Reconcile accounts faster at close
Use an agentic tool to match transactions, surface only the real exceptions, and draft reconciliation write-ups every close cycle, so your team shrinks a multi-day chore into a few reviewed hours.
Likely tools or environments
Scores run from 1 to 5. Ease and impact: higher is better. Risk: higher means more care and human review. Scored by our team as a general guide. Your tools, information and policies can change the picture. How we score
What this could change
What changes when the close starts from matched transactions and a short exceptions list
- Before: Teams match thousands of line items across several systems by hand; in Ledge's 2025 survey, cash reconciliation alone takes 20 to 50 hours every month. After: Obvious matches are made the same way every period, only the real exceptions are listed, and the reconciliation memo arrives drafted for review.
- What it needs: Ledger detail and the matching source exports, matching rules and tolerances your team agrees, prior closes to check against, and approved environments for financial data.
- What stays human: Nothing is auto-cleared or auto-posted: a person investigates every exception, and named preparers and reviewers sign off each reconciliation, as auditors expect.
The exact design depends on your tools, information, policies, and tolerance for risk. Aravise explains the outcome and requirements publicly; the implementation happens inside an engagement — coached so you can run it yourself, or built with your team through Embedded AI Delivery.
Sources
- 50% of finance teams take six or more business days to close the books — Ledge 2025 Month-End Close Benchmarks
- Cash reconciliation alone takes finance teams 20 to 50 hours every month — Ledge 2025 Month-End Close Benchmarks
More in Finance & Accounting use cases or all AI use cases.
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Walk into the board meeting with the variance story already drafted. Your finance team turns closed, reconciled actuals into first-draft board-pack commentary they own and edit — instead of writing every line from a blank page each month.
Draft and review journal entries
An AI agent drafts recurring and adjusting journal entries from your source data and prior periods, attaches the support, and flags anomalies for a human to approve, cutting the manual grind out of month-end close.