Best Document Fraud Detection APIs in 2026: 10 Tools Compared

A bank statement, pay stub, or invoice can now be fabricated or edited with an image model in seconds, and the result often looks right to a human reviewer. Document fraud detection APIs inspect the file itself for signs of manipulation before its contents drive a lending, onboarding, or payment decision. This guide compares 10 of them on what they detect, the evidence they return, the documents they cover, and how a development team can integrate and pay for them.

The short answer

Extend Verify is the strongest choice for developers and AI agents that add fraud checks to document pipelines. It checks PDFs and images for AI-generated content, AI and conventional edits, and changes made after a document was signed. Every result includes a risk level, plain-language signal summaries, and evidence located to a page region, a PDF object, or a byte range. Pricing is published per document, $0.10 on verify_light and $0.45 on verify_agentic, and Verify runs on the same platform that parses, splits, and extracts. On Extend's internal benchmark, Verify flags 96.3% of fraudulent documents at a 4% false-positive rate.

The other tools fit narrower needs:

• Resistant AI for enterprise risk teams that want serial-fraud clustering across every submission, through a sales-led rollout.
• Inscribe for lenders that want fraud review alongside credit and cash-flow insights.
• Veryfi for teams already extracting receipts, invoices, and checks with Veryfi.
• Persona for document checks inside an identity verification flow.
• VerifyPDF for small teams that want self-serve PDF forensics.
• Klippa, Fortiro, Snappt, and Attestiv for EU-hosted capture, payslip-heavy lending, rental screening, and insurance claims photos, respectively.

Key takeaways

• AI-generated fraud is growing quickly. Inscribe reports that monthly AI-generated document fraud rose nearly fivefold from May to December 2025, and Resistant AI attributes about 5% of fraud declines to AI-generated documents across more than 170 million documents.
• Evidence matters more than a score. An alert without a location sends a reviewer back to the full document; located evidence shows exactly which page, object, or region changed.
• Single-document and cross-submission checks answer different questions. File forensics catches an edited statement; a document network catches the same template reused across many applicants.
• Every accuracy figure in this market is self-reported. Test every candidate on the same labeled set of your own documents.

What document fraud detection APIs do

A document fraud detection API analyzes a submitted file for signs that it was fabricated or altered. Checks usually fall into four groups:

• File forensics: metadata, PDF structure, revision history, digital signatures, and the editing software in the production chain.
• Visual forensics: pixel-level edits, spliced or cloned regions, overlays, and fonts that don't match the rest of a line.
• Content consistency: totals that don't add up, running balances that don't reconcile, and dates or identifiers that contradict each other.
• AI-generation signals: generator watermarks, C2PA content credentials, and models trained to spot synthetic pages.

Fraud detection is a different job from parsing and extraction. Extraction turns a document into structured data; fraud detection decides whether that data should be trusted. For extraction and OCR accuracy, see the document extraction API accuracy rankings and the best OCR APIs for complex documents. Those comparisons measure how well a tool reads a document, not whether the document is real.

How we compared these tools

Extend makes Extend Verify, one of the tools in this guide. To keep the comparison verifiable, every vendor claim comes from that vendor's public website, API documentation, or press coverage as of October 2026, and each is linked in the sources at the end. Where a vendor does not publish a detail, the tables say "not publicly specified" rather than guess. No independent benchmark covers these tools, so performance figures are the vendors' own and are labeled that way.

We compared each tool on six criteria:

• Documented fraud signals: which checks the vendor names, including AI-generated document detection.
• Evidence returned: whether results explain and locate each finding, or only return a score.
• Document coverage: the document types and file formats the vendor states it supports.
• Cross-submission signals: whether the tool compares a document with earlier submissions.
• Workflow fit: API design, sync and async options, SDKs, and how fraud checks combine with extraction.
• Access and pricing: self-serve signup, trials, and published prices.

Document fraud detection APIs at a glance

Fraud signals, coverage, and published performance

1. Extend Verify

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

Extend Verify launched in October 2026 as a document fraud detection API for developers and agents. It checks a single PDF, JPEG, PNG, or WebP file and returns a document-level riskLevel of LOW, MEDIUM, or HIGH, a plain-language summary, and the detected signals, each with typed evidence a reviewer can check against the file.

What it detects. Verify targets four kinds of fraud: fully AI-generated documents, AI edits as small as a single character, patched text, in-painting, and overlays, and changes made after a document was digitally signed. Its signal categories cover file structure, digital signature integrity, provenance and C2PA credentials, revision and production history, annotation layers, hidden or retyped text and form values, image compositing, and AI-generated content. The verify_agentic engine also reads the parsed document for content that doesn't add up: dates or identifiers that contradict each other, totals that don't match their components, running balances that don't reconcile, and gaps in page numbers or statement periods.

