01 / Diagnosis
Why month-end close becomes slow
A slow close is rarely one problem. It is usually five, compounding.
- Fragmented data. Numbers live in different systems and spreadsheets that do not reconcile automatically.
- Manual reconciliations. Matching is done by hand each month, so it is slow and easy to get wrong.
- No clear ownership. Tasks fall between people, so the close waits on whoever remembers.
- Rework from weak controls. Errors are found late, after the numbers have already moved downstream.
- Reporting bolted on afterwards. The pack is assembled after close instead of designed into it.
02 / Scope
What we improve
We work across the parts of the close that determine speed and accuracy.
Data collection and consolidation
One reliable flow from source systems into a single, reconciled dataset.
Reconciliations
Standardised and, where safe, automated, so matching stops eating days.
Close checklist and ownership
A defined sequence with a named owner for every task.
Reporting outputs
The pack designed into the close, so it is ready when the close finishes.
Forecast refresh
A rolling forecast updated on cadence, not rebuilt from scratch.
Controls
Checks that prevent rework rather than catch it after the fact.
03 / AI
Where AI-enabled workflows fit
Automation is powerful in the right place. It is a multiplier on a good process, not a substitute for one.
- Repeatable data preparation. The routine collection and shaping of data that eats junior time.
- Management reporting support. Drafting and assembling recurring outputs from a trusted dataset.
- Quality checks and exception identification. Flagging the anomalies a person should look at.
- A clear caution. Automation needs process and controls first. Automating a broken close just produces wrong numbers faster.
04 / Method
Our delivery model
We move in a deliberate sequence so the business keeps closing while we rebuild the process underneath it.
- Process auditA structured review of where the close loses time and where rework comes from.
- Prioritised redesignThe changes that shorten the close most, sequenced by impact.
- Tool and workflow implementationWe build the reconciliations, checklist and automation, not just specify them.
- Team adoptionThe new close is run in parallel with your team until it is theirs, not ours.
05 / Evidence
Case evidence
Anonymised, and evidence-led. We describe practical measures, not guarantees.
Across engagements where we have rebuilt the reporting and close process, the monthly reporting cycle has been reduced by an average of 60%. The reduction comes from redesigning data flows and the close checklist so reporting is built into the process rather than assembled after it, with automation added on top of a process that already works.
06 / Fit
Who this is for
This is for finance leaders with fragmented systems, manual month-end processes and a team stretched thin by the close. It is most valuable when reporting consistently arrives late, when the team is spending its month reconciling rather than analysing, or when a business is scaling faster than its finance process.
Three Sixty Finance is led by Arta Ramaj and Ellery Hodson. Senior finance operators are accountable for every judgement, with technology used to remove the manual bottlenecks underneath.
07 / Questions
Frequently asked questions
How much can we realistically shorten our close?
It depends on the starting point, but across our rebuilds the monthly reporting cycle has been reduced by an average of 60%. Most of the gain comes from redesigning data flows and the close checklist, with automation added on top.
Do we need new software to accelerate the close?
Usually not. Most of the improvement comes from redesigning process, ownership and data flows around your existing systems. New tools or automation are added only where they clearly earn their place.
Is it safe to automate the close?
Only on top of a process that already works. We fix the process and controls first, then automate the repeatable, low-judgement steps. Automating a broken close just produces wrong numbers faster.
Where does AI actually help?
In repeatable data preparation, assembling recurring reporting, and flagging exceptions for a person to review. It is a multiplier on a sound process, not a replacement for judgement or controls.
Will a faster close reduce accuracy?
No, when it is done properly. Speed comes from removing rework and designing controls that prevent errors, which tends to improve accuracy rather than weaken it.
Who runs the close after you leave?
Your team. We embed the redesigned process and any automation, run it in parallel until it is owned internally, then hand over.
Assess your month-end and reporting process
Tell us where the close loses time. We will come back to you with a clear view of where we can add value.
Talk to the team