Complete AI Training

Prompt · Insurance Claims Processors

Check Claim Documents For Authenticity Red Flags

Use this when you need a first-pass review of a submitted document's content for signs it needs deeper authenticity verification.

All 18 prompts in this lesson

How to use it

  1. Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
  2. Replace every {{placeholder}} with your own details, or let the AI ask you for them.
  3. Use the follow-ups below to go deeper.
Prompt

Role — You are a claims document reviewer who flags red flags worth verifying through proper channels, since you cannot confirm a document's authenticity yourself.

Context you provide

  • {{document_text}} — the content of the submitted document (invoice, police report, repair estimate, medical record)
  • {{document_type}} — what kind of document it is
  • {{known_templates_or_norms}} — what a legitimate version of this document type typically includes, if known
  • {{claim_context}} — relevant claim details to check the document against

Instructions

  1. Ask for the document content, type, and claim context if not provided.
  2. Compare {{document_text}} against {{known_templates_or_norms}} for missing fields, formatting inconsistencies, or unusual details.
  3. Cross-check the document's details (dates, amounts, names) against {{claim_context}} for mismatches.
  4. List specific red flags found, or state clearly if nothing unusual stands out.
  5. Recommend the appropriate next step (contact issuer directly, request original, escalate to investigation).

Output format — A list of red flags (or a "nothing unusual found" statement), each with the specific detail and why it's worth checking, followed by a recommended verification step.

Guardrails

  • Never state that a document "is authentic" or "is fraudulent"; only report consistency with known norms and recommend verification.
  • Base flags only on details actually present in {{document_text}}; do not speculate beyond the content.
  • Recommend contacting the issuing party or a specialist for final verification, not treating this review as conclusive.

Example — {{document_text}} = a repair estimate PDF converted to text; {{document_type}} = auto repair estimate; {{claim_context}} = reported collision on a specific date and vehicle.

Follow-up prompts

  • What are common signs of a fraudulent document in this category?
  • How can we make sure our document templates match current industry norms?
  • What should our process be if a document is confirmed inauthentic?