Best synthetic document detection vendors in 2026

Image models can now produce a bank statement, pay stub, invoice, or receipt that passes a human review in seconds. Synthetic document detection vendors check whether a submitted file was generated or altered by AI before it drives a lending, onboarding, payment, or claims decision. This guide compares eight of them on how they detect synthetic documents, the accuracy they publish, and the use cases they fit.

The short answer

Extend Verify is the strongest synthetic document detection vendor for developers and AI agents.

• It catches full fakes and partial AI edits. Verify combines generator watermarks, C2PA content credentials, and a detection model that judges whole pages or individual regions synthetic, and it detects AI edits as small as a single character.
• Every flag shows where the AI content is. Results include a risk level, a plain-language summary, and evidence located by page and bounding box, PDF object, or byte range.
• It fits the pipeline you already run. Pricing is published per document ($0.10 on verify_standard, $0.45 on verify_agentic), and Verify uses the same file ID as Extend's Parse and Extract APIs.

In a challenging internal benchmark that includes single-character AI edits as well as fully AI-generated documents, Verify flags 96.3% of fraudulent documents at a 4% false-positive rate.

The other vendors fit narrower needs:

• Resistant AI for teams that need serial-fraud detection across submissions and a sales-led rollout.
• Inscribe for lenders that want AI-generated document flags alongside credit and cash-flow review.
• Veryfi for receipts, invoices, and checks already extracted with Veryfi.
• Persona for AI-generated non-ID documents inside an identity verification flow.
• Klippa, Fortiro, and Attestiv for EU-hosted capture, payslip-heavy lending, and insurance claims photos, respectively.

Key takeaways

• AI-generated documents are still a small share of fraud but growing. Inscribe says AI-generated flags have stayed above 0.1% of all documents processed across its network every month since April 2026, and Resistant AI attributes about 5% of fraud declines in its adaptive decisioning sample to AI-generated documents.
• Metadata and watermark checks are not enough. Not every generator writes provenance data, and a screenshot or re-save removes it.
• Page-level detection misses partial edits. A genuine statement with one AI-edited balance needs region-level analysis.

How synthetic document detection works

Vendors combine four methods, and the strongest ones use more than one:

• Provenance checks read generator watermarks, C2PA content credentials, and generator metadata. When present, they name the generator with high confidence. When stripped, they say nothing.
• Visual detection models look for the textures, structural patterns, and rendering artifacts image generators leave behind, and keep working after a screenshot.
• Model fingerprinting matches a document to the specific generator that produced it, or flags it as outside the distribution of genuine documents of its type.
• Content checks read the document and test whether it holds together: balances that reconcile, totals that match their components, and dates that agree. Generated documents often look right and add up wrong.

Detection scope matters as much as method. A page-level check answers "was this page generated?" A region-level check also catches a genuine document with one AI-edited value, which is the more common attack on financial documents.

Synthetic document detection vendors at a glance

1. Extend Verify

Best for: developer teams and AI agents that need to trust the documents they act on.

Extend Verify checks a PDF, JPEG, PNG, or WebP file and returns a riskLevel of LOW, MEDIUM, or HIGH, a plain-language summary, and the signals it found, each with evidence a reviewer can check against the file.

How it detects synthetic documents. Verify's AI_GENERATED_CONTENT signal covers generator watermarks, content credentials that assert generation, and pages or regions a detection model judges to be synthetic. A separate provenance check flags C2PA credentials that fail to verify and watermarks whose manifest was stripped. Extend trained its models on millions of pages of fake documents, and Verify also detects AI edits as small as a single character inside an otherwise genuine document.

Beyond AI generation. The same run checks for patched or retyped text, spliced or painted-over regions, and changes made after a document was signed. On verify_agentic, it also reads the parsed document for totals, balances, and dates that don't reconcile.

Accuracy. In a challenging internal benchmark covering four fraud types (fully AI-generated documents, AI edits as small as a single character, patched and overlaid text, and changes made after signing), Verify flags 96.3% of fraudulent documents at a 4% false-positive rate. Extend open-sources its other benchmarks; this one stays private to prevent misuse.

• Engines and pricing: verify_standard runs without parsing for $0.10 per document, and verify_agentic adds the content checks for $0.45 per document (pricing).
• Integration: synchronous POST /verify and asynchronous /verify_runs, with examples for Python, TypeScript, Java, Go, and cURL.
• Scope: Verify focuses on the document itself, one file per run, and pairs with any identity provider for checks on the person.

