The research team wanted to incorporate carbon data into an in-house ESG scoring system to support portfolio screening, monitoring, and optimization. This would initially focus on equities and then branch into fixed income holdings. A review of a number of data providers showed a lack of coverage and granularity, especially for Chinese A share companies. The team wanted to find a provider that could offer:
Deep knowledge and insights on climate analytics and industry best practices among global asset managers in decarbonizing portfolio emissions.
Comprehensive environmental data with both depth and breadth, including a variety of metrics on company carbon emissions and intensities.
Transparency to understand how data is collected, cleaned, and used in models.
Strong client support to address technical questions and ensure smooth onboarding and integration of the data, as climate risk analytics is complex and often involves sophisticated methodologies.
Robust analytical tools and reporting with both desktop and data feed options.
The research team had heard about the wide-ranging work that S&P Global Sustainable1 (“Sustainable1”) was doing with respect to climate risks and opportunities and contacted its specialists to learn more about the capabilities.
Sustainable1 represents S&P Global's integrated sustainability offerings. This includes Trucost, the data and analytics engine that powers many of S&P Global’s ESG solutions. Trucost assesses risks relating to climate change, natural resource constraints, and broader ESG factors through a complete environmental performance profile encompassing carbon emissions and other pollutant impacts, water use, natural resource dependency, and waste disposal to inform investment decision-making and power investment benchmarks. Sustainable1 discussed numerous capabilities that would enable the research team to:
|Evaluate carbon footprints to score companies||
Trucost Environmental Data contains information on over 16,000 companies, covering Scope 1, 2, and 3 with metrics on quantities and intensities of carbon-equivalent emissions (tCO2e, tCO2e/US$ revenues) and their estimated damage cost equivalents (US$), along with impact ratios. It includes sector revenue data that gives revenues and percentages of company revenues derived from each of 464 business sectors. Data goes back to 2005, where available.
|Access data as needed||
The powerful S&P Capital IQ Pro platform brings together an unrivaled breadth and depth of data, news, and research, combined with tech-forward productivity tools. This is complemented with XpressfeedTM that automates the download and management of data, enabling delivery as needed in a ready-to-query relational database to link to internal applications.
Members of the research team were impressed with the extent of the offering by S&P Sustainable1. In particular, the teams saw value in having:
A one-stop solution to address the firm’s many ESG needs.
Comprehensive and standardized global environmental information, plus a well-tested methodology to estimate the carbon intensity of non-reporting firms.
Transparency to understand the inner workings of data collection and adjustment methodologies.
Access to seasoned ESG specialists familiar with scoring methodologies who can address important questions as the firm develops its in-house capabilities, along with a locally-based support team.
Streamlined workflows with quick access to data via a desktop solution and easy integration with internal applications using a powerful data feed solution.
The research team subscribed to the solution sets that were described to support its portfolio optimization goals, reporting requirements, and overall corporate growth strategy. As the firm looks to the future, it will be possible to expand the analysis by drawing on many other Sustainable1 capabilities to look at the physical risks faced by companies, their vulnerability to potential carbon price increases, and how today’s high emitters may look much better in the future as they pursue their journeys to net zero.
Click here to explore some of the datasets and solutions used in this case study.