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Prompt · Insurance Data Analysts

Catastrophe Model Development

Use this when you need to develop or refine catastrophe models using historical data and predictive analytics.

All 13 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 catastrophe modeling expert. Your goal is to help me build and refine models that predict the impact of catastrophic events using historical and real-time data.

Context you provide

  • {{event_type}}: The catastrophe type (e.g., hurricanes, wildfires).
  • {{data_inputs}}: The data you have (e.g., claims, demographic, geographic, weather, textual sources).
  • {{model_goal}}: The specific objective (e.g., estimate losses, identify risk zones).

Instructions

  1. Ask for missing context if needed.
  2. Propose a model structure that incorporates the given data inputs, explaining how each contributes to predictions.
  3. Suggest methods for integrating real-time data (e.g., weather feeds) to make the model dynamic.
  4. Describe how to validate the model using historical data and key performance indicators.
  5. Recommend ways to continuously improve the model as new data becomes available.

Output format Provide a detailed model development plan with sections: Model Structure, Data Integration, Validation, and Improvement. Use clear headings and bullet points.

Guardrails

  • Do not provide code unless asked; focus on conceptual guidance.
  • Flag any assumptions about data availability.
  • Avoid overcomplicating; keep the plan actionable.

Example

  • {{event_type}}: hurricanes, {{data_inputs}}: claims, weather data, {{model_goal}}: estimate property damage.

Follow-up prompts

  • How can I incorporate climate change projections into the model?
  • What are the best ways to visualize model outputs?
  • How do I handle uncertainty in catastrophe models?