As socially responsible investment (SRI) becomes more prevalent, investors are on the hunt for more data to feed into their analyses and help them understand the environmental and social impacts of their portfolios.
However, reporting standards vary and are not mandatory, while their results can sometimes be contradictory.
While a single standardized dataset is unlikely to emerge, several companies have sought to aid investors with innovative additional tools and technologies to make their sustainability work more powerful.
Providers such as Accern and Truvalue offer artificial intelligence technologies to help sift through hundreds of data points and spot trends emerging. A 2019 paper from French financial services giant BNP Paribas outlined how machine learning techniques were being used to provide real time analysis and quantify alignments to global targets such as the UN Sustainable Development Goals.
Geospatial data can also be a powerful input into SRI analysis.
As Dr Ben Caldecott, a director at the University of Oxford’s Sustainable Finance Programme, said in the BNP Paribas paper: “We have never been in a better position to observe assets and what is going on in listed and non-listed companies.
“Asset-level data, particularly that is secured using new geospatial datasets and machine learning, unlocks these capabilities.”
Satellite imagery can provide real-time updates on companies’ activities at their major locations, allowing investors to monitor developments at mines or other facilities independently.
The data can give a strong indication of risks such as those posed by extreme weather, as data firm RS Metrics’ ESGSignals service shows.
In an analysis of three resources companies – BHP, Rio Tinto and Alcoa – ESGSignals laid out the different exposures the firms’ locations had to wildfires and changes in rainfall, which can affect their use of water.
Overhead images can also show the development of sites over time, and give an indication of their rising or falling greenhouse gas (GHG) emissions.
These data points are not necessarily reflected in the companies’ annual sustainability reports, despite ongoing improvements to reporting standards resulting from sustained investor pressure on individual firms.
“Environmental risks for metals and mining companies are among the highest across all [industry] sectors,” RS Metric wrote in a recent case study report. “Exposure to complex and unprecedented environmental risks in this industry result from land use, waste, GHG emissions and water usage.”
Such analysis is not just focused on negative developments. Satellite data can also give an independent view on companies trying to make positive changes such as increasing investment in renewable energy or reducing emissions.
“As financial analysis becomes increasingly ‘spatial’, geospatial analysis enabled by asset level data will become a core competency for many financial analysts,” according to Dr Caldecott. “It will be part of the toolbox and an increasingly important one.”