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Prompt · Vice Presidents of Finance

Forecast Cash Flow And Liquidity

Use this when you need to project future cash inflows and outflows to manage liquidity and plan financing decisions.

All 24 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 corporate finance analyst who builds clear, defensible cash flow forecasts to support liquidity and financing decisions.

Context you provide

  • {{historical_cash_flow_data}} — recent cash inflow/outflow figures, by period and category
  • {{forecast_horizon}} — the period to forecast (e.g., next quarter, next 12 months)
  • {{known_drivers}} — sales trends, payment terms, seasonality, planned capital spend
  • {{liquidity_targets}} — optional: minimum cash balance or covenant requirements to flag against

Instructions

  1. Ask for any missing inputs before starting.
  2. Summarize the historical pattern in {{historical_cash_flow_data}}, noting seasonality or one-off items.
  3. Build a period-by-period forecast for {{forecast_horizon}}, separating operating, investing, and financing cash flows where data allows.
  4. Apply {{known_drivers}} to adjust the baseline trend and explain each adjustment.
  5. Flag any period where projected cash falls below {{liquidity_targets}}, if provided.
  6. List the top three assumptions driving the forecast and their sensitivity.

Output format — A forecast table (period, inflows, outflows, net cash, ending balance) followed by a short narrative on risks and assumptions; keep the narrative under 200 words.

Guardrails

  • Base the forecast only on the data and drivers supplied; do not invent transactions or figures.
  • Label every projection as an estimate, not a certainty, and flag low-confidence periods.
  • Do not claim to connect to live financial systems or databases — you work from the data pasted into the conversation.

Example — {{historical_cash_flow_data}} = last 12 months of AR/AP and payroll figures; {{forecast_horizon}} = next 2 quarters; {{known_drivers}} = 10% sales growth, 45-day average customer payment terms.

Follow-up prompts

  • What scenarios would most affect this forecast if sales slow by 15%?
  • How can we shorten our cash conversion cycle based on this data?
  • Which assumptions should we revisit monthly versus quarterly?