Credit risk

Major Asian company links climate change to credit risk

Regulations on measuring climate-related risks and communicating adequate information continue to evolve rapidly in Asia and abroad. This justifies the need for financial institution risk managers to develop ways to monitor the resilience of their portfolios to climate-related financial risks. These financial institutions tend to use different climate scenarios developed by the Network for Greening the Financial System (NGFS), especially since the NGFS is endorsed by and includes a group of more than 120 central banks, financial authorities and observers.[1]

As a leader in ESG measurement and reporting, this Asia-based financial services holding company had been disclosing the emission levels of its loan portfolio for some years in accordance with the recommendations of the Taskforce on Climate-related Financial Disclosures (TCFD) . The company will also have to conduct a regulatory stress test exercise related to climate risks in the near future. To comply with these two commitments, it sought a unified approach to climate scenario analysis and stress testing to meet the needs of investors, regulators and other stakeholders. While NGFS scenarios are in the public domain, members of the risk management team wanted to use a robust methodology that would allow them to link climate impacts, particularly transition risks, to a company’s finances to assess and report on credit risk.


Pain points

The risk management team wanted to assess the impact of different weather scenarios on the finances of some of its major corporate clients and needed to identify a robust methodology that would generate reliable results.

The risk management team wanted to examine the impact of different scenarios on transition paths and risks on approximately 1,000 corporate clients of the bank involved in high-carbon sectors and how this would affect the creditworthiness of debtors. Given the scale of the business, the team needed:

  • A solid methodology to assess transition paths to net zero under different climate scenarios.
  • An automated approach to deliver portfolio-wide results.
  • The ability to capture industry-specific nuances.
  • Access to complete and reliable financial and environmental data necessary for the analysis.

The team had previously worked with S&P Global Market Intelligence (“Market Intelligence”) to calculate the carbon footprint of the operations of the holding company and those of the companies and assets it finances. Market Intelligence has been contacted to discuss how it could contribute to this latest initiative.


The solution

Market Intelligence began by discussing Climate Credit Analytics, a highly dynamic industry approach that enables counterparty and portfolio level analysis of climate-related financial and credit risks for thousands of companies across multiple industries. The solution makes the critical link between climate change and credit risk by translating climate scenarios into financial performance drivers tailored to specific sectors. These factors are then used to forecast the company’s full financial statements under various climate scenarios, including those published by NGFS.

Developed through a collaboration between Market Intelligence and Oliver Wyman,[2] Climate Credit Analytics includes an automated capability to assess over 1.6[3] millions of public and private companies, as well as the ability for users to enter proprietary information to expand this analysis. The solution covers five carbon-intensive sectors (Airline, Automotive, Metals & Mining, Oil & Gas, and Power Generation) and also provides a generalized approach for all other sectors to complement portfolio analysis.

Climate Credit Analytics leverages Market Intelligence’s proprietary datasets and capabilities, including financial and industry-specific data, sophisticated quantitative credit scoring methodologies, and firm-level data from Trucost, the engine data and analytics platform that powers many of S&P Global’s ESG solutions. These capabilities would allow users of the risk management team to:

Perform climate scenario analysis

Analysis of climate credits translates climate scenarios into scenario-adjusted financial data and creates credit ratings[1] at the enterprise level. The solution enables the analysis of climate scenarios up to 2050 by natively incorporating the 2021 scenarios published by NGFS and assessing both climate-related risks and opportunities. It also supports the evaluation of user-defined scenario values.

Integrate differentiated data

Analysis of climate credits Automatically extracts relevant company financial data, borrower-level credit scores, and industry-specific data from Market Intelligence to support a bottom-up modeling approach. This includes:

S&P Capital IQ Premium Financial Services which provides standardized data for over 5,000 financial, supplemental and industry-specific data elements for over 150,000 companies worldwide

Private company data this covers over 10 million private companies with financial statements, allowing users to use these data points along with any other proprietary information for analysis

SNL Energy which covers more than 9,000 power plants, 3,000 North American energy companies, 1,700 active coal mines and 120 gas pipelines. This includes details on financials, supply and demand fundamentals, timings
market pricing and tariff cases.

Trucost environmental data it contains Informations about more than 16,000 companies, covering scopes 1, 2 and 3, with measurements on the quantities and intensities of carbon equivalent emissions (tCO2e, tCO2e/revenue US$) and their damage cost equivalents estimated (US$), as well as the impact ratios. It includes industry revenue data that gives the company’s revenues and revenue percentages from each of the 464 business sectors. For companies where this data is not available, the analysis is extended estimate emissions using industry-specific environmental impact data as well as quantitative macroeconomic data. Data goes back to 2005, when available.

Access cutting-edge analytics

Credit analysis combines state-of-the-art models with robust data to help users reliably assess the credit risk of listed and unrated, public and private companies around the world.

Reporting climate risks with confidence

The tool produces comprehensive financial statements, including balance sheets, income statements and counterparty cash flow statements for the forecast period, plus on an aggregated basis for the sector. This provides clients with the ability to transparently and efficiently report on various operational parameters related to the impact of climate transition risk.


Key Benefits

The risk management team found the combination of Market Intelligence’s data and credit analysis resources and Oliver Wyman’s weather scenario and stress testing expertise to be very impressive. It was decided to use the Climate Credit Analytics offer to provide the holding company with:

  • A solution that embeds Market Intelligence’s proprietary datasets, including renowned financial and environmental information.
  • A unique methodology translating complex climate scenarios into drivers of financial performance.
  • Sector modeling which covers the main carbon emitting sectors, as well as others.
  • A sophisticated approach to calculate the impacts of climate change on credit ratings and probabilities of default.
  • The option of using projected financial data in an internal credit rating platform.
  • A scalable standardized approach to serve operations in other jurisdictions.
  • Support in progress to fully understand the underlying data and methodologies.
  • Access to Capital IQ Pro, a robust desktop solution with state-of-the-art productivity tools.

Click on here at explore some of the datasets and solutions used in this case study.



[2] Oliver Wyman is a third-party consulting firm and is not affiliated with S&P Global or any of its divisions.

[3] All coverage issues as of December 2021.

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