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Financial Analysis & ModelingFREE

Month-end flux analysis: which moves need an explanation

Before the books close you need to find which account movements are unusual enough to explain, and draft the explanations reviewers will ask for.

The prompt — copy and run it

You are a controller running a month-end flux review for [ENTITY] on the trial balance or account-level figures I paste below (this month, last month, same month last year). Produce:
1. A FLUX TABLE by account: current, prior month, prior year, change in currency and percent, computed only from my figures.
2. FLAGS: every account that crosses the threshold I set (default: 10% and [AMOUNT]) plus any account that changed sign, went to zero, or appeared for the first time.
3. For each flag: the most likely explanation category (volume, timing of an accrual, reclassification, one-off, error) and the single document or report that would confirm it.
4. PAIRS THAT SHOULD MOVE TOGETHER: accounts whose movements usually offset (for example accruals and the related expense) where one moved and the other did not.
5. A draft explanation line for each flag in the style a reviewer expects, clearly marked DRAFT where the cause is not confirmed.
Here is my data:
[PASTE: account-level balances for the three periods, the threshold, any known one-offs]

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.
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How to use this prompt

  1. Copy the full prompt above with the Copy button.
  2. Fill in your inputs. Replace each bracketed placeholder with your specifics: [ENTITY][AMOUNT]
  3. Paste into ChatGPT, Claude, or Gemini and run. Read the reality guardrail below before you act on the output.

Why this prompt works

Reviewers ask about the same things every month: big moves, sign flips and pairs that stopped moving together. Screening for exactly those and drafting explanations marked as unconfirmed saves the back-and-forth without pretending a guess is a finding.

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Reality guardrail: this prompt makes the model reason from data you paste — it does not source or verify facts for you. Check every claim, keep confidential data out of consumer AI tools, and follow your employer's AI-use policy.

Frequently asked

When should I use this prompt?

Before the books close you need to find which account movements are unusual enough to explain, and draft the explanations reviewers will ask for.

Why does this prompt work?

Reviewers ask about the same things every month: big moves, sign flips and pairs that stopped moving together. Screening for exactly those and drafting explanations marked as unconfirmed saves the back-and-forth without pretending a guess is a finding.

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PromptSharp prompts are drafted with AI assistance and human-reviewed. They structure how a model reasons over data you provide — they do not source or verify facts for you, and you own every output. Nothing here is financial, legal, tax, or investment advice. Never paste confidential, client, or material non-public information into consumer AI tools; follow your employer's AI-use policy. © 2026 PromptSharp.