Data Quality in Financial Reporting: A Direct Consequence of Economic Uncertainty

The pressure on finance teams is growing in an uncertain economic environment, creating significant financial reporting data quality uncertainty. Management and the board of directors demand precise and rapid analyses to steer the company, yet the underlying accounting data is becoming more fragile. Manual and historically developed process chains are no longer just an efficiency problem — they are evolving into a direct business risk that jeopardises the reliability of decisions.

Uncertainty Weakens Data Quality

The stability of the economic environment has a direct impact on the quality of accounting information. A recent study of listed companies confirms this connection. It shows that environmental uncertainty, measured by sales volatility, significantly affects the quality of accounting information (doi.org 2024a). For Swiss SMEs, this uncertainty manifests itself in volatile raw material prices, fluctuating exchange rates or unforeseeable changes in supply chains. Such factors lead to more estimates, provisions and extraordinary entries that must be processed and valued manually.

Each of these manual valuations increases the susceptibility to errors. The data foundation becomes less stable. However, the same study also identifies a potential solution. Digital transformation has a positive and statistically significant effect on the quality of accounting information (doi.org 2024a). The findings underscore the importance of digital technologies. They help to maintain the quality of accounting information under unstable business conditions (doi.org 2024a). A digitised and standardised process is more resilient to external shocks because it reduces the number of manual and error-prone interventions.

Complexity in Reporting Increases the Risk of Errors

An uncertain environment is only one side of the problem. The other is the internal complexity of reporting processes. A second study, which analysed data from 2018 to 2024, substantiates this. It shows that the complexity of financial reporting is a significant predictor of fraudulent financial reporting (doi.org 2024a). While fraud is the most extreme form, the principle also applies to unintentional errors — the more complex the process, the higher the risk.

Complexity is a measurable factor here. The researchers assessed it using readability indicators, the length of reports and the structure of disclosures (doi.org 2024a). In practice for SMEs, this often means a confusing chain of Excel files. The process begins with an export from the ERP system. The data is imported into a central Excel file, linked with other spreadsheets and supplemented with manual entries. In the end, the results are copied into a presentation or a PDF report. Every manual step in this chain is a potential source of error. The longer and more convoluted the process, the more difficult it becomes for the CFO or Head of Finance to maintain control.

The Double Danger for the Finance Team

For finance managers in Swiss SMEs, these findings present a double warning. On the one hand, economic uncertainty makes the underlying data more susceptible to errors. On the other hand, the often historically developed and manual reporting processes increase the likelihood that these errors will go undetected or that new ones will be introduced. This creates a dangerous combination of unstable input data and an error-prone processing workflow.

This combination is precarious. The reliability of financial reports is the foundation for strategic decisions by management. If data quality suffers, forecasts become inaccurate and risks are misjudged. An overlooked error in liquidity planning can have real-world consequences. The manual process chain from the ERP export to the final management report thus transforms from a known inefficiency into an acute risk for corporate governance. The responsibility for the accuracy of the figures ultimately lies with the CFO.

The Path to a Robust and Auditable Process

The solution is not to buy another software tool that creates new data silos. It lies in the systematic simplification and standardisation of existing processes. The goal is a robust and traceable path from the data source to the final report. Automation is a means to an end — not the end itself. The purpose is a stable, controllable and transparent process chain.

A standardised process drastically reduces the number of manual interventions. This lowers the risk of human error. At the same time, the entire procedure becomes transparent and auditable. Every figure in the final report can be traced directly back to its origin in the ERP system. This traceability is the core of a reliable internal control system (ICS) and a requirement for external auditors. The studies also point in this direction. They highlight how advanced computer technologies can significantly improve accuracy in identifying anomalies (doi.org 2024a). For an SME, this means relying on proven automation to stabilise the process chain and secure data quality.

What You Can Do This Month

Improving data quality begins with a clear analysis of the status quo. You do not have to overhaul the entire reporting system at once. Focus on gradual and measurable improvements to reduce risk in a targeted manner.

• Document a process chain. Select an important, recurring report — for example, the monthly income statement or a liquidity report. Map out the entire process on a piece of paper or in a simple flowchart. Note down every single step from exporting the data from the ERP system to the final version of the report, including every file and every person involved.
• Identify the weak points. In your process documentation, highlight the areas with the highest complexity and the greatest manual effort. Where is data manually copied and pasted? Which Excel files contain complex, hard-to-follow formulas? Where is the greatest risk of discrepancies? Assess the risk for each step.
• Plan a concrete simplification. Choose the most critical or time-consuming step from your analysis. Consider exactly how this one step could be simplified or automated. Often, it is a single linking or consolidation step that takes the most time and poses the highest risk. The goal is to strengthen the chain at one point. This small improvement already increases the reliability of the entire report and creates a foundation for further optimisations.

This analytical approach allows you to systematically identify and reduce the risks in your reporting system. It creates a solid basis for providing reliable information for decision-making, even in uncertain times.

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