AI for Insurance

Give claims leadership a reproducible, vendor-pattern-aware blueprint for standing up an agentic claims orchestration layer on top of existing claims skills (FNOL intake, fraud, subrogation, reserve, CAT triage, narrative, coverage explanation, COI). The skill takes a file — or a batch of files — and produces an orchestration plan: which sub-agent runs next, what inputs it needs, what HITL checkpoint it must clear, what evidence is captured in the audit trail, what authority tier it routes to, what bias / Section 1557 / ADA / FCRA / CMS-0057-F / per-state UCSPA / NAIC-AI / CO-SB-21-169 / NY-DFS-Reg-187 / IN-HB-1271 / AL-SB-63 / EU-AI-Act-Annex-III / WA-OIC-PA / TX-PA / AZ-PA / MD-PA gates apply, and how the explainable decision record is composed at each branch. Output is a per-file orchestration runbook, a program-level governance artifact a DOI examiner / NAIC AI Systems Evaluation Tool / external auditor / reinsurer / model-risk-officer / chief-AI-officer can read from the same artifact, and a multi-vendor handoff envelope (MCP / A2A / Agent-to-Agent) so the controller logic is portable across Duck Creek's Agentic AI Platform (AI Assurance + AI Gateway), Sedgwick Sidekick / Sidekick+, Travelers AI Claim Assistant (OpenAI Realtime API), Cytora Autopilot, AIG-style orchestration, Microsoft / Cognizant stack, Convr Intake, Sixfold AI, Intellect AI, Docugami, illumend COI, Sure MCP, in-house Python harness, and Anthropic / OpenAI / Google API-direct stacks.

Turn a certificate of insurance (COI) — along with the underlying contract, the per-contract requirements library, the per-holder standard-requirements library, the per-state required-endorsement library, and any referenced endorsements — into a structured, per-contract / per-holder / per-state compliant decision: does this certificate meet the insurance requirements in the contract, what is missing or non-compliant, what follow-up is required from the vendor or producer, and what is the renewal tracking plan. The skill produces an AI-bias-audited, authority-checked, distribution-scoped, per-role-signed, multi-language-deliverable bundle the vendor risk manager, the procurement officer, the GC superintendent, the legal reviewer, the producer, the vendor, the carrier compliance officer, and (where applicable) the state DOI examiner can read from the same artifact without rework. Designed to replace line-by-line manual review of ACORD 25 / 27 / 28 / 75 / 855 / 855CA and carrier-branded certificate forms.

Turn a flood of catastrophe (CAT) FNOLs into a prioritized, routable triage queue during surge events — hurricanes, wildfires, severe convective storms, winter freezes, floods, hail, earthquakes, and named perils. Produces a per-claim triage record (severity band, coverage sanity check, vendor/adjuster recommendation, reserve seed, communication plan) and a batch-level dashboard (queue by severity, ZIP cluster, assignment status, SLA risk) so CAT desks, field network managers, and customer service can move from "everything is urgent" to "these 20 first, these 200 next, these 2,000 by Friday." Output is personalized to the carrier's named CAT event library, per-peril severity thresholds, field capacity roster, contractor networks, authority limits, and reserve-category labels drawn directly from `config.yml`.

Transform raw adjuster notes, recorded statements, and claim documentation into a polished, chronological claims narrative suitable for the claim file, coverage determination, litigation support, or regulatory reporting. Output is sized and structured by narrative purpose, governed by jurisdiction-specific documentation standards and AI-bias laws, and keyed to the company's reserve-category conventions and authority-limit thresholds in `config.yml`.

Produce a defensible initial or revised claims reserve recommendation — broken out by indemnity, medical, expense (ALAE / ULAE), and recovery offsets — from the current state of a claim file. The skill surfaces the drivers behind the number, the coverage and jurisdictional factors considered, the actuarial method named, the confidence range with a three-point estimate, the reserve-adequacy traffic light, the reinsurance-treaty notification cue, the AI-bias / disparate-impact check on any per-zip / per-class adverse pattern surfaced, the authority-check against the adjuster's reserve / payment / declination authority, the triggers that should prompt a reserve re-evaluation, and a distribution-scoped, per-role-signed deliverable bundle the adjuster, the supervisor, the claims manager, the actuary, the carrier compliance officer, the reinsurance-claims officer, and (where applicable) the state DOI examiner can read from the same artifact without rework. The skill is the upstream feeder for the Claims Narrative Drafter v3.0, the Coverage Explanation Letter v3.0, the Subrogation Opportunity Finder, the Loss Run Analyzer v2.0 (whose reserve-adequacy verdict cross-checks against this skill's recommendations), the Underwriting Risk Profile v2.0 (which uses the reserve-trend signal in its renewal verdict), and the Renewal Review Brief v3.0.

