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ESG Ratings at Crossroads: Need to address strategic shortcomings

Synopsis: A couple of weeks ago, the Board of the International Organization of Securities Commissions (IOSCO) published a Consultation Report titled ‘Environmental, Social and Governance (ESG) Ratings and Data Products Providers’ with the aim of assisting the members in understanding the implications of the activities of ESG ratings and data products providers. Highlighting the challenges in the ecosystem and its impact on the users, it shows that there is little clarity and alignment on definitions, including on what ratings or data products intend to measure apart from a lack of transparency about the methodologies. Certain industries or geographical areas benefit from more coverage than others, thereby leading to gaps for investors. Many ESG and Sustainability data and ratings providers are excessively focused on the end result while the process is more important for the users. This clearly means that as this space evolves and the systems get more structured, the ESG data and ratings providers would need to take care of the basics including, a) focus on process, b) quality over quantity, and c) the mix of tech and domain expertise. It is clear that, a) very few people need readymade ratings, and more people want quality data, b) different clients need different pitch and for that solid background research is necessary, and c) because of conflict of interest, ratings are not advisable to be offered by everyone nor are they for all the asset managers unless they know how to use them and what is going on in the process.

IOSCO Consultation Report on ESG Ratings and Data Products Providers

The Board of the International Organization of Securities Commissions (IOSCO) has published a Consultation Report titled ‘Environmental, Social and Governance (ESG) Ratings and Data Products Providers’ to assist the IOSCO members to better understand the implications of the activities of ESG ratings and data products providers. They include organizations like ESG rating providers, ESG data products providers as well as providers who offer both ESG ratings and data products.

The report proposes recommendations to mitigate risks associated with ESG ratings and data products and to address some of the existing challenges faced by ESG ratings and data products providers, users of ESG ratings and data products, and the companies that are the subject of these ESG ratings or data products. The report was published towards the end of July for public consultation only. It has not been approved for any other purpose by the IOSCO Board or any of its members.

The market is growing rapidly

The popularity of ESG and Sustainability has increased among investors and asset managers are preparing themselves to respond to this surge in demand. It also means that investment managers need to either have an in-house framework for ESG evaluation or use external service providers. This has created a lucrative market opportunity for ESG ratings and data products.

The asset managers in particular and the ESG ecosystem, in general, are using these products and service providers to assess the sustainability track record of the companies in which either they invest or evaluate them on ESG performance. These ESG ratings and data products providers offer investors a method to screen companies for ESG performance.

As highlighted, this rise in demand has led to the entry of several participants in the ESG ratings and data products industry. This trend is expected to continue, with forecasts that the market for ESG data products could reach USD 1 billion by 2021, with an expected annual growth of 20 percent, while ESG indexes could grow by 35 percent.

The IOSCO consultation paper also says that the market for ESG ratings and data products is currently in a phase of rapid growth and is expected to continue growing over the coming years, driven by two reasons:

First, there is increasing legislative and regulatory focus on financial market participants’ consideration of the ESG characteristics of potential investments, with some jurisdictions imposing or considering imposing new regulatory obligations.

Second, there is increasing demand from investors for products that will push society towards a greener economy and mitigate the risks stemming from climate change. These two drivers are only likely to increase in intensity over the coming years, leading to ESG ratings and data products taking on a more important role in the financial sector.

Consistency and Quality: Two major issues for providers of ESG Ratings

The consultation report mentions that IOSCO has undertaken a fact-finding exercise with ESG ratings and data products providers, users of ESG ratings and data products, and the companies that are the subject of these ESG ratings or data products. The fact-finding exercise carried out by IOSCO revealed some very disturbing yet expected facts:

  • There is little clarity and alignment on definitions, including on what ratings or data products intend to measure;
  • There is a lack of transparency about the methodologies underpinning these ratings or data products;
  • While there is wide divergence within the ESG ratings and data products industry, there is uneven coverage of products offered, with certain industries or geographical areas benefitting from more coverage than others, thereby leading to gaps for investors seeking to follow certain investment strategies;
  • There may be concerns about the management of conflicts of interest where the ESG ratings and data products provider or an entity closely associated with the provider performs consulting services for companies that are the subject of these ESG ratings or data products; and
  • Better communication with companies that are the subject of ESG ratings or data products was identified as an area meriting further attention, given the importance of ensuring that the ESG ratings or other data products are based on sound information.

