AI Tools Can Tackle Opaque ESG Data

Bridgewise’s AI-powered analysis toolkit adds to technologies addressing unstructured data, amid ever-growing reporting requirements. 

Industry experts have highlighted the key role that artificial intelligence (AI) tools can play in consolidating and enhancing ESG data, despite governance concerns marring the technology. 

According to estimates, up to 90% of data generated globally each day – including on sustainable finance – is unstructured. This remains an endemic issue across the industry. 

“AI can process and analyse vast amounts of this unstructured data from different sources,” Ilan Furman, CIO at AI-based technological research company Bridgewise, told ESG Investor. “It has the ability to identify patterns and provide actionable insights for investors.” 

Bridgewise is one of an increasing number of companies developing AI-powered tools to assist investors in navigating disorganised, and often limited, publicly available ESG data. 

One such tool is the International Financial Corporation’s AI-powered MALENA, released earlier this week. The platform aims to enhance ESG analysis for emerging markets through the use of 15 years’ worth of emerging markets data and natural language processing, refining unstructured information into “actionable” sustainable investments insights. 

Last October, Bridgewise launched an AI-powered ESG analysis toolkit aiming to support growing market demand for such products. The group said its goal was to help financial institutions easily identify ESG-friendly companies, evaluate investments, and remain compliant with regulatory requirements. 

“The capability to measure ESG and the data around it is quite opaque,” said Furman. “In general, AI-powered tools are trying to add transparency to this data.”

Bridgewise’s toolkit covers 16,000 stocks worldwide, and serves an estimated two million users. The company deploys algorithms to provide insights on 44,000 public companies globally, and generates research reports to fill what it describes as an “information gap” on companies’ ESG commitments. Its algorithms consolidate ESG data into a single rating, comprising 26 ESG factors. 

Tool proliferation 

Berlin-based software firm Briink’s CEO Tomas van der Heijden previously told ESG Investor that mistrust and lack of comprehension of AI technologies were likely the root cause of hesitancy around the technology’s adoption. 

This lack of trust is perhaps most visible when it comes to AI governance. The topic was by far the most discussed at Davos last month, with roughly half of the world’s politicians expressing concerns over the technology’s ability to warp election outcomes over the next 12 months. Additionally, almost all CEOs attending the conference expressed fears of being outflanked if they didn’t adopt the technology quickly or effectively enough.  

Notwithstanding those views, the use of AI is already widespread, as illustrated in a recent McKinsey survey, which found that 79% of respondents had had some sort of exposure to generative AI, and 22% were regularly using it in their work. 

“An increasing amount of people are interested in or required to demonstrate their ESG credentials – hence the increasing demand for tools that can help with this,” said Furman. 

According to research by IT firm Infosys, AI should add an estimated US$14 trillion in gross value to corporations by 2035. Meanwhile, Goldman Sachs claims that the global GDP could increase by 7% between now and 2033 thanks to generative AI. 

“Another driver behind the rise in demand for AI-powered tools is heightened awareness of the need to implement ESG principles,” said Furman. “It’s also the massive flow of funds we are seeing being managed under various ESG umbrellas, which is also triggering demand.” 

Many companies in the sustainable investment space have already incorporated AI tools into their practices. Similar to Bridgewise’s toolkit, Manifest Climate’s recently launch risk-planning solution software uses AI to extract and analyse data from public company disclosures.  

Last May, Net Purpose – a data analytics platform for impact investors – used part of its US$11 million Series-A funding round to enhance its use of AI. The platform aimed to address the proliferation of sustainability data, which has created confusion for users of ESG ratings and given rise to greenwashing accusations. 

Elsewhere, Iceberg Data Lab launched generative AI-powered tool Barbatus last July, which it described as an “AI-ESG assistant” for analysts interpreting ESG-related data, aiming to improve benchmarking and assess corporates’ environmental impact. 

“AI tools can enable ESG analysis teams increase their productivity and improve accuracy, reliability and access to relevant data,” said Iceberg CEO Matthieu Maurin. 

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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