Claims Adjudication
The decision at the heart of insurance: is this claim covered, for how much, and can you show why?
Claims adjudication is the determination at the core of insurance operations: reviewing a submitted claim against the policy's terms and the supporting evidence to decide whether it is covered, what amount is payable, and under what conditions — approval, partial payment, denial, or referral for investigation. In health insurance, adjudication runs against benefit plans, coding rules, and medical necessity criteria; in property and casualty, against policy wordings, exclusions, deductibles, and loss documentation. Every adjudication is a small legal-financial judgment, executed millions of times.
The process is documentary from end to end. The inputs are documents — claim forms, invoices and bills, medical records, adjuster and police reports, photos, policy schedules and endorsements — and the historical cost of adjudication was largely the cost of humans reading them. Document AI restructures this: extraction turns the submission into structured facts; coverage verification matches those facts against the policy's actual terms; validation catches internal inconsistencies (treatment dates outside the policy period, invoice totals that don't sum); and rules or models evaluate the assembled picture. Clean, well-evidenced claims within authority limits adjudicate automatically; the rest route to human adjusters with the extracted facts, the relevant policy language, and the specific anomalies pre-assembled.
Because adjudication decisions are consequential and contestable — a denial can be appealed, litigated, or examined by a regulator — automated adjudication carries a high evidential bar. Each decision needs a reconstructable basis: the extracted values (with provenance to source documents), the policy provisions applied, the rules or model versions involved, and the confidence at each step. Jurisdictions increasingly constrain full automation of adverse decisions, so mature programs automate approvals aggressively, keep humans on denials, and treat the audit trail not as overhead but as the thing that makes the automation defensible.
A caseworker made of software — assembling the file, chasing the gaps, and moving the claim toward resolution.
The emergency room model for claims — severity assessed at the door, so the right cases reach the right desks first.
Is this actually covered? Answered by reading the policy, not by remembering it.
Proof Perimeter runs document AI inside your own perimeter — with a provenance record on every field.
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