Ten key takeaways relevant for providers of ESG Ratings and data

The interesting characteristic of this space in which providers of ESG ratings and data operate is that the smaller companies operate in the ESG ratings and data products market alongside those large, international providers. These smaller companies generally tend to have a specific regional presence and/or specialization in specific data sets (e.g., climate, controversies), coverage (e.g., small and medium enterprises, sovereign issuers), or services (e.g., certification, second-party opinions, and consulting services). There are also many start-ups and fintech companies entering the market and offering new products, which usually focus on using and leveraging big data and artificial intelligence in their product offerings. In our assessment, the ten major takeaways are as follows:

  1. For rating coverage, while some providers do cover private companies, there is a heavier weighting of rating coverage for publicly listed companies and more coverage of sophisticated or developed financial markets.
  2. A number of ESG data products providers highlighted that demand for their data products was higher in jurisdictions with a higher level of legislative and regulatory or client focus on ESG investing, namely Europe and the U.S.
  3. Outside of Europe and the U.S., respondents highlighted that demand for ESG data products was related to the size of the client, with apparent differences in the types of ESG data products demanded.
  4. There are regional variations, which link to historical differences in terms of approach to socially responsible investment. For example, in the case of Europe, screening approaches are more prominent in the Nordics, The Netherlands, and Germany. Meanwhile, the most advanced market is France.
  5. The fee model for ESG ratings and data products is largely based on a “subscriber pays” basis. Where figures in terms of the ratio of revenues from “subscriber pays” versus “issuer pays” were provided, these put the split at between 85% and 100% of revenues being derived from “subscriber pays”. The subscriber pays vs. issuer pays revenue mix has been stable for several years.
  6. Uses (whether actual or intended) of AI and ML were almost unanimously flagged as mainly for the support of human analysis and would in no case act as a substitution to the work currently being performed by human analysts. Such AI/ML help would allow for more frequent updates of the data or for more convenient data collection processes, therefore freeing human resources for more valuable tasks such as analysis, making recommendations, and determining outcomes.
  7. While AI and ML have a role in simplifying the data compilation process, other uses have also been observed. These include using AI and ML techniques for the purpose of assessing the sentiment and behavior of the market towards key ESG issues or to provide estimates of historical carbon emissions.
  8. In recent years, companies have started utilizing NLP to a greater degree, which improves efficiency in data extraction and enables them to cast a wider net when processing news and media data sources. With the increase in ESG data requirements and with more companies and third parties reporting relevant data, they are collecting more data points for more companies now than 2 years ago.
  9. Most companies indicated that ESG ratings are generally incorporated into investment decisions but did not describe how ESG ratings are used in investment decision-making processes.
  10. All public users, and some private users, responded that they do not implement verification processes on raw data underlying ESG ratings or ESG data products because such processes are resource-intensive and may not be possible with available information.

What could be the major implications

There is haphazard growth in the industry and many ESG and Sustainability data and rating providers are excessively focused on the end results while the process is more important for the users. This clearly means that as this space evolves and the system gets more structured, the ESG data and rating providers would need to take care of the basics including, a) focus on process, b) quality over quantity and c) the mix of tech and domain expertise. The other important implications are as follows;

  1. There is a gap in ESG coverage across asset classes and in the near future, the other asset classes will also see a proliferation of ESG data and ratings. It will take a while to catch up, but the process is already underway and the market opportunity will get more attractive for the ESG data and rating providers.
  2. This issue of ‘conflict of interest’ will become very important for the ESG ratings and data providers. The users will expect that these companies make a complete disclosure and address this issue, wherever it is relevant.
  3. The multiple frameworks in ESG and Sustainability matter even more and as the complexity and scrutiny increase, the ESG ratings and data providers will be required to pay more attention to the interoperability of frameworks and the flexibility to pick and choose parameters on the basis of their relevance.
  4. Most asset managers are already using ESG ratings and are incorporating them into their investment decisions. Although many of them would not use the ESG ratings in similar ways for their investment decision-making processes, this does indicate that asset managers are receptive to the idea and ESG is going to be more common as an investment filter.
  5. The other interesting thing is that different people use ESG ratings and ESG data products differently. There is enough space for new people in this area and people are willing to give newcomers a chance. The space is still evolving and the ecosystem is exploring and experimenting.
  6. The users are comfortable with variance. It sounds counterintuitive because, at a lot of places, the problem highlighted was lack of comparable ratings or data and lack of standardization. Our sense is that it is not that entirely inconsistent. Because what it means is that people are ready to accept all types of data depending on its utility. They want standardization but they are also fine for the time being if it is not there.
  7. Once an ESG ratings and ESG data products provider enter a new place, it will have to undergo a stringent process and scrutiny. However, once they get accepted and the ball starts rolling, they will find that the users will be using their inputs consistently and continuously. The entry is not easy but once it happens, there is no looking back for ESG ratings and ESG data providers.
  8. Since the lack of transparency around external ESG rating methodologies is a key factor in encouraging users to build proprietary rating methodologies, the ESG ratings and ESG data providers will need to offer different products for different clients, as per their requirements.
  9. While it is true that given the current “subscriber-pay” model, in general there is no incentive for the ESG ratings or data products providers to interact meaningfully with the companies, it is important to avoid unnecessary influence and a cosy relationship between the parties. This is very important for fair play.
  10. This challenge of conflicts of interest is real where the relationship on the consulting side of business of a company may provide an unfair advantage in terms of receiving a good rating or data product outcome from the ESG rating or data product side of the business.

