Spotting Expense and Invoice Fraud Early: Hidden Patterns and Forensic Tactics

Corporate finance and operations teams are navigating a new level of sophistication in expense and invoice abuse. The core challenge is not only stopping obvious false claims but revealing the subtle signals that hide in plain sight. This article explains how to detect the most costly patterns early, why expense fraud risks in businesses are rising in 2025, and how a layered forensic approach fits into real workflows without slowing them down.

Several independent data points show the shift in risk. Business email compromise remains one of the most damaging attack types, often used to redirect invoice payments by impersonating trusted vendors. The FBI’s overview of business email compromise outlines the common triggers and the importance of out of band verification for any change to banking details (FBI). In parallel, seventy nine percent of organizations reported attempted or actual payments fraud activity in 2024, with vendor impersonation and spoofed communications highlighted as key factors (AFP).

Against this backdrop, finance and shared services leaders are rethinking controls. The most effective programs combine policy and approval rules with forensic checks on documents and images. This is where targeted automation helps. The goal is to surface high risk anomalies within minutes, not weeks, and to route only a small fraction of cases to manual review. That is how organizations meaningfully reduce expense fraud risks in businesses while keeping operations smooth for legitimate employees, customers and vendors.

Why expense and invoice fraud is accelerating now

Expense reimbursement fraud and invoice manipulation thrive where volumes are high, pressure to pay is real and documents are treated as proof at face value. Three market shifts deserve attention in 2025. First, generative tools make it easier to fabricate convincing receipts and invoices that pass a quick visual check. Our analysis of how AI systems can create fake receipts and invoices shows how accessible these tools have become. Second, social engineering has become more targeted. Senior decision makers receive tailored messages that reference real projects or vendors, which increases the success rate of payment redirection. For a look at how threat actors industrialize these tactics, see our piece on eepfake as a service and executive impersonation trends. Third, procurement and shared services teams carry large backlogs and limited headcount, which means manual checks catch only a subset of red flags. When verification relies on eyeballing screenshots or PDFs, subtle edits and reused media tend to slip through.

Regulators and standard setters are also moving. The OECD’s updated guidelines for fighting bid rigging offer practical signals for collusion in public procurement that translate well to corporate sourcing and vendor management (OECD 2025). Meanwhile, the security community continues to promote verification outside the email channel for any change to beneficiary data. The key takeaway is simple. Fraud patterns increasingly blend document tampering, identity deception and small but telling anomalies across data fields and media files. That is exactly what forensic detection is designed to spot.

Hidden patterns that drive the biggest losses

The most expensive patterns are rarely the most visible. They masquerade as ordinary paperwork and ordinary messages. Finance and compliance teams should prioritize the following signals in accounts payable, travel and expense, and claims flows.

• Vendor impersonation with banking detail changes. Attackers forward a legitimate invoice thread, then request a new account number for the next payment. Always verify banking changes through a known phone number or portal rather than replying to the email.
• Shell suppliers and inflated services. Red flags include PO box addresses, vague descriptions, sudden spend spikes with a new supplier and overlaps between employee and vendor contact data.
• Threshold splitting and duplicates. Multiple small invoices or card transactions sit just below approval thresholds. Duplicate payments hide behind minor changes such as freight or tax lines. Government audits have documented these patterns for years and the lessons apply to corporate programs too.
• Receipt manipulation and reuse. Offenders submit the same receipt twice with small edits, or generate an entirely synthetic receipt that mimics a real merchant template. For a deeper look at the mechanics and risks, see our analysis of AI generated document fraud.
• Bid patterns that hint at collusion. Unusually close pricing across bidders, rotation of winners and repeated subcontractor relationships after awards can indicate coordinated behavior.

Even a single pattern may be enough to trigger a review. The strongest results come from connecting signals across data sources and files. For example, a new supplier with a mailbox address is not necessarily suspicious. Combine that with a banking change request sent after hours and a set of invoices with round amounts and the risk picture changes. This is why organizations pair policy controls with forensic analytics that operate on both structured fields and the media itself.

Early detection with forensic signals that scale

Forensic checks do not need to be heavy or academic. They can be fast, repeatable and integrated into daily finance operations. The aim is to cut through volume and route a small number of high signal cases to human reviewers. The following checks consistently surface risk without creating workflow friction.

