PromptSharp › Daily briefs › Finance › October 14, 2026

Finance prompt of the day

October 14, 2026 · for Investment banking, sales & trading, equity research, FP&A. One sharp, copy-paste prompt — free, every weekday.

You are a financial analyst doing a linkage-first read of [COMPANY]'s statements for the periods I paste below. Do not compute ratios yet. Instead:
1. PROFIT TO CASH: bridge net income to cash from operations line by line (non-cash charges, working-capital movements, other), and say what share of profit turned into cash in each period.
2. BALANCE SHEET ROLL-FORWARD: for receivables, inventory, fixed assets, debt and equity, check that opening balance plus the flows shown elsewhere equals closing balance. List every roll-forward that does not tie and by how much.
3. ONE-OFFS AND RECLASSIFICATIONS: items that look non-recurring, restated, or moved between lines, and how each changes the picture.
4. THE STORY: in five sentences, what the three statements together say about how this business earns, spends and funds itself.
5. The three questions I would ask management or look for in the notes before trusting the numbers.
Here are the statements:
[PASTE: income statement, balance sheet, cash flow statement, at least two periods; any notes you have]

Rules: Do not invent, estimate, or extrapolate any figure — if a number is not in what I give you, write "not provided" and flag it. Mark every claim I should verify externally before relying on it. Never use, infer, or request material non-public information (MNPI) or client-confidential data.

What changed for Finance

How to run “Financial statement analysis: tie the three statements together”, step by step

The situation this prompt is built for: You have a company's income statement, balance sheet and cash flow statement and want to know whether they tell one consistent story before you rely on any of them. Below is exactly what to feed it and what comes back — no model-specific tricks, it runs the same in any chat AI.

What each placeholder does

Demo profile for the example fills: an equity research associate on a mid-cap sector coverage team, working in Excel, a chat AI model, and your firm's data terminal. Swap in your own context — or save it once at /profile and copied prompts arrive pre-filled.

• [COMPANY] — this is the input the whole output quality hangs on. Demo fill: what you sell in one plain sentence, plus who buys it. Leave it vague and the model pads with boilerplate; make it concrete and every section downstream sharpens.

What the model hands back

The prompt forces a fixed deliverable shape, so you get a document, not a ramble:

1. PROFIT TO CASH: bridge net income to cash from operations line by line (non-cash charges, working-capital movements, other), and say what share of profit turned into cash in each period.
2. BALANCE SHEET ROLL-FORWARD: for receivables, inventory, fixed assets, debt and equity, check that opening balance plus the flows shown elsewhere equals closing balance. List every roll-forward that does not tie and by how much.
3. ONE-OFFS AND RECLASSIFICATIONS: items that look non-recurring, restated, or moved between lines, and how each changes the picture.
4. THE STORY: in five sentences, what the three statements together say about how this business earns, spends and funds itself.
5. The three questions I would ask management or look for in the notes before trusting the numbers.

Why this structure works

Ratios computed on statements that do not tie produce confident wrong answers; checking profit-to-cash and the balance-sheet roll-forwards first tells you whether the numbers deserve analysis at all, and where to look when they do not.

On Pro, the roll-forward checks and one-off flags are tuned to your sector's accounting (software, industrials, retail, financials) from your profile.

When to use it — and when not to

Reach for it when

• You have a company's income statement, balance sheet and cash flow statement and want to know whether they tell one consistent story before you rely on any of them.
• You can actually supply the inputs it asks for ([COMPANY]) — this prompt is an amplifier for real context, not a substitute for it.
• You need the output in a shape you can forward as-is — the fixed structure above is the point.

Skip it when

• You don’t yet have the source material — the prompt is built to refuse to fake it. Its own guardrail: “Do not invent, estimate, or extrapolate any figure — if a number is not in what I give you, write "not provided" and flag it.” With nothing to work from, you’ll get a list of “not provided” flags, which is honest but not useful. Collect the inputs first.
• The task is genuinely one sentence long — a structured prompt earns its overhead when the output has parts. For quick one-off questions, just ask.

