Testing The Taxonomy: Insights From the PRI Taxonomy Practitioners Group | Recommendations to Investors | UN PRI
INSIGHT by UN PRI
This report shares insights from the first comprehensive set of case studies around how to use the EU taxonomy. Starting in late 2019, over 40 investment managers and asset owners worked to implement the taxonomy on a voluntary basis in anticipation of upcoming European regulation. The investors assessed taxonomy alignment before many details of the final regulation are in place, and before widespread corporate reporting against the taxonomy is available. Many challenges remain, not least the availability of data and potential changes to the detailed taxonomy criteria. Nonetheless, the progress made by the group is encouraging. The case studies detailed here demonstrate that the taxonomy framework can be operationalised, and offer important insights for investors beginning their taxonomy preparation.This report also summarises recommendations from the group to policymakers and supervisors who will oversee the implementation and development of the taxonomy. The PRI hopes that by circulating these findings, this report will foster confidence and facilitate implementation of the taxonomy. Summary: recommendations to investorsBased on their experience of implementing the taxonomy, we asked investors to offer advice to other financial market participants who will be required to disclose against the taxonomy in the future. This advice is detailed throughout the report, but broadly can be grouped into four steps: Establish a framework
- Ensure adequate resources are set aside and management is aware of this regulatory requirement
- Integrate the taxonomy into the investment strategy
- Manage expectations
- Start early. Allocate time and expertise for detailed analysis
- Quantify findings as far as possible
- Start small. Test one sector/product/region
- Apply a step-by-step approach
- Take a bottom-up approach
- Strictly adhere to thresholds wherever possible
- Carefully consider reliability levels for different sources of data
- Verify with companies when in doubt
- Provide context for results
- Engage on data
- Share with partners
- Work with data providers
- Support innovation and improvement from data providers
- Investigate validation and external assurance