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Linking Climate Transition Risks and Credit Risks


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Linking Climate Transition Risks and Credit Risks

The impact of climate change on our planet remains a major concern for the wellbeing of future generations. Many policymakers around the world continue to push forward with plans to try and achieve a net-zero carbon economy. At the same time, we are seeing industry-led initiatives, such as the Task Force on Climate-related Financial Disclosures (TCFD) and the International Capital Market Association’s Green Bond Principles, the latter aiming to stimulate investment in funds and companies with greener credentials. A sharper focus on climate-related issues since the 2015 Paris Agreement has been further strengthened by growing consumer awareness, increased returns on environmental, social, and governance (ESG) funds,[1] and new proposed regulations, such as those outlined in the EU taxonomy for sustainable activities.[2]

There are two types of business risks posed by climate change: (1) Transition risks that are based on steps taken by governments and other organizations to help alleviate climate change and transition to a low carbon economy, such as carbon taxes, and (2) Physical risks that are the result of events such as hurricanes and droughts that can have a negative impact on businesses and the overall economy. Looking at transition risks, investors will need to understand how this might impact the credit strength of companies in their portfolios, while companies directly exposed to these risks will need to take steps to measure and mitigate the financial impact to their businesses.

Analysing Transition Risks

An important challenge with measuring transition risk is the difficulty in linking climate-related risks and credit risk. ‘What-if’ scenario analysis is a technique that is widely accepted amongst industry practitioners to assess multiple potential outcomes under different assumptions about the future. This has long been a staple of financial institution workflows and supported by regulatory authorities, including the Bank of England and the European Central Bank. These organizations are actively requiring that climate-related stress tests be incorporated in a financial institution’s annual stress-testing exercise.[3] While such stress tests make sense, there is still the issue of how to model the link between climate risk and credit risk.

To address this challenge, S&P Global Market Intelligence recently launched the Climate Credit Analytics suite of transition risk scenario tools (that will also expand to physical risk) based on the notion that carbon taxes will be a widely used policy lever to reduce greenhouse gas emissions, as already seen in the United Kingdom, Ireland, Australia, Chile, and Sweden.[4] Developed in conjunction with Oliver Wyman,[5] the offering includes a fundamentals-based approach focused on several energy-transition sensitive sectors. The solution set combines Oliver Wyman’s risk expertise in financial modelling/stress testing with S&P Global Market Intelligence’s granular and sector-specific data and Credit Analytics’ CreditModel™, a statistical model that generates quantitative credit scores that statistically match a credit rating by S&P Global Ratings.[6] Together the capabilities generate a detailed view of the financial impact on a firm and its credit score due to future energy-transition scenarios for thousands of public and private companies across multiple sectors globally.

A Sample Climate Scenario for a Subset of Companies

There has been debate regarding the carbon pricing levels that will be needed to reach the objectives of the Paris Agreement. An extensive piece of research undertaken by the High-Level Commission on Carbon Prices[7] concluded that, in order to achieve the targets specified in the Agreement, at a minimum the carbon price levels would need to be US$40–80 per ton of CO2 emissions (US$/tCO2) by 2020 and US$50–100/tCO2 by 2030.

Using the Climate Credit Analytics toolset, we looked at 10 large upstream oil and gas producers[8] and the distribution of changes in credit scores generated by CreditModel between 2019 and 2022, after applying the following two carbon tax scenarios:

  • US$50/tCO2 applied to all companies in the sample by 2022
  • Shock scenario of US$100/tCO2 applied to all companies in the sample by 2022.

In Figure 1 below, the blue bars represent the credit score in 2019 prior to a carbon tax being levied, while the orange and red bars forecast what the credit score would be following a carbon tax of US$50/tCO2 and US$100/tCO2, respectively. As can be seen for 2019, the best credit score for this group of companies is ‘a-’. In 2022 following the carbon tax, all companies in the sample transition to poorer levels of creditworthiness. With a carbon tax of US$50/tCO2, three out of 10 companies have a credit score of ‘b’ or below. With a carbon tax of US$100/tCO2, the number of companies in this lower credit score range (higher credit risk) doubles to six out of 10. A reduction in carbon emissions will be needed to limit the impact of these shocks.

 Figure 1. Distribution of credit scores between 2019 and 2022 after carbon taxes

Source: S&P Global Market Intelligence, as of October 8, 2020. For Illustrative purposes only.

The results indicate that the absolute level of carbon tax will have a major impact on the creditworthiness of these companies in the short term, although there are long-term implications, as well. For the companies in this subset, and in the sector more generally, investments in green technology and renewable energy will be important to help lower costs and potentially increase revenues, thereby reducing their credit risk.

To learn more about Climate Credit Analytics, get in touch

[1] “ESG Investing Shines in Market Turmoil, With Help From Big Tech”, The Wall Street Journal, May 2020,

[2] “EU taxonomy for sustainable activities”, European Commission,

[3] “Climate Change”, Bank of England,

[4] “Where Carbon is Taxed”, Carbon Tax Center,

[5] Oliver Wyman is not affiliated with S&P Global or any of its divisions.

[6] Lowercase nomenclature is used to differentiate S&P Global Market Intelligence credit model scores from the credit ratings issued by S&P Global Ratings.

[7] “Report of the High-Level Commission on Carbon Prices”, High-Level Commission on Carbon Prices, 2017, Carbon Pricing Leadership Coalition,

[8] Companies used in the analysis include: ConocoPhillips, Pioneer Natural Resources Company, Chesapeake Energy Corporation, Devon Energy Corporation, Diamondback Energy, Inc., California Resources Corporation, WPX Energy, Inc., Cimarex Energy Co., Parsley Energy, Inc., and SM Energy Company.

Learn more about Climate Credit Analytics

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