Investing in the Age of AI
AI, EU Taxonomy, Regulatory ComplianceArticles

EU Taxonomy Reporting: Maximizing Coverage with High-Quality Supplementary Data

Published: December 14, 2023
Modified: June 25, 2025
Key Takeaways

How public disclosures help address the information gap for companies not reporting Taxonomy Alignment

The financial sector continues to play a central role in the EU’s efforts to become Net Zero by 2050, including through the sector’s central role in flagship sustainable policies such as the Sustainable Finance Disclosure Regulation (SFDR), the EU Taxonomy for Sustainable Activities, and the Corporate Sustainability Reporting Directive (CSRD).

Under SFDR, Asset Managers looking to market their funds within the EU are required to categorize them under three disclosure categories: those that promote sustainability characteristics (Article 8), those with specific sustainability objectives (Article 9), or neither (Article 6).

For asset managers disclosing under Article 8 or 9 and promoting environmental characteristics or pursuing environmental objectives, it is required they report their fund’s alignment to the EU Taxonomy. Given the steady increase of Assets under Management’s share over time for these fund types, many Asset Managers are seeking an EU Taxonomy reporting solution to provide them with all the necessary data to fulfill their regulatory requirements.

Addressing the 90% coverage gap in reported data

Companies outside the EU represent close to 90% of the global equity market capitalization, and as these companies will initially be outside the scope of the CSRD regulation, they are not required to report EU Taxonomy indicators. 

Consequently, funds that allocate investments on a global scale lack the data for precise calculation and reporting of their portfolio’s alignment. Investors are then left to either report 0% alignment from these investments (potentially compromising their sustainability credentials) or to seek alternative methods to evaluate the investees’ alignment.

Hence, models capable of assessing Taxonomy Alignment for companies outside the regulatory scope of the bloc hold significant value. But to what extent can the use of estimates or equivalent data increase EU Taxonomy coverage of a typical portfolio while remaining accurate and in line with the regulation?

To ensure compliance with the EU Taxonomy regulation, we adhere to the precautionary principle. Considering ESMA’s recommendations on the use of estimates we have designed our models to estimate alignment based on company disclosures, (such as power generation data split by technology, or proportion of electric vehicle sales of auto manufacturers), only using estimations on limited and specific data points, with a focus on the transparency of our methodologies to our clients.

To assess both the accuracy and potential coverage increase of our models, we performed a comparative analysis utilizing Clarity AI’s extensive report-based dataset of over 1600 companies as well as the results of our alignment models.

Coverage: Clarity AI’s models result in a threefold increase in portfolio Taxonomy Alignment of the MSCI ACWI

For our analysis on coverage, we computed the alignment of the MSCI ACWI as a benchmark for a representative global diversified equity portfolio. The MSCI ACWI is an index comprising close to 3,000 companies that represent 85% of the global market capitalization of listed equities.

Among the 3,000 companies, approximately 15% directly disclose EU Taxonomy indicators. Employing Clarity AI’s models enables us to assess the alignment of an additional 83%, thus achieving close to full coverage of the MSCI ACWI. These assessments translate into a significant increase in alignment, as indicated by the next chart:


Figure 1: Comparative analysis of Taxonomy Alignment percentage in MSCI ACWI. Note: Data shown for 2868 companies within the MSCI ACWI Index. 424 companies reported EU Taxonomy Indicators. 2386 companies were estimated. Reported data is directly sourced from company reports. Data as of October 15th, 2023. Source: Clarity AI

Accuracy: Clarity AI’s conservative approach to EU Taxonomy assessment  results in an error rate below 1.5%

To gauge the models’ effectiveness, we have calculated the estimated alignment for the 1600 entities within Clarity AI’s database of reported data, predominantly encompassing publicly traded European firms across diverse sectors. We then cross-referenced the estimations from the models against the reported alignment from the same companies, dividing the results into three cases, as detailed in the following graph:

Figure 2: Comparison of reported Alignment against modeled Alignment. Note: Data shown for 1,600 companies. Reported alignment sourced directly from company reports. Data as of October 15th, 2023. Source: Clarity AI

Adhering to the precautionary principle, we categorize instances as errors only when a company’s alignment is overestimated by more than 5 percentage points. Given that such occurrences are limited to approximately 1% of cases, we are content with the accuracy of our models.

The Opportunity for Asset Managers

As shown by the data, Clarity AI’s EU Taxonomy reporting tool can expand the coverage of taxonomy data available to financial market participants including asset managers. This can add robust evidence to support increased taxonomy alignment figures, enabling the product to attract inflows associated with Article 8 or Article 9 status.

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