PromptSharp › Daily briefs › Finance › October 12, 2026

Finance prompt of the day

October 12, 2026 · for Investment banking, sales & trading, equity research, FP&A. One sharp, copy-paste prompt — free, every weekday.

You are a treasury analyst building a 13-week direct cash flow forecast for [COMPANY] from the balances, receivables, payables and payment schedules I paste below. Produce:
1. A WEEKLY TABLE for weeks 1-13: opening cash, receipts by source (customer collections, other), disbursements by category (payroll, suppliers, rent, debt service, tax, capex), net flow, closing cash, and headroom against the minimum cash level I state.
2. COLLECTIONS LOGIC: how you turned the receivables ageing into weekly receipts, with the collection pattern stated as an assumption I can change.
3. THE TIGHT WEEK: the week with the lowest headroom, what drives it, and whether it is a timing gap or a structural shortfall.
4. LEVERS: up to five actions that would move cash in or out of that week (payment timing, collections push, deferral, facility draw), each with the amount it moves and what it costs or risks.
5. A variance plan: which three lines to re-forecast every week first because they carry the most uncertainty.
Here is my data:
[PASTE: opening bank balance, AR ageing, AP ageing, payroll dates, debt schedule, known one-off payments, minimum cash level]

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 “13-week cash flow forecast: build it and find the tight week”, step by step

The situation this prompt is built for: Cash is tight or a lender wants a short-term liquidity view, and you need a week-by-week forecast that shows exactly when headroom runs out. 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. A WEEKLY TABLE for weeks 1-13: opening cash, receipts by source (customer collections, other), disbursements by category (payroll, suppliers, rent, debt service, tax, capex), net flow, closing cash, and headroom against the minimum cash level I state.
2. COLLECTIONS LOGIC: how you turned the receivables ageing into weekly receipts, with the collection pattern stated as an assumption I can change.
3. THE TIGHT WEEK: the week with the lowest headroom, what drives it, and whether it is a timing gap or a structural shortfall.
4. LEVERS: up to five actions that would move cash in or out of that week (payment timing, collections push, deferral, facility draw), each with the amount it moves and what it costs or risks.
5. A variance plan: which three lines to re-forecast every week first because they carry the most uncertainty.

Why this structure works

Monthly forecasts hide the week you actually run short; forcing a receipts-and-payments view by week, then naming the tight week and the levers that move it, turns a liquidity worry into a short list of decisions.

On Pro, the disbursement categories and collection patterns are set to your industry's payment terms and your role (corporate treasury, restructuring adviser, lender) from your profile.

When to use it — and when not to

Reach for it when

• Cash is tight or a lender wants a short-term liquidity view, and you need a week-by-week forecast that shows exactly when headroom runs out.
• 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

“13-week cash flow forecast: build it and find the tight week” 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 equity capital markets banker framing FINANCING STRUCTURE OPTIONS for an issuer I describe: [ISSUER: size, listing status, ownership, use of proceeds,…

You are a desk strategist building a POSITIONING & SENTIMENT map for [NAME / ASSET / MACRO THEME]. Using only the data I paste below, produce: 1. A POSITIONING read…

You are a buy-side analyst pressure-testing my VARIANT PERCEPTION on [NAME]. Using my notes below, produce: 1. A CONSENSUS-vs-MY-VIEW table: on the 3-4 issues that…

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.

• [Odd Lots] Nate Soares on How AI Really Could Kill Us All (podcast) — Since the Hugging Face incident, concerns over AI doomsday scenarios has entered the mainstream. But of course, some people have been warning about this for years, long before…
• [Limitless AI] OpenAI’s Unreleased Model Solved Math: Is Biology Next? (podcast) — An internal model from OpenAI reportedly solved around 90 of the hardest open mathematics problems and what that could mean for fields like physics, chemistry, and biology. We…

Quick answers

Is “13-week cash flow forecast: build it and find the tight week” 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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