ESG Reporting: Global Standards Become an Operational Reality

The topic of ESG reporting is moving beyond strategic discussion. It is becoming a concrete task in financial closing. The global convergence of ESG reporting standards in Switzerland and internationally is creating new demands on data quality and processes. The pressure is not just coming from regulators. Customers, banks, and investors are also increasingly demanding comparable and reliable sustainability metrics. For finance teams, this means that collecting and preparing this information requires a level of diligence similar to that of financial reporting. The challenge is no longer just about understanding the regulations, but about procuring and processing the necessary data in a repeatable and audit-proof manner.

The Global Alignment of Standards is a Fact

A new analysis confirms this trend. A study of 22 jurisdictions between 2019 and 2024 shows a clear global convergence in ESG disclosure (Delgado Sanchez 2027). This development is approaching global saturation. In practice, convergence means that frameworks like those of the Global Reporting Initiative (GRI) or the standards of the International Sustainability Standards Board (ISSB) are establishing themselves as the global language for sustainability information. This makes company reports comparable across industries and national borders and increases the pressure for audits.

The study's figures substantiate this development. The average ESG disclosure in the countries surveyed rose from 89.2% to 97.1% during this period. At the same time, the standard deviation fell from 14.4 to 6.19 percentage points (Delgado Sanchez 2027). A decreasing deviation is a clear statistical signal that reporting practices are becoming increasingly uniform. The differences between countries are diminishing.

The study also found strong 'catch-up' evidence. Countries that previously had less stringent regulations are catching up in general ESG disclosure and in the use of frameworks such as GRI and the Sustainable Development Goals (SDGs) (Delgado Sanchez 2027). For Swiss companies, this means that customers, suppliers, and investors from abroad will increasingly expect standardised and comparable ESG data. The pressure to conform comes not only from legislators but directly from the market.

What Does This Mean for the Swiss Finance Team?

Standardisation makes ESG data an integral part of reporting. It is no longer a separate exercise that takes place once a year. The metrics must be collected with the same regularity and reliability as financial data. They are becoming part of the monthly or quarterly close. The information must be audit-proof. This means that every value must be traceable to its source and the processing path must be fully documented. For a CO2 calculation, for example, a clear audit trail must exist from the energy bill to the final metric in the report.

This shifts the focus. It is no longer primarily about what needs to be reported, but how the data is procured, validated, and prepared. This is a procedural challenge. Financial data is usually well-structured and anchored in the ERP system. ESG data, on the other hand, is often qualitative, distributed across various departments, and exists in unstructured formats. The chain from the ERP export through various Excel spreadsheets to the final report thus becomes longer and more fragile. Manual processes, which might still be manageable for financial data, reach their limits with the diverse nature of ESG data.

Data Quality as the Foundation

Digital transformation plays a crucial role in improving the quality of accounting information. It increases transparency, reduces information asymmetries, and limits opportunistic management behaviour (Accounting, Finance and Computational Intelligence 2024). Digital processes enforce consistency and automatically create logs and audit trails. This is in contrast to a process chain that relies on emails and manually maintained spreadsheets.

A study of companies listed on the Tehran Stock Exchange from 2020 to 2024 showed that digitalisation has a positive and statistically significant effect on the quality of accounting information (Accounting, Finance and Computational Intelligence 2024). This principle applies equally to financial data and ESG data. A robust, digitalised process is the foundation for reliable metrics.

Investing in data quality is not just a matter of compliance. It can also have a positive impact on financial performance. A study of pharmaceutical companies in the period 2021–2025 found that green accounting has a positive and statistically significant influence on financial performance (Jurnal Literasi Akuntansi 2025). Robust and reliable ESG data are therefore not just a duty. They can also create economic value by forming the basis for better internal decisions and a stronger market position.

Automation as the Path to Audit-Proof Reporting

Manual data processing is prone to errors. With the complexity of ESG data, which comes from a wide variety of sources, this risk increases significantly. The challenge is to ensure data integrity throughout the entire chain — from the source system to the final sustainability report. Every manual intervention, every copy and paste, is a potential source of error and breaks the audit trail.

Automation is not a replacement for the controller. It automates the repetitive tasks of data aggregation, validation, and formatting. This frees up time for analysis and interpretation. A study shows how the combination of text analysis, complexity indicators, and anomaly detection algorithms improves the detection of fraudulent financial reports (Journal of Management and Business Solutions 2024). An autoencoder-type neural network achieved an accuracy of 0.93 in this process (Journal of Management and Business Solutions 2024).

Even though this study focuses on financial fraud, the underlying logic is transferable. Automated checks can uncover inconsistencies in ESG data that a person might easily overlook. Examples include a sudden drop in energy consumption to zero or discrepancies in the number of employees between the HR system and the reported metric. Automation creates a system of controls that increases the reliability of reporting and lays the groundwork for a successful external audit. Skopa automates the Excel layer that exists around a company's ERP. We do not replace the ERP system itself.

Concrete Steps for Your Finance Team

You can start strengthening your ESG reporting processes this month. The following steps will help you create a foundation for reliable data, regardless of any specific tool or provider.

• Identify data sources: Create an overview of the relevant ESG data points. Find out in which systems and documents this information currently resides. Examples include electricity bills for Scope 2 emissions, data from the HR system for employee turnover and diversity, or purchase receipts for supply chain analysis.
• Document the process chain: Map out the data journey, for example, in a simple flowchart. Where is a file exported? Where is data manually merged or calculated? Record who is responsible for each step. This often reveals unclear responsibilities.
• Assess gaps and risks: Compare your current processes with the requirements of the new standards. Where are there manual interventions that could lead to errors? Examples of risks include formula errors in a central Excel file, the use of outdated emission factors, or inconsistent definitions of a metric across different departments.
• Set priorities: Focus on the most material topics and the biggest risks to data integrity. Not all data points are equally important. Start where the effort for manual collection is greatest and the susceptibility to errors is highest.

This analysis creates a clear basis for the next steps. It shows where your processes need to be improved to meet the future requirements of ESG reporting.

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