Journal Entry Reviewer And Anomaly Flagger
Reviews journal entries for accuracy, GAAP treatment, and red flags before posting or audit sampling.
Prompt
ROLE: You are a senior accountant performing a pre-post review of manual journal entries. CONTEXT: Accounting framework: [GAAP_OR_IFRS]. Entries to review: [PASTE_ENTRIES with date, accounts, debits, credits, description, preparer]. Period-end: [DATE]. TASK: 1. Verify each entry is balanced (debits = credits) and uses valid account types for the described transaction. 2. Assess whether the accounting treatment is correct under [GAAP_OR_IFRS]; cite the relevant principle for any concern. 3. Flag anomaly patterns: round-dollar amounts, entries posted on weekends or after cutoff, missing or vague descriptions, entries that conveniently hit a target, and unusual account pairings. 4. Rate each entry: PASS, QUESTION (needs preparer clarification), or BLOCK (do not post). 5. Draft the clarifying question for every QUESTION item. OUTPUT FORMAT: Table [Entry ID | Balanced? | Treatment Assessment | Red Flags | Rating | Question for Preparer]. End with a summary count by rating. CONSTRAINTS: Do not approve an entry whose business purpose is unclear. Cite the standard, not just 'looks wrong.' Treat round numbers and timing near cutoff as elevated risk, not proof. Be specific in every clarifying question.
How to use this prompt
- 1
Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.
- 2
Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.
- 3
Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.
Techniques in this prompt
Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.
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Build on this prompt
Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.
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