For Insurance & Claims
First notice of loss is where fraud hides.
AI can fabricate damage, erase it, or doctor a repair estimate in seconds, and touchless claims pay it. Mighty screens the photo, the estimate, and the paperwork at intake, before the payout.
01Built around your team
Mighty flags what to review. Your adjusters keep the judgment.
Full automation isn't the goal. Mighty marks the suspicious file at intake so your adjusters and SIU spend their time where it actually matters, not re-checking the clean ones.
Touchless and straight-through claims stay fast on the clean files. The suspicious ones get an SIU referral with the evidence attached, before the indemnity goes out.
02The synthetic claim
The defining fraud isn't one fake. It's a whole file built to agree with itself.
A doctored estimate alone can slip past. Mighty reconciles the claim across its pieces, the damage photo against the estimate against the first notice of loss, and surfaces the contradiction. When the numbers line up too perfectly to be real, that's a tell too.
Damage photo
Loss shown, vehicle and angle
Repair estimate
Line items, parts, labor, total
Intake packet
Date, location, narrative of loss
Contradiction found. The estimate total does not match the damage in the photo. Routed to SIU before the payout.
Reconciliation across photo, estimate, and intake, on a single claim file.
03Where the loss leaks
Each fake is a line of loss leakage your loss ratio never sees coming.
Damage added or erased
Indemnity paid on a loss that never happened
Totals and line items altered
Inflated severity, straight to leakage
Fabricated charges
Padded indemnity spend on every file
Hidden instructions planted in the file
Automation steered to pay without review
04How it works
Screen the file at intake. A verdict before the claim pays.
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.
05The stakes
$308.6B in fraud a year. A growing share arrives as a tampered file.
- U.S. insurance fraud per year
- $308.6B
- of detected P&C fraud is a tampered document
- ~1/3
- human accuracy on AI-altered images
- ~50%
- YoY rise in digital forgery
- 244%
Coalition
Shift / Deloitte
56-study meta-analysis
Entrust 2025
Sources: Coalition Against Insurance Fraud · Shift Technology / Deloitte · Entrust Identity Fraud Report 2025.
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.