What Happens If My CSRD Data Is Wrong?

Introduction

It’s a common worry among first-time reporters: what if some of my CSRD data turns out to be wrong?

The good news is that CSRD reporting is built on transparency and improvement, not punishment. The Corporate Sustainability Reporting Directive (EU 2022/2464) and the European Sustainability Reporting Standards (ESRS) recognise that companies — especially small and growing businesses (SMEs) — will face data gaps, estimation challenges, and occasional errors.

If your data isn’t perfect, that’s not a compliance failure. What matters is how you handle, correct, and communicate those errors.

This article explains what happens when CSRD data is wrong, how auditors deal with inaccuracies, and how you can fix issues without damaging credibility.

For guidance on data reliability expectations, see How Accurate Does CSRD Data Need to Be?.

1. The Role of Accuracy in CSRD Reporting

Under ESRS 1 (General Requirements), sustainability information must be:

• Faithful and free from material misstatement,
• Comparable and verifiable, and
• Based on reasonable estimates where exact figures aren’t available.

That means some level of uncertainty is acceptable — especially for Scope 3 data or social indicators — as long as:

• The method is sound,
• The assumptions are transparent, and
• The margin of error doesn’t change key conclusions.

In short: wrong numbers happen, but misleading ones are the real risk.

2. How Auditors Handle Errors Under Limited Assurance

From 2025 onwards, all CSRD reports will be subject to limited assurance, where auditors check that your data is plausible and traceable, not perfect.

If auditors find inaccuracies or inconsistencies, they will:

1. Flag them for clarification — asking for backup documentation or explanation.
2. Assess materiality — deciding if the error significantly affects the overall picture.
3. Recommend correction — either before publication or as part of the audit report.

If you acknowledge the issue and correct it transparently, there are usually no penalties. The assurance report might include a note about data limitations, but this is normal and not considered a failure.

3. When Data Errors Become “Material Misstatements”

A material misstatement occurs when an error, omission, or misclassification could influence stakeholder decisions or distort the overall sustainability picture.

Examples:

• Reporting zero waste when records show 15 tonnes.
• Excluding an entire factory’s energy use.
• Claiming “100% renewable electricity” without proof.

If a misstatement is material:

• Auditors may issue a qualified assurance opinion (with an explanatory note).
• You’ll be asked to correct or restate the affected figures in the next report.
• Regulators or stakeholders might request clarification — but sanctions are rare unless deliberate misrepresentation is proven.

For SMEs under the VSME Standard, proportionality applies — meaning small data errors aren’t treated harshly as long as the overall process is sound and improving.

4. How to Correct CSRD Data Errors

If you discover an error before submission:

1. Update the figures and keep a record of the correction.
2. Document what changed and why (e.g. “updated energy factor from 2023 to 2024 version”).
3. Notify your assurance provider so the final version reflects accurate data.

If the error is found after publication:

• Correct it in your next CSRD report.
• Add a brief note explaining the restatement (similar to financial reporting practice).

Example:

“Scope 2 electricity emissions for 2024 were revised from 220 tCO₂e to 190 tCO₂e following updated utility data.”

Transparency is always the right answer — even minor corrections build trust.

5. Common Causes of Incorrect Data (and How to Avoid Them)

Simple controls — like version control, data ownership, and annual factor reviews — drastically reduce reporting errors.

6. The Regulator’s Perspective: Intent Matters

EU regulators understand that CSRD introduces new processes for many companies. The focus is on building reliable systems, not punishing small mistakes.

However, intentional misreporting (e.g. greenwashing or false claims) could lead to:

• Public correction requests by national authorities,
• Reputational damage, or
• In severe cases, financial penalties under national law.

For genuine errors, honesty and continuous improvement are always viewed positively.

Frequently Asked Questions

What if I can’t get full data from suppliers?

You can use estimates or industry averages, as long as the approach is transparent. See How to Estimate Missing Data for CSRD Reporting.

Can I correct data after publishing the report?

Yes. Note the correction in the next reporting cycle — auditors and regulators expect iterative improvement.

Will an error automatically affect my audit opinion?

Only if it’s material and not addressed. Minor inaccuracies are typically corrected before final assurance.

What’s the best defence against wrong data?

Documentation. Keep a clear trail of how each figure was calculated, including sources and emission factors.

Key Terms

• Limited assurance – Moderate-level audit confirming data plausibility.
• Material misstatement – An error that could mislead users of the report.
• Restatement – Correcting a previously published figure in a future report.
• Emission factor – Conversion rate between activity data and emissions.
• VSME Standard – Simplified EU framework for voluntary SME sustainability reporting.

Conclusion

If your CSRD data turns out to be wrong, don’t panic — what matters most is how you respond. The CSRD framework prioritises transparency and learning, not punishment.

Correct errors openly, document your methods, and update data in the next cycle. Auditors and stakeholders will value your honesty far more than perfection.

To get your team ready for assurance and data checks, see How to Prepare for Your First CSRD Audit or Review.

To help ensure your data is accurate from the start, use our checklist generator to create a comprehensive data collection checklist:

This tool will help you identify all the data points you need to collect and ensure proper documentation to prevent errors.