FraudFinder reads the surface of a document - trained UK/Irish templates, metadata, structure - scored across 350+ indicators in about three seconds. Teams switch to TamperCheck when the documents they're missing were generated whole, with no edit history for a surface check to find.
Why teams look for a FraudFinder alternative
- The fakes you're missing were never edited - a generated payslip has clean metadata and no resave history by construction, and satisfies template and structure checks the same way.
- Your documents sit outside a trained template set - template depth stops helping the moment a format hasn't been taught.
- Client Data is retained for up to six years by default, and terms permit anonymised, aggregated use in model training - a data posture worth re-reading before renewal.
At a glance
The same fifteen questions we answer on the homepage, with FraudFinder in the third column.
Documents covered
- TamperCheck.ai
- 100+ document types from 190+ countries
- FraudFinder
- Bank statements, utility bills and financial documents; UK and Irish bank templates
Forensic checks per document
- TamperCheck.ai
- 200+ forensic layers on every upload
- FraudFinder
- 350+ fraud indicators - fonts, metadata, software history, barcodes, structure (their claim)
AI-generated documents
- TamperCheck.ai
- Dedicated synthesis pass, resolved to the field
- FraudFinder
- Checks against ChatGPT images and known template farms
Image forgery detection
- TamperCheck.ai
- Pixel-level: splice, resave and edge-sharpness deltas
- FraudFinder
- Present, but the method is template- and metadata-led
PDF & file structure
- TamperCheck.ai
- Objects, fonts, metadata and editor traces
- FraudFinder
- Yes
Field-level alteration
- TamperCheck.ai
- Yes - the altered field named and located
- FraudFinder
- Indicators rolled into one document decision
Scans, photos & physical marks
- TamperCheck.ai
- Stamps, embossing, signatures, print artefacts
- FraudFinder
- PDFs and images accepted
Automated QC on findings
- TamperCheck.ai
- Every finding re-validated before you see it
- FraudFinder
- Not published
What you get back
- TamperCheck.ai
- A verdict, the field named, in plain English
- FraudFinder
- A risk report across the indicators that fired
Time to verdict
- TamperCheck.ai
- About a minute, unattended
- FraudFinder
- About 3 seconds (their claim)
Price per document
- TamperCheck.ai
- $0.50, published
- FraudFinder
- Not published - credit bundles or an order form after a demo
Commitment
- TamperCheck.ai
- None - no seat fees, no minimum, no cap
- FraudFinder
- Credit bundle or contract
How you start
- TamperCheck.ai
- Self-serve - first top-up matched free, live the same day
- FraudFinder
- Book a demo
Document retention
- TamperCheck.ai
- Zero - analysed in memory, never written to disk
- FraudFinder
- Client Data held up to six years unless deletion is requested
Training on your documents
- TamperCheck.ai
- Never
- FraudFinder
- Terms permit anonymised, aggregated Client Data for model development
| TamperCheck.ai | FraudFinder | |
|---|---|---|
| Detection depth | ||
| Documents covered | 100+ document types from 190+ countries | Bank statements, utility bills and financial documents; UK and Irish bank templates |
| Forensic checks per document | 200+ forensic layers on every upload | 350+ fraud indicators - fonts, metadata, software history, barcodes, structure (their claim) |
| AI-generated documents | Dedicated synthesis pass, resolved to the field | Checks against ChatGPT images and known template farms |
| Image forgery detection | Pixel-level: splice, resave and edge-sharpness deltas | Present, but the method is template- and metadata-led |
| PDF & file structure | Objects, fonts, metadata and editor traces | Yes |
| Field-level alteration | Yes - the altered field named and located | Indicators rolled into one document decision |
| Scans, photos & physical marks | Stamps, embossing, signatures, print artefacts | PDFs and images accepted |
| Automated QC on findings | Every finding re-validated before you see it | Not published |
| What you get back | A verdict, the field named, in plain English | A risk report across the indicators that fired |
| Speed & cost | ||
| Time to verdict | About a minute, unattended | About 3 seconds (their claim) |
| Price per document | $0.50, published | Not published - credit bundles or an order form after a demo |
| Commitment | None - no seat fees, no minimum, no cap | Credit bundle or contract |
| How you start | Self-serve - first top-up matched free, live the same day | Book a demo |
| Data handling | ||
| Document retention | Zero - analysed in memory, never written to disk | Client Data held up to six years unless deletion is requested |
| Training on your documents | Never | Terms permit anonymised, aggregated Client Data for model development |
FraudFinder figures are taken from their own published material - fraudfinderai.com product pages and published terms, checked September 2026. Anything they state about themselves and we cannot verify is marked “their claim”. For the full head-to-head breakdown, see the TamperCheck vs FraudFinder comparison.
What switching gets you
- Per-field rendering forensics and a dedicated AI-generation pass, built for documents that were never edited in the first place.
- No template library required - an unfamiliar issuer isn't a coverage gap.
- Zero retention, never trained on your documents - no six-year retention window to explain.
When FraudFinder is still the better fit
- You underwrite UK and Irish applicants exclusively, where template coverage (95%+ of UK/Irish bank formats) is real and well-tuned.
- You need extraction, affordability checks and AML in one contract, not verification alone.
Moving from surface checks to per-field forensics
The switch matters most for the class of fraud a template-and-metadata method structurally can't see: documents generated end-to-end, which are template-correct and metadata-clean by construction because nothing was ever edited. If that's the gap you've identified, TamperCheck's per-field comparison and dedicated AI-generation pass are built for exactly that case, and the response shape changes accordingly - from an indicator count to a named field.
If your applicant base is genuinely UK/Ireland-only and extraction plus affordability checks are part of what you rely on FraudFinder for, weigh that against what you're giving up: template coverage doesn't extend to formats it hasn't been trained on, and it can't distinguish a genuine document from one generated to match its own template.
FraudFinder alternative: common questions
Does TamperCheck catch what FraudFinder's 350+ indicators catch?
It covers the same ground - metadata, structure, fonts - as part of a 200+ layer forensic stack, and adds per-field rendering comparison and a dedicated AI-generation and deepfake pass that a template-and-metadata method doesn't run.
Why would a template-trained system miss an AI-generated document?
Because a generated document is template-correct by construction, has clean metadata since it was written once, and has no resave history since nothing was edited - every signal a surface check depends on is simply absent.
How does data retention compare between the two?
FraudFinder's published terms provide for Client Data retention of up to six years unless deletion is requested, with anonymised aggregate use permitted in model training. TamperCheck never writes the document to disk and never trains on it.
See how TamperCheck handles your own documents
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