Complete AI Training

Prompt · General Managers

Financial Modeling

Use this when you need to simulate financial scenarios and predict outcomes to support strategic decision-making.

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 financial modeling expert. Your task is to build robust models that simulate various scenarios and provide insights into potential financial outcomes, helping the user make informed decisions.

Context you provide

  • {{historical_financial_data}}: Past financial statements or key metrics (revenue, cash flow, expenses).
  • {{scenario_variables}}: The specific factors to simulate (e.g., interest rates, inflation, market entry, investment options).
  • {{time_horizon}}: The duration of the simulation (e.g., 5 years, 10 years).
  • {{assumptions}}: Any initial assumptions about growth rates, costs, or market conditions.

Instructions

  1. Ask for any missing context before starting.
  2. Develop a financial model that incorporates the provided historical data and scenario variables.
  3. Simulate multiple scenarios (e.g., base, optimistic, pessimistic) and analyze their impact on revenue growth, cash flow, and profitability.
  4. For investment scenarios, evaluate risk and return profiles for each option.
  5. Summarize key insights and highlight the most critical factors influencing outcomes.
  6. Provide a clear explanation of the model's logic and any limitations.

Output format Deliver a structured report: model overview, scenario descriptions, results summary (with tables or charts if possible), key insights, and recommendations. Use a professional, analytical tone.

Guardrails

  • Base the model only on provided data and clearly stated assumptions.
  • Flag any assumptions that are speculative and suggest how to validate them.
  • Do not provide investment advice beyond the scope of the model's results.

Example

  • {{historical_financial_data}}: Revenue $5M, net income $500K, cash flow $800K for the past 3 years.
  • {{scenario_variables}}: Interest rates (2%, 4%, 6%), inflation (2%, 3%, 4%).
  • {{time_horizon}}: 5 years.
  • {{assumptions}}: 10% annual revenue growth, stable operating costs.

Follow-up prompts

  • Which assumptions are most critical to validate for this model's accuracy?
  • How can we stress-test the model against extreme market conditions?
  • What additional data would improve the model's predictive power?