Super statement fraud

Fake Super Statement Detection — Catch Edited AU Statements

Built for fraud ops at lending, insurance & compliance teams

A super statement balance can be edited in five minutes — and most reviewers will not notice. Property managers ask for super statements as backup income proof. Lenders use them as asset evidence. Visa applicants attach them as savings demonstrations. The fund-issued PDF is treated as authoritative, but the AustralianSuper, AwareSuper, HostPlus, REST, or Cbus original can be opened in any PDF editor, the balance bumped, and re-exported. The visual is unchanged. The file structure is not.

~3 sec
per document
59 checks
forensic layers
From $15
per month
1,500+
docs / month on Growth
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 altered or fabricated super statement, we’re the most specific tool for it.

When HTPBE? returns INCONCLUSIVE on a super statement, that’s itself a fraud signal in this context — real fund-portal exports always carry the fund’s institutional producer signature, never a desktop tool.

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 super statements actually look

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

01

Balance edited after fund download

Authentic super statement from the fund portal opens in any PDF editor. Balance bumped from $42,000 to $142,000. Exported as PDF. Producer field changes from the fund’s document engine to whichever editor was used. Visual page renders identically; structural metadata flips.

02

Statement fabricated in Word from a template

A template lifted from a fund’s public sample, populated with the user’s name and a desired balance, exported. Producer is Microsoft Word; the structured fund metadata authentic statements carry is missing entirely.

03

Real statement with edited contribution history

Genuine fund statement with the contribution history rewritten to show consistent employer payments where there were gaps. Incremental update markers in the xref chain expose the post-issuance edit.

The scale

~50%
of AU tenancy fraud involves fake or doctored income / asset documents
~3 sec
per super statement via API
No fund
no fund-side API integration needed — works on the file

Why your existing checks miss this

AUSfund APIs check the fund. They do not check the file.

And applicants who edited the statement rarely consent to fund-side fraud detection.

Funds operate their own portals; aggregators (Basiq, Frollo, Illion) handle Open Banking-style asset fraud detection — but only when the applicant agrees to connect. Applicants who edited the file rarely do. AUSfund and ATO super lookups are not accessible to private property managers or lenders. HTPBE? catches the super statement the applicant uploaded, regardless of whether fund-side or aggregator access is available — standalone, no fund API, no ATO lookup.

Results in under 3 seconds30 to 1,500+ documents/monthFrom $15/mo

What HTPBE? checks

Detection capabilities

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

Producer signature on the statement

Authentic super statements come from fund document systems — recognisable producer signatures specific to AustralianSuper, AwareSuper, HostPlus, REST, Cbus, Australian Retirement Trust, UniSuper, and other major funds. When the producer is Microsoft Excel, Word, LibreOffice, Chrome Headless, or a generic PDF library, the document was edited or fabricated on a desktop.

Incremental update trail

A clean fund export has one cross-reference table. Re-saves through Excel or PDF editors append a second xref — visible structural evidence of post-export editing.

Balance and contribution arithmetic

Line arithmetic across the statement (opening balance → contributions → returns → fees → closing balance) is checked row by row. Edited closing balances break the chain unless every dependent field is also adjusted.

Modification timestamp gap

A real statement issued in July has CreationDate ≈ ModDate in July. A six-month gap on a "freshly issued" statement is a high-confidence flag for post-export editing.

Font subset divergence across pages

Multi-session edits or page reassembly leave font subset prefix shifts. Single-session legitimate fund exports have consistent subsets across all pages.

Image-stream artefacts in fabricated headers

Fabricated statements often paste fund logos lifted from the fund’s site. The pasted image stream carries different compression characteristics than authentic embedded headers — a structural fingerprint.

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

$15/mo

30 checks/mo

Manual spot-checks and integration testing

most common

Growth

$149/mo

350 checks/mo

Active document processing pipelines

high volume

Pro

$499/mo

1,500 checks/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

Does HTPBE? work with statements from any Australian super fund?

Yes. The analysis is producer-agnostic — it inspects whichever PDF the applicant submits. Authentic statements from AustralianSuper, AwareSuper, HostPlus, REST, Cbus, Australian Retirement Trust, UniSuper, Hesta, BUSSQ, Sunsuper-pre-merger, and other major funds all carry recognisable producer signatures. Re-saves through Excel or generator tools change those signatures, which HTPBE? flags.

How is this different from Basiq or Frollo asset fraud detection?

Basiq, Frollo, and similar aggregators check assets by connecting to the applicant’s accounts via Open Banking-style consent. HTPBE? inspects the super statement PDF the applicant uploaded directly, without consent or aggregator integration. Applicants who edited the statement rarely consent to aggregator access.

Can it catch SMSF balance statements?

Yes. SMSF statements come from the fund’s administration software (BGL Simple Fund 360, Class Super, Supermate). Authentic exports carry producer signatures from these systems. Hand-edited or fabricated SMSF statements show producer mismatches and incremental update trails the same way major-fund statements do.

What about scanned super statements?

A scan-to-PDF made from a real printed statement typically returns inconclusive — institutional metadata is gone because the scanner authored a fresh PDF. Treat inconclusive on a super statement as a prompt for manual review or a request for the original PDF download from the fund portal.

What does an INCONCLUSIVE verdict mean for a super statement?

HTPBE? returns INCONCLUSIVE when a super statement PDF lacks the institutional metadata that genuine fund-portal exports carry — typically because the file was authored on a desktop with consumer software (Word, Excel, LibreOffice) rather than downloaded from the fund's member portal. In the super-statement context, INCONCLUSIVE is itself a high-confidence fraud signal: authentic statements from AustralianSuper, AwareSuper, HostPlus, REST, Cbus, and other major funds always come from their document engines, never from a desktop tool. Treat INCONCLUSIVE on a super statement as fraud-positive and request the original PDF directly from the fund portal before making any asset or income decision.

Secure your workflow

Create your account — API key on signup, free test environment on every plan.
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