How EMAlpha can help

On the basis of AI-ML based analysis of the available news flow on ESG ratings and data products providers and our interaction with the sustainable finance ecosystem, we think it is clear that, a) very few people need readymade ratings, and more people want quality data, b) different clients need different pitch and for that solid background research is necessary, and c) because of conflict of interest, ratings are not advisable to be offered by everyone nor are they for all the asset managers unless they know how to use them and what is going on in the process.

An ESG ratings or data products provider can offer data to asset managers for portfolio evaluation. They don’t always need to offer ESG ratings on individual issuers. This requires that the ESG ecosystem needs to be better prepared with the best possible tools and support for investors and asset managers in helping with this transition.

At EMAlpha, we have incorporated a Flexible Framework Management System, based on EMAlpha’s proprietary technology making inferences framework agnostic. This also offers a quick adaptation for the users (asset managers, companies and investment advisors). As such, the EMAlpha’s ESG and Sustainability offering is centred around addressing some of the most critical issues.

The EMAlpha algorithms provide a choice for separate relevant frameworks and these can be used to review the performance more transparently. This not only helps the investment advisors but also make the clients understand the granular details better which in turn is helpful for them to understand their preferences better. To achieve this, we focus on the following;

  • Go beyond the official reported version – The data source matters and there is a need to look beyond what the companies are reporting and what the official version is. It is essential to rely on the company reported data because other sources might not be collating as much information. Although often, there are other sources as well for environment related information. They include the information disclosure as mandated by regulators and the EMAlpha algorithms scan through unstructured data to pick the unofficial information too.
  • No two ESG scores are same despite same headline figure – It is the composition that makes a big difference and all the three parameters that make up ESG need to be evaluated separately. The EMAlpha algorithms provide separate scores for E, S and G so that an investor can review the sectoral performance more transparently. Over and above, a key feature of EMAlpha’s NLP algorithms is that the attribution analysis is fairly simple and straight forward.
  • An ESG score without context and background is meaningless – The ESG is as much about intent as it is about execution. For this balanced evaluation, having an understanding of the local factors is very crucial. A very good ESG track record (probably more driven by excellent performance in E and/or S) may hide serious Governance related risks and the investors can only ignore them at their own peril. EMAlpha analysis meticulously incorporates this critical part of the ESG evaluation jigsaw puzzle.

References

  1. International Organization of Securities Commissions https://www.iosco.org/publications/?subsection=public_reports (Accessed on 11th August 2021)
  2. Report on Sustainability-related Issuer Disclosures https://www.iosco.org/library/pubdocs/pdf/IOSCOPD678.pdf (Accessed on 11th August 2021)
  3. Recommendations on Sustainability-Related Practices, Policies, Procedures and Disclosure in Asset Management https://www.iosco.org/library/pubdocs/pdf/IOSCOPD679.pdf (Accessed on 11th August 2021)
  4. ESG Ratings and Data Products Providers https://www.iosco.org/library/pubdocs/pdf/IOSCOPD681.pdf (Accessed on 11th August 2021)
  5. ESG Data Market: No Stopping Its Rise Now opimas.com/research/547/detail/ (Accessed on 11th August 2021)
  6. IOSCO to force the issue on quality of ESG data disclosure – Asset managers complain a lack of standardisation in ratings can create confusion and can raise questions about relevance, reliability and greenwashing https://www.etfstream.com/news/iosco-to-force-the-issue-on-quality-of-esg-data-disclosure/ (Accessed on 11th August 2021)
  7. IOSCO issues consultation report on ESG ratings, data providers https://www.ipe.com/news/iosco-issues-consultation-report-on-esg-ratings-data-providers/10054189.article (Accessed on 11th August 2021)
  8. IOSCO Consults on Regulation of ESG Data and Ratings Providers https://www.jdsupra.com/legalnews/iosco-consults-on-regulation-of-esg-5041851/ (Accessed on 11th August 2021)

EMAlpha Products and Services

In most Emerging Markets, information discovery is a major challenge. For example, even if global investors do show interest, how do they solve the problem of timely access to information? The world’s largest capital allocators hold USD 60 trillion and they include GPIF (Japan), GPF (Norway), ADIA (Abu Dhabi), GIC (Singapore) etc. However, only 10% of the capital gets allocated to EMs and ~90% goes to G10. The big hurdle for EMs is: Foreign investors cannot access relevant local information in a timely fashion.

