This Week’s Tech and Tools News: Sustainable Fitch Launches ESG Ratings

ESG Investor’s weekly round-up of news on technology and tools in the sustainable investing sector, including Sustainable Fitch, MSCI, Insig AI and the Science Based Targets initiative.

Credit ratings agency Fitch Group has launched a new business line, Sustainable Fitch, which will offer “a comprehensive range” of ESG ratings products, at both entity and instrument level, and across asset classes. Sustainable Fitch’s ESG Ratings coverage will initially be focused on the ESG-labelled market, extending eventually to the entire fixed income investable universe. The new business will be headed by Andrew Steel, Fitch’s Global Group Head of Sustainable Finance. According to Fitch, the new ratings are backed by clear methodologies, with source data derived using the same “trusted principles and platforms” that underpin its credit ratings, providing an objective, full assessment of ESG performance at entity, instrument and framework level. The announcement follows the 2019 launch of Fitch Ratings ESG Relevance Scores, which highlight the impact of ESG factors on credit rating decisions and are now maintained on over 10,500 issuers and transactions. Sustainable Fitch’s capabilities will include: ESG-integrated credit research and analysis via existing ESG Relevance Scores; climate risk assessment through its existing Climate Vulnerability Scores; pure ESG analysis and reports via the new ESG Ratings; and ongoing sector/thematic ESG research. “Investors want transparent, cross comparable ESG ratings that look beyond labelling or targets to assess ESG fundamentals,” said Steel. “Sustainable Fitch will provide investors with best-in-class ESG Ratings, supported by data and analysis backed by the key tenets of consistency, comparability, coverage and granularity.”

Data, analytics and research services provider MSCI has introduced an Implied Temperature Rise solution, designed to equip investors globally with data to map how companies in their investment portfolios are aligning with global temperature targets. The company-level dataset will cover nearly 10,000 publicly listed companies based on the MSCI ACWI Investable Market Index. Used alongside MSCI’s Target Scorecard, a framework to assess companies’ decarbonisation and net-zero climate targets, the firm says its analytical tools will help investors strengthen their engagement on climate risk and navigate the transition to a net-zero world. To enable investors to analyse the pace at which companies are transitioning, the solution captures both 2°C and 1.5°C limits. MSCI’s Temperature Rise solution converts current and projected greenhouse gas emissions, taking into consideration emissions reduction targets, of each company to an estimated rise in global temperature. Projections are calculated by comparing those projected emissions with the global carbon budget that remains if the planet is to keep temperature rise this century below 2°C, a benchmark also linked to MSCI’s quarterly Net-Zero Tracker.

Insig AIa provider of machine learning solutions for asset managers, has launched Insig ESG, a new tool to help investors develop proprietary and best practice ESG strategies. The firm says Insig ESG combines machine learning with the analytical tools to “surface, visualise and compare” ESG disclosures across a vast library of company published reports, including 10-Ks, annual reports, earnings call transcripts and ESG/sustainability reports. Insig AI has developed 15 individual machine learning models to find evidence of disclosure across a comprehensive range of corporate sustainability issues. These are built on Insig AI’s ESG framework that maps directly to standards such as SASB, TCFD, GRI, and the structures used by ratings agencies such as S&P and MSCI. Noting issues with the scope, timeliness and granularity of ESG data and ratings, Insig AI says the Insig ESG product framework will provide: transparency and ability to drill down to a sentence or metric; speed of analysis across multiple document types, at any volume; and ability to ingest and analyse private and public company data. “Insig ESG combines the best machine learning technology with the highest standards of ESG. We’re not aware of any other provider that now offers this capability,” said Diana Rose, Director of ESG, Insig AI.

The Science Based Targets initiative (SBTi) will launch Version 1.0 of its Net-Zero Standard on 28 October, following a public consultation from 20 September to 6 October. The new standard is designed to provide companies with a framework to guide their long-term decarbonisation strategy, and is expected to be of particular value to firms in capital-intensive sectors with long-life assets and 30-year investment horizons. SBTi, the global body enabling businesses to set emissions reduction targets in line with climate science, had previously focused on helping firms set interim targets, for five to ten years, for example. The new standard was developed in consultation with SBTI’s Expert Advisory Group and has been road-tested over the summer by more than 80 companies. “This consultation aims to collect input from external stakeholders on the clarity of the Net-Zero Standard materials, understand and build support for the SBTi’s future direction, and identify areas of improvement,” SBTi said.

The practical information hub for asset owners looking to invest successfully and sustainably for the long term. As best practice evolves, we will share the news, insights and data to guide asset owners on their individual journey to ESG integration.

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