoices that closely mimic legitimate vendors, and the differences in those documents are often imperceptible to the human eye. An automated system, by contrast, screens every transaction against historical patterns, flags anomalies, and routes suspicious activity for review before a payment is authorized.

The Threat Has Gotten More Sophisticated

Finance teams that believe employee training is their primary fraud defense are working from an increasingly outdated model. Companies have treated fraud as a people problem for years, operating on the assumption that employees could be trained to spot fake emails and catch something suspicious. Generative AI has made that approach less reliable, as fraudulent invoices, emails, and even voice requests have become much harder to distinguish from the real thing.

The fraud methods most commonly deployed against AP teams exploit the specific vulnerabilities of manual workflows. A fake invoice that closely resembles a legitimate vendor's document can pass a human visual review, and a payment request that appears to come from a trusted executive may generate urgency that overrides careful verification.

Automated systems do not eliminate the need for human judgment. Rather than asking finance professionals to screen every transaction manually, automated tools handle the routine screening at scale and escalate exceptions for human review — a more effective use of both the technology and the expertise of finance teams.

Where Fraud Is Most Likely to Succeed

Understanding the fraud patterns most common in AP operations helps finance leaders identify where the risk sits in their own processes.

Invoice fraud remains one of the most prevalent attack vectors. Fraudsters submit invoices for services not rendered, or modified versions of legitimate invoices with altered bank details. In a manual environment, catching these requires someone to notice discrepancies, usually while evaluating a high volume of documents under time pressure. Automated systems can cross-reference invoice data against purchase orders, flag duplicates, and identify documents that do not match vendor records.

Business email compromise (BEC) targeting AP functions continues to grow. These attacks use spoofed or compromised email accounts to request payment changes, vendor account updates, or urgent wire transfers, and the requests often impersonate senior executives or trusted vendors. Without a systematic verification process tied directly to the payment workflow, the burden of detection falls entirely on the individual receiving the request.

Vendor account manipulation exploits the update processes many AP teams handle through email. A fraudster contacts the AP team claiming to be a vendor and requests a change to banking details. Without automated verification and a formal change management workflow, these requests can succeed.

What Finance Teams Can Do

The Yooz data shows that moving fraud prevention from a people-dependent function to a process-embedded one can keep fraud at bay. Making that change requires teams to structure workflows so that human judgment is applied where it adds the most value, while automated screening handles the volume.

Finance teams that have not yet moved beyond primarily manual AP operations can take meaningful steps without a complete technology overhaul. Centralizing invoice intake through a single, controlled channel removes the vulnerability of scattered email submissions. Establishing a formal, system-based process for vendor banking changes eliminates the attack vector that makes account manipulation possible. Requiring two-step verification for payment changes above defined thresholds protects against impersonation fraud.

There is also significant opportunity for organizations that have implemented some automation but have not extended it into fraud-specific workflows. The Yooz 2026 AI in Finance Report found that only 19% of finance teams say they use AI for audit, risk, compliance, or fraud detection and prevention, even as AI-powered detection has become one of the most effective tools available for screening transactions at scale. Integrating AI into fraud prevention workflows adds further protection through continuous monitoring — a level of oversight that manual review and periodic audits cannot replicate.

Ultimately, the data shows that fraud prevention needs to be structural, not situational. Training employees to recognize suspicious activity remains important, but systematic controls that screen every transaction, verify every vendor change, and flag every anomaly before payment authorization are the foundation those training efforts need to rest on.

Finance teams looking for a deeper look at the current fraud landscape and what the data shows about readiness across different types of organizations can explore the full findings in the Yooz 2026 Payment Fraud Readiness Report.

Source: FinTechZoom