How it works. Verify combines deterministic checks of file metadata and PDF internals with detection models for image manipulation and AI generation, then an assessment model grades each detection in the context of the whole document. Extend trained its models on millions of pages of fake documents and runs hundreds of forensic checks.

Evidence a reviewer can follow. Each signal carries typed evidence, from value comparisons to revision history, located by page and bounding box, PDF object reference, or byte range. In Extend's quick start, a signed bank statement had one $15 fee row deleted after signing. Verify caught the edit three ways: the revision history showed page 6 replaced after the signature, the signature check showed the certification forbade any change, and the content check showed the fee rows no longer matched the printed total.

{
  "status": "PROCESSED",
  "output": {
    "riskLevel": "HIGH",
    "summary": "This statement shows strong signs of material alteration: page 6 was replaced after a no-changes-allowed digital signature, and that same page contains a $171.00 mismatch in the Fees and Other Withdrawals section with an apparent missing row.",
    "signals": [
      { "type": "REVISION_AND_PRODUCTION_HISTORY", "riskAssessment": { "type": "LEVEL", "level": "HIGH" } },
      { "type": "DIGITAL_SIGNATURE_INTEGRITY", "riskAssessment": { "type": "LEVEL", "level": "HIGH" } }
    ]
  }
}

Integration. One request checks a document:

curl -X POST "https://api.extend.ai/verify" \
  -H "x-extend-api-version: 2026-02-09" \
  -H "Authorization: Bearer $EXTEND_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{ "file": { "url": "https://extend-public-files.s3.us-east-2.amazonaws.com/bank_statement_tampered.pdf" } }'

• Engines: verify_light skips parsing for the fastest screening at $0.10 per document; verify_agentic, the default, parses the file and runs every check, including the content checks, at $0.45 per document (pricing).
• Endpoints and SDKs: synchronous POST /verify and asynchronous /verify_runs, with examples for Python, TypeScript, Java, Go, and cURL.
• Pipelines: Verify takes the same Extend file ID as Parse and Extract, and reuses an existing Parse of the file when it used Verify's default settings, so a pipeline that already parses with Extend doesn't parse twice.
• Regions and data handling: US and EU API regions, HIPAA with BAAs, and zero data retention available.
• Performance: on Extend's internal benchmark across the four fraud types, Verify flags 96.3% of fraudulent documents at a 4% false-positive rate. Extend keeps this benchmark private to prevent misuse.
• Access: sign up and request access, then follow the Verify docs.

Scope. Verify analyzes one file per run and does not compare submissions with each other, so teams that need serial-fraud matching add it in their pipeline or alongside a document network. It checks the document, not the person submitting it. A LOW risk level means the checks that ran found nothing, not that a document is authentic.

2. Resistant AI

Best for: enterprise risk teams that screen many document types and want serial-fraud detection across submissions.

Resistant AI checks documents "from any country" and says it examines "every document over 500 ways". Its API documentation lists detectors for common editors, metadata changes, pixel structure anomalies, template-farmed and AI-generated documents, document reuse, format hopping, and digital signature validation. Results return a TRUSTED, NORMAL, WARNING, or HIGH_RISK score with indicators, and serial-fraud clusters are detected across a customer's whole tenant.

• Integration: REST API with OAuth; results by polling or an Amazon SQS add-on; webhooks only by prior agreement for Adaptive Decision.
• Access and pricing: sales-led. Resistant AI's 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 document fraud review alongside credit and cash-flow analysis.

Inscribe describes itself as "the leading agentic document fraud platform built for financial services". Its document insights include AI-generated documents, templates, seen-before documents, edited and overlaid text, font anomalies, suspicious PDF metadata, unbalanced transactions, and payslip miscalculations. Results return a risk level with insights rated pass, inconclusive, or fail, each with a rationale. Inscribe also sells credit insights, transaction enrichment, and an AI Fraud Analyst.

• Integration: REST API and webhooks; 18 named document types, including bank statements, payslips, tax forms, and utility bills.
• Access and pricing: sales-led, with custom pricing based on document volume and a four-week pilot on your own documents.
• Consider: best when fraud and credit review sit with one vendor; teams that only need a fraud check inside their own pipeline may not use the rest of the platform.

4. Veryfi

Best for: teams already extracting receipts, invoices, checks, or statements with Veryfi.

