EU taxonomy alignment case study: Royal London Asset Management

ORGANISATION DETAILS
Name	Royal London Asset Management (RLAM)
Signatoy type	Investment manager
Region of operation	UK
Assets under management	£127.8bn

COVERED IN THIS CASE STUDY
Fund	RLAM Sustainable Leaders Fund Manager
Geography	UK, Europe, US
Asset class	Equity
Environmental objective	Mitigation and adaptation
Economic activity	All

RLAM has long recognised that there is a need for a uniform definition of sustainable investing. We take pride in the success of our sustainable funds, first launched in 2003, and we work hard to ensure we deliver on the sustainable label. However, we are aware that, given the diversity of fund types and strategies, we need to work with our industry peers to provide greater clarity to our end customers. The taxonomy is one tool that may help to achieve this.

Other aspect you would like to mention?

The fund seeks to invest in sustainable companies, which we define as companies that either provide a positive net benefit to society through their products and services, or are leaders in managing their ESG risks and opportunities. The fund is not explicitly a ‘green’ fund, nor does it specifically target climate change mitigation or adaptation companies. We acknowledge the social and environmental benefits that companies can provide, and therefore our investment universe is much broader than the scope of the taxonomy.

Taxonomy implementation

Principles, criteria, thresholds

We took a manual approach to applying the principles, metrics and thresholds criteria. First, we downloaded the Technical Expert Group (TEG) report on the EU Taxonomy excel tool and embedded it into our working document. This proved helpful, because by using a formula we could pull out specific and relevant criteria for each stock under review.

When applying the criteria, we relied on company disclosure to assess whether a stock was aligned, potentially aligned or not aligned. Again, our review was manual, mainly leveraging company annual reports, accounts and websites.

Do no significant harm assessment

We reviewed DNSH manually, basing our assessments on company disclosure from websites and reports. We estimated potential alignment when specific company information was not available. We considered these cases as potentially aligned, though we excluded them from the final aligned figure.

We took a conservative approach and only considered a stock as potentially aligned if there was solid evidence to support our calculations and assumptions. We recognise that other companies may be more generous in applying potentially aligned criteria and we are interested in gauging the consensus on this specific point.

Social safeguards assessment

We applied a number of screens from MSCI ESG ratings, which we believed were aligned to the social safeguard factors. Whilst the MSCI screen factors did not fully align with the taxonomy’s safeguard factors, we felt that they would highlight any instances in which a company’s behaviour required further investigation to determine whether it failed the safeguard assessment.

In time, we expect that data providers will develop screen factors that fully align with the taxonomy, facilitating the application of this approach without the need for further investigation.

Turnover/capex/opex alignment

First, we applied the Bloomberg eligibility tool. This was the most automated and simple part of the process, as the tool enabled us to quickly identify which stocks and revenue were potentially aligned. Instead of manually reviewing all stocks in the fund, we were able to quickly reduce the scope to the ones that had revenue aligned with activities/sectors identified by the taxonomy.

As most companies report revenue against business units rather than activities and/or products, the next step was far more manual. In many cases, we were unable to verify whether the revenue of an aligned activity/product was contributing, and so it was often reported as not aligned. In these instances we did not engage with companies to try and obtain this information.

Going forward, as company reporting improves and becomes better aligned with taxonomy requirements we expect to see a positive impact on our taxonomy- aligned percentage.

Alignment results

Overall, we were surprised by the lack of disclosure to assess the taxonomy alignment of company activities and products in the portfolio. This had a significant impact on our overall taxonomy-aligned percentage. If companies do not quickly update their disclosures to meet investor needs, we believe our ability to accurately assess taxonomy-alignment may be undermined.

Further, the current level of manual work was significant, and application across a range of funds would be a significant undertaking potentially spanning months. In time, we hope that data providers are able to provide tools that undertake many of the required assessments, freeing up our resources to review results and determine how to update our investment approach to improve alignment.

Whilst we recognise the environmental focus of the taxonomy, we strongly feel that ‘sustainability’ also has a social focus. Funds that have strong social benefits could be undermined by low taxonomy-aligned figures. We support the goal of the taxonomy to drive investment to more environmentally-focused companies, funds and investments, but this may have the unintended consequence of driving capital away from funds and companies that support important social themes.

The following table shows the output of the Bloomberg eligibility tool. We have only included companies with reported eligible revenues, showing which sectors they fall in. The fund had 43 stocks, but only 15 had taxonomy-eligible activities according to Bloomberg. We were surprised by the low number of eligible companies for a sustainable fund, as broader sustainability factors lie at the core of our investment process.