• Supplier master analytics. Cross check vendor and employee records for shared addresses, phone numbers or email domains. Flag one time suppliers, mail drops and sudden changes to banking details for out of band review.
• Invoice level anomaly checks. Use fuzzy duplicate detection across invoice numbers, dates, amounts, tax and freight to uncover repeats with small edits. Cluster analysis around approval thresholds helps reveal deliberate splitting.
• Journal and amount distribution checks. Benford style tests and round amount clustering are useful to prioritize which items deserve closer attention.
• Media and document authenticity analysis. The strongest blind spots live inside the files themselves. A modern approach inspects image and PDF characteristics, detects signs of AI generation or editing, and highlights regions of concern at pixel level so reviewers can decide quickly. It also checks metadata consistency and can extract provenance signals where available. For context on the promises and limits of metadata frameworks, see our primer on the C2PA standard C2PA under the microscope.
• Payment behavior monitoring. New beneficiary accounts that receive large or urgent payments, late night approvals and a sudden shortening of time from invoice to cash out are all reasons to pause.

For organizations that want to operationalize these checks, Vaarhaft provides a pragmatic path. The Fraud Scanner is an AI based forensic software that verifies the authenticity of digital images and documents in seconds and returns a clear PDF assessment for each analysis. Reviewers see highlighted regions at pixel level where potential manipulation is detected, which improves decision speed. The same engine is available as a web tool and as a REST API so teams can integrate authenticity checks into existing expense, claims or supplier workflows without building a new system. All processing is fully GDPR compliant with models developed and hosted in Germany, and analyzed media are deleted after processing. For document centric use cases such as receipts and invoices, see the dedicated entry point for document analysis.

In environments where synthetic or tampered media is suspected, a second line of defense can confirm authenticity during collection. Vaarhaft SafeCam is a browser based camera experience delivered by SMS that guides users through verification steps and only accepts photos of real three dimensional scenes. Attempts to photograph screens or printouts are detected and blocked. There is no app to install or login to manage, which keeps friction low when you need a quick proof. SafeCam complements the Fraud Scanner by providing verified follow up images only when an initial file looks suspicious. This reduces false positives and helps teams make confident decisions.

A lean workflow that fits real operations

The most successful programs keep the bar high for evidence while keeping the path smooth for legitimate users. Below is a simple operating model that many finance, claims and shared services teams can adopt without a long change program.

1. Screen everything with lightweight analytics. Apply vendor master checks and invoice level anomaly tests to all incoming items. Focus on duplicates, threshold clusters, new beneficiary accounts and timing anomalies. The ACFE maintains a compact library of anti fraud analytics ideas that can be adapted to most ERP and T&E systems.
2. Escalate risky items to forensic media checks. Run suspicious receipts, invoices and supporting photos through an authenticity analysis. Use pixel level highlights and metadata findings to make a quick decision and to document the rationale. If the signal is strong, investigate. If the signal is weak but non zero, move to step three.
3. Collect verified follow up evidence. Invite the user to submit new photos through SafeCam to confirm that the scene is real and not a photograph of a display or printout. This allows you to approve legitimate claims quickly and stop synthetic submissions before payment.

This model delivers two benefits. It puts forensic depth exactly where it matters most and it keeps throughput high for honest users. The combination of light touch analytics, targeted authenticity checks and verified recapture creates a repeatable pattern that scales across functions. Whether you are handling travel and expense in HR and finance, processing supplier invoices in shared services or reviewing supporting photos in insurance claims, the logic is the same. Start broad with data signals, go deep only when needed, and give users a simple way to provide reliable proof.

If your team is building a content provenance strategy, keep in mind that metadata alone is not a silver bullet. It is a valuable layer when available but it can be missing, stripped or forged. Our primer on the C2PA standard explains what the framework can provide and where its limitations are today (C2PA under the microscope). This is why combining metadata signals with intrinsic media analysis is important for resilience.

Expense fraud risks in businesses will continue to evolve. The good news is that layered defenses are very practical today. If you want to see how the Fraud Scanner and SafeCam fit into your procure to pay, expense or claims process, schedule a short conversation with our team here.