ChatGPT Prompts for Financial Analysis

<context> Build a common-size income statement for [COMPANY]. Income statement figures: [FIGURES] (revenue and each expense/income line). Period: [PERIOD]. </context> <task> 1. Express every line item as a percentage of total revenue. 2. Output a table: Line item | Amount | % of revenue. 3. Identify the three largest cost lines as a share of revenue. 4. Comment on where margin is being lost or preserved. 5. State explicitly that you have not changed any reported figure, only re-expressed it, and ask me to verify the percentages. </task>

<context> Build a common-size balance sheet for [COMPANY]. Balance sheet figures: [FIGURES] (every asset, liability, and equity line). Period: [PERIOD]. </context> <task> 1. Express each asset line as a % of total assets and each liability/equity line as a % of total liabilities + equity. 2. Output two tables (assets; liabilities & equity) with Amount and %. 3. Note the composition of the asset base (e.g. asset-heavy vs. asset-light) and the funding mix. 4. Flag any line that exceeds a reasonable concentration threshold. 5. Confirm totals foot to 100% and ask me to verify. </task>

<context> Perform horizontal analysis for [COMPANY]. Multi-period figures: [FIGURES] (same line items across at least two periods). Periods: [PERIOD]. </context> <task> 1. For each line item, compute the absolute change and the % change versus the prior period. 2. Output a table: Line item | Prior | Current | Change | % change. 3. Rank the five line items with the largest % moves. 4. Group the moves into a short narrative (growth, cost pressure, one-offs) labelled as interpretation. 5. Remind me that % changes off small bases can mislead, and to verify the underlying numbers. </task>

<context> Interpret the cash flow statement for [COMPANY]. Figures: [FIGURES] (operating, investing, financing cash flows; net income; capex; D&A). Period: [PERIOD]. </context> <task> 1. Summarize cash generated/used by each activity and the net change in cash. 2. Compute free cash flow (operating cash flow - capex) and the cash flow to net income ratio. 3. Assess earnings quality: does operating cash flow support reported net income? 4. Flag any reliance on financing inflows to fund operations. 5. Note that this is analysis support, not advice, and ask me to verify the figures. </task>

<context> Check consistency across the three statements for [COMPANY]. Figures: [FIGURES] (net income, depreciation, change in retained earnings, ending cash, beginning cash). Period: [PERIOD]. </context> <task> 1. Verify that net income flows correctly into retained earnings and the cash flow statement. 2. Confirm the cash flow statement's ending cash matches the balance sheet cash. 3. List each linkage checked with a Pass/Fail and the figures compared. 4. For any Fail, describe what could explain the discrepancy. 5. State clearly that a Pass here does not guarantee accuracy and that source data must still be verified. </task>

<context> Run budget-versus-actual variance analysis for [COMPANY]. Figures: [FIGURES] (budgeted and actual amounts per line item). Period: [PERIOD]. </context> <task> 1. For each line, compute the variance (actual - budget) and the % variance, labelling favorable (F) or unfavorable (U). 2. Output a table: Line | Budget | Actual | Variance | % | F/U. 3. Apply a materiality threshold of [THRESHOLD] and list only variances that breach it. 4. For each material variance, list plausible drivers to investigate (do not assert causes). 5. Remind me to verify the figures and confirm the favorable/unfavorable convention matches our reporting. </task>

<context> Decompose a revenue variance for [COMPANY] into price and volume effects. Figures: [FIGURES] (budget vs actual units and price/unit; or total revenue with unit and price detail). Period: [PERIOD]. </context> <task> 1. Compute the price variance and volume variance using the standard decomposition (price variance = (actual price - budget price) x actual volume; volume variance = (actual volume - budget volume) x budget price). 2. Show the formula, the inputs, and the result for each. 3. Confirm the two variances sum to the total revenue variance. 4. State which effect dominates and what it suggests about demand vs. pricing. 5. Ask me to verify the reconciliation and the input figures. </task>

<context> Investigate operating cost variances for [COMPANY]. Figures: [FIGURES] (standard/budget cost and actual cost per category, with volume if available). Period: [PERIOD]. </context> <task> 1. Compute the variance and % variance for each cost category. 2. Where volume data exists, split into rate and efficiency/usage components and show the formulas. 3. Rank categories by absolute unfavorable variance. 4. For the top three, propose specific questions to ask the cost owner — not assumed answers. 5. Note any category lacking enough data to split, and remind me to verify all figures. </task>

<context> Compare the latest forecast to actuals for [COMPANY]. Figures: [FIGURES] (prior forecast and actual results by line and by month/quarter). Period: [PERIOD]. </context> <task> 1. Compute forecast accuracy per line: variance, % variance, and absolute error. 2. Identify which lines are consistently over- or under-forecast across periods. 3. Summarize overall forecast bias (optimistic/pessimistic) with supporting numbers. 4. Recommend which forecast assumptions to revisit, framed as suggestions. 5. Remind me that conclusions depend on data accuracy and must be verified. </task>

