Document Forensics

Fake Invoice Checker

Catch fake, altered, vendor-impersonation, and AI-generated invoices before money leaves your account.

AP and finance teamsSmall business ownersMarketplaces and platformsVendor management teams
4.9·132+ reviews

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TrueDoc ROI and performance stats

<120sForensic report
10× fasterFraud review
40+Fraud signals
8+ hrsSaved / 100 docs

Estimated savings based on replacing a 10–15 minute manual document review with automated TrueDoc analysis.

Built on Trusted AI Infrastructure
Google Cloud
Gemini
OpenAI
Anthropic
Google Cloud
Gemini
OpenAI
Anthropic
Google Cloud
Gemini
OpenAI
Anthropic
Google Cloud
Gemini
OpenAI
Anthropic
Google Cloud
Gemini
OpenAI
Anthropic
Google Cloud
Gemini
OpenAI
Anthropic
Google Cloud
Gemini
OpenAI
Anthropic
Google Cloud
Gemini
OpenAI
Anthropic
Google Cloud
Gemini
OpenAI
Anthropic
Google Cloud
Gemini
OpenAI
Anthropic
Google Cloud
Gemini
OpenAI
Anthropic
Google Cloud
Gemini
OpenAI
Anthropic

Multi-layer forensic logic

Proprietary detection scans template variance, metadata drift, pixel-level retouching, and structural anomalies the human eye misses.

▸ Document Analysis · LiveID: 8829-XQ
Risk score: High · 94%Signals matched: 12,042

Metadata deep-dive

Inspects EXIF, software signatures, edit history, and structural fingerprints.

SoftwareAdobe Photoshop 2024
ModifiedDetected
Geo-tagMismatch

Privacy-first by design

Originals are processed in encrypted memory and removed after analysis. Reports stay redacted by default.

No training on your data
Team & admin controls
▸ 01 · The Problem

Why eyeballing a document no longer works

Invoice fraud has shifted from copy-paste edits to fully synthetic invoices generated by AI in seconds — and many AP workflows still rely on the human eye.

TrueDoc's fake invoice checker inspects invoice structure, metadata, math, vendor details, and AI-generation signatures so finance teams can spot tampered or fake invoices before payment.

▸ 02 · Fraud Signals

What we look for

Cross-checked across 5+ vectors
▸ Primary signal

AI-generated invoices that look real but reference no actual transaction

Detected at pixel + metadata + structural layers

Altered amounts, bank details, or due dates in legitimate invoices

Vendor impersonation with spoofed logos and templates

Recycled invoices submitted multiple times across periods

Metadata inconsistencies between PDF creator tools and claimed dates

What gets checked

Vendor invoices (PDF and image)
Pro-forma invoices
Marketplace and platform invoices
Reimbursement and freelance invoices
▸ 03 · Workflow

From upload to verdict

01

Upload the invoice

PDF or image, up to 10MB.

02

Run forensic + AI analysis

Layout, math reconciliation, metadata, font, and AI-generation signals.

03

Review evidence

See per-field findings — totals, vendor details, dates — with regions highlighted.

04

Decide

Approve, hold for review, or escalate to fraud with the full evidence attached.

Vendor invoice fraud detection

Vendor invoice fraud detection covers the highest-loss invoice attacks: silent bank-detail swaps on legitimate vendor invoices, vendor impersonation with spoofed logos and templates, and recycled or round-tripped invoices submitted across periods.

TrueDoc compares structural fingerprints across submissions in your queue, flags metadata that disagrees with claimed vendor and date, and surfaces inconsistencies between the rendered invoice and the underlying PDF objects.

AI-generated invoice detection

AI-generated invoice detection evaluates layout regularities, font fingerprints, and generative-AI signatures common to invoices produced by current image and PDF generators.

Fully synthetic invoices from non-existent vendors are now one of the most common ways busy AP queues are attacked. TrueDoc's AI-generated invoice detection catches them alongside hand-edited tampering in a single trust score.

Common invoice fraud patterns in 2026

Wire-fraud variants where bank details on a legitimate vendor invoice are silently swapped.

Fully synthetic invoices from non-existent vendors targeting busy AP queues.

Round-tripping where the same invoice is resubmitted with minor edits across months.

AI-generated invoices that perfectly match a known template but reference no real PO.

How to spot a fake invoice — red flags AP teams should review

Math that doesn't reconcile. Line items, quantities, unit prices, subtotal, tax, and total should add up exactly. Even a $0.02 mismatch on a clean line-item invoice is a red flag for hand-editing.

Last-minute bank-detail changes. A request to update bank details on a known vendor's invoice — especially via email and especially under time pressure — is the single highest-risk signal in AP fraud. Verify via a known, out-of-band channel before paying.

Vendor identity drift. Subtle changes in legal name, address, tax ID, or domain (e.g. acme-payments.com vs acme.com) often indicate vendor impersonation.

Invoice number anomalies. Sequence breaks vs the vendor's prior invoices, duplicated numbers across periods, or formats that don't match the vendor's normal scheme.

Missing or mismatched PO reference. An invoice with no PO when the vendor normally issues against POs — or a PO number that doesn't match any open order — should never auto-approve.

Font, alignment, and metadata inconsistencies. Mixed fonts, misaligned columns, or PDF metadata (Producer, ModDate, incremental updates) that disagrees with the claimed vendor and date.

AI-generation signatures. Fully synthetic invoices from non-existent vendors are increasingly common — TrueDoc's AI-generated invoice detection catches them alongside hand-edited tampering in a single trust score.

Run a real document. Get a forensic verdict.

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▸ FAQ

Frequently asked questions