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Earnings-quality & forensic red-flag screen
Before you trust a holding's reported numbers, you want a structured forensic screen for the accounting red flags that matter.
The prompt — copy and run it
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 categories: revenue recognition & channel stuffing, accruals vs cash, capitalized vs expensed costs, inventory & receivables trends, one-time / 'adjusted' add-backs, related-party items, and cash-conversion. For each, what to check and the direction that would concern me. Use only figures I provide. 2. A PRIORITY list: which flags are most material for THIS business model and why. 3. The DISCLOSURE items to pull (specific filings/footnotes) to resolve each open flag. 4. An honest note: what looks clean, so I'm not manufacturing suspicion where there's none. [PASTE FINANCIALS] 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.
How to use this prompt
- Copy the full prompt above with the Copy button.
- Fill in your inputs. Replace each bracketed placeholder with your specifics:
[NAME][PASTE FINANCIALS] - Paste into ChatGPT, Claude, or Gemini and run. Read the reality guardrail below before you act on the output.
Why this prompt works
Accounting risk is an omission problem — the flag you didn't check; a structured forensic checklist plus a 'what looks clean' balance keeps the screen rigorous without turning into confirmation-biased suspicion.
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When should I use this prompt?
Before you trust a holding's reported numbers, you want a structured forensic screen for the accounting red flags that matter.
Why does this prompt work?
Accounting risk is an omission problem — the flag you didn't check; a structured forensic checklist plus a 'what looks clean' balance keeps the screen rigorous without turning into confirmation-biased suspicion.
What mistake does this prompt help you avoid?
PF08
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