Based on our experience the finance professionals care about the most is data accuracy. The second most important thing is financial reporting automation.
Most professionals working in finance are overworked already so being stuck with manual Excel spreadsheets is a pretty frustrating part of the job.Our financial analytics consultants have helped 700+ businesses including Dermalogica, Autodesk and Heineken to automate financial reporting. Some of our developers used to work in FP&A and accounting so we have been in your shoes.
In this guide we are writing about our typical step-by-step process for automating financial reporting. It is designed to help you with a few key decisions like selecting the right software and ensuring data accuracy. It is written for CFOs, financial controllers and finance leads who want to save time for their team. By the end you should have a clear picture of what building this looks like, how long it takes and where the effort actually goes.
We recently automated financial reporting for a CFO of a financial services company. Watch our managing director demonstrating every solution that we developed for them in the video below.
Financial reporting automation involves creating fully automated management reports that refresh on the schedule. An end-to-end automation would cover data extraction, transformation, refresh and maintenance.
For example in small businesses financial reporting automation would cover:
In enterprise settings this process would look very similar but the data would come from more sophisticated ERP systems like Netsuite or SAP Hana.
You most definitely already have financial reports that your business depends on. Chances are they are created in Excel and currently take a lot of time to maintain.
We need to work backwards to understand how to automate your reports. What data sources do your key reports have? Is it QuickBooks Online? Anaplan? Recieving scheduled emails with excel attachments?
Make note of your sources and key columns that you need to create these reports. We will be looking for a way to automatically bring this data in next.
Key tools: Claude, Power Automate
Some automated financial reporting software products have direct integrations to common data sources like QuickBooks Online, Xero and FreshBooks. You may want to consider those.
If you need a fully custom process that you own, the process is a bit different. Here are your options.
We recommend saving your data somewhere where it would be easy to access: Excel or a business intelligence data warehouse.
Key tools: Power Query, SQL
Finance professionals need to transform data after extraction: delete columns, remove duplicates, replace values, etc.
In most of our financial reporting automation projects we use Power Query because of it’s simplicity. It is available as a native part of Excel and Power BI so it’s easy to use in your current reports.
Power Query allows you to specify data transformation steps that will be applied every time your data gets refreshed. You can then connect your reports to the transformed data.
If you are a bit more technical you can set up a data warehouse and then write SQL code for transforming your data. This approach is usually more scalable for big data so it’s worth considering if you find your data volume too big for Excel. If you need help with this, our cloud data warehousing consultants are available for a custom project.
Key tools: Power BI, Fathom, Tableau
Your most important decision here is choosing a reporting tool that allows you to automate financial reporting. Excel or Google Sheets are very manual so we usually recommend other automated financial reporting software. Explaining every option in detail is beyond the scope of this article but you can read a comprehensive comparison in our guide.
These tools allow you to schedule data refresh, automatically fetch the transformed data and send you email notifications when the data refresh breaks.
If you want to go ahead with Power BI, you might find our free Power BI templates for QuickBooks Online, Xero and Zoho Books useful. They contain all the formulas to make your numbers match and a ready-made data model so you don’t have to start from 0. If you need help building out your reports, our dashboards development consultants would love to help!
No matter what financial reporting software you choose from our guide, they all have functionalty to schedule refresh. Make sure that you schedule it to happen after your data transformation is complete.
Then make failure visible. Alerts go to a named owner, with an agreed retry or escalation path. Every report should carry a visible last successful refresh timestamp, so a finance user can tell at a glance whether they are looking at this morning’s position or last Tuesday’s. When the timestamp looks stale, the user contacts the report owner, and the owner already knows because the alert reached them first.
Platform limits shape the schedule. In Power BI, scheduled refresh runs up to 8 times per day on a Pro license and up to 48 times per day on Premium Per User or a Fabric capacity. These limits change from time to time, so check current Microsoft documentation when you plan your cadence.
A reliable refresh gets the data moving, but the cycle only finishes when the approved report reaches the right people. Different recipients need different outputs. Executives who like to explore get a live dashboard. The board gets a PDF pack. FP&A may still want a spreadsheet, and investors a presentation. Define who gets which format, how each output is produced from the same approved model, and on what schedule it goes out.
Before the automated process replaces the manual one, run it in parallel with a completed reporting cycle and compare the two line by line. Finance accepts the figures, and recipients confirm they can open what they should and cannot open what they should not. A compact acceptance checklist keeps this honest:
Handover means training and documentation: the mappings, the transformation rules and who owns changes to them. Agree the maintenance scope up front, because the business will change. New entities, revised KPIs, changed mappings and broken source connections all need a route back to whoever maintains the process, whether that is your team or ours.
The steps above only mean something if they survive contact with real projects. Here are three from our portfolio, each backed by a verified client review, with the figures kept strictly to their own projects.
Before the project, procurement and financial reporting data sat in SAP Ariba and had to be pulled manually every time a report was needed. We automated the extraction from SAP Ariba into Power BI so the reporting data refreshes without anyone exporting files. The result was around 5 hours saved every month and reports that update far more often than the manual process allowed. The scope here was extraction and reporting rather than a full seven step cycle, which is worth being clear about.
