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Assessing Energy Transition Risks and Opportunities


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Assessing Energy Transition Risks and Opportunities

Anthropogenic greenhouse gas (GHG) emissions pose significant economic threats worldwide since ensuing climate change can increase physical risks, both short term (e.g., floods, hails, and hurricanes) and long term (e.g., rising sea levels). This can result in business disruptions and, potentially, financial losses. This may also lead to further detrimental consequences, ranging from a slowdown of a country’s economic output to increased unemployment to financial market instability.[1]

Since the Paris Agreement entered into force on November 4, 2016, 180+ parties[2] have committed to accelerate the transition to a low-carbon economy by enacting a variety of policies, such as the introduction or increase of a carbon tax penalizing firms operating in high CO2-emitting sectors.[3] These transition efforts will likely require an unprecedented level of investment over the next decades. This may contribute to the onset of a new type of financial risk that could have negative effects on a company’s financial performance by eroding liquidity needed to service short- and long-term debt commitments.

In the next few months, several major central banks and financial regulators across the world (e.g., US Federal Reserve, Bank of England, and European Central Bank) are planning to test the financial markets’ preparedness for major physical and transition risks by introducing ad-hoc scenarios to financial institutions’ annual stress-testing exercises.

While scenario analysis is routinely performed by risk managers at financial institutions and non-financial corporations, energy transition risks pose new challenges, such as longer time horizons needed for the analysis, the lack of quality company emission data, and the lack of an established quantitative approach linking energy transition risks and opportunities to credit risk.[4]

S&P Global Market Intelligence’s Climate Credit Analytics offers two innovative, automated tools that address these challenges. These tools can help financial practitioners analyse the impact of a pre-defined or user-defined carbon tax increase on a firm’s creditworthiness, or across companies and entire portfolios.

• The upstream Oil & Gas tool offers a fundamentals-driven view of how a future carbon tax increase may affect each financial item reported within company statements over the next three years. The tool, developed in consultation with Oliver & Wyman,[5] currently covers more than 1200+[6] public and private companies operating in one of the most carbon-intensive sectors (i.e., the upstream Oil & Gas industry). Users can explore the impact of global carbon tax scenarios (where the carbon tax increases by a user-defined percentage across all countries) or the integrated scenarios generated via a global energy-economy-climate model (REMIND).[7] The estimated financials can then be run via Credit Analytics’ CreditModelTM, a quantitative model generating a credit score. The score aims to statistically match S&P Global Ratings issuer credit ratings for rated companies, which can also be applied to unrated companies.[8]

• The public firms tool offers a market-driven view of how earnings of public companies may change over the next three decades under multiple carbon tax scenarios.[9] The tool leverages Trucost’s company-specific GHG emission data and accommodates pre-defined country and industry-specific carbon tax scenarios or user-defined global carbon tax scenarios. The tool calculates the change in credit score between today and a future year.

These tools can help users perform stress-testing and scenario analysis, as well as comply with the Task Force for Financial Disclosures (TCFD) recommendations. These recommendations are expected to become mandatory over the next few years for the signatories of the Principles for Responsible Investment (PRI).[10]

The Materials Sector: Public Firms Tool

Figure 1 shows the distribution of credit score changes between 2019 and 2050 for public companies within the Materials sector, one of the highest CO2-emitting sectors. We employ the public firms tool for a fast (i.e., two degrees Celsius) transition scenario, where the carbon tax rapidly increases and companies react in one of four ways:

Yellow bars: Companies keep increasing carbon emissions and do not invest in new/greener technology, but pay carbon taxes on increased emissions.

Green bars: Companies manage to meet CO2 emission reduction targets in 2050 by investing in greener technology and, thus, sustaining abatement costs in addition to carbon tax costs. Revenues include both a growth component and a cost-related component.

Amber bars: Companies maintain current (2019) levels of CO2 emissions, saving on abatement costs, but sustaining carbon tax costs. Revenues grow only in proportion to the fraction of total costs passed on to customers.

Red bars: Companies do not invest in new/greener technology and pay high carbon taxes, plus governments introduce additional policies that forcefully reduce carbon emissions (e.g., by progressively banning use of certain materials), thus leading to revenue losses on affected companies.

