AI Agents

Context

Built for insurance within the Fraud detection & alerting stack, this agent is used during claim assessment and pre-settlement to verify that what’s being claimed aligns with the policy actually in force—declarations, endorsements, limits, deductibles, and exclusions. Typical scenarios include FNOL-to-assessment transitions, midstream coverage disputes, and cases where recent endorsements may have shifted coverage.

What it does

The agent reads the claim file (loss description, dates, items/services, invoices) alongside the policy pack (declarations, schedule, riders/endorsements, limits/deductibles, exclusions) and cross-checks who is covered, what is covered, when coverage applies, and how much is payable. It flags mismatches—such as a claimed peril excluded by wording, items outside scheduled limits, dates outside the effective window, or deductibles not applied—and returns a structured pass/flag outcome with a concise rationale and a link to the exact clause or table used.

Core AI functions

Document classification and section parsing isolate the relevant policy and claim sections; OCR and clause/table extraction normalize dates, amounts, limits, deductibles, perils, and covered items; cross-document alignment reconciles claim attributes with policy terms; contradiction and omission checks surface issues like referenced riders that are absent from the schedule or excluded perils named in FNOL; and reason-code generation explains each flag in plain language with clause-level lineage.

Problem solved

Manual reconciliation between claim content and policy terms is slow and error-prone. Endorsement drift, unclear limits and deductibles, or missed exclusions create late reversals, leakage, and inconsistent outcomes.

Business impact

Assessments become faster and more defensible: non-covered items are filtered early, approvals are cleaner where coverage is clear, disputes decline because decisions cite clause-level evidence, and adjusters spend less time rebuilding the link between claim and coverage.

Integration and adjacent use cases

Integration is light–moderate: ingest claim files and policy documents from your DMS or core; write pass/flag results, reason codes, and evidence links into your claims workflow or case management—no changes to cores required.

Common combinations in this stack include:

• Behavioral pattern analyzer (claims SIU),

• Image & document authenticity detector,

• Network association risk detector, and

• Suspicious claim escalation agent to round out SIU referrals with a complete evidence bundle.