This carbon metric has become a firm favourite across the banking industry
Carbon intensity is a tool popular with climate-conscious banks. What is it and how are firms using it?
Climate risk reports are growing up. The latest wave issued by banks based on the Task Force on Climate-related Financial Disclosures (TCFD) recommendations are far more sophisticated and detailed than those published even a year before. The furtive, faltering, early attempts, in which climate disclosures made up a single page, or just a few paragraphs, of annual reports have given way (at least in some quarters) to expansive documents brimming with data and statistics.
Barclays’ ESG reports exemplify the shift. In 2018, the TCFD segment was six pages long. This year’s edition spreads to 24 pages and, unlike last year, contains a wealth of information in the “metrics” section — a pillar of TCFD sorely neglected by many signed-up supporters. Analysis by BCS Consulting last year found just 31% of lenders were making advanced disclosures on the carbon impact of their banking services.
Barclays’ 2019 carbon metrics are worth digging into. The firm lays out its greenhouse gas (GHG) emissions by scope, and separately the emissions it finances through its loan book and debt and equity underwriting. It also offers a breakdown of its carbon-related assets, as per the TCFD guidelines, alongside a more comprehensive, sector-by-sector calculation of assets subject to “elevated carbon risk”.
One metric the company is especially focused on is carbon intensity. This indicator will be used to gauge the banks’ success at “steering” its loan portfolio to net zero emissions by 2050. As a first step, it’s pledging to reduce the intensity of its energy and power portfolios by 15% and 30%, respectively, by 2025. Furthermore, the bank will only lend to certain fossil fuel firms “who have projects to reduce materially their overall emissions intensity”.
Barclays isn’t the only firm making carbon intensity its lodestar to the Paris Agreement. UK rival HSBC has also put this front and centre of its transition strategy. Singapore’s DBS uses it, too. Like many climate change-related metrics, though, carbon intensity means different things to different entities — and its utility as a climate risk management tool is up for debate.
At its simplest, carbon intensity is calculated as the CO2 emission rate relative to the intensity of a specific activity. In relation to energy utilities, it could be expressed as Kg CO2/kilowatt hour (kWh). Applied to residential mortgages, it could be Kg CO2/m2 of each home.
It’s a subtler metric than absolute carbon emissions as it allows a bank to distinguish between clients within the same sector on their energy efficiency and allocate funds accordingly. For example, two energy utilities may produce the same absolute carbon emissions each year, but if one generated far more kilowatt hours than the other than their carbon intensity measures would differ.
A carbon-conscious bank can use intensity data as a jumping off point for client engagements and to set targets — as Barclays has. Those clients with poor carbon intensity “scores” could even be selected for sustainability-linked products that offer discounts if they improve on them each year.
Another version of the carbon intensity metric is expressed as Kg CO2/dollar millions of revenue. This provides a measure of how “dirty” a client’s cash flows are and as such can be used as a crude gauge of transition risk.
Right now, a low price is assigned to CO2 emissions through either direct taxes or cap-and-trade programs. A New York Times survey of carbon taxes found that “most countries have found it politically difficult to set prices that are high enough to spur truly deep reductions.”
But this could — and should — change as governments step up efforts to honour the Paris Agreement, meaning far higher prices on carbon may be on their way. Knowing how dirty their clients’ revenues are today offers banks a means of staying ahead of the transition curve tomorrow.
Internal climate stress tests show how this can work in practice. In its latest sustainability report, Singapore’s DBS laid out a transition stress test “focused on potential credit risk arising from climate-related factors”.
The test featured three transition scenarios covering a high, medium and low carbon price. These were applied to a sample of 368 companies analysed through its existing credit risk models “to evaluate their potential credit deterioration arising from the impact of higher carbon costs on their cash flows”.
What DBS found was that those carbon-intensive clients unable to pass the increased costs projected by the scenarios on to their own customers were most vulnerable to transition risk. Of the 368 test subject, 16% were estimated to incur a credit rating downgrade of at least one notch in a higher carbon cost environment.
Third-party vendors offer similar analysis to investors. Trucost, part of S&P Global, identifies those investments most exposed to a ramp up of carbon prices. It uses a suite of carbon pricing scenarios to set the parameters for sector-level carbon prices and, in doing so, the difference between the carbon price paid today and the likely price to be paid in future years.
No silver bullet
But the carbon intensity metric falls short in some respects as a credit risk management tool.
First of all, the way it is measured matters. For example, HSBC has used the Carbon Disclosure Project’s (CDP) data to generate carbon intensity ratios for its clients. This relies on reported emissions data from signed-up companies and estimates calculated by the CDP themselves.
Source: HSBC ESG report 2019. Customer responses to CDP have been used to formulate the carbon intensity metrics. The carbon intensity ratio is calculated by CDP using both reported figures and estimated data. Carbon emissions are measured in tonnes of carbon dioxide equivalent (tCO2e) and revenue is measured in millions of US dollars.
If a specific client isn’t self-reporting to the CDP, its carbon intensity is essentially extrapolated using available data and statistical models. The resulting figures are the result of sound analysis, but are still estimates. As the world learned from the abominable example of Volkswagen, trusting company’s self-reported data and estimates based thereupon could lead to false conclusions. In addition, it can be exceedingly difficult for many firms to get in-depth information on the carbon intensity of their own suppliers, which must also be factored in to get an accurate carbon intensity “score”.
Second of all, the revenue-based carbon intensity metric may be too one-dimensional to base credit risk decisions on. In a high carbon price environment, those companies with high carbon intensities but chunky profit margins may be able to absorb the extra costs without endangering their creditworthiness (expressed as a probability-of-default), while those with razor-thin margins may be knocked out even if they have a low carbon intensity.
Furthermore, a bank’s exposure-at-default (EAD) is typically calculated net of collateral. But what if the value of that collateral is also affected by carbon pricing? Take the example of a loan to a US shale producer backed by hydrocarbon reserves. In an extreme transition scenario, not only could this producer default on its loans because of a higher carbon prices, the underlying collateral could simultaneously lose value as it turns into a “stranded asset”. In this situation, the firm’s EAD would explode.
Put simply, a basic carbon intensity metric could drastically underestimate some credit exposures while overestimating others.
Then there’s the question as to whether steering a portfolio using carbon intensity is best for the planet. Imagine a power plant that in year one produced one million kilowatt hours at an average CO2 emission rate of 0.4483 kgs per kWh (the US average). It would have emitted 448,300 kgs, or 494 US tons. But what if in year two it finds a way to reduce its emission rate by 15% (good for its carbon intensity metric) but then goes on to produce 1.2 million kWh? Its total emissions for that year would be 504 tons — more than in its less energy efficient year.
Hypotheticals like this underline the dangers of solely relying on carbon intensity to inform credit risk and as a means of measuring a lender’s overall carbon footprint.
What’s encouraging is that no-one appears to be going down this route. TCFD recommendations themselves say that firms should disclose the metrics they use to assess climate related risks, but also all scope 1, 2, and 3 GHG emissions, allowing for an absolute carbon footprint to be calculated.
Climate risk analysis should be detailed, the emissions profile of each client captured using a range of metrics, and never should too much faith be placed in one single measure. Wizened financiers remember how over reliance on the Gaussian copula model contributed to the wild mispricing of structured products that later blew up in the financial crisis.
Furthermore, trumpeting a single metric such as carbon intensity is not the same as managing climate-related risk. Each company has to use their respective measures as a map for the long road to a low-carbon future. But knowing the road and walking it are two different things.
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