A faster close comes from preparation, not automated approval

A faster month-end close comes from having the work ready when reviewers arrive, not from letting agents approve their own work. Agents shorten the close by preparing reconciliations, accruals, journals and commentary overnight, each with its support attached. Reviewers then spend their time deciding rather than assembling, and approval stays exactly where it was.

Where does close time actually go?

Ask a finance team where the days of the close go and the answer is rarely "approving things". The month-end close is mostly a sequence of preparation tasks with waiting in between. Someone pulls bank statements and matches them. Someone else gathers invoices received but not yet entered, to estimate accruals. Another person chases a department for a figure. Journals are drafted, supporting schedules built, variances investigated, commentary written. Only at the end does a controller review and approve.

The approval step is short. Reviewing a well-prepared reconciliation takes minutes. What takes days is getting it well prepared, and the waiting while one task depends on another.

That is where agents help. They do not get tired, they do not wait for office hours, and they can work on many preparation tasks at once.

What can an agent prepare?

Most of the close checklist, at depth 1 and 2:

• Bank and account reconciliations: matched items, unmatched items with suggested explanations, proposed adjustments.
• Accruals and prepayments: calculations from purchase orders, contracts and prior periods, with the source for each.
• Recurring journals: depreciation, amortisation, standard allocations, drafted for review.
• Intercompany balances: matched across entities, with differences explained.
• Variance analysis: actual against budget and prior period, with draft explanations.
• Payroll changes: starters, leavers and adjustments assembled for approval, as described in how to let an AI agent prepare payroll changes for approval.

Each item arrives with its supporting evidence attached and every figure traced to a ledger entry or source document. The full list, task by task, is in month-end close: what the agent prepares.

Why not let the agent approve to save more time?

Because the saving is small and the risk is not. If preparation took four days and approval took half a day, automating approval saves a few hours at most. In exchange, the firm loses its main control over the numbers it reports.

Approval is where segregation of duties lives. The person who reviews a reconciliation or a journal is the check on the person, or agent, that prepared it. If the agent prepares and approves, there is no check. Errors and misstatements, whether from a misread source or a misunderstood instruction, go straight into the ledger.

There is also an accountability point. The financial controller and finance director sign off the numbers. They need to have reviewed them, not just trusted that an agent did. Whether an AI agent can run the month-end close is a fair question, and the answer is that it can run much of the preparation, while people run the close.

How do approval limits fit?

Some routine, low-value items can be posted by an agent within tight bounds, once it has earned the depth on evidence. Most should be prepared and held. Limits make the line explicit.

Setting those limits is a decision in its own right, covered in how to set approval limits for an AI agent in finance. The principle is that the lower of the customer's limit and the agent's certified depth applies, and judgemental items always reach a person.

What does a well-prepared item look like?

A reviewer should be able to approve it without opening another system. That means the item includes the figure, how it was calculated, every source it relied on, anything unusual the agent noticed, and anything it could not resolve. A reconciliation with three unmatched items should list them with the agent's best explanation for each and a clear marker where it has none.

The test of good preparation is how often reviewers have to go and look something up. If they routinely need to open the ledger to check a figure, the preparation is incomplete. If they can approve from the pack, the close gets faster in the place where it counts.

What should you measure?

The obvious measure is days to close. It is worth tracking, but it combines many effects. More useful are:

• Preparation complete time: when each item was ready for review, compared with when it used to be.
• Review time per item: whether good preparation is making review faster.
• Return rate: how often reviewers send items back, and why.
• Post-close adjustments: whether errors are slipping through.

The last one is the guard. A faster close that leads to more corrections next month has not improved anything. If post-close adjustments rise, preparation quality has fallen, and depth should be reconsidered.

What should you do differently?

Map your close by where time goes, not by who approves what. Point agents at the preparation tasks that take longest and depend most on gathering information. Leave approval with people, and use the time saved to review more carefully rather than to approve faster. The close will be shorter, and the numbers will be at least as reliable as before. That is the aim of AI agents for finance: books you can audit.