Insurance
Document fraud detection for insurance claims
Doctored invoices, staged-loss documentation, and identity misuse at claim time. Detectory renders forensic verdicts on claims documents before payouts, and maps the provider and repair-shop rings behind organized claim fraud.
The problem
Claims fraud costs US insurers over $300B a year
The Coalition Against Insurance Fraud estimates fraud drains $308B annually, and document manipulation is the workhorse: inflated repair invoices, altered medical bills, backdated policy documents, and staged-loss photo sets. SIU teams review a fraction of flagged claims by hand while organized provider and repair-shop rings industrialize the paperwork.
$308B
annual US insurance fraud cost
Coalition Against Insurance Fraud
10-20%
of claims contain some element of fraud
industry estimates
<20%
of suspected fraud referred for investigation
SIU benchmarks
Example verdicts
The documents your team sees, scored
Representative documents from this workflow with the forensic verdict Detectory renders and the finding behind it. Suspect documents are never auto-denied; they route to your reviewers with the evidence itemized.
Repair estimate (auto claim)
Body-shop invoice supporting a collision claim
Finding: Line items duplicated from a prior claim with inflated labor hours; same shop letterhead appears in 27 claims across 4 carriers
Medical bill (injury claim)
Provider superbill for soft-tissue treatment
Finding: CPT code pattern matches a known upcoding profile and the provider NPI is newly registered; routed to SIU
Proof of loss (property claim)
Inventory and receipts for a theft claim
Finding: Receipt metadata predates the purchase dates claimed; two receipts generated by the same online template service
Policy document (coverage dispute)
Policyholder-submitted declarations page
Finding: Document matches issued policy record byte-for-byte; cleared instantly
What Detectory does here
Purpose-built detection for this workflow
Pre-payout document verdicts
Invoices, estimates, bills, and loss documentation scored before the claim pays, moving fraud detection out of pay-and-chase.
Provider & shop ring analytics
Template reuse, billing-pattern, and identity signals across claims expose organized provider, clinic, and repair-shop rings.
Photo & receipt forensics
Metadata, reverse-template, and manipulation analysis on submitted photos and receipts catches staged and recycled loss evidence.
SIU referral packets
Consolidated cases with itemized exhibits and timestamps, formatted for SIU investigation, NICB referral, and litigation.
Case walkthrough
One body shop, four carriers, 27 claims
A repair shop inflates estimates using recycled line items and doctored photos, spreading claims across carriers to stay under each one’s radar. Detectory recognizes the shared letterhead artifacts, duplicated damage photos with altered metadata, and the billing cadence, and clusters all 27 claims into a single ring case.
Outcome: The SIU receives one consolidated referral with cross-claim exhibits, and every new claim referencing the shop is scored on arrival.
Send a redacted set of paid claims through Detectory and audit what slipped past.
Other industries