<context> Draft management commentary on this period's variances for [COMPANY]. Figures: [FIGURES] (key variances and their confirmed drivers, supplied by me). Period: [PERIOD]. Audience: [AUDIENCE]. </context> <task> 1. Using only the drivers I provided, write 4-6 concise commentary bullets explaining the most material variances. 2. Lead each bullet with the variance figure, then the driver, then the implication. 3. Keep the tone factual and suited to [AUDIENCE]; avoid speculation beyond the drivers given. 4. Add a one-line outlook only if I supplied forward data; otherwise omit it. 5. End by noting the figures should be reconciled to the close before distribution. </task>

<context> Build a driver-based revenue forecast for [COMPANY]. Figures: [FIGURES] (historical revenue, units, price, growth rates, and the drivers I want to use). Forecast horizon: [PERIOD]. </context> <task> 1. Lay out the forecast logic: revenue = driver 1 x driver 2 (e.g. customers x ARPU), and state each assumption explicitly. 2. Project revenue for each period in the horizon, showing the math. 3. Output a table: Period | Driver values | Forecast revenue. 4. List every assumption in one place so I can challenge each. 5. Caveat that this is a model, not a prediction, and that inputs must be verified. </task>

<context> Build base, bull, and bear scenarios for [COMPANY]. Figures: [FIGURES] (base-case assumptions for revenue growth, margins, and key costs). Horizon: [PERIOD]. </context> <task> 1. Define the assumption changes for each scenario (e.g. bull = +X% growth, bear = -Y% growth) — ask me to confirm the deltas if I did not specify them. 2. Project revenue, operating income, and net income for each scenario across the horizon. 3. Output a table: Metric | Bear | Base | Bull per period. 4. Quantify the spread between bull and bear at the final period. 5. Note the key assumption that drives the widest spread and remind me to verify inputs. </task>

<context> Run a sensitivity analysis for [COMPANY] on a target metric. Figures: [FIGURES] (base-case model, the output metric, and the inputs to flex). Target metric: [METRIC]. </context> <task> 1. Hold all inputs at base case, then flex one input at a time by -10%, -5%, +5%, +10%. 2. Show how [METRIC] responds to each input change in a table: Input | -10% | -5% | Base | +5% | +10%. 3. Rank inputs by how much they move [METRIC] (most to least sensitive). 4. State which input the result is most fragile to. 5. Caveat that flexing inputs independently ignores correlations, and ask me to verify the base model. </task>

<context> Project cash runway for [COMPANY]. Figures: [FIGURES] (current cash balance, monthly revenue, monthly operating costs, expected changes). Horizon: [PERIOD]. </context> <task> 1. Compute monthly net burn (or net cash generation) and the projected cash balance for each month. 2. Output a table: Month | Inflow | Outflow | Net | Ending cash. 3. State the month, if any, when cash reaches zero (runway). 4. Show how runway shifts if burn rises or falls by [DELTA]%. 5. Caveat that timing assumptions are critical and figures must be verified against the latest actuals. </task>

<context> Stress-test the assumptions behind [COMPANY]'s forecast. Figures: [FIGURES] (the forecast and its underlying assumptions). Period: [PERIOD]. </context> <task> 1. List every assumption embedded in the forecast that you can identify. 2. For each, classify the risk level (low/medium/high) and explain why. 3. Identify which two assumptions, if wrong, would most damage the forecast. 4. Propose a leading indicator to monitor for each high-risk assumption. 5. Remind me that this is analysis support and that I must validate the assumptions and figures. </task>

<context> Value [COMPANY] using trading multiples. Figures: [FIGURES] (target metrics — revenue, EBITDA, earnings — and peer multiples I supply). Valuation date: [PERIOD]. </context> <task> 1. Apply each supplied peer multiple (EV/Revenue, EV/EBITDA, P/E) to the matching target metric. 2. Output a table: Multiple | Peer value | Target metric | Implied value. 3. Present an implied valuation range (low/median/high) across the multiples. 4. Note why each multiple might over- or under-state value for this company. 5. State that comps are only as good as the peer set and that all inputs must be verified — this is not investment advice. </task>

<context> Walk through a simplified DCF for [COMPANY]. Figures: [FIGURES] (projected free cash flows, discount rate, terminal growth rate, net debt, shares outstanding). Horizon: [PERIOD]. </context> <task> 1. Discount each projected free cash flow to present value, showing the discount factor and math per period. 2. Compute the terminal value (Gordon growth) and its present value, showing the formula. 3. Sum to enterprise value, subtract net debt for equity value, and divide by shares for value per share. 4. Output each step in a clear table. 5. Caveat heavily that DCF output is highly sensitive to the discount and terminal-growth rates, and require me to verify every input. Not investment advice. </task>