Capture a complete, well-structured First Notice of Loss (FNOL) from unstructured inputs — phone transcripts, email bodies, chat logs, digital form submissions, and incident photos — and convert them into a standardized intake record with claim classification, coverage applicability, missing-data prompts, severity triage, and routing recommendation. Output is personalized to the carrier's per-LoB / per-state / per-peril routing rules, coverage-vs-peril sanity-check rules, acknowledgment templates, authority limits, reserve-category labels, and file-note ID format drawn directly from `config.yml`.

Analyze a claim file (claim notice, adjuster notes, supporting documents, photos, medical bills, repair estimates, prior-claim history) and produce a structured fraud-indicator report — line-of-business-specific, jurisdiction-aware, NICB-aligned, AI-bias-tested, and SIU-ready. The output names every red flag with the indicator code from the carrier's fraud-indicator library, scores severity, applies a per-LoB SIU-referral-threshold (configurable per the carrier's authority and state mandatory-reporting law), recommends a disposition (auto-process, escalate to senior adjuster, refer to SIU, refer to NICB, refer to state Fraud Bureau), and produces a distribution-scoped packet (handler / SIU / counsel / regulator) the receiving party can act on without reformatting.

Extract, organize, and analyze loss-run data to identify claim trends, loss drivers, IBNR exposure, reserve adequacy, and actionable insights for underwriting decisions, renewal strategy, submission packaging, and risk-management recommendations. The skill ingests raw loss-run reports across the 12 most common carrier formats and the four most common AMS / aggregator formats, parameterizes large-loss thresholds and the IBNR method per the carrier or agency configuration, runs a per-LoB metric library, projects reserve adequacy, runs an AI-bias / disparate-impact check on any per-zip / per-class adverse pattern surfaced, runs an authority-check against the underwriter's authority limits, and ships a distribution-scoped, per-role-signed analysis the underwriter, broker-of-record, producer, insured, and (where applicable) state DOI examiner can read from the same artifact without rework.

Produce a renewal review brief that drives **a specific retention decision** — Renew As-Is, Re-Negotiate, Restructure, Remarket, or Decline-to-Renew — backed by a quantified retention tier, a config-driven carrier-appetite read, a loss-experience verdict, a state non-renewal-notice clock, and a Producer-ready talk-track tuned to whatever rate change the brief recommends.

Parse incoming new business or renewal submission packages and extract key risk details into a structured, at-a-glance summary that enables rapid triage, appetite matching, and assignment to the appropriate underwriter.

Review an open or recently paid claim file and surface recovery opportunities — third-party liability, product defect, contractor negligence, landlord / tenant transfer of risk, uninsured / underinsured motorist, MSP / ERISA / COB offsets, and inter-company arbitration candidates — before the reserve hardens, evidence goes stale, the statute of limitations runs, the contractual notice window closes, the Arbitration Forums filing window expires, or the made-whole / common-fund / anti-subrogation rule blocks pursuit. The skill produces a per-state-deadline-aware, per-LoB-driver-aware, AI-bias-audited, authority-checked, distribution-scoped, per-role-signed, multi-language-deliverable bundle the adjuster, the subrogation specialist, the supervisor, the SIU, the recovery vendor, the recovery counsel, the Arbitration Forums filer, the excess-carrier-claims officer, the reinsurance-claims officer, the carrier compliance officer, and (where applicable) the state DOI examiner can read from the same artifact without rework. The skill is the upstream feeder for the Claims Reserve Recommender v2.0 (whose recovery-offset analysis cross-checks against this skill), the Loss Run Analyzer v2.0 (whose recovery-credit verdict cross-checks against this skill), and the Renewal Review Brief v3.0 (which uses the recovery-trend signal in the renewal verdict).