2. Resistant AI

Best for: teams that need serial-fraud detection across submissions and a sales-led rollout.

Resistant AI says its "ensemble of detectors analyzes visual textures, structural inconsistencies, and subtle signs of manipulation (far beyond simple metadata checks)", and names GPT-4o, Gemini, Grok, Midjourney, Canva, and Adobe Firefly among the generators it covers. Results return a verdict (trusted, warning, or high risk) with indicator-level explanations and localized visualization when supported.

• Published figures: an 86% average out-of-the-box detection rate before customer-specific training, and false positives under 1%, with no test set described. Its 2026 fraud report attributes about 5% of fraud declines in its adaptive decisioning sample to AI-generated documents.
• Access and pricing: sales-led. The AWS Marketplace listing shows $10,000 per month for each analysis type.
• Consider: a strong fit for large risk teams with a procurement process; teams that want to start from an API key will find the onboarding heavier.

3. Inscribe

Best for: lenders and fintechs that want AI-generated document flags alongside credit and cash-flow review.

Inscribe launched a dedicated AI-generated document detector in 2025. Its 2026 State of Document Fraud Report describes the approach as image forensics and model fingerprinting: "fingerprinting how specific generative models create documents and detecting whether a document falls outside the distribution of what real documents look like." The AI_GENERATED insight appears in its document insights, and advanced insights require access to its AI Fraud Analyst.

• Published figures: no accuracy or false-positive rate for the AI detector. Inscribe reports that AI-generated flags have held above 0.1% of all documents processed across its network every month since April 2026, with bank statements the most common AI-generated document type.
• Access and pricing: sales-led, with custom pricing based on volume.
• Consider: best when fraud and credit review sit with one vendor.

4. Veryfi

Best for: receipts, invoices, checks, and statements already extracted with Veryfi.

Veryfi says its fraud engine analyzes "how the document was built: pixel patterns, font rendering, layer artifacts, generation fingerprints", not only metadata, and names ChatGPT, Stable Diffusion, Midjourney, Gemini, DALL-E, and GANs among the sources it detects. AI detection results come back inside the extraction response as a fraud score, color, signal types, and attribution.

• Published figures: none for AI detection.
• Access and pricing: a 14-day free trial; the Fraud Detection Suite is an add-on to extraction plans without a published price.
• Consider: strongest when Veryfi is already your extraction layer; less suited to documents processed elsewhere.

5. Persona

Best for: AI-generated non-ID documents inside a KYC or KYB flow.

Persona's Document AI Enhanced analyzes "hundreds of visual, non-visual, and contextual fraud signals, including digital edits and tampering, screenshot use, synthetic and generative AI documents, and content inconsistencies" for non-government-ID documents. It returns a risk level and fraud indicators, with visual overlays in Persona's document viewer.

• Published figures: none.
• Access and pricing: available on Growth and Enterprise plans and enabled by the account team; not available on Startup or Essential plans.
• Consider: strongest when you also need selfie matching and liveness; heavier if you only need to check uploaded files.

6. Klippa Doxis AI.dp

Best for: EU-hosted capture pipelines that add AI detection to extraction.

Klippa's generative AI check runs two modules: a metadata module that reads generator information embedded in the file and can name the generator and model, and a visual model that looks for patterns of AI-generated content. Klippa's docs state the check "works at the level of pages and higher, so it does not verify if specific elements, such as text or images within the document, were generated by AI."

• Published figures: none; Klippa says its scores "do not confirm or rule out fraud definitively."
• Access and pricing: annual licenses or pay-per-document plans by quote.
• Consider: page-level scope means partial AI edits need another check; fraud detection doesn't run on Word or Excel files.

7. Fortiro

Best for: lenders verifying payslips, bank statements, and tax documents.

Fortiro Protect is built to detect "deepfake and shallowfake documents and images — from basic PDF edits through to advanced AI manipulations", with generative AI image and document detection, pixel-based manipulation detection, reverse image search, and layout analysis. Results show fraud indicators overlaid on the page, through the API, the user interface, or a PDF report.

• Published figures: none with a stated basis.
• Access and pricing: sales-led annual subscriptions; hosted on AWS in Sydney.
• Consider: its named customers are Australian lenders, so teams elsewhere should confirm data residency.

8. Attestiv

Best for: insurance claims photos and submitted files.

