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esg data sources, integrating ESG

Vast and Deep, Firms Need to Make Choices on ESG Data Sources

Financial services firms looking to comply with environmental, social and corporate governance (ESG) standards are encountering a number of ESG data challenges. They need a variety of different data points, multiple ESG data sources for those data points where available, and their own analytical capability to digest that data.

ESG data points that companies report increasingly go beyond basic compliance. These now include forward-looking metrics such as temperature increases, alignment with net-zero emissions, carbon management practices, “green” revenues and more, according to Gerrit Ledderhof, a responsible investment manager at Aegon Asset Management in the Netherlands.

Aegon Asset Management uses two primary vendors of ESG data, to get a diversity of opinion. “We are looking at balancing our need for data with the different types of data available,” says Ledderhof. “New types of data solutions are making use of new market data sources, non-financial data, and AI-based approaches. It’s a really innovative space and really growing. We see the value but have to figure out how to bring that into our process.”

Other specialized data points include activity data and emerging regulatory standards, he adds. “These will require more collaboration between reporting companies, data vendors and users, ultimately generating more insight,” says Ledderhof.

After bringing in data that Aegon Asset Management finds is necessary or useful, the company adds its own “active, internal house view,” he adds. The components of this information can sometimes come from different vendors or the same vendor, but is used to build a holistic view. The end result is that Aegon Asset Management can serve client needs to measure greenhouse gas emissions related to their holdings, for example, to name just one metric. From that data, Aegon Asset Management can then produce its own in-house assessments to support its investment process.

Other approaches to ESG data sources

Investment firms can choose to be selective about what data they need to tackle the ESG data challenges for their investment processes. They can do this by setting up use cases to determine what data and what data quality is required. A firm that regularly buys a lot of market data, and has done so for many years, will need to see value to be convinced to add new ESG data sources.

Firmer definitions of what ESG data is and what standards are required for ESG disclosures are creating a new category of data, however. The EU put Sustainable Finance Disclosure Regulation (SFDR) into effect last March, and the US Congress and SEC are beginning to take steps on ESG disclosure rules. Investment firms’ clients are going to be asking them for all that new ESG data. To meet that demand, these firms will most likely need to buy data rather than creating it through their own work.

When breaking down what data is available about areas relevant to ESG that previously were never considered, sourcing and standards can be vague. For instance, data on greenhouse gas emissions in emerging markets is often just estimates. One way to pinpoint such data more accurately is to start with company reporting. With companies’ reports of such data in hand, a data service provider can compare that measured, concrete information to emissions information that is just estimated, and get a sense of its accuracy or lack thereof. Data on environmental phenomena, such as water scarcity or biodiversity, has to be further interpreted and translated to measure how ecosystems are being affected by companies’ actions.

Quantifying a social issue like human rights requires information from sources like NGOs (non-governmental organizations). Investors looking to assess company policies on such social issues need data measures of their impact. Investment firms may need to develop their own key impact indicator data to assess ESG compliance in social reform aspects. There are also structural or operational challenges with ESG data and reporting, as we’ve previously covered, such as transparency, measurement, formatting and reliability.

With all these issues in play, the financial services industry has a lot of work to do in the next few years to get a handle on ESG data challenges.

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