One of the main opportunities AI presents for financial oversight and regulation is analyzing large data sets and identifying new opportunities. Several research projects have explored how AI can assess climate risk cases from text, and how it can be used to track and disclose the environmental impact of supply chains.

But questions remain about its effectiveness and whether its energy use is worth the cost.

Central banks are experimenting with AI

Central banks are already exploring how AI can be used in their own work, including for understanding climate risks.

A Banque de France research note explores how AI could help estimate corporate carbon emissions and finds that it predicts carbon intensity in 69% of cases but struggles with extremes such as heavily polluting emitters. And in Vietnam, the deputy governor at the State Bank of Vietnam has said that AI could be used to improve ESG reporting.

Meanwhile, the Bank for International Settlements (BIS) has two projects in its innovation hub focused on AI use around climate: Project Gaia and Project Symbiosis. Project Gaia uses a large language model (LLM) to automatically extract climate-related indicators from publicly available reports. The objective, BIS says, is to overcome a lack of global reporting standards in order to compare information on climate-related risks. The Gaia project is still ongoing with additional use cases and “is relevant in a much broader context than climate-related data analysis,” a BIS summary of the project states.

Project Symbiosis builds on the work done in Gaia by using various machine-learning subsets like LLM, deep learning and natural language. The collaboration looks at how AI can be used to collect, interpret and calculate Scope 3 emissions, identify opportunities to reduce emissions, and use the data to match suppliers with funding sources to decarbonize the supply chain.

With 95% of financial sector emissions falling within Scope 3, the project aims “to showcase how novel technologies offer a viable technical pathway to positively impact core stakeholders . . . by reducing critical information gaps impeding the climate transition.”

The findings from the project are in line with other AI and risk work and could set the basis for more standardized emissions and help improve issues around standardizing Scope 3 calculations.

AI’s usefulness for assessing climate risk

Interest in the use of AI for climate risk mitigation goes beyond central banks.

Several projects are exploring how to apply AI to imagery data, such as satellites, and advancing multi-input models that compile data points from imagery and text together.

This includes aspects like using image segmentation to look at the carbon footprints of certain areas, or classifications based on which plants are known to grow in those areas, says Peter Schwendner, a machine-learning expert at the Zurich University of Applied Sciences.

If done with intention, and if the levers are applied in a focused manner using AI production, the impact can be really, really meaningful and positive.

 – Mattia Romani, partner, Systemiq

From a regulatory perspective, he says, such AI use is “about improving market transparency, and then the financial market should improve the asset allocation with the objective of allocating more capital to, say, sustainable assets. This should work both in investing and in lending.”

It’s exactly the type of project that spaceborne AI firm Kuva Space hopes to expand on. The Finnish company has partnered with WWF Indonesia to explore how AI can be applied to hyperspectral imaging to understand changes to the region’s coastal ecosystem.

Hyperspectral imaging uses advanced satellite cameras to capture images in areas that are often difficult to reach. Kuva Space’s AI system is able to signal potential changes or anomalies, such as changes in the status of seagrass, an important marine carbon store, which can then be confirmed by scientists on the ground.

While the program is in a pilot stage, the project could have a larger impact for not only tracking ecosystems; it could also help regulators and investors identify and track project areas for sectors like blue carbon.

Investors and regulators are asking for this information, but they don’t have it, says Malathy Eskola, commercial director at Kuva Space. “We’re actually going to be making it more science-based or evidence-based, and provide that information so that the decision-makers can be confident.”

Needed: better data (and more of it)

But for AI to be truly effective in understanding climate risk and nature loss, more data is needed, especially from companies, Schwendner says.

Companies themselves do not need to crunch the numbers or create the models, but they do need to provide the raw data for analysis. “Academics and data providers are very eager to work with this data, so I don’t think it’s necessary for the public to invest a lot here,” he says. “This can be done by, say, collaborations between scientists and data providers, but the raw data on the company’s operations needs to be available.” 

This includes information such as which companies are sourcing raw materials, at what volumes and from which locations. “At the moment, we only know this in very rough terms, and we need to know exact numbers . . . If we know that, and if we know the production volumes, if we know the energy, where it comes from at this local production facility, then we can estimate . . . the environmental consequences. Then we can estimate the climate impact.”

While more data was expected this year as a result of the European Union’s climate disclosure rules, the bloc’s sustainable omnibus measures have meant there may be less information available than anticipated.

Will AI be positive or negative for the environment?

The other burning question around using AI to mitigate climate-change risk is whether it’s worth the energy use and environmental impacts.

