A recent study of asset managers by the investment arm of Institutional Shareholder Services (ISS) showed that more than 12% of respondents reported heightened importance of ESG considerations in their investment decisions or stewardship activities compared to before the pandemic.
In the area of hedge funds, there has been an increased demand for ESG-integrated investments since the start of COVID-19, according to 50% of all respondents of a hedge fund survey conducted by BNP Paribas Corporate and Institutional Banking of 53 firms with combined assets under management (AUM) of at least USD 500B.
ESG criteria may have a practical purpose beyond any ethical concerns, as these criteria may be able to help avoidance of companies whose practices could signal risk. As ESG gets more traction, investment firms such as JPMorgan Chase, Wells Fargo, and Goldman Sachs have published annual reports that highlight and review their ESG approaches and the bottom-line results.
But even with more options, the need for clarity and standards on ESG has never been so important. In my opinion, there must be an enhanced effort to standardise and harmonise ESG rating metrics.
How are ESG ratings made?
ESG ratings need both quantitative and qualitative/narrative disclosures by companies in order to be calculated. And if no data is disclosed or available, companies then move to estimations.
No global standard has been defined for what is included in a given company’s ESG rating. Attempts at standardising the list of ESG topics to consider include the materiality map developed by the Sustainable Accounting Standard Board (SASB) or the reporting standards created by the Global Reporting Initiative (GRI). But most ESG rating providers have been defining their own materiality matrices to calculate their scores.
Can ESG scoring be automatically integrated?
Just this month, Morningstar equity research analysts announced they will employ a globally consistent framework to capture ESG risk across over 1,500 stocks. Analysts will identify valuation-relevant risks for each company using Sustainalytics’ ESG Risk Ratings, which measure a company’s exposure to material ESG risks, then evaluate the probability those risks materialise and the associated valuation impact. ESG rating firms such as MSCI, Sustainalytics, RepRisk, and ISS use a rules-based methodology to identify industry leaders and laggards according to their exposure to ESG risks, as well as how well they manage those risks relative to peers.
Their ESG Risk Ratings measure a company’s exposure to industry-specific material ESG risks and how well a company is managing those risks. This approach to measuring ESG risk combines the concepts of management and exposure to arrive at an assessment of ESG risk – the ESG Risk Rating – which should be comparable across all industries. But some critics of this form of approach feel it is still too subjective and too industry-specific to be relevant. This criticism is relevant when you understand that the use of the ESG ratings and underlying scores may in future inform asset allocation. How might this better automated and controlled? Perhaps adding some AI might be useful to address this?
In one example, Deutsche Börse has recently led a USD 15 million funding round in Clarity AI, a Spanish FinTech firm that uses machine learning and big data to help investors understand the societal impact of their investment portfolios. Clarity AI’s proprietary tech platform performs sustainability assessments covering more than 30,000 companies,198 countries,187 local governments and over 200,000 funds. Where companies like Cooler Future are working on an impact investment app for everyday individual users, Clarity AI has attracted a client network representing over $3 trillion of assets and funding from investors such as Kibo Ventures, Founders Fund, Seaya Ventures and Matthew Freud.
What about ESG Indices? What do they tell us about risk?
Core ESG indexing is the use of indices designed to apply ESG screening and ESG scores to recognised indices such as the S&P 500®, S&P/ASX 200, or S&P/TSX Composite. SAM, part of S&P Global, annually conducts a Corporate Sustainability Assessment, an ESG analysis of over 7,300 companies. Core ESG indices can then become actionable components of asset allocation when a fund or separately managed accounts (SMAs) provider tracks the index.
Back in 2017, the Swiss Federal Office for the Environment (FOEN) and the State Secretariat for International Finance (SIF) made it possible for all Swiss pension funds and insurance firms to measure the environmental impact of their stocks and portfolios for free. Currently, these federal bodies are testing use case with banks and asset managers. Its initial activities will be recorded in an action plan, which is due to be published in Spring 2021.
How can having a body of sustainable firms help create ESG metrics?
Creating ESG standard metrics and methodologies will be aided when there is a network of sustainable companies to analyse, which leads us to green fintech networks (GFN) of companies interested in exploring how their own technology investments can be supportive of ESG objectives. Switzerland is setting up a Green Fintech Network to help the country take advantage of the “great opportunity” presented by sustainable finance. The network has been launched by SIF alongside industry players, including green FinTech companies, universities, and consulting and law firms. Stockholm also has a Green Fintech Network that allows collaboration towards sustainability goals.
We should be curious about how ESG can provide decision-oriented information about intangible assets and non-financial risks and opportunities. More information and data from ESG data providers like SAM, combined with automation or AI tools can potentially provide a more complete picture of how to measure the long-term sustainable performance of equity and fixed income asset classes.
Singapore FinTech Festival 2020: Investor Summit
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