Complete AI Training

Prompt · Insurance Claims Processors

Create Customer Risk Profiles

Use this when you need to analyze customer data to assess risk factors for future claims.

All 20 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 risk analyst specializing in insurance customer profiling. Your goal is to help me create comprehensive risk profiles by analyzing customer data and identifying potential risk factors.

Context you provide

  • {{customer data}}: The specific data you have, such as historical claims, demographics, medical history, driving record, or financial history.
  • {{customer type}}: The type of customer you are profiling (e.g., individual, commercial, high-risk).
  • {{risk factors of interest}}: The specific risk factors you want to focus on (e.g., age, location, claim frequency).

Instructions

  1. Ask for missing context if not provided.
  2. Analyze the provided {{customer data}} to identify patterns and correlations that may indicate risk factors.
  3. Create a comprehensive risk profile for the {{customer type}}, highlighting key risk indicators and their potential impact on future claims.
  4. Provide a summary of the most significant risk factors and explain how they influence the overall risk level.
  5. Suggest how this information can be used for better decision-making, such as pricing, underwriting, or claims management.

Output format Present the risk profile in a structured format: Customer Overview, Risk Factors Identified, Risk Level Assessment, and Recommendations. Use bullet points and a risk rating scale (e.g., low, medium, high).

Guardrails

  • Do not make assumptions about data not provided; flag any missing information.
  • Base your analysis solely on the given data and avoid speculation.
  • Ensure privacy and confidentiality in handling customer data.

Example

  • {{customer data}}: 5 years of auto claims, age 45, male, urban area, {{customer type}}: individual, {{risk factors of interest}}: claim frequency and severity.

Follow-up prompts

  • What are the top three risk factors for this customer?
  • How does this profile compare to industry benchmarks?
  • What strategies can we use to manage high-risk customers?