AI consumes a lot of energy and water, and those working on AI projects in the climate space are aware of the contradiction in using something for environmental aims that itself uses a lot of natural resources.

The biggest issue with AI consumption, experts say, is the type of models being used and how they are being applied. Training models requires a lot of energy, increasing the electricity demand for data centres. It accounted for 1.5% of all demand in 2024, but is projected to account for 10% of energy demand growth by 2030.

Even researchers from the BIS innovation hub noted in their report on Project Symbiosis that “any use of AI is likely to generate significant emissions, even as electricity grids worldwide continue to slowly decarbonise at different paces.”

But some say AI could have a positive environmental impact.

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A study from the London School of Economics finds that AI could reduce global emissions by 3.2 to 5.4 billion tonnes of carbon dioxide equivalent by 2035 if applied in key areas such as innovating resource efficiency, nudging behavioural change, modelling climate and policy system interventions, and managing resilience and adaptation. “If done with intention, and if the levers are applied in a focused manner using AI production, the impact can be really, really meaningful and positive,” says Mattia Romani, a partner at Systemiq and one of the authors of the report.

AI could also be used to help streamline the collection and accessibility of company data. There is an issue around responsible data sharing, Romani says, which is where regulators can step in to ensure safe data practices to “enable private actors to contribute data without risking a competitive or legal exposure.”

If AI is used for practical applications like emissions reductions, then its intentional use could justify the added cost of energy, Romani says. “If you continue to use AI to sell you more stuff on Instagram, then the emissions associated with the additional power, I’m afraid, are going to be substantial.”

Moriah Costa is an award-winning U.S. journalist based in Paris.

This article was originally published by Green Central Banking. It has been edited to conform with Corporate Knights style. View the original here. 

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To Waller, a governor of the Federal Reserve that sets U.S. monetary policy, glacial growth is proof that the Fed’s efforts to tame inflation are working. “Our goal is to rein in demand,” he said, noting that the Fed’s higher interest rates had already dampened consumer spending, slowed home sales and shaken up the tight job market. By mid-2022, the labour shortage had driven annual wage growth above 10% for the first time in 40 years.

Canada has shown similar steel as the annual inflation rate jumped from 1% in early 2021 to 8% by mid-2022. The Bank of Canada hiked interest rates seven times last year: a harsh reality for anyone who recently took out a mortgage with a variable interest rate. Yes, high rates halted the red-hot housing market, but with mortgage costs doubling, fewer Canadians can now afford to own their own homes.

In the United States, activist group Accountable.US has labelled the inflation battle a war on workers. “Apparently, millions of Americans likely losing their jobs under further rate hikes is a sacrifice the Fed is willing to make,” noted Accountable.US spokesperson Liz Zelnick in November. The former policy analyst for the Massachusetts Treasurer’s Office blames runaway inflation on companies taking advantage of COVID and supply chain chaos to hike prices way beyond normal levels. Indeed, by mid-2022, U.S. companies’ gross profit margins rose to 15.5%, a 72-year high.

“The Fed’s ill-advised policy only draws attention from the real culprit behind out-of-control costs: corporate greed,” said Zelnick. “Highly profitable corporations have kept raising prices on working families while rewarding wealthy investors with billions in new handouts.”

It’s not just activist groups saying so. In September, a number of speakers took turns accusing businesses of price gouging at a congressional hearing on “corporate influence on inflation.” The best known was former U.S. labour secretary Robert Reich, who said wages have lagged inflation for more than a decade. Reich said businesses are “raising their prices above increases in their costs.”

And those prices stick, he said, because most businesses “face so little competition. Since the 1980s, two-thirds of all American industries have become more concentrated.”

Reich urged Congress to adopt a windfall profits tax – and beef up antitrust enforcement to discourage unnecessary price increases, concluding that “the major effect of interest-rate hikes is to depress wages and eliminate jobs.”

Apparently, millions of Americans likely losing their jobs under further rate hikes is a sacrifice the Fed is willing to make.

-Liz ZelnickAccountable.US spokesperson

Canadians face similar pressures, but the inflation-relief debate is mostly missing. At the Conference Board of Canada, a leading economic policy think tank, chief economist Pedro Antunes says he supports the Bank of Canada’s anti-inflation medicine. He says the central bank reacted too slowly when inflation began creeping above its 2% inflation target in early 2021. “Inflation was eating away at our purchasing power, because there wasn’t enough production to meet demand.” With the central banks using a fiscal firehose to cool things down, Antunes believes the hard part is now over. The Conference Board now forecasts inflation will hit 3.8% in 2023 before settling around 2.2% in 2024.

