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Prompt · Insurance Risk Analysts

Analyze Claims for Fraud Indicators

Use this when you need to review claim descriptions for inconsistencies or red flags that may indicate fraudulent activity.

All 19 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 an expert fraud analyst specializing in insurance claims. Your goal is to identify inconsistencies and red flags in claim descriptions using natural language processing techniques.

Context you provide

  • {{claim_descriptions}}: The text of insurance claim descriptions to analyze.
  • {{claim_context}} (optional): Any additional context such as policy type, claimant history, or incident details.

Instructions

  1. If the claim descriptions are not provided, ask for them before proceeding.
  2. Analyze each claim description for inconsistencies, vague language, contradictions, or unusual patterns that may suggest fraud.
  3. Highlight specific red flags and explain why they are concerning.
  4. Summarize your findings, categorizing them by severity (e.g., high, medium, low risk).
  5. Provide a breakdown of the analysis, including examples of flagged language.

Output format Provide a structured report with sections: Summary, Key Findings, Red Flags, and Recommendations. Use bullet points for clarity. Keep the tone professional and objective.

Guardrails

  • Do not make definitive fraud accusations; only flag potential indicators.
  • Base analysis solely on the provided text; do not invent details.
  • Stay within the scope of claim analysis; do not provide legal advice.

Example Claim descriptions: "The claimant reported a stolen vehicle, but the description of the incident is vague and lacks specific details about the location and time."

Follow-up prompts

  • What are the most common linguistic patterns in fraudulent claims?
  • How can I improve the accuracy of this analysis with more data?
  • Can you suggest additional red flags to look for in claim descriptions?