Synthesize a submission package, supplemental applications, third-party data (D&B, ISO PolicyFinder, NICB, SOC 2 / SOC for Cybersecurity reports, public records), and the carrier or agency's appetite into a **decision-ready underwriting risk profile** — line-of-business-specific, jurisdiction-aware, AI-bias-tested, AMS-handoff-ready, and distribution-scoped (internal / broker-distributable / carrier-submission / regulator-response). The output names every exposure with the carrier's risk-coding language, scores each risk dimension on a numeric scale calibrated to the carrier's underwriting authority and appetite, applies a five-verdict disposition matrix (`DECLINE` / `REFER-UP` / `APPROVE-WITH-CONDITIONS` / `APPROVE-AS-IS` / `APPROVE-WITH-CREDIT`), produces a producer talk-track tuned to the verdict, and ships an AMS-ready activity-log block.

Produce a deployment-ready specification and compliance pack for an AI-native insurance distribution channel — a quoting or servicing surface where the consumer interacts with a third-party AI assistant (ChatGPT App, Claude desktop app, voice assistant, embedded chatbot) or with an outbound autonomous broker agent rather than with a human producer or a carrier portal. The spec covers the conversation policy, the tool-call (MCP server or equivalent) inventory, the per-state license and disclosure overlay, the audit-record and observability plan, the human-in-the-loop escalation triggers, and a regulator response kit. The output is the artifact a Distribution lead, Compliance lead, and Counsel can sign off on before the channel goes live, and the artifact a state DOI or NAIC examiner can be given when an exam request lands.

Scan an agency's book of business — or a single household or commercial account — and identify coverage gaps, rounding opportunities, life-event triggers, and logical next-policy recommendations, with a prioritized outreach plan the producer can execute the same day. Output is personalized to the agency's carrier appetite, licensed product mix, per-state licensure authority, and retention-correlated bundling rules drawn directly from `config.yml`.

For a commercial insured that is using, building, or embedding generative or agentic AI inside its operations, produce a defensible coverage-gap brief and a placement specification for affirmative AI liability coverage. The skill is built for the post-2026-01-01 commercial market, where the ISO/Verisk CG 40 47 (Coverage A and B) and CG 40 48 (Coverage B) generative-AI exclusion endorsements are now appearing on CGL renewals across the US, Tech E&O policies are being amended with similar language, and a new specialty market for affirmative AI liability has opened up through Lloyd's coverholders (Armilla AI, Testudo) and Munich Re-backed surplus-lines paper. The output is a producer-ready brief plus a structured submission spec the broker can use to place affirmative coverage with the right specialty market — not an "AI strategy memo."

Produce a clean, apples-to-apples side-by-side comparison of two or more insurance policy options — showing coverages, limits, deductibles, exclusions, endorsements, premium, and carrier strength — with a plain-language explanation of what each difference actually means for the insured, a ranked recommendation, an AI-bias / disparate-impact check on any pricing or appetite signal driving the recommendation, an authority-check against the producer's appointment / licensure scope, and a distribution-scoped, per-role-signed, multi-language deliverable bundle the producer, the broker-of-record, the insured, the carrier marketing rep, and (where applicable) the state DOI examiner can read from the same artifact without rework.

Give an insurance producer real-time guidance during a sales, service, save, or renewal call: next-best discovery questions tied to the prospect's exposures, coverage-gap prompts tied to the LoB and state, objection-handling language with empathy + reframe + clarifying-question structure, jurisdictional compliance reminders (recording, AI interaction, licensing, Medicare scope-of-appointment, two-party-consent, TCPA, FCRA), red-line statements the producer must not make, a momentum check across the producer's stated objectives, and a CRM-ready end-of-call recap with action items, signer block, AMS activity-log handoff, and a follow-up email draft. The skill turns a rolling call transcript and a short account snapshot into prompts the producer can act on within seconds — without breaking the natural flow of the conversation, without nudging the producer outside their licensure scope, and without bypassing a regulatory disclosure to "keep the call moving."

Turn a completed producer or service call into a structured, coaching-ready scorecard: a quality score per dimension (discovery depth, coverage-gap surfacing, objection handling, empathy, compliance, momentum, next-step), concrete moments from the transcript that earned or lost points, a ranked coaching plan, and a role-play prompt tied to the specific weakness. Designed to be the retrospective half of the pair with the Producer Live-Call Copilot v2.0 — the Copilot prompts the producer in the moment; the Scorecard grades what actually happened and feeds the next coaching conversation. Output is personalized to the agency's QA dimension weights, approved-language and verbatim-disclosure libraries, per-state licensure verification, coaching-plan micro-practice library, and producer history drawn directly from `config.yml`.