Antunes is loath to address business profiteering. He says corporate profits are usually a percentage of sales – meaning that if prices are on the rise, you can expect higher profits than normal.

Not so sanguine is Sheila Block, senior economist with the Canadian Centre for Policy Alternatives. She agrees the inflation wave had many drivers – from COVID to Russia’s invasion of Ukraine – but insists that wage costs have not been to blame. She also notes that corporate profits rose from 12.5% of GDP in 2019 to 16.8% in mid-2022 – near their historic highs. She says Canada’s inflation problem stems not from excess consumer demand, but from a “perfect storm” of international issues and business opportunism.

“I don’t think the Bank of Canada is operating on any ill will,” she says, “but its policies are compounding the negative impacts of inflation.”

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Australia is the latest country to move forward with climate stress tests. It follows the lead of the Bank of England, which released a detailed discussion paper in December outlining how it intends to run its own tests on banks and insurers.

Canada’s financial industry should take notice. The Bank of Canada announced last year that it intends to run climate stress tests in the future – although when exactly, we don’t know. What could Canadian banks and insurers expect?

We can look to the UK to get an idea.

The UK’s proposed scenarios are by far the most detailed of any central bank and provide important insights into how financial regulators view climate risk. The goal of the UK climate stress test is to understand the financial exposure of banks and insurers to climate-related risks. The test covers both physical risks, such as droughts, floods and extreme weather events, and transition risks, such as sharp increases in carbon prices or changes in unemployment or corporate bond yields resulting from market or technological disruptions.

The Bank of England’s framework consists of three scenarios. The first two involve pathways whereby the world, over a 30-year period, reduces greenhouse gas emissions to limit global warming to below 2C.

The first scenario is an orderly one, where government policies move in a clear direction and firms have time to adapt and manage the transition.

The second scenario is “late policy action.” After a decade of delay, governments are compelled to act. They rapidly implement sweeping policy changes in an effort to dramatically reduce emissions. Asset prices see a sudden, sharp re-pricing.

In the third scenario, the world fails to take steps to limit warming below 2C, resulting in devastating impacts: extreme heat, droughts, floods, forest fires and storms at a level we have not seen before, all with horrific implications for the health and well-being of our economy and natural environment.

UK banks and insurers must run their balance sheets through the lens of each scenario, assess its financial impact and aggregate it across their various portfolios. Following the first phase, the Bank of England will look for areas where banks and insurers diverge in their forecasts and go back to them with adjusted information. If insurers disclose that they expect to phase out certain types of insurance, for example, banks need to revise their lending plans accordingly.

There are also qualitative aspects to the stress test. Participants need to outline what management actions they would take to mitigate risk and position their businesses to thrive in the transition to a carbon-neutral economy. The stress test recommends that companies use the Task Force on Climate-related Financial Disclosures (TCFD) framework to explain how climate change will affect them.

Climate scenarios can’t be predicted based on historical patterns; they are constantly evolving, and there is no one “right” answer. Evaluating the disclosure of climate risks is challenging because businesses often use different data sets.

The Bank of England aims to overcome this barrier by laying out scenarios with specific data points, allowing for a much closer apples-to-apples comparison. The direct nature of the stress test means firms are forced to confront – and disclose – what extreme but plausible climate scenarios could mean for their balance sheets, making it easier for the Bank of England to identify systemic risk.

As the bank’s governor, Mark Carney, said at the launch of the COP26 Private Finance Agenda this week, corporate disclosures need to move beyond the static (current emissions) to the strategic (plans to reduce emissions).

As pressure builds on businesses to disclose what they’re doing about climate change, the UK’s stress test provides a glimpse into the types of climate-risk questions Canadian banks and insurers need to be able to answer. Canada’s economy is far more carbon-intensive than most, and scrutiny from investors and regulators about climate risk is only going to grow.

Companies that can articulate how their business models will support – and thrive – in a low-carbon economy will prosper. Those that can’t coherently explain their plans for a climate-adjusted future can expect to be punished by investors.

In a research note on climate change published in November, the Bank of Canada said its first step is to evaluate the exposures of Canadian financial institutions to climate-related risks. The Bank of England is sharing its stress test findings with the Network for Greening the Financial System – of which the Bank of Canada is a member. There’s no reason Canada’s banks and insurers can’t get ahead of the curve.

It’s not a matter of if, but when: climate stress tests are coming to Canada. For banks that want to demonstrate leadership and understand what climate change could mean for them, the UK’s climate stress test is a good place to start.

Kevin Quinlan is a senior advisor with Mantle314, a Toronto-based climate change consulting firm.

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