Adapting today’s prompt for adjacent roles

“Financial statement analysis: tie the three statements together” sits in the Financial Analysis & Modeling lane of the finance pool. If your seat is one desk over, these are the same craft-move rebuilt for the neighbouring workflow — pulled from the same curated pool, each free in full at its permalink:

You are an M&A associate building a SYNERGY CASE for a combination I describe: [ACQUIRER + TARGET: overlap, cost base, revenue lines, integration context]. Produce: 1.…

You are a sales trader drafting an AFTERMARKET client note on a recent new issue / IPO: [DEAL: name, pricing vs range, size, sector, allocation context I can share].…

You are a buy-side analyst running an EARNINGS-QUALITY / FORENSIC screen on [NAME] from the financials I paste. Produce: 1. A RED-FLAG SCAN across the classic…

Common failure modes (and the fixes)

• Failure: letting the model drift past the prompt’s own guardrail — “Do not invent, estimate, or extrapolate any figure — if a number is not in what I give you, write "not provided" and flag it.” Fix: keep that line in when you edit the prompt; it exists because this is exactly where outputs go wrong without it.
• Failure: letting the model drift past the prompt’s own guardrail — “Mark every claim I should verify externally before relying on it.” Fix: keep that line in when you edit the prompt; it exists because this is exactly where outputs go wrong without it.
• Failure: letting the model drift past the prompt’s own guardrail — “Never use, infer, or request material non-public information (MNPI) or client-confidential data.” Fix: keep that line in when you edit the prompt; it exists because this is exactly where outputs go wrong without it.
• Failure: filling [COMPANY] with a vague summary. The output can only be as specific as this input — generic context in, generic deliverable out. Fix: paste raw specifics (real names, real numbers, real constraints), then trim the model’s output, not your input.
• Failure: accepting the first pass. Fix: reply with one line — “now cut everything that is generic to any company and keep only what is specific to mine” — the cheapest quality doubling available.

Where AI is landing for investment banking right now

Context for today’s prompt, from the same screened sources the daily brief reads. Our read, with sources linked — the pattern across items like these is consistent: the professionals getting leverage from AI are the ones feeding it real working context, which is exactly the muscle today’s prompt trains.

• [Limitless AI] I Used to Hate Meta: Muse Wonder Changed My Mind (podcast) — Meta’s new AI model Wonder marks a massive move for Meta into the AI race against Anthropic and OpenAI. Today we cover the model’s versions, benchmark results, pricing, and…
• [a16z Podcast] Can Open Models Keep Up With the AI Frontier? | Nathan Lambert (podcast) — a16z Partner Lisha Li sits down with AI researcher and Trillium founder Nathan Lambert to ask how durable the gap really is between frontier AI labs and open models.Nathan argues…

Quick answers

Is “Financial statement analysis: tie the three statements together” free to use?

Yes — every weekday issue of the PromptSharp Finance publishes one full pool prompt free on the web, and it stays free in the archive. Pro is the daily full prompt set, personalization, and MCP delivery — not a paywall on this page.

Which AI model does this prompt work with?

Any of them. Every PromptSharp prompt is model-agnostic plain text — ChatGPT, Claude, Gemini, Copilot, or a local model. No plugins, no custom GPTs; paste and run.

How is the finance prompt of the day chosen?

Deterministic rotation over the curated finance pool — currently 80 prompts across 5 sections — the same single source the paid brief reads. Same date, same prompt: the archive never silently changes under you.

What goes in the [BRACKETED] placeholders?

Your context — the walkthrough above covers each one. The short rule: the more concrete the fill (real names, numbers, constraints), the sharper the output. Save your details once at /profile and web copies arrive pre-filled.

How do I get this in my inbox instead?

The capture form above. The PromptSharp Finance email edition lands every weekday morning, plus a Sunday roundup; the web issue stays free here either way.

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