Receipt fraud

Fake Receipt Detection – Catch Regenerated and Edited PDFs

Built for fraud ops at lending, insurance & compliance teams

A receipt-generator site can produce a plausible-looking PDF in seconds – and most expense reviewers cannot tell. Finance and AP teams approve thousands of expense receipts a month. Insurance claims adjusters see receipts attached to every property and travel claim. Tax preparers receive client-uploaded receipts as substantiation. The fabrication scripts have changed – generator sites, AI tools, edited real receipts – but the visual still passes review every time.

~3 sec
per document
63 checks
forensic layers
1,500+
docs / month on Growth
Plans
subscriptions or one-off packs – see pricing
Scope

HTPBE? analyzes the structural layer of the PDF file – the layer that records every edit, even invisible ones. We don’t inspect holograms, phone photos, or ID biometrics. If your fraud problem is a digitally fabricated or tampered receipt, we’re the most specific tool for it.

When HTPBE? returns INCONCLUSIVE on a receipt that should have come from a POS or platform issuer (Uber, Square, Stripe, hotel PMS, restaurant POS), that is a reason to escalate to manual review, not proof of fraud – it means HTPBE? cannot confirm the file as an untouched original.

The problem

Modern document fraud is invisible to visual review

A growing class of document fraud opens a genuine PDF, edits a balance, a date, or a beneficiary, and re-saves it. Visually nothing changes – the document passes pixel-level review, layout review, and KYC.

Structural PDF analysis reads the layers rendering engines never expose: revision history, object structure, signature coverage maps. That is where edits leave fingerprints they cannot wipe.

Common tampering patterns

  • Modified balances or totals after export
  • Swapped IBAN or beneficiary on invoices
  • Post-signature edits on contracts
  • Backdated issue and modification dates
  • Fabricated documents from consumer PDF tools

What this looks like

How fake and tampered receipts actually look

Three real fraud mechanics we catch at the structural PDF layer.

01

Generator-tool fabrication

Free online receipt-generator sites and AI tools produce a plausible PDF for any merchant, amount, and date the user types in. A receipt comes back MODIFIED when the file itself carries evidence of editing or fabrication, whatever tool produced it; one HTPBE? cannot confirm as an untouched original goes to manual review.

02

Real receipt edited after issuance

Authentic Uber receipt or hotel folio downloaded by an actual customer, opened in any PDF editor, the amount or date bumped, exported. The edit typically leaves traces of the editor in the file – structural evidence of post-issuance editing.

03

Same receipt submitted multiple times across expense periods

A real receipt is reused across multiple expense reports with the date subtly edited each time. Each edited copy carries structural evidence of the change, so HTPBE? flags it – the underlying payment was made once but reimbursed three times.

The scale

~5%
of annual T&E spend lost to expense fraud on average
$1.9M
median annual cost of expense fraud at mid-market companies
~3 sec
per receipt via API

Why your existing checks miss this

OCR extracts the amount. It does not check the file.

Concur and Expensify read whatever the receipt shows – even if the receipt was generated this morning.

Expense management platforms (Concur, Expensify, Ramp, Brex, Pleo, Navan) extract receipt data via OCR and run policy rules. They cannot tell you whether the receipt PDF was issued by a real merchant or fabricated five minutes ago through a generator site. Tax-filing software accepts receipt PDFs at face value. HTPBE? catches the receipt PDF the employee or claimant uploaded at the moment of intake – standalone, no platform integration required.

Results in under 3 seconds30 to 1,500+ documents/month

What HTPBE? checks

Detection capabilities

Deterministic structural signals. No probabilistic scores, no model training.

Looking right earns nothing

However closely a receipt copies the Uber, Square, Stripe or hotel layout, it is not passed on looks. INCONCLUSIVE means HTPBE? cannot confirm the file as an untouched original – a reason for manual review, not proof of fraud.

Evidence in the file decides

A receipt comes back MODIFIED when the file itself carries evidence of editing or fabrication, whatever tool produced it – generator site, AI tool or desktop software. One HTPBE? cannot confirm as an untouched original should go to manual review.