Name	Percent Eligibilty	Agriculture	Construction	Energy	Information Systems	Manufacture Low Carbon Tech	Manufacture Metal & Cement	Manufacture Plastic & Chemicals	Real Estate	Transport	Water & Waste
Investable Universe (43)	30.1	0	2.4	5	4.5	2.9	0	3.8	9.1	0	2.3

ANSYS INC	100	0	0	0	100	0	0	0	0	0	0
UNITE GROUP PLC/THE	100	0	3.6	0	0	0	0	0	96.3	0	0
SPIRAX-SARCO ENGINEERING PLC	100	0	0	14.9	60.8	24.2	0	0	0	0	0
VICTREX PLC	100	0	0	0	0	0	0	100	0	0	0
SEVERN TRENT PLC	100	0	0	0	0	0	0	0	0	0	100
SHAFTESBURY PLC	100	0	0	0	0	0	0	0	100	0	0
VISTRY GROUP PLC	100	0	100	0	0	0	0	0	0	0	0
NATIONAL GRID PLC	100	0	0	100	0	0	0	0	0	0	0
HALMA PLC	100	0	0	0	0	100	0	0	0	0	0
SEGRO PLC	100	0	0	0	0	0	0	0	100	0	0
SSE PLC	99.5	0	0	99.5	0	0	0	0	0	0	0
ST. MODWEN PROPERTIES PLC	94.5	0	0	0	0	0	0	0	94.5	0	0
CRODA INTERNATIONAL PLC	64.7	0	0	0	0	0	0	64.7	0	0	0
RELX PLC	33.4	0	0	0	33.4	0	0	0	0	0	0

Challenges and solutions

NO.	CHALLENGE	SOLUTION
1	Given the mainly manual method of applying the taxonomy and the lack of data providers with the required tools, a significant amount of time was spent assessing companies against the various criteria.	We found that the best analysis approach was collaborative, leveraging responsible investment specialists. Financial analysts with significant company knowledge can feed into the process and reduce the time required. We also believe a collaborative approach will ultimately support the purpose of the taxonomy, sustaining its role in investment decision making. However, this approach is very manual, and not very scalable or efficient for client reporting or fund documentation.
2	The ability to report a potentially aligned figure was useful, though we were concerned that there were various approaches to calculating these figures, and their application may vary drastically across the sector.	RLAM lists integrity as one of the values grounded in the way we operate. Therefore, we applied a conservative approach to calculating our potentially aligned figure. This ensured that evidence was available to support any assumptions, and estimates were driven by robust calculations supported by an audit trail. This focus on accuracy and auditability meant that our taxonomy alignment was on the low side
3	We chose not to actively engage with any companies to gather further information. This ultimately meant that our aligned percentage was significantly lower than it otherwise might have been. The amount of taxonomy-relevant information published by companies is currently very limited.	For future reporting we would actively engage with holdings to obtain information we could not secure from disclosure. We believe that this would have a material impact on our aligned percentage and also result in more companies publishing taxonomy-relevant information in the future. Over time, we believe that standards of disclosure relating to the taxonomy will improve, which will ultimately aid our reporting process. We also believe it will help to close the gap between aligned and potentially aligned percentages.

NO.

CHALLENGE

SOLUTION

Given the mainly manual method of applying the taxonomy and the lack of data providers with the required tools, a significant amount of time was spent assessing companies against the various criteria.

We found that the best analysis approach was collaborative, leveraging responsible investment specialists. Financial analysts with significant company knowledge can feed into the process and reduce the time required. We also believe a collaborative approach will ultimately support the purpose of the taxonomy, sustaining its role in investment decision making. However, this approach is very manual, and not very scalable or efficient for client reporting or fund documentation.

The ability to report a potentially aligned figure was useful, though we were concerned that there were various approaches to calculating these figures, and their application may vary drastically across the sector.

RLAM lists integrity as one of the values grounded in the way we operate. Therefore, we applied a conservative approach to calculating our potentially aligned figure. This ensured that evidence was available to support any assumptions, and estimates were driven by robust calculations supported by an audit trail. This focus on accuracy and auditability meant that our taxonomy alignment was on the low side

We chose not to actively engage with any companies to gather further information. This ultimately meant that our aligned percentage was significantly lower than it otherwise might have been. The amount of taxonomy-relevant information published by companies is currently very limited.

For future reporting we would actively engage with holdings to obtain information we could not secure from disclosure. We believe that this would have a material impact on our aligned percentage and also result in more companies publishing taxonomy-relevant information in the future.

Over time, we believe that standards of disclosure relating to the taxonomy will improve, which will ultimately aid our reporting process. We also believe it will help to close the gap between aligned and potentially aligned percentages.

Recommendations

We recommend using data provider tools to significantly ease the burden on manual input. In our experience, the use of Bloomberg and MSCI ESG ratings supported the overall process, though they still require further development to be more useful to investors.

The process of applying the taxonomy to a fund should be carried out collaboratively, involving responsible investment specialists. This will not only reduce the manual burden but also help to embed the taxonomy in investment decision-making. Market participants should recognise that applying the taxonomy is time-consuming in terms of the preparation in understanding criteria and implementation. We estimated that reviewing 15 stocks within a fund of 43 took one colleague from 1-1.5 days.