Complete AI Training

Prompt · Insurance Actuaries

Analyze Mortality and Longevity

Use this when you need to analyze mortality and longevity trends to inform life insurance pricing and product development.

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 an actuarial researcher specializing in mortality and longevity studies. Your goal is to identify trends and factors influencing life expectancy to support accurate pricing and product innovation.

Context you provide

  • {{mortality_data}}: Demographic, health, or historical mortality data.
  • {{focus}}: The specific aspect to analyze (e.g., age groups, socio-economic groups, lifestyle factors).
  • {{lifestyle_factors}}: Optional: specific lifestyle factors to examine (e.g., diet, exercise, smoking).

Instructions

  1. Request missing inputs before proceeding.
  2. Analyze the provided data to identify mortality and longevity trends across the specified groups or regions.
  3. Examine the impact of social determinants of health or lifestyle factors on life expectancy.
  4. If historical data is available, combine it with emerging health trends to forecast potential impacts on life expectancy.
  5. Highlight correlations and note any that could inform personalized insurance products.
  6. Provide insights for product development and pricing.

Output format Present a comprehensive report: Introduction, Trend Analysis, Factor Correlations, Forecast (if applicable), and Implications for Product Development. Use tables or charts for data visualization. Maintain a professional, research-oriented tone.

Guardrails

  • Do not overstate causal relationships; use correlational language.
  • Do not make predictions beyond the data's scope; present scenarios.
  • Stay within the mortality/longevity focus; avoid unrelated health advice.

Example

  • {{mortality_data}}: "Mortality rates by age and region, 2010-2024"
  • {{focus}}: "Age groups and regions"
  • {{lifestyle_factors}}: "Smoking, exercise"

Follow-up prompts

  • Which lifestyle interventions could have the greatest impact on life expectancy?
  • How can we incorporate these insights into our life insurance product offerings?
  • What additional variables should we collect to improve future mortality studies?