Attestiv flags generative AI images from popular text-to-image platforms, including DALL-E, Stable Diffusion, and Midjourney, alongside metadata, provenance, and editor-trace checks. It returns a 0–100 tamper score, with 50 as the default threshold, and masks showing where some edits were found.

• Published figures: each model is "tested to a minimum of 97% AUC and biased toward false negatives", with no test set described.
• Access and pricing: plans with API access; custom pricing.
• Consider: strongest on photos and claims media; check coverage for financial documents.

Synthetic documents vs. synthetic identity fraud

The terms overlap but describe different problems:

• A synthetic document is a file generated or altered to look genuine: an AI-generated bank statement, a pay stub with an AI-edited salary, or a fabricated utility bill.
• Synthetic identity fraud combines real and fake personal data into a new identity, which fraudsters then support with synthetic documents.

Document detection vendors check the file. Extend Verify lists identity credentials among the documents it checks, so it can inspect an ID document itself for AI generation or edits. Identity verification providers check the person, usually with selfie matching and liveness. Teams fighting synthetic identities typically run a document check on every supporting document and pair it with an identity provider; see the best ID verification APIs for that side.

How to test synthetic document detection

1. Collect 100 to 200 genuine documents from your own flow, including scans, phone photos, and born-digital PDFs.
2. Generate fakes of the same document types with current image models, and make partial edits: one AI-changed balance, name, or date in an otherwise genuine document.
3. Screenshot or re-save some fakes to strip their metadata and watermarks.
4. Send the same set to every vendor and record detection and false-positive rates separately, for full fakes and partial edits.
5. Check what each flag returns. A reviewer should be able to see where the AI content is without rereading the whole document.

FAQ

What is the best synthetic document detection vendor?

Extend Verify is the best synthetic document detection vendor for developers and AI agents. It combines generator watermarks, C2PA content credentials, and a detection model that judges whole pages or individual regions synthetic, so it catches fully generated documents and genuine documents with AI-edited values, and it locates each finding on the page. It has published per-document pricing ($0.10 or $0.45). Resistant AI fits teams that need serial-fraud detection across submissions and a sales-led rollout.

How do vendors detect AI-generated documents?

Vendors combine four methods: provenance checks that read generator watermarks, C2PA content credentials, or generator metadata; detection models trained to recognize the textures and structure image generators leave behind; model fingerprinting that matches a document to the generator that produced it; and content checks that catch values that don't add up. Metadata and watermark checks are fast and precise but disappear when a document is screenshotted or re-saved, so production detection needs a visual model too.

What is the difference between synthetic documents and synthetic identity fraud?

A synthetic document is a file generated or altered to look genuine, such as an AI-generated bank statement or pay stub. Synthetic identity fraud combines real and fake personal data into a new identity, which may be backed by synthetic documents. Document fraud detection checks the file; identity verification checks the person. Teams fighting synthetic identities usually need both: a document check on every supporting document and an identity provider for selfie and liveness checks.

How accurate is AI-generated document detection?

No independent benchmark covers these vendors, and each one measures detection on its own documents and definitions. Extend Verify flags 96.3% of fraudulent documents at a 4% false-positive rate in a challenging internal benchmark that includes single-character AI edits as well as fully AI-generated documents. Test every candidate on the same set of genuine and AI-generated documents from your own flow.

Can synthetic document detection catch AI edits to a real document?

Only if the vendor analyzes regions, not just whole pages. Extend Verify detects AI edits as small as a single character and judges individual regions as well as pages. Klippa's documentation states that its generative AI check works at the page level and does not verify whether specific text or images within a document were generated. Ask each vendor whether it detects partial AI edits and test with genuine documents where one value was changed by an image model.

Sources

Checked in November 2026:

• Extend: Introducing Extend Verify, Verify overview, Verify signals, How credits work
• Resistant AI: Gen AI fraud, Documents product, API documentation, Global Document Fraud Report 2026, AWS Marketplace listing
• Inscribe: Fraud detection, Document insights, 2026 State of Document Fraud Report
• Veryfi: Fraud detection, Pricing
• Persona: Document AI Enhanced
• Klippa: Fraud component docs
• Fortiro: Protect, Security
• Attestiv: Homepage, FAQ

More guides

• Best document fraud detection APIs
• Receipt fraud detection API: how it works and vendors compared
• Best ID verification APIs
• Introducing Extend Verify