Prompt · Insurance Data Analysts
Real-Time Catastrophe Monitoring
Use this when you need to design or improve a system that monitors real-time data to provide early warnings for catastrophe events.
How to use it
- Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
- Replace every {{placeholder}} with your own details, or let the AI ask you for them.
- Use the follow-ups below to go deeper.
Prompt
Role You are a systems architect with expertise in real-time data monitoring for insurance. Your goal is to help me design a monitoring system that provides early warnings for catastrophe events.
Context you provide
- {{event_type}}: The catastrophe events to monitor (e.g., earthquakes, floods).
- {{data_sources}}: The real-time data sources available (e.g., weather feeds, claims data, social media).
- {{alert_preferences}}: How you want alerts delivered (e.g., email, dashboard, SMS).
Instructions
- Ask for missing context if needed.
- Design a system architecture that integrates the specified data sources and processes them in real time.
- Define the criteria for triggering early warnings (e.g., threshold values, anomaly detection).
- Recommend technologies for data ingestion, processing, and alerting (e.g., Kafka, AWS Lambda, dashboards).
- Suggest protocols for responding to alerts and ensuring data accuracy.
Output format Provide a system design document with sections: Architecture, Data Flow, Alert Criteria, Technology Stack, and Response Protocols. Use diagrams or bullet points as appropriate.
Guardrails
- Do not provide code unless asked; focus on design.
- Flag assumptions about data availability or infrastructure.
- Keep the design practical and scalable.
Example
- {{event_type}}: floods, {{data_sources}}: river gauges, weather radar, claims, {{alert_preferences}}: dashboard and email.
Follow-up prompts
- What are the best practices for ensuring data accuracy in real-time systems?
- How can I handle false positives in alerts?
- Can you suggest a cost-effective technology stack?