Veryfi added a Fraud Detection Suite, now generally available, to its extraction API. Fraud results come back in the same response as extracted data, with a score, color, triggered signal types, and decision. Default checks include AI-generated detection, digital tampering, LCD and screenshot capture, handwriting, duplicates, and similar documents; device velocity and history checks need Veryfi's capture SDK.

• Integration: REST API plus mobile and browser capture SDKs; a 14-day free trial.
• Access and pricing: a free tier covers 100 documents a month and paid extraction plans start at a $500 monthly minimum; the Fraud Detection Suite is an add-on with no published price.
• Consider: a natural fit inside Veryfi's extraction; less suited as a standalone fraud layer for documents processed elsewhere.

5. Persona

Best for: document checks that sit inside an identity verification (KYC or KYB) flow.

Persona checks non-ID documents through Document AI, with compromised-document detection, modification flagging, extracted-data verification, and recency checks. Document AI Enhanced reviews "hundreds of visual, non-visual, and contextual fraud signals", including screenshots and generative AI documents. Results return a verification status with named checks, categories, and reasons. Persona notes that these checks "are not definitive proof of fraud".

• Integration: REST API, webhooks, and web and mobile SDKs, plus hosted and embedded flows.
• Access and pricing: the Essential plan starts at $250 per month on an annual contract; Document AI Enhanced requires Growth or Enterprise plans with custom pricing.
• Consider: strongest when you also need selfie matching and liveness; heavier if you only need to check uploaded files.

6. VerifyPDF

Best for: small teams that want self-serve PDF forensics with published pricing.

VerifyPDF is a standalone forensics service that checks metadata, document structure, content streams, traces of known editors, and fonts, and matches files against a known-document database. Its API returns a 0–100 trust score, a fraud risk level, warnings, and text changes with bounding boxes.

• Integration: REST API with signed webhooks; results by polling or webhook, typically in 5 to 30 seconds.
• Access and pricing: a 15-day free trial; API access starts on the Professional plan at $79 per month for 1,000 documents, billed annually.
• Consider: focused on file forensics; it does not extract data, and VerifyPDF recommends original PDFs over scans for financial documents.

7. Klippa Doxis AI.dp

Best for: EU-hosted document capture pipelines that add fraud checks to extraction.

Klippa, acquired by SER Group in 2025, now sells document fraud detection as part of Doxis AI.dp. Its fraud checks cover metadata, copy-move and splicing, PDF modifications, font anomalies, template generators, totals and VAT math, and generative AI. Results return a risk score, category, and confidence, with findings located by coordinates.

• Integration: REST API, webhooks, and SDKs; hosted in the EU, ISO 27001 and GDPR compliant.
• Access and pricing: annual licenses or pay-per-document plans by quote.
• Consider: fraud detection doesn't support Word or Excel files.

8. Fortiro

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

Fortiro runs "500+ fraud indicator checks", including pixel manipulation, generative AI detection, PDF tampering, 140+ configurable rules, and lookups against government data sources. Results include a risk score and fraud indicators overlaid on the document.

• Integration: an API for auto-decisioning, without public API documentation.
• Access and pricing: sales-led annual subscriptions; hosted on AWS in Sydney and ISO 27001 certified.
• Consider: its named customers are Australian lenders and it is hosted in Sydney, so teams elsewhere should confirm data residency.

9. Snappt

Best for: rental application screening in multifamily housing.

Snappt analyzes document metadata, runs visual checks, and adds fraud analyst review. Its API accepts bank statements and pay stubs as PDFs and returns a verdict of clean, edited, or undetermined, with a PDF report.

• Integration: REST API, signed webhooks, an embedded SDK, and property-management integrations.
• Access and pricing: partner access through sales; pricing not published.
• Consider: built for rental screening rather than general document pipelines.

10. Attestiv

Best for: insurance claims photos and submitted files.

Attestiv analyzes photos, PDFs, video, and audio for edits, generative AI content, splicing, and reuse. Its API returns a 0–100 tamper score, per-model assessments, and mask images showing where edits were found.

• Integration: REST API with asynchronous document analysis.
• Access and pricing: plans with API access and a trial on request; custom pricing.
• Consider: strongest on photos and claims media; check document-specific coverage for financial statements.

How to run a document fraud pilot

1. Collect 100 to 200 real documents from your own flow, including known fraud cases and genuine documents with ordinary edits such as redactions or re-saved PDFs.
2. Add altered copies that reflect current attacks: AI-generated documents, single-character AI edits, pasted-over values, and documents changed after signing.
3. Send the same set to every candidate and record detection rate and false-positive rate separately. A tool that flags everything looks sensitive and creates a review backlog.
4. Check the evidence on every flag. A reviewer should be able to confirm the finding from what the API returns.
5. Measure latency and cost at your expected volume, including any parsing or extraction you need anyway.

