As investors grapple with the complexities of carbon emissions reporting, it is becoming clear that artificial intelligence has an important role to play in improving the quality of underlying data.
The issue of reliable and consistent emissions data was highlighted last month after the $330-billion US pension fund Callisters discovered significant data problems for delaying the publication of its 2023 carbon footprint report. .
In Asia-Pacific (APAC), New Zealand Super is already considered to be using one of the most advanced environmental management practices, but even that forced it to qualify its reporting as such. Goes: “External data, and our reliance on external data providers” due to “controls in data preparation, data incompleteness, unverified data sources, and complexity when obtaining data on emissions and There are risks to the decision.”
Australian climate scientist Ben McNeill said Asian investors The first challenge for any company's emissions analysis is determining whether it is using a good data set for scope one, two, and three reporting.
“The reality is that we still don't have satisfactory data sets. It's difficult for corporates to invest the time and money to understand their carbon footprint. Even today, 80% of listed companies worldwide – that's 50,000 companies – They don't report anything.”
When it comes to scope three, which deals with companies' supply chain emissions, only 1% are reporting in any meaningful way, McNeil said. “Then when you look at the private markets, obviously nobody does that — so there's a huge gap.”
NZ Super reports that in 2022 and 2023, it was able to collect data from institutions representing around 8.4% of the fund's unlisted holdings by asset value.
Data analysis
The emergence of artificial intelligence and their ability to process complex datasets on climate impacts, thereby helping to model portfolio climate risk, is attracting the attention of large asset owners in the region. five years ago,
McNeil co-founded Emmi Solutions, a technology firm focused on helping financial institutions understand how future carbon constraints will translate to carbon transition risk.
“There are ways to evaluate every aspect of emissions data and by using different machine learning techniques, we can refine which carbon footprint models work best,” he said.
Michael Wyrish
Vision Super
Spirit of Australia uses Super Emmi to analyze their private markets exposure, including infrastructure assets and real estate.
“We analyze how this translates into portfolio risk, taking financial data from their investments and projecting future climate scenarios,” McNeil said.
“We can give them different outcomes for a 1.5 degree world, or 2 degrees, or 4. That will allow them to take action to protect their portfolio.”
Reporting Objectives
Michael Verish, CIO of Vision Super said Asian investors that their investment team is currently investigating the use of AI to improve their carbon footprint reporting.
“One problem that is very difficult to deal with is the systematic underreporting of emissions, and that is a problem,” Wyrsch said.
A Singaporean technology firm, STACS, has established a platform that, among other things, powers the Monetary Authority of Singapore's Greenprint ESG Registry. According to managing director Benjamin Soh, advances in AI have played a major role in enhancing ESG management over the past year, enabling companies to comply with increasing ESG regulations.
Data quality is the biggest challenge, Suh said.
“When we set up, we realized there were a lot of gaps in Asia. Instead of assigning estimates or proxies, we have tried to deal with upstream companies, collecting data directly at the source. Every data point we receive is from a legitimate source.
One of the ways these technology firms plan to capture more data points is by partnering with AI expert solution providers. One such, California-based Eugenie.ai, has developed an emissions tracking platform that combines satellite images with machine and process data. AI then analyzes this data to help companies track, trace and reduce their emissions by up to 30%.
Suh said that the application of AI in sustainability efforts is expected to increase significantly.
“The magnitude of the problem is such that we need technology to help us, because we're talking about literally thousands of companies that need to do something they've never done before.”
NZ Super is closely monitoring developments, stating, “We will consider new approaches as part of reviewing and updating our next set of carbon reductions.”
¬ Haymarket Media Limited. All rights reserved.