Why now
The documents that pass today are the losses of tomorrow.
AI can forge a flawless paystub, bank statement, or damage photo in seconds. Manual review was never built to catch it, and every model release widens the gap. Detection has to move from the human eye to a signal your systems can act on.
As models improve, the human eye falls behind.
01The shift
Forgery went digital faster than review did.
The fake is no longer a clumsy cut-and-paste. It is pixel-clean, generated on demand, and rising fast. The trend line, year over year, runs against the reviewer.
- 2023PhysicalForgery was still mostly paperCut-and-paste edits a trained reviewer could catch
- 2024+244%YoY rise in digital document forgeryEntrust Identity Fraud Report, 2025
- 202557%of document fraud is now digitalDigital forgery passed physical forgery
- 2027$40Bprojected GenAI fraud lossesDeloitte Center for Financial Services
02What you are up against
Two things hide in the files you accept.
Changes you cannot see
A number edited, damage added, a stamp moved. The forgery looks authentic to any reviewer, and to the model that reads it next.
Instructions you are not meant to read
Text hidden inside a file to steer the AI that processes it. Your automation obeys; the loss surfaces later as a decision no one can explain.
03The trust gap
The fake gets trusted before anyone checks.
In a touchless pipeline, a forged file becomes trusted data the moment it lands. You learn the truth at repurchase or payout, when the exposure is already on your books. Mighty adds the one checkpoint that was missing.
The forged document is trusted the moment it arrives. You find out at repurchase or payout, after the money is gone.
Mighty verifies the document itself first, then returns an auditable decision your workflow acts on, before you fund or pay.
04The case
Why a defensible signal, not a second look.
Detection moves from a person to a signal
A reviewer can flag what they happen to notice. A signal runs on every file, returns a verdict, and leaves an audit trail you can defend.
Reading a file is not checking it
The tools that pull the text out of a document read it faithfully, including content that should never have been trusted. Tidying a file into neat fields does not confirm it is genuine.
Touchless workflows need a gate
Automation cannot consume unverified material safely. A clear allow, review, or block has to land before anything acts on the document.
05Common questions
The honest scope.
- Does this replace our verification or document-reading vendor?
- No. Mighty sits beside them and verifies the document itself, so the content they read is content you can trust.
- Is this full fraud detection?
- No. The claim is document trust before a decision: the file is genuine, or it is flagged before it moves. We're precise about scope, see the Product page for what we do and don't claim.
- Where do we start?
- One workflow. Income documents before you fund a loan, or claim evidence before you pay a loss.
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.