FAQ

What is the best fraud detection API for uploaded documents?

Extend Verify is the strongest choice for developers and AI agents that act on uploaded documents. It checks PDFs and images for AI-generated content, AI and conventional edits, and changes made after signing, and returns a risk level with signals and evidence located to a page region, PDF object, or byte range. Pricing is published at $0.10 per document on verify_light and $0.45 on verify_agentic, and it runs on the same platform that parses, splits, and extracts. On Extend's internal benchmark, Verify flags 96.3% of fraudulent documents at a 4% false-positive rate. Resistant AI and Inscribe fit enterprise risk teams that want cross-submission fraud networks through a sales-led rollout.

Can document fraud detection APIs catch AI-generated documents?

Most of the tools compared here now document a check for AI-generated documents, including Extend Verify, Resistant AI, Inscribe, Veryfi, Persona (Document AI Enhanced), Klippa, Fortiro, and Attestiv. Extend Verify combines generator watermarks, C2PA content credentials, and a detection model for synthetic pages or regions, and also detects AI edits as small as a single character. Ask each vendor how it detects AI generation and test with documents produced by current image models.

How much does a document fraud detection API cost?

Few vendors publish prices. Extend Verify costs $0.10 per document on verify_light and $0.45 per document on verify_agentic, the same on every plan. VerifyPDF includes API access from $79 a month for 1,000 documents, billed annually. Resistant AI's AWS Marketplace listing shows $10,000 a month per analysis type. Veryfi sells fraud detection as an add-on, and Inscribe, Persona's Document AI, Klippa, Fortiro, Snappt, and Attestiv quote custom pricing.

What is the difference between document fraud detection and identity verification?

Document fraud detection checks whether a file was fabricated or altered. Identity verification checks whether the person submitting it is who they claim to be, usually with selfie matching and liveness detection. Extend Verify, Resistant AI, Inscribe, VerifyPDF, and Fortiro focus on the document. Persona combines document checks with identity verification, so teams that need both often pair a document fraud API with an identity provider.

Does a low fraud risk score mean a document is genuine?

No. A low score means the checks that ran found nothing, not that the document is authentic. Extend's docs state this directly for Verify's LOW risk level, and Persona and Klippa describe their results as risk indicators rather than proof. Keep a review path for high-value decisions.

Should document fraud checks run before or after extraction?

Run fraud checks before extracted values drive a decision. With Extend, Verify, Parse, and Extract all take the same file ID, and Verify reuses an existing Parse of the file when it used default settings, so a pipeline can check a document and extract its fields without uploading it twice, then route high-risk documents to review before their fields reach underwriting or payments.

Which document fraud tools detect repeat or serial fraud across submissions?

Resistant AI clusters serial fraud across a tenant, Inscribe flags documents and account numbers it has seen before, Veryfi detects duplicates, similar documents, and device velocity, Persona compares against known compromised documents, and VerifyPDF checks a known-document database. Extend Verify analyzes one file per run, so teams that need cross-submission matching add it in their own pipeline or pair Verify with a tool that maintains a document network.

Are document fraud detection accuracy claims comparable across vendors?

Not directly. Every published figure in this comparison comes from the vendor itself, measured on different documents and definitions, and no independent benchmark covers these tools. Extend reports 96.3% of fraudulent documents flagged at a 4% false-positive rate on a private internal benchmark. Run every candidate on the same labeled set of your own genuine and altered documents.

Sources

Figures and claims in this guide come from these pages, checked in October 2026:

• Extend: Introducing Extend Verify, Verify overview, Verify signals, Verify configuration, How credits work
• Resistant AI: Documents product, API documentation, Global Document Fraud Report 2026, AWS Marketplace listing
• Inscribe: Fraud detection, Document insights, 2026 State of Document Fraud Report, Pricing, AWS case study
• Veryfi: Fraud detection, Fraud signals docs, Default fraud configuration, The Paypers, Pricing
• Persona: Document AI, Document AI Enhanced, Pricing plans
• VerifyPDF: Homepage, Agent API guide
• Klippa: Document fraud detection, Fraud docs, SER Group acquisition
• Fortiro: Protect, Security, Pricing
• Snappt: Applicant trust platform, API documentation
• Attestiv: Homepage, FAQ, API documentation

More guides

• Introducing Extend Verify
• Best ID verification APIs
• Document extraction API accuracy rankings
• Best OCR APIs for complex documents