Most market participants and investors from across the world realise that the low rates in G10 makes EM attractive for investors. But, a) Information access is usually a cost and time intensive process for investors, and b) In many EMs, language is a big barrier and because of multiple regional languages, there is a significant delay before news makes it to the mainstream English language. To address these issues, you need solutions like, a) Real time news collection from multiple languages and, b) Instantaneous machine translation and text analytics leading to actionable recommendations for investors.

There are further challenges such as ensuring that companies behave responsibly and that they adopt sustainable business practices. There is a need to ensure that the investors are contributing towards making the world a better place by making investment decisions which reward responsible behaviour of companies. Case in point, ESG (Environmental, Social & Governance) which is increasingly being used as a filter for investment decisions. There are other issues as well such as which data to use and a lack of a standardized framework for evaluation.

Some of these issues are too important to be postponed to a later date and it is in this regard that EMAlpha is making its contribution. EMAlpha has developed a Flexible ESG Framework Management System which is a proprietary technology that makes ESG scores framework agnostic, thus allowing for quick adaptation. In addition, the users decide what matters to them and the EMAlpha system does a classification into E, S, G and more granular categories.

EMAlpha also has solutions for Multilingual data collection and real time targeted information which are based on proprietary processes to collect relevant data across multiple markets. The coverage expands across emerging market equity, currencies and commodities and the work has also been very successful in testing the signals in some key markets for live trading strategies. This is a continuous cycle and a virtuous loop that allows for iterative improvement through AI-human feedback.

With developments in AI and technology in areas like NLP, there are considerable new possibilities to bridge the gap in information between Emerging Markets and the more Developed Markets. This is an area which is turning out to be very exciting because some of the tools mentioned were not available even a couple of years ago. This implies that the evolution in the field will only get faster as time goes on. While the Emerging Markets and the Capital Flow Conundrum is a complex one, there is now much more hope and optimism that with the usage of technology, things will only get better.

At EMAlpha, the ESG team is doing further research on why some issues like Social get more prominence as compared to others like Environmental or Governance issues. To look at specific cases in the context of ESG is a very intense yet interesting exercise and this has been an incredible learning experience for the EMAlpha Research team. The data, information and ratings are a humongous challenge for ESG and it takes time to reach to the depth of the issues as the field is evolving very quickly.

EMAlpha is making a solid contribution in tackling these challenges. EMAlpha has solutions for ESG which are practical, user friendly and although not too simplistic yet easy to use. EMAlpha has developed a Flexible ESG Framework Management System which is a proprietary technology that makes ESG scores framework agnostic, thus allowing for quick adaptation. In addition, the users decide what matters to them and the EMAlpha system does a classification into E, S, G and more granular categories.

We strongly believe that the entire ESG ecosystem requires multiple stakeholders to pull in the right direction in order to make it operational and that will be the most critically determining factor for ESG’s success in making the corporate responsibility actually work. Most importantly, the investors should view ‘E’, ‘S’ and ‘G’ individually and should not confound issues when it comes to the comprehensive ESG evaluation. It is important to understand the right reasons behind ESG investing because this bias could hurt their investment decision making and portfolio performance.

Research Team
EM Alpha LLC

For more EMAlpha Insights on Emerging Markets, please visit https://emalpha.com/insights/. To know how you can use EMAlpha’s unstructured data and ESG (Environmental, Social and Governance) solutions for better investment decisions, please email us at research@emalpha.com.

About EMAlpha:

EMAlpha, a data analytics and investment management firm focused on making Emerging Markets (EMs) more accessible to global investors and unlocking EM investing using machines. EMAlpha’s focus is on Unstructured Data as the EMs are particularly susceptible to swings in news flow driven investor sentiment. EMAlpha works on information discovery and ESG solutions for Investors in Emerging Markets, using AI and NLP tech. Our mission is: “To help increase capital flow, in terms of FDI and FPI, to Emerging Markets by lowering information barriers using AI/NLP”. EMAlpha Products help achieve both alpha and ESG solutions and the idea is to help asset allocators, asset managers, banks and hedge funds along with companies with cost and time efficient access to relevant information. We use thoroughly researched machine learning tools to track evolving sentiment specifically towards EMs and EMAlpha pays special attention to the timely measurement of news sentiment for investors as these markets can be finicky and sentiment can be capricious. Our team members have deep expertise in research and trading in multiple Emerging Markets and EMAlpha’s collaborative approach to combining machine learning tools with a fundamental approach help us understand these markets better.

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