Fig. 1: Distribution of credit score change between 2019 and 2050, for public companies in the Materials sector over a fast transition. Please, note the semi-logarithmic scale used to zoom into the y-axis.


Source: S&P Global Market Intelligence. As of September 1, 2019. For illustrative purposes only.


Despite some of these scenarios being quite extreme or unlikely, they are still useful to obtain a sense of the potential impact of company inaction or abrupt government policies in comparison to alternative, more rational choices.

A few comments:

    1. 1. In all cases, a significant percentage of companies (up to 44%) remains with the same credit score under the fast transition. The remainder change their credit score in either direction, confirming the importance of managing risks, but also seizing opportunities over the long term.

    1. 2. In the yellow case (where emissions keep growing at a forecasted pace, and companies do not invest in new/greener technology), the distribution of score changes is skewed towards the left, due to the expected revenue growth. However, a significant number of companies may also be affected negatively, and up to 10% of firms in this sector may end up in a technical default (‘d’) if their projected market capitalization falls to zero or to a negative value by 2050. This type of scenario essentially shows the cost of inaction by companies that simply bear carbon tax costs on increasingly higher carbon emissions. It is worth noting that the technical defaults reported here are a cumulative rate over the next 30 years. For comparison purposes, the long-term average cumulative (30-year) default rate of BBB-rated companies by S&P Global Ratings is higher than 10%.[11]

    1. 3. The green case shows the advantage of investing in new/greener technology, thus reducing carbon emissions and paying a lower carbon tax, while incurring higher operating costs on new technology. In this case, the vast majority of companies (71%) will experience an improvement in their credit scores by one or more notches, while 26% will remain with the same score, and only 1% will incur a technical (cumulative) default over the next 30 years.

    1. 4. The amber case assumes companies maintain current emission levels without converting to new technology, and will pay a hefty carbon tax (over the fast transition scenario), and increase their revenues only in proportion to the fraction of costs passed to their customers. This leads to a significant distribution skew towards the right-hand side of the graph, with 38% of companies at risk of technical default.

    1. 5. The red case corresponds to an extreme situation, where companies do not convert to new technology, but have to pay an increased carbon tax. This is while governments enforce restrictive laws to curb carbon emissions (e.g., by banning the use of obsolete technology or imposing carbon emission caps), and induce revenue losses among companies in proportion to the carbon emissions reduction. In this case, the technical (cumulative) default rate over the next 30 years increases to almost 79%, with potentially severe consequences for the Materials sector and the economy as a whole.

This analysis shows the flexibility of the tool in accommodating various transition scenarios and firm behaviors, as well as the importance of striking a balance between carbon pricing policies and the actions that companies will need to take in order to adopt new technology and reduce carbon emissions.

Finally, the public firms tool enables users to gauge the impact of a scenario for each individual company, rather than on a given sector. A detailed discussion at the company level will be covered in following work.

If you would like to learn more about our climate-related tools, please visit us at

[1] “Climate Change: why it matters to the Bank of England”, Bank of England (available at: - November 1, 2019).

[2] Paris Agreement - Status of Ratification”, United Nations Climate Change, 2019,

[3] “Chapter XXVII – Environment – 7.d Paris Agreement”, United Nations (December 12, 2015).

[4] S&P Global Market Intelligence’s Trucost has recently released a new dataset on physical risks that may be included in the tool at a later stage.

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

[6] Source: S&P Global Market Intelligence. As of November 1, 2019.

[7] “Description of the REMIND model (Version 1.6)”, G. Luderer, et al. (Potsdam – November 1, 2015).

[8] S&P Global Ratings does not contribute to or participate in the creation of credit scores generated by S&P Global Market Intelligence. Lowercase nomenclature is used to differentiate S&P Global Market Intelligence PD credit model scores from the credit ratings issued by S&P Global Ratings.

[9] Source: S&P Global Market Intelligence. As of November 1, 2019.

[10] “TCFD-based reporting to become mandatory for PRI signatories in 2020, Joy Frascinella (February 18, 2019).

[11] Source: S&P Global Market Intelligence’s CreditPro® database (as of September, 1 2019).

Learn more about Climate Credit Analytics
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