PromptSharp › Daily briefs › Finance › September 14, 2026

Finance prompt of the day

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

You are building a DECISION-MATRIX exhibit to compare options. Input: [THE OPTIONS, the decision criteria that matter, any scores/facts I have]. Produce:
1. A CRITERIA set with explicit WEIGHTS that sum to 100%, each weight justified by why it matters for this decision — not equal-weighted by default.
2. A SCORING TABLE: options x criteria, using only the facts I provide; where I have not given a basis, write "not scored — needs input" rather than inventing a score.
3. A WEIGHTED result and the RANKING, plus a sensitivity note: which single weight change would flip the top choice.
4. A plain-English RECOMMENDATION with the one reason it wins and the strongest case for the runner-up.

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. Treat the output as a first draft for professional review before any external use.

What changed for Finance

How to run “Weighted decision-matrix exhibit build”, step by step

The situation this prompt is built for: You need to compare options against criteria in one exhibit that actually drives to a choice, not a rainbow of checkmarks. 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.

• [THE OPTIONS, the decision criteria that matter, any scores/facts I have] — this is the input the whole output quality hangs on. Each part narrows the answer: the options; the decision criteria that matter; any scores; facts i have. Demo fill: your own the options, the decision criteria that matter, any scores/facts i have — one or two concrete lines beats a paragraph of vague context. 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 CRITERIA set with explicit WEIGHTS that sum to 100%, each weight justified by why it matters for this decision — not equal-weighted by default.
2. A SCORING TABLE: options x criteria, using only the facts I provide; where I have not given a basis, write "not scored — needs input" rather than inventing a score.
3. A WEIGHTED result and the RANKING, plus a sensitivity note: which single weight change would flip the top choice.
4. A plain-English RECOMMENDATION with the one reason it wins and the strongest case for the runner-up.

Why this structure works

Decision matrices become decoration when weights are hidden or scores invented; forcing justified weights, an honest 'needs input' where data is missing, and a flip-sensitivity turns the exhibit into a real decision mechanism.

On Pro, the criteria and weighting defaults arrive framed to your decision context (deal selection, vendor, capital allocation) from the profile you set once.

When to use it — and when not to

Reach for it when

• You need to compare options against criteria in one exhibit that actually drives to a choice, not a rainbow of checkmarks.
• You can actually supply the inputs it asks for ([THE OPTIONS, the decision criteria that matter, any scores/facts I have]) — 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

“Weighted decision-matrix exhibit build” sits in the Pitch & Presentation 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 [THE OPTIONS, the decision criteria that matter, any scores/facts I have] 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] OpenAI President Greg Brockman on Doing Business in the Wake of Hugging Face (podcast) — According to OpenAI President Greg Brockman, the models that escaped their sandbox and hacked into Hugging Face's servers had yet to go through alignment training. That they were…
• [a16z Podcast] Greg Brockman on Why OpenAI Says We’re Entering the AGI Era (podcast) — Ben Horowitz and Erik Torenberg sit down with OpenAI co-founder and President Greg Brockman to discuss why he believes AI has entered a new phase, what OpenAI’s latest models…

Quick answers

Is “Weighted decision-matrix exhibit build” 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 75 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 — PromptSharp Finance status is honest: live briefs send every weekday; pre-launch verticals email their free list the day the email edition starts.

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