Month-end reports, without days of copying between spreadsheets.

What gets automated is the preparation work around the report, not the analysis itself. The solution collects the data from the ERP system, the bank statements and the spreadsheets your team works with and brings it together in one place. AI then checks it for inconsistencies and missing data and drafts the commentary for the report, which a finance person edits.

We start with a map of the reporting process: we describe the steps from the first data export to the finished report and mark the ones that repeat every month in the same way. Those are the steps we automate first. Judging which variance matters, what it means for the business and what to tell management stays with people. The solution is part of our AI business process automation service and runs on top of the systems you already have, without replacing your accounting system.

The finance team is responsible for the numbers, just as it is today. AI prepares and checks, and people approve. The report does not go out and the commentary does not reach management before a person has reviewed and accepted them.

That is why the checks are built to direct attention. When AI finds an inconsistency between sources or missing data, it flags the item, and the item waits for review by a finance person instead of slipping through. The draft commentary is a starting point: the finance person edits it, adds the context only they know and decides what stays in the report.

Before it reaches production, the solution goes through a pilot on a real month-end close under supervision. In the first week we agree the metrics we will measure success by: time, cost and errors. If the solution does not deliver against the baseline, we do not continue with it and pick the next process.

No, Microsoft Copilot is not required. We choose the tool to fit the systems your company already works with. If the team is on Microsoft 365 and the reports are built in Excel, Microsoft Copilot in Excel is a natural extension of the automation. If you work with other tools, the solution is built on top of them.

Automation and training go together. Data collection, checks and the draft commentary take over the routine part, but finance people also need the skills to work with AI in their day-to-day analysis. That is why training for the team in Microsoft Copilot in Excel can be added to the solution, with hands-on work on anonymised company data. If the team is only starting with AI, the first step is AI training for companies, and automation comes after it. People then understand what the solution does and can judge when its output needs correcting.

You start with a free 30-minute call in which we look at the report, the sources and the steps that repeat. Afterwards you know whether automation makes sense for you. As a standalone project it starts with a review of the reporting process and is quoted on request, and the first measurable results usually come within 2–4 weeks of the start.

The automation can also be part of a full AI transformation with the Encorp AIM (AI Implementation Method). There the reporting process is one of the processes chosen at Gate 1 from the opportunity map, moving from the first quick win by week 4 to solutions in production in weeks 11–12. In both cases the code, the model instructions and the deployment are yours, and after go-live the solution moves to AI Ops, with support and improvements every month and response within 24 hours.