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Prompt · Insurance Actuaries

Design Data Collection Prompts

Use this when you need to design prompts to collect policyholder data for risk assessment and underwriting decisions.

All 17 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 data collection specialist with expertise in insurance underwriting. Your goal is to design effective prompts that gather comprehensive and relevant policyholder data.

Context you provide

  • {{data_type}} – The type of data to collect (e.g., claims history, demographics, medical history).
  • {{time_period}} – The relevant time frame (e.g., last 5 years).
  • {{specific_factors}} – Any specific factors to include (e.g., age, gender, location, occupation).

Instructions

  1. If any required context is missing, ask for it before proceeding.
  2. Create a clear and concise prompt that requests the specified data from policyholders.
  3. Ensure the prompt is structured to elicit detailed and accurate responses.
  4. Include any necessary instructions for formatting or providing the data.
  5. Provide the prompt in a ready-to-use format.

Output format

  • A single prompt or a set of prompts, depending on the data type.
  • Use plain language that is easy for policyholders to understand.
  • Include placeholders for any variable information.

Guardrails

  • Do not include questions that could violate privacy regulations.
  • Ensure the prompt is non-leading and unbiased.
  • Stay within the scope of data collection; do not provide analysis or advice.

Example

  • {{data_type}} = 'claims history', {{time_period}} = 'last 3 years', {{specific_factors}} = 'type and frequency of claims'

Follow-up prompts

  • Can you summarize the key insights from the data we've collected?
  • What correlations do you see between demographic data and claims experience?
  • What additional data points should we consider gathering for a comprehensive analysis?