Cut month-end close from two weeks to under five days with AI flux explanations, automated journal entry review, and a centralized checklist.
In a financial-services or PE-backed finance function, the month-end close runs 5–10 days and lands on the same handful of people: flux analysis, accruals, supporting schedules, intercompany tie-outs, and journal-entry review, all under pressure because investors and lenders are waiting on the numbers. Much of that work is pattern recognition an assistant can do faster — this expense line is $14k higher than last month, likely because of the annual insurance renewal that posts every June; this account has no accrual this period but had one for the prior twelve. AI-assisted close generates draft flux explanations from the underlying data, reviews journal entries for anomalies, and runs a centralized checklist so the team sees what is done and what is blocking — while the controller reviews and owns every number. For a multi-entity firm, it is the difference between a two-week scramble and a calm close that frees up the back half of the month.
A PE-backed company with several entities cut its close from roughly ten days to under five by auto-drafting flux explanations the controller edits rather than writes from scratch, and by running a single shared close checklist across entities. A three-person finance team at a financial-services firm uses the journal-entry anomaly review to catch the misclassified or duplicated entry before sign-off instead of after. A fund administrator standardized its close checklist so the same steps complete in the same order every period, which also made the close resilient to someone being out.
Before adopting any AI tool, write the actual close steps in order. Most teams discover their close is undocumented or out of date. Capture: trigger date, owner, system, and dependencies.
Numeric reads from QuickBooks, NetSuite, Xero, or Sage Intacct. The first sync takes ~30 minutes and establishes the baseline trial balance.
Tell the platform: 'flag any GL account where current month vs prior month varies by >15% or >$10K.' The AI then generates a draft explanation from transactional data.
Import your documented checklist. Assign owners. Set dependencies. The platform tracks status in real time and shows blockers.
Every journal entry over $1K (set threshold per team) flows through an AI reviewer that compares it against historical patterns and flags anomalies. Controller spends time only on flagged entries.
At close, the platform produces signed-off flux explanations, supporting schedules, and a complete journal-entry audit trail. Send to external accountants or auditors in one click.
After each close, review: which steps took longest, where the AI got it wrong, what to automate next. Aim for 1-2 day shave each quarter.
Tuned for Financial Services. Use as-is or adapt to your voice.
For each account where the period-over-period change exceeds [threshold $ or %], draft a flux explanation from the supplied GL detail and prior-period data. State: the account, the change ($ and %), and the most likely driver evidenced in the transactions (name the specific entries). If the data does not support an explanation, write UNEXPLAINED — needs controller input rather than guessing. Keep each explanation to 1–2 sentences in the firm’s reporting voice. Output a table the controller can edit and approve; never finalize.
Review the period’s journal entries and flag for human review: round-dollar manual entries above [threshold]; entries posted after the close cutoff; reversing entries with no original; entries miscoded relative to their memo; duplicate entries (same amount/account/description); and top-side adjustments. For each flag give the entry, the reason, and a question for the preparer. Do not post or modify anything — produce a review list ranked by materiality.
Standardize the close as an owned, sequenced checklist: bank & cash reconciliations → AR/AP cutoff → accruals (recurring + one-time) → prepaid amortization → fixed assets/depreciation → intercompany tie-out → revenue recognition review → flux analysis → JE review → financial statement draft → controller review → CFO sign-off. For each step: owner, dependency, due day, and evidence to mark complete. Surface blockers daily; a step cannot be checked complete without its supporting schedule attached.
You are reviewing the month-over-month change in {{account_name}}. Current month: ${{current}}. Prior month: ${{prior}}. Variance: ${{variance}} ({{pct}}%).
Using the transactional detail below, identify the top 3 contributors to the variance. For each, state: vendor, $ amount, transaction date, and the most likely business driver. Be concise — one sentence per contributor.
Transactional detail:
{{paste_gl_export}}Day 1: Bank reconciliations (Controller) Day 1: Credit card reconciliations (Senior accountant) Day 2: Accruals — payroll, rent, recurring software (Senior accountant) Day 2: AP cutoff and aging review (Controller) Day 3: AR cutoff and aging review (Controller) Day 3: Revenue recognition (Controller) Day 4: Flux analysis (AI-generated, Controller review) Day 4: Journal entry review (AI-flagged only) Day 5: Financial statement generation Day 5: Sign-off + send to leadership
Auto-flag for human review if: - Entry posted to a new account (no prior history) - Entry > 3x median size for that account - Entry posted by an unusual user for that account - Entry posted on a weekend or after 8pm - Round-number entry > $10K
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Skip if your close is already under 3 days. Skip if you do not have a documented chart of accounts (fix that first). Skip if your team is one person and you do not have audit obligations — the workflow overhead exceeds benefit at solo scale.
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