How technological innovation is reshaping the ESG data market
This article was originally written for and published by Innovando News – the online, Italian Swiss-based, innovation magazine. Click here for the original article (in Italian).
How to effectively treat environmental, social and governance issues, collectively referred to as ‘ESG’, is becoming one of the most important agendas of our time. Hence, businesses are under increasing pressure to report on their ESG impacts. The COVID-19 pandemic has starkly demonstrated the fragility of our world and its interconnectedness – further solidifying the importance of ESG issues.
Many businesses are realising the benefits of embedding ESG criteria into their core business practices. These benefits include improving baseline performance, gaining competitive advantage, reducing exposure to a range of risks, and creating long-term value. In line with this, BlackRock CEO Larry Fink detailed that “we focus on sustainability not because we’re environmentalists, but because we are capitalists and fiduciaries to our client.” Amid the COVID-19 pandemic, more than half of the ESG- linked funds, included in the S&P Global Market intelligence analysis, outperformed the S&P 500 in the first few months of 2021.
The ESG Data Landscape– Issues and Opportunities
Data and analytics are at the very core of ESG reporting, so as the demand for ESG reporting proliferates, so too does the need for high-quality data. Global spending in the ESG data market is set to reach $5 billion by 2025, up from around $1 billion in 2021. However, many companies struggle to collect and compare data on ESG progress, as well as to act on the associated risks and opportunities, due to the low degree of transparency and standardisation in ESG reporting practices. Hence, businesses have been working in silos and cannot effectively share key learnings and best practices; all of which are hindering companies’ attempts to enter the already complex space of ESG. Resultingly, paving the way for third-party ESG rating providers to enter the market; many of whom are demystifying these existing complexities.
The Promise of AI
In this expanding market, more and more third-party ESG rating providers are creating ratings based on data collected through Artificial Intelligence (AI) technologies; this tech-driven approach to data collection is providing a more transparent and objective perspective of companies’ sustainability performance. Simultaneously, redistributing the control over ESG data away from a handful of powerful financial actors.
A range of AI techniques, including sentiment analysis, relationship extraction and automatic summarisation, are being deployed to collect relevant ESG data. These examples use natural language processing (NLP) to amalgamate enormous amounts of unstructured, qualitative data from the Internet and other online sources to assign quantitative values to these qualitative datasets. In layman terms, NLP essentially judges what the world thinks about a company and translates these sentiments into analysable datasets. This is just one of the multi-faceted AI technologies that can hugely benefit the ESG data market. For example, Sensefolio uses NLP, combined with machine learning algorithms to track and assess over 30,000 companies’ ESG involvement, based on 150 ESG metrics. In a similar vein, RepRisk systematically identifies material ESG risks by using advanced machine learning to evaluate more than 500,000 documents daily.
Before AI, human analysts conducted ESG reporting, often using relatively primitive technologies, like spreadsheets, to manually collect and analyse data. However, with the sheer volume of potentially relevant information that’s out there, it simply cannot be achieved by humans alone. Thus, AI not only helps unearth relevant information from existing data sources, but also offers exciting opportunities to create new ones.
The Data Problem Revisited
AI technologies are adding transparency and standardisation to a messy data landscape so investors and other stakeholders can make informed decisions based on companies’ ESG performance. However, we must not get ahead of ourselves; the business world is far from becoming an ESG data utopia. These innovative developments are unevenly playing out across the three pillars of ESG; wherein the social and governance factors are lagging, in comparison to progress made in environmental reporting. This is because it is easier to quantify the ‘E’, than the ‘S’ and the ‘G’. Therefore, more attention needs to be paid to tech-driven reporting of social- and governance-related data.
What’s Next?
According to Larry Fink, in his 2022 annual letter to CEOs, “the next 1,000 unicorns won’t be search engines or social media companies, they’ll be sustainable, scalable innovators.” This statement broadly encapsulates the promise of AI-driven ESG rating companies. With the continuous emergence of disruptive technologies, it is anticipated that the ESG data market will grow exponentially over the next few years; this is a cause for optimism and a space very much worth watching.