Insurance work combines dense documents, incomplete evidence, regulated decisions, and customers who need clear explanations. AI is useful for the first and last parts: organizing a file and improving communication. It must not quietly take over the decisions in the middle.
The prompts below produce review artifacts, not determinations. Coverage, liability, reserving, pricing, fraud referral, adverse action, settlement authority, and regulated communications stay inside approved workflows with authorized professionals. For general governance, see AI prompts for compliance.
Claims Intake and Review
1. Create a claim-file synopsis
Create a factual synopsis from this redacted claim record. Include reported loss,
timeline, parties by neutral labels, property or coverage involved, documents
received, actions completed, open requests, and contradictions. Cite a source ID
for every fact. Do not infer coverage, liability, fault, or fraud.
Record: [APPROVED, REDACTED EVIDENCE]
2. Build a missing-information checklist
Compare the file contents with this approved intake checklist. Return items
present with source IDs, items absent, items ambiguous, and the neutral request
needed to resolve each gap. Do not request data outside the checklist.
3. Reconcile a claim timeline
Build a chronological table with event time, reported time, event, source ID,
and confidence. Preserve conflicting accounts side by side and identify gaps.
Never invent a timestamp or choose which account is true.
4. Prepare an adjuster handoff
Draft a handoff for the assigned adjuster. Include file status, verified facts,
pending documents, customer commitments and due dates, diary items, approvals
needed, and next action. Keep opinions separate from the factual record.
5. Review estimate differences
Compare these two estimates line by line. Identify matched items, scope differences,
quantity differences, unit-price differences, missing documentation, and questions
for review. Calculate only from supplied values. Do not recommend payment.
Underwriting Support
6. Assemble an underwriting review packet
Organize the approved submission into applicant facts, requested coverage,
exposures, controls, loss history, documents supplied, data conflicts, and missing
information. Cite each source. Do not score, price, approve, decline, or infer a
protected characteristic.
7. Compare submission data across documents
Compare the application, schedule, inspection, and prior-carrier information.
List only material inconsistencies, the exact values and source IDs, why the
difference may matter under the supplied underwriting guideline, and a neutral
clarification question. Do not resolve conflicts by guessing.
8. Map facts to underwriting guidelines
Create a review table mapping verified facts to the supplied guideline sections.
Use columns: fact, source, relevant guideline, possible interpretation, missing
evidence, and authorized reviewer question. Do not make an eligibility decision.
9. Draft a risk-improvement conversation
Draft a collaborative conversation about the approved risk-improvement items.
Explain the observed condition, practical consequence, requested improvement,
acceptable evidence of completion, and deadline. Use neutral language and do
not add requirements absent from the approved list.
Policy and Customer Communication
10. Explain a policy provision in plain language
Explain this exact policy provision at an eighth-grade reading level. Distinguish
the contract language from the plain-language explanation, define key terms,
give a clearly hypothetical example, and state that the complete policy and
facts control. Do not say whether a real claim is covered.
Policy text: [VERBATIM APPROVED TEXT]
11. Draft a status update
Write a concise customer update using only these verified case facts. Include
what has been completed, what is still needed, who owns the next step, expected
response window from the service standard, and contact path. Do not promise an
outcome or date not present in the record.
12. Quality-check a customer letter
Review this draft letter for unsupported claims, unclear deadlines, undefined
insurance terms, inconsistent facts, missing appeal or contact information from
the approved template, and language that could sound accusatory. Quote issues;
do not rewrite until the reviewer confirms them.
13. Convert a complaint into an issue brief
Summarize this complaint into customer concern, desired resolution, verified
timeline, prior commitments, policy or service standard implicated, unresolved
facts, and next accountable owner. Preserve the customer's wording for the core
concern without adopting unverified allegations as fact.
Quality, Audit, and Learning
14. Audit a file against a checklist
Audit this redacted file against the supplied quality checklist. For every item,
show pass, fail, or not verifiable; supporting source; exact gap; and remediation
question. Do not infer compliance from the absence of evidence.
15. Find process lessons across cases
Analyze these de-identified case summaries for recurring process friction. Group
observations by handoff, documentation, system, communication, and policy clarity.
Report counts, preserve outliers, and propose process hypotheses plus a measure
that could test each one. Do not evaluate individual employee performance.
Keep the Decision Boundary Visible
Every AI-assisted insurance artifact should say what it is: synopsis, comparison, draft, checklist, or hypothesis. None of those words means decision. Make the boundary visible in the workflow with a reviewer field, source citations, an approval state, and a record of the final rationale.
That discipline also improves customer communication. A careful draft based on verified facts is faster to review and less likely to overpromise. The customer-service prompt guide offers more patterns for tone, escalation, and response quality.