<context> Estimate WACC for [COMPANY]. Figures: [FIGURES] (cost of equity inputs — risk-free rate, beta, equity risk premium; cost of debt; tax rate; market values of debt and equity). Period: [PERIOD]. </context> <task> 1. Compute cost of equity via CAPM (risk-free + beta x equity risk premium), showing inputs. 2. Compute after-tax cost of debt. 3. Weight by the capital structure to derive WACC, showing the weights and formula. 4. Output a table of every input and the final WACC. 5. State that small input changes move WACC materially, ask me to verify all inputs, and note this is not investment advice. </task>

<context> Estimate value for [COMPANY] on an asset basis. Figures: [FIGURES] (assets and liabilities at book; any fair-value adjustments I provide). Period: [PERIOD]. </context> <task> 1. Compute book equity (total assets - total liabilities). 2. Apply any fair-value adjustments I supplied and recompute adjusted net asset value. 3. Output a table: Item | Book | Adjustment | Adjusted. 4. Explain when an asset-based approach is most and least appropriate for this company. 5. Caveat that book values may diverge from market values and that figures must be verified. Not investment advice. </task>

<context> Reconcile multiple valuation approaches for [COMPANY]. Figures: [FIGURES] (value-per-share or equity value from each method you have run: comps, DCF, asset-based). Period: [PERIOD]. </context> <task> 1. Tabulate the value from each method side by side. 2. Compute the range and the spread between the highest and lowest. 3. Explain the most likely reasons the methods disagree. 4. Suggest which method deserves the most weight for this company and why — as analysis, not a recommendation. 5. Caveat that no single method is definitive, require verification of all inputs, and state this is not investment advice. </task>

<context> Write an executive summary of [COMPANY]'s financial results. Figures: [FIGURES] (headline metrics, key variances, and confirmed drivers I supply). Period: [PERIOD]. Audience: [AUDIENCE]. </context> <task> 1. Open with a 2-3 sentence headline on overall performance, grounded only in the figures provided. 2. Add 4-5 bullets on revenue, margin, cash, and the most material variance with its confirmed driver. 3. Keep it under 200 words and tuned to [AUDIENCE]. 4. Avoid jargon and do not introduce numbers or drivers I did not provide. 5. End with a note that figures are subject to verification before distribution. </task>

<context> Explain a financial metric for a non-finance audience at [COMPANY]. Metric and figures: [FIGURES] (the metric, its value, and how it was calculated). Audience: [AUDIENCE]. </context> <task> 1. Define the metric in one plain sentence with a relatable analogy. 2. Explain what this specific value means for [COMPANY], using the figure provided. 3. State what would make the metric better or worse. 4. Note one common misconception about the metric. 5. Keep it jargon-free and remind the reader the figure should be verified against the source. </task>

<context> Draft talking points for a board finance update for [COMPANY]. Figures: [FIGURES] (the metrics and confirmed narrative points I supply). Period: [PERIOD]. </context> <task> 1. Produce 5-7 crisp talking points, each anchored to a specific figure I provided. 2. Group them under: Performance, Cash & Liquidity, Risks, Outlook. 3. For each risk, pair it with the mitigation I supplied (do not invent mitigations). 4. Keep each point to one sentence a presenter can deliver verbally. 5. Flag any section where I have not provided enough data, and note figures need verification. </task>

<context> Define a finance KPI dashboard for [COMPANY]. Context: [FIGURES] (the metrics I want to track and any current values). Audience: [AUDIENCE]. </context> <task> 1. For each KPI, specify: definition, formula, data source, target/benchmark, and reporting frequency. 2. Output a table with those columns. 3. Group KPIs into Growth, Profitability, Liquidity, and Efficiency. 4. Recommend which 3-4 KPIs belong "above the fold" for [AUDIENCE]. 5. Note that targets are placeholders to be confirmed and that values must be verified. </task>

<context> Prepare anticipated questions on [COMPANY]'s results. Figures: [FIGURES] (the results, key variances, and confirmed context I supply). Audience: [AUDIENCE] (e.g. investors, lenders, leadership). </context> <task> 1. Generate 8-10 tough questions [AUDIENCE] is likely to ask, based only on the figures and variances provided. 2. For each, draft a factual answer grounded in the supplied data; where I have not provided the answer, mark it "NEED DATA". 3. Order questions from most to least likely. 4. Flag any question that touches a sensitive or unresolved area. 5. Remind me to verify all figures and have answers reviewed before the meeting. </task>