Investors seek increasingly complex sustainability data
As sustainable investing matures and gains more prominence, efforts to provide the quantitative information to support investors’ goals are becoming more complex. Increasingly sophisticated data capabilities are needed to answer questions related to environmental impact, inclusivity and more, according to Sebastiaan Reinders, head of innovation and research at Goldman Sachs Asset Management’s Sustainable Investing and Innovation Platform.
A few years ago, data demands related to sustainable investing were more uniform, Reinders said during a panel discussion at the Goldman Sachs Global Sustainability Forum in New York. Investors may have been looking for general environmental, social, and governance (ESG) scores for a portfolio holding, for example.
It’s not that simple any longer. Clients now come with a heterogenous set of questions, Reinders explained. An institution may seek assistance from its investment manager or advisor for specific sustainable investment goals, preferences, or exclusions. They may be pursuing thematic investments with carefully defined clean energy or inclusive growth parameters.
“You need to be creative and you need to have the tools to be creative,” Reinders said. A nimble and modern data platform has become necessary to answer a growing variety of sustainability questions with reliable, quantifiable information, he said. Investors increasingly are relying on their investment managers and specialized data vendors to find the insights they are looking for.
“In our experience, you cannot buy all of those tools off the shelf yet,” Reinders said. “You have to go after it yourself and get your hands dirty.”
For example, the scarcity of reporting on companies’ biodiversity-related activities makes public equity investing in this theme challenging. GSAM has used natural language processing to examine reams of corporate communications to find companies that are taking action on biodiversity. There are signs of increasing attention to this theme: Their analysis shows that 21% of the companies in the MSCI ACWI Index mentioned biodiversity-related topics such as deforestation in their 2021 annual reports, up from 13% in 2017. The share of companies reporting an intention to take action related to biodiversity — a commitment, pledge, target or policy — or steps already taken tripled over the same period to 9%.
Put another way, investors are increasingly moving beyond sustainability reports and are seeking forward-looking datapoints, according to Brian Singer, global head of Goldman Sachs Research’s GS SUSTAIN, which hosted the event. That includes forecasting sustainability performance and considering companies’ transition plans, Singer wrote in the team’s report summarizing the forum.
“Investors noted an increasing availability of ESG-related data and rising concern surrounding separating the noise from value,” Singer wrote, adding that panelists at the GS SUSTAIN event pointed to AI as a source of alternative data on forward-looking statements. “ESG investing has shifted from a risk mitigation mindset to an opportunity mindset, highlighting the importance of material metrics.”
GS SUSTAIN’s scoring framework across more than 7,000 companies includes a product alignment framework, which is based on sustainable development goals, EU taxonomy, and Goldman Sachs analyst views. The framework “can help investors cast a wider net in the search for impact ideas aligned to less obvious sustainability themes,” Singer wrote.
How AI can be used in sustainable investing
Natural language processing has become vital to sift through large unstructured data sets. This includes volumes of text from regulatory filings, transcripts of conference calls and so on. The necessary technologies, powered by machine learning and artificial intelligence, are getting better and better at finding the information investors are looking for on various sustainability topics, Reinders said. “And then your job shifts a little bit, from searching for the information to interpreting it.”
AI is also being harnessed to accelerate key social and environmental goals, Singer wrote. More rapid drug discovery and development, as well as exponential advances in climate modelling and simulation, were among the AI-driven efforts that were in focus at the conference.
Sophisticated data capabilities are becoming valuable not just to meet sustainable investment goals but to maintain a performance edge, according to James Norman, global head of sustainable investing client strategy, Goldman Sachs Asset Management, who also spoke on the panel.
Climate change, in particular, is having an enormous impact across a wide range of assets, and there is growing interest in having climate factors incorporated into the capital markets assumptions that affect strategic asset allocation, Norman said. “Investors are spending more time on it as they find current approaches underestimate physical risk impacts and lack transparency on how models translate climate scenarios to macroeconomic factors that drive asset class return assumptions,” he said. “I think we’re going to see a lot of work come out over the next one to three years on how to do this in a more robust way.”