Neterra’s management reporting was maintained by hand in Excel, absorbing the equivalent of a full time analyst and limiting what leadership could see. We built automated Power BI reports connected directly to their ERP, used across finance, sales, procurement and operations. After launch the leadership team identified a one off cost saving of 50,000 euros almost immediately, and insights from the dashboards unlocked an additional 10,000 to 20,000 euros in monthly recurring revenue. The automation also removed the need for the full time analyst role that had maintained the Excel reports. The CFO built their application for Bulgaria’s CFO of the Year 2024 on this transformation and won the Ernst and Young category for Transformation of the Financial Function.
This client ran their business across six disconnected systems, and consolidating the numbers for management reporting was a heavy manual job every cycle. We centralized the data into a single cloud database with automated feeds and Power BI reporting on top. Their CEO reported a 95 percent reduction in manual data consolidation, an 80 percent drop in data entry errors, data integrity improved to 99.7 percent and strategic decisions made around 40 percent faster on the back of real time dashboards.
Faster Report Prep
One of the biggest benefits of financial reporting automation is it cuts way down on the time spent gathering, combining and prepping financial data.
Instead of exporting data from a bunch of different systems and having to manually update spreadsheets, finance teams can work with reports that just update on their own – automatically. This means they can focus on analysing performance instead of just cranking out reports.
More Accurate Reports
When you’re doing reporting manually you’re basically asking for trouble – you’re bound to have formula errors, duplicate entries, wrong calculations and just plain out of date data.
Financial reporting automation cuts way down on the manual work by getting data straight out of the source systems and then applying the right reporting rules. This helps organisations get way better data quality and keep people trusting their reported numbers.
Faster Financial Decisions
Automating reports gives executives current financial information right away – no waiting around for the end of the month or having to have reports manually prepped.
With up to the minute reports and dashboards, leadership teams can spot issues sooner, dig deeper into trends way faster and make decisions based on the most up to date data they’ve got.
Better Visibility Into Performance
Automating financial reports makes it way easier for leadership teams to track key financial metrics – think profitability, cash flow, expenses and all that good stuff.
Instead of relying on static reports, decision-makers can dig into interactive dashboards that let them drill into trends, compare different periods and figure out what’s behind the numbers.
While financial reporting automation can deliver huge benefits, getting it right requires some serious planning up front. And the truth is – most of the challenges you’ll face aren’t even caused by the reporting tools themselves, but by the underlying data, processes and systems that support reporting.
Poor Data Quality
Financial reporting automation only works if you’ve got accurate source data to work with. And that means your accounting records, customer data, product information and transaction classifications all need to be consistent, or the automation will just churn out inaccurate reports faster.
The solution is to get a grip on your data governance, standardise your reporting structures, and make sure you’re doing regular data validation checks before you distribute those reports.
Mapping and Consolidation
Businesses that operate across multiple entities, currencies or countries often find that automating financial reporting is a lot harder than it looks.
Inter company eliminations, foreign currency translation and differing account structures can make consolidation a real nightmare if you haven’t designed it right. So, the key is to get your chart of accounts structure standardised and your consolidation rules clearly set out from the word go.
Resistance To Change
Finance teams often rely on reporting processes that have evolved over years, so replacing familiar spreadsheets and manual workflows can be a bit of a culture shock. They might worry about losing control, or that the automated reports won’t be accurate.
The best way to get round this is to automate the reports that you already have, and then validate that the automated outputs match up with what you’re currently reporting. That way you can build confidence in the solution before introducing anything too fancy.
The Security Risks of Automated Reporting
Financial reports often contain sensitive information that should only be accessible to people who are authorised to see it.
Without proper controls, automated reporting can increase the risk of exposing confidential financial data, so it’s really important to put in place role-based permissions, secure data storage, audit trails and approval processes to make sure that users can only access the information that they need for their job.
Keeping Reporting Logic Up To Date
Reporting requirements change over time as businesses grow, or new products or entities come on board. So it’s really important to document your reporting logic, account mappings and business rules during implementation, so that you can easily update reports in the future.
That way you can keep your reports accurate, even as the business evolves.
If you are considering an implementation, the most useful thing you can share is your current process: which systems hold your data, which reports you prepare, how often they go out, who receives them and which manual steps you want gone. From there we can tell you what a pilot would look like for your setup and exactly what it would prove.
Our team designs and builds custom reporting solutions around your systems and your reporting cycle, so get in touch to discuss your financial reporting automation project.
Financial reporting automation is the process of turning raw transactions in your source systems into approved reports without the manual work in between. Instead of exporting data, rebuilding spreadsheets and emailing packs by hand, an automated workflow collects the data, transforms it into your reporting structure, validates the figures, refreshes the reports on schedule, routes them for approval and delivers them to the people who need them
No. Automation starts from the accounting system or ERP you already run, and a new platform only makes sense when the current one genuinely cannot hold the data you need. If you are weighing up the software side, our automated financial reporting software guide covers the options in detail.
Without validation, approval and controlled delivery you have automated data movement, not reporting, and recipients have no way of knowing whether the refreshed numbers were ever checked.
Yes. An automated pipeline can still deliver Excel files alongside dashboards and PDFs. The difference is that Excel becomes an output of the process rather than the process itself, so nobody is rebuilding workbooks by hand.
