Document-fraud detection · Lending & Insurance
The document looks real. That's the problem.
AI can forge a paystub or a damage photo well enough to pass review. Mighty flags it before you fund a loan or pay a claim.

- Income figure was altered
- File edited after it was created
- Hidden instructions found inside
01The problem
One was altered by AI. Can you tell?
Most reviewers can't, and neither can the automation behind them. Mighty reads the document itself: the math, the pixels, and the instructions hidden inside.
One was altered by AI. Pick the fake.
Tap a documentChanges you can't see
A number edited, damage added, a stamp moved. The forgery looks authentic to any reviewer.
Instructions you're not meant to read
Text hidden inside a file to steer the AI that reads it. Your automation obeys; you never see it.
02Where it hits you
Built for the moment before the money moves.

For Lending & Underwriting
It passed review. That's how it becomes a buyback.
Altered paystubs, W-2s, and bank statements clear manual review, then surface as misrepresentation and repurchase demands. Verify the document before you fund.
Repurchase risk caught before funding
Explore lending
For Insurance & Claims
First notice of loss is where fraud hides.
AI can fabricate damage or doctor an estimate in seconds, and touchless claims pay it. Screen the file at intake, before the payout.
Synthetic damage caught before payout
Explore claims03The stakes
$308.6B in fraud a year. Most of it arrives as a document.
- Year-over-year rise in digital document forgery
- 244%
- of document fraud is now digital
- 57%
- human accuracy on AI-altered images
- ~50%
- projected GenAI fraud losses by 2027
- $40B
Entrust, 2025
Passed physical forgery
56-study meta-analysis
Deloitte
Sources: Entrust Identity Fraud Report 2025 · Coalition Against Insurance Fraud · Deloitte Center for Financial Services.
04How it works
One scan. Every file, photo, and field. A verdict before anyone trusts it.
Any document, photo, or extracted text, through one API.
- Document math
- Pixel & layout tampering
- Cross-document consistency
- Hidden instructions
Mighty inspects the artifact itself, not just the text it contains.
An auditable decision your workflow can act on, before anyone trusts the file.
Documents · Images · The text we read · Audio
The anti-fraud signal
See what your intake is already missing.
Bring a sample of your real documents. We'll show you the edits and fakes your reviewers and automation can't see, before they reach a decision.