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CASE STUDY — 26 Apr, 2022
Highlights
The Client: An Asia-based financial services holding company
Users: Risk management team
Regulations on measuring climate-related risks and providing adequate disclosures continue to evolve quickly in Asia and abroad. This warrants the need for risk managers at financial institutions to develop ways to monitor their portfolios’ resilience to climate-related financial risks. These financial institutions tend to use of different climate scenarios developed by the Network for Greening the Financial System (NGFS), especially since NGFS is endorsed by and comprises a group of over 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 emission levels in its loan portfolio in line with the recommendations of the Taskforce on Climate-related Financial Disclosures (TCFD) for a few years now. The company will also need to conduct a regulatory-driven stress testing exercise related to climate risks in the near future. To comply with both of these undertakings, it was looking for 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 utilize a robust methodology that would enable them to link climate impacts, particularly transition risks, with a company’s financials to assess and report on credit risks.
Pain Points
The risk management team wanted to evaluate the impact of different climate scenarios on the financials of some of its top corporate clients and needed to identify a robust methodology that would generate reliable results.
The risk management team wanted to look at the impact of different scenarios for transition pathways and risks on approximately 1,000 of the bank’s corporate clients involved in high carbon-emitting sectors and the how this would affect the creditworthiness of obligors. Given the scope of the undertaking, the team needed:
The team had already worked with S&P Global Market Intelligence (“Market Intelligence”) to calculate the carbon footprint of the holding company’s operations and those of the companies and assets that it finances. Market Intelligence was contacted to discuss how it could help with this latest initiative.
The Solution
Market Intelligence began by discussing Climate Credit Analytics, a highly dynamic, sector-specific approach that enables counterparty- and portfolio-level analysis of climate-related financial and credit risks for thousands of companies across multiple sectors. The solution makes the critical link between climate change and credit risk by translating climate scenarios into drivers of financial performance tailored to specific industries. These drivers are then used to forecast complete company 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 evaluate more than 1.6[3] million public and private companies, as well as the ability for users to input proprietary information to expand this analysis. The solution covers five carbon-intensive sectors (Airlines, Automotive, Metal & Mining, Oil & Gas and Power Generation) and also provides a generalized approach for all other sectors to complete the 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 company-level data from Trucost, the data and analytics engine that powers many of S&P Global’s ESG solutions. These capabilities would enable users at the risk management team to:
Key Benefits
The risk management team thought the combination of Market Intelligence’s data resources and credit analytics and Oliver Wyman’s climate scenario and stress-testing expertise was very impressive. A decision was made to utilize the Climate Credit Analytics offering to provide the holding company with:
Click here to explore some of the datasets and solutions used in this case study.
[1] NGFS, as of February 14, 2022, www