Draft a clear, legally-sound letter that explains a coverage decision to a policyholder or claimant — whether the decision is a full grant of coverage, a partial coverage with limitations, a reservation of rights, or an outright denial — in plain language, with the required regulatory elements, in a tone that protects the carrier or agency from bad-faith or E&O exposure, and in a distribution-scoped, per-role-signed, multi-language deliverable bundle the carrier, the producer, the broker-of-record, the insured, and (where applicable) the state DOI examiner can read from the same artifact without rework.

Generate a grounded, source-cited FAQ set a policyholder self-service assistant can answer from — built directly from the policy contract, endorsements, declarations page, schedule of benefits, certificate of coverage, carrier-approved SOPs, and prior complaint or call-reason data. Every question maps to a plain-language answer, the exact policy citation that supports it, an escalation condition, the required state-specific regulatory disclosures, and an AI-bias / authority check against jurisdictional rules. The output is designed to drop into a retrieval-augmented chatbot, an interactive voice response flow, a help-center article set, a producer cheat sheet, a Medicare.gov plan-finder companion, an SMS / WhatsApp / WeChat surface, or any other consumer self-service channel — with per-channel format, length, and disclosure rules pre-tuned and a per-product, per-state, per-language deployment package the carrier or agency can ship the same week.

Produce an insurance-grade model card and governance artifact bundle for any AI system used in underwriting, claims, pricing, marketing, or customer service. The output is structured to satisfy, in a single document: the NAIC AI Model Bulletin (including readiness for the NAIC AI Systems Evaluation Tool that state regulators are using in market-conduct and financial exams), the EU AI Act high-risk obligations that apply to life and health insurance pricing and risk assessment from August 2026, state AI laws (Texas TRAIGA, California AB 489, Indiana HB 1271 on downcoding, Colorado SB 21-169, Alabama SB 63, NY DFS Reg 187), and the carrier's own model-risk policy. When the system being documented is an inventoried model, the skill pre-populates the system identification block from `config.yml.ai_governance.model_inventory` to eliminate re-entry and ensure alignment with the official model register. Output is the artifact a model-risk officer, a DOI examiner, a data-protection authority, and an executive sponsor should all be able to read without rework.

Generate state-specific and regulation-specific compliance checklists for policy documentation, AI model governance, operational audits, and DOI market-conduct preparation. Output is a defensible, evidence-linked checklist (not a prose memo) with requirement, citation, owner, deadline, evidence location, and status fields — structured so the carrier's compliance team, a model-risk officer, and a state examiner can read the same artifact without rework.

Turn rough notes, a bullet list, an inbound thread, or a one-line ask into a polished, on-voice insurance business email that is ready to send — with the right subject line, length, structure, single call-to-action, recipient-class signature block, role-tuned voice, state-specific compliance footer, AMS activity-log handoff line, and (where applicable) a multi-language consumer-facing variant.

Turn a raw transcript, recording, or handwritten notes from an insurance meeting into a structured, decision-ready recap — Decisions, Action Items (Owner · Action · Due · Account/claim ref), Open Questions, Coverage / Claim / Regulatory Flags, and FYIs — in the agency or carrier's voice, ready to paste into a CRM, claims diary, AMS activity log, or Outlook / Slack / Teams thread. Produces parallel **distribution-scoped** copies (Internal-Only / Insured-Distributable / Carrier-Distributable / Counsel-Distributable / Regulator-Distributable) with privilege and PII redaction applied per scope, and emits an explicit decision-record export consumable by an AMS / CRM API.

Draft a compliant, on-voice public response — and a paired private outreach — to an online review of an insurance agency, carrier, or individual producer. Calibrated to the review's star rating, sentiment driver (claims, rate, service, coverage, billing, employer), platform (Google, Yelp, BBB, Facebook, Apple Maps, Trustpilot, Glassdoor, Indeed, NextDoor, Reddit, Clearsurance, Healthgrades, Medicare.gov plan-finder reviews, state DOI public-complaint portal, NAIC market-conduct portal), recipient-class signer block, distribution scope, and (where applicable) a multi-language consumer-facing variant. Public response avoids creating PII, bad-faith, E&O, or unfair-claims-practices exposure; private outreach is allowed to go deeper once identity is verified.