Post-issuance edit detection

Editing a platform receipt after issuance – in a PDF editor, or by rebuilding it in other software – leaves structural evidence behind. HTPBE? flags it as MODIFIED.

Reused-template detection

HTPBE? detects documents built from a reused template – the pattern behind one source turning out receipts for ‘different’ merchants or dates.

Dates that disagree

A ‘freshly issued’ receipt whose own dates show it was changed months later is a high-confidence flag for post-issuance editing.

Reworked documents

HTPBE? detects documents reworked after their original creation and documents assembled from pages of different sources.

Share with engineering

Wire this into your intake pipeline in under a day

Two API calls – one POST to submit the PDF, one GET to retrieve the verdict. Forward this page to your engineering team; the full API reference, quotas, and copy-paste examples in cURL, JavaScript, Python, PHP, Go, and Ruby are one click away.

Pricing

Self-serve plans, no sales call

All plans include the same forensic checks. Pick the quota that matches your monthly document volume.

manual

Starter

30 credits/mo

Manual spot-checks and integration testing

most common

Growth

350 credits/mo

Active document processing pipelines

high volume

Pro

1,500 credits/mo

High-volume automation and API integrations

Enterprise (unlimited, on-premise available) — see full pricing

API key on signup. Free test environment on every plan. No card required.

Customer Stories

Teams that stopped document fraud

Compliance, finance, and risk teams use HTPBE? to catch manipulated PDFs before they become costly mistakes.

Caught an invoice where the total had been changed by less than a thousand dollars. Without this I would have approved it without a second look.

Sarah M.

AP Manager

United States

We had three applicants in the same week with bank statements that looked completely fine. Two of them were flagged as modified. You simply cannot see this by reading the document — it is in the file structure.

Lars V.

Risk Analyst, Online Lending

Netherlands

Salary slips were coming with altered figures. We identified two problematic files before the placement was finalised.

Priya K.

HR Operations Lead

India

Since we started checking documents this way, we stopped two applications early in the process that would have been very difficult to reverse later.

Julien R.

Fraud Analyst, Fintech

France

Some applicants were sending PDFs that looked authentic but had been edited in ways not visible to the eye. We now ask for checked originals when something is flagged. Already saved us from a few bad decisions.

Marta S.

Compliance Coordinator

Spain

One invoice was caught because there was a mismatch between the document dates and structure. That particular case would have cost us significantly.

Tariq A.

Finance Manager

United Arab Emirates

FAQ

Frequently asked questions

How is this different from Concur or Expensify?

Concur, Expensify, Ramp, and Brex extract receipt data via OCR and apply policy rules. They process whatever the PDF shows, including fabricated PDFs. HTPBE? inspects the PDF file structure to detect that the receipt was authored on a desktop, generated by a tool, or edited after issuance. Use both: extraction tools for data capture, HTPBE? for integrity fraud detection.

Can it catch ChatGPT or other AI-generated receipts?

A receipt comes back MODIFIED when the file itself carries evidence of editing or fabrication, whatever tool produced it – AI tools included. A receipt HTPBE? cannot confirm as an untouched original should go to manual review. For a deeper treatment of AI-generated documents specifically, see /use-cases/ai-generated-document-detection.

What about phone photos of receipts?

Phone photos are raster images with no PDF structure to analyse – outside scope. Always require digital PDF receipts where possible. Most modern receipt issuers (Uber, Stripe, Square, hotel PMS) email PDFs directly; require those rather than phone photos for any receipt above your audit threshold.

What does an INCONCLUSIVE verdict mean for a receipt?

INCONCLUSIVE means HTPBE? cannot confirm the file as an untouched original. For receipts that should come from issuers (Uber, Lyft, hotel chains, Square, Stripe, e-commerce platforms), INCONCLUSIVE is a review trigger: it is not evidence of fraud, and it is not a pass. Route the case to manual receipt sourcing or a merchant check.

Secure your workflow

Create your account – check PDFs on the web or with an API key, both ready on signup.
No sales call. Cancel any time.