The Reliability of Automated Financial Processes: A Question of Method

The month-end closing is complete, the ERP export is ready. Now the work in Excel begins to prepare the data for reporting, consolidation, or the VAT return. Many of these steps are repetitive and suitable for automation. But this raises a central question: the reliability of automated financial calculations. This question is not purely an IT topic. It is a matter of corporate security. The figures must be correct.

Automation as a Security Issue

In engineering, the reliability of safety-critical systems is ensured methodically. Engineers do not build a bridge or program a machine controller and then simply hope it works. There are established processes for design, testing, and maintenance. An automated financial calculation can be considered such a safety-critical system. An error can lead to incorrect business decisions, faulty reports to authorities, or undiscovered losses. The integrity of financial figures is a cornerstone of corporate governance.

The complexity of financial reporting is a known risk factor in this context. One study showed that high complexity can be a significant predictor of fraudulent financial reporting (doi.org 2024a). Confusing, manually maintained Excel files with many links and manual adjustments contribute to this risky complexity. Automation can provide a remedy here, but only if it does not itself become a new, opaque layer of complexity. The goal must be a traceable, transparent chain from raw data acquisition to the final key figure.

The Challenge of Constant Change

A process, once set up, rarely remains stable. The technological environment is subject to constant change. Your ERP provider rolls out updates. Your operating system is updated. The Office software on which your Excel automation runs continues to evolve. These changes often happen in the background and without your direct intervention. They can pose a latent risk to the stability of your automated processes.

An example of this is the introduction of new features in widely used software. Microsoft is introducing new Copilot features according to a 'safe deployment model' (Microsoft 2026). In this process, changes are gradually rolled out to larger user groups. This approach makes sense from the manufacturer's perspective to minimise risks. For your finance team, however, it means that the functionality of your tools can change without notice. A formula, a script, or a query that worked yesterday may produce a different result or generate an error tomorrow.

An automation based on the 'set it and forget it' principle can prove to be inadequate. The chain of calculations — from the ERP export through the transformation in Excel to the final report — is only as strong as its weakest link. An external change to one of the links can affect the entire chain. Reliability must therefore be actively and continuously managed.

The Methodical Approach to Reliability

The answer to this challenge lies in the method. Automation should be understood as an engineering process, not as a one-off programming project. The focus is less on the quick solution to a task. Rather, it is on creating a permanently reliable solution. This approach is consistent with findings that digital transformation can improve the quality of accounting information by increasing transparency and reducing information asymmetry (doi.org 2024a).

A methodical approach comprises three core areas. Firstly, careful documentation. All essential calculation steps, assumptions, and data sources should be recorded clearly and traceably. Secondly, consistent versioning. Significant changes to the logic or sources must remain traceable. This ensures that, if necessary, it is clear which version of a report was created with which calculation basis. Thirdly, integrated tests. The automation should check itself for plausibility. Control totals, variance analyses, and reconciliations should be part of the automated process and ideally not a subsequent manual step.

What Does This Mean for Practice in the Finance Team?

As a CFO or Head of Finance, you do not need to become a programmer yourself. Your task is to set the right requirements for automation. The focus shifts from pure functional fulfilment to process quality. The crucial questions expand. In addition to the question 'Does the process deliver the right result?', others arise: 'Is the process robust against changes?', 'Can we trace a figure in the report back to its origin?', and 'Does the process report on its own if something is wrong?'.

Research shows advanced approaches in this direction. Studies demonstrate that the combination of text analysis, complexity indicators, and anomaly detection algorithms can improve the detection of irregularities in financial statements (doi.org 2024a). A so-called Autoencoder Neural Network achieved high accuracy in fraud detection (doi.org 2024a). These are highly sophisticated tools. However, the principle behind them is relevant for many finance teams: a reliable system actively searches for errors and anomalies. It assumes that errors can happen and is designed to find them.

Steps Towards Greater Reliability This Month

You can start improving the reliability of your existing processes today. It is about applying an engineer's mindset to your Excel-based workflows. Begin with a small but important process. The following steps will help you to systematically identify weaknesses.

• Select a recurring report based on an ERP export, for example, a contribution margin analysis or a cash flow plan.
• Document the manual steps that you or your team perform from opening the raw file to the final figure.
• Identify the implicit assumptions in the process. Where is rounding applied? Where is a cell manually overwritten? Which data is taken for granted?
• Perform a control calculation with the previous month's data. Only replace the input file and execute the documented steps again. Is the result still correct?
• Discuss the identified deviations and weaknesses with the team. This creates an awareness of the fragility of manual and semi-automated processes.

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