During the recent Climate Week in New York, Saumya Mehrotra, Associate Principal for Sustainable Investment at Qontigo, took part in a panel of experts to discuss the evolution and current challenges around ESG data.
The debate, entitled ‘ESG data – the backbone of sustainable investment decision making?’ offered a chance for various specialists from the investment community and service providers to give their viewpoints on standout issues in the landscape of corporate sustainability information.
Saumya’s intervention touched upon how ESG data is changing. Specifically, she said that amid a new generation of ESG datasets and applications, innovation can be seen both in the types of sets that are emerging but also in how they are being used.
“We are seeing an evolution in not just the datasets becoming more granular, but also more specialized,” focusing, for example, on things like biodiversity or gender, Saumya said. “The second way in which this is happening is through very interesting metrics that can add a lot of accountability to forward-looking climate strategies – through information on capex, R&D investments and even patents that a company has filed. In addition, there is innovation in terms of how the data is sourced.” She mentioned, as an example, the potential use of satellites as a novel way to source companies’ ESG data.
While more refined ESG data is available, investors’ understanding and use of ESG data in fund design is also evolving and becoming more nuanced.
“While our conversations with clients were previously about, ‘hey, can you help us improve our ESG profile?’ the question has now changed to: ‘what is your sustainable investment objective?’” Saumya said.
Investors are becoming less reliant on point-in-time, static data, and more interested in data that’s progressive and measured over time, Saumya said. Employing such forward-looking metrics could incentivize companies to set transition plans, instead of excluding from portfolios systemically important companies purely based on current or historical emissions data.
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Subscribe >Narrowing down an ESG objective
Amid the barrage of ESG data, regulation and methodologies, it is important to identify the client’s sustainable investment objective. This can often be encapsulated within three essential questions, according to Saumya. They are: Are you looking to invest in companies that are seeking to minimize harm on their own specific grounds? Are you looking for companies that are exposed to certain material risks and they are doing well to manage them? Or, finally: Are you looking at companies that are providing solutions to the global transition?’
Once an investor can narrow down their objective, they can identify the most suitable dataset and determine how it should be used in the index methodology.
Optimizing investment impact, risk and returns
ESG objectives are also now placed alongside, rather than separate from, traditional risk-return goals, Saumya said.
“You see an increased adoption of optimization as a process to balance out all of these priorities and make sure that you are getting the maximum ESG improvement in your portfolio along with your concerns around risk, return and other factors,” she told the audience.
The role of technology
Speaking at the same panel, Patricia Pina, Head of Product Research & Innovation at Clarity AI, discussed the growing treatment of ESG data by using artificial intelligence. Clarity AI is a technology company that has partnered with Qontigo to develop solutions that measure the sustainability impact of companies, through ESG metrics and frameworks such as the UN Sustainable Development Goals (SDGs).
“Natural language processing allows us to process large amounts of information in real time without human bias,” Patricia said. “We use AI to process hundreds of thousands of documents per day. We can also use machine learning to learn complex patterns.
We can clean the data and assess the reliability of data. With advanced machine learning, we can create estimation models for all our coverage gaps. So clearly, there is huge potential.”
Patricia added that one challenge in using AI is in the transparency and reporting of the processes.
“How do we address those challenges? Humans can address the limitations of AI and AI can address the limitations of humans,” she said. At Clarity AI, she explained, sustainability experts work together with data scientists to create “hybrid human interloop models.” “Our sustainability experts need to able to understand the results and then we quantify the confidence of those models.”
The horizon
To conclude, Saumya said that climate indices should look to incorporate transition-focused data in order to deploy capital toward companies that are most efficiently moving to a net-zero world.
“We need to have more accountability metrics” around transition-focused data, she said. “How climate risk is being governed, how companies are committed to science-based targets, where they are making investments, and monitoring how companies are lobbying.”
Sustainable Investment Forum North America, an annual gathering organized by Climate Action, took place on Sept. 19-25 alongside Climate Week NYC and the UN General Assembly.
