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Detect Fake Documents – Government, Benefits & Specialised PDFs

Built for fraud ops at lending, insurance & compliance teams

A category hub for fake-document detection use cases that don’t fit the major document buckets – government scheme PDFs, retirement and superannuation statements, regional benefit forms. The same structural API that powers our other hubs, applied to specialised document types.

~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. We do not validate the document against the issuing authority’s database (NDIS portal, ATO, individual super funds, etc.). For database-lookup workflows, combine HTPBE? with the issuer’s own lookup API where one exists. HTPBE? catches the editing and fabrication layer that database lookups miss.

Government, scheme, and regional documents come from a heterogeneous set of issuers – some institutional, some via Office or letterhead templates. INCONCLUSIVE means HTPBE? cannot confirm the file as an untouched original – a reason to escalate to manual review, not proof of fraud. The page-level guides below cover the fraud patterns for each document type.

The problem

Specialised documents fly under the fraud radar

Visa officers, benefits administrators, lenders, insurers, and HR teams all accept specialised documents – NDIS plans, superannuation statements, benefit award letters, regional permits – as proof of eligibility, income, or status. These documents rarely have central fraud detection APIs, so reviewers fall back on visual inspection.

Visual inspection misses every form of structural fabrication. A specialised document edited in a consumer PDF tool looks identical to its source – until the file itself is examined. Its structure and edit history tell a story the rendered page hides.

Each spoke under this hub addresses a specific document type with the patterns and signals unique to that issuer. The hub aggregates the patterns; the spokes deliver the depth.

Why specialised docs are high-fraud

  • Few central fraud detection databases for reviewers to query
  • Long-tail issuers – no per-document AI training data
  • Visual templates are easy to clone; structural origin is harder to fake
  • Reviewers default to visual checks when database access is unavailable
  • Fraud rings target categories with the weakest fraud detection infrastructure

What this looks like

Document fraud in 2026 – three concrete patterns

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

01

Few central fraud detection databases for reviewers to query

02

Long-tail issuers – no per-document AI training data

03

Visual templates are easy to clone; structural origin is harder to fake

04

Reviewers default to visual checks when database access is unavailable

05

Fraud rings target categories with the weakest fraud detection infrastructure

63 layers
Forensic checks per document
~3 sec
Median analysis time, end to end

The detection gap

KYC platforms check the document. HTPBE? checks the file.

Two different checks – both matter.

KYC & identity platforms

Plaid · Persona · Alloy · Jumio

  • Is this a real bank statement template?
  • Does the account number match the identity?
  • Is the document format consistent with the issuing bank?

Detects fake documents. Does not detect edited real documents.

HTPBE? tamper detection API

Structural PDF integrity

  • Was this specific PDF file modified after it was generated?
  • Does the file carry evidence of editing after export?
  • Were digital signatures valid at the time of signing?

Catches edits invisible to visual review and template checks.

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

What HTPBE? checks

How structural analysis works on specialised documents

Same engine, document-type-specific interpretation

No pass for template lookalikes

A specialised document saved as PDF from Word, Excel or LibreOffice does not come back INTACT, however closely it copies the issuer’s layout. With no sign of later editing it returns INCONCLUSIVE for manual review; with evidence of editing or fabrication, MODIFIED.

Post-issuance edit detection

Edits saved after issuance leave evidence in the file. The marker fires regardless of document type.

Dates that disagree

HTPBE? flags timestamps inside the file that disagree with each other – a high-confidence flag.

Pasted seals and logos

Government and scheme documents typically embed institutional seals or logos as part of the template. HTPBE? detects seals and logos lifted from another document and pasted in.

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.

Full API reference for engineering

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

Secure your workflowView API docs

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

Which specialised documents does this hub cover?

Currently NDIS plan documents (Australia) and superannuation member statements (Australia). New types are added based on customer demand – typical additions are regional benefit award letters, government scheme correspondence, and member statements from financial schemes that don’t fit other hubs.

How does this differ from the top-level Document Fraud Detection API?

The /document-fraud-detection-api page is the top-level API hub for developers. This page is a use-case hub that groups specialised document types together. Both are powered by the same engine – this hub adds document-type-specific guidance.

Can I request a new specialised document type?

Yes. Most additions are reactive – when a customer reports a recurring fraud pattern on a document type that doesn’t fit existing hubs, we add a spoke under this hub with document-type-specific guidance.

Are these documents region-specific?

Yes, frequently. NDIS is Australian. Superannuation is Australian. Other regional documents – Indian benefit letters, UK scheme correspondence, EU national-document fraud – fit the same model. The structural API is region-agnostic; the page guidance is regional.

Is this a fake document detector I can use online?

Yes – drop a PDF into the free check and HTPBE? returns a structural verdict (intact, modified, or inconclusive) in about three seconds. When you need to screen documents at scale, sign up and run them through the REST API.

Can HTPBE? work as an edited-image detector?

HTPBE? detects edited or lifted images embedded inside a PDF – forged seals, swapped logos, images patched over original content – even when the rendered page hides them. A standalone image file (a JPEG or PNG with no PDF wrapper) is outside our scope; for those, pair HTPBE? with a dedicated image-forensics tool.

Can I use this as a certificate-of-authenticity checker?

Yes, for PDF certificates of authenticity – HTPBE? detects whether a COA PDF was edited or fabricated after issuance (editing-tool traces, a post-issuance edit trail, tampered embedded seals). It does not query an issuer’s registry, so combine it with the issuer’s own lookup where one exists. Drop the certificate into the free check to see the verdict.

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.

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