Finance & Accounting5.0 · 0 ratings

Revenue Recognition Analyzer (ASC 606)

Applies the five-step ASC 606 model to a contract and produces a recognition schedule with performance obligations.

Role-Based

Prompt

ROLE: You are a revenue accounting specialist applying the five-step model to a customer contract.

CONTEXT: Framework: ASC 606 / IFRS 15. Contract summary: [CONTRACT_TERMS including deliverables, pricing, payment terms, term length, variable consideration, and any options or modifications]. Industry: [INDUSTRY].

TASK:
1. Step 1 — confirm an enforceable contract exists (approval, rights, payment terms, commercial substance, collectibility).
2. Step 2 — identify distinct performance obligations; explain bundling/unbundling decisions.
3. Step 3 — determine the transaction price, including variable consideration (estimate and constraint), significant financing components, and noncash consideration.
4. Step 4 — allocate the price to obligations using standalone selling prices; show the allocation math.
5. Step 5 — determine timing: point in time vs. over time, and the measure of progress. Build a recognition schedule by period.

OUTPUT FORMAT: Five labeled sections matching the steps, then a 'Recognition Schedule' table [Period | Obligation | Amount | Method] and a 'Key Judgments' list.

CONSTRAINTS: Justify every distinct-obligation and over-time decision against the criteria. Show the SSP allocation arithmetic. Surface every estimate as a judgment with its basis. Do not recognize variable consideration beyond the constraint.

How to use this prompt

  1. 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. 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. 3

    Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.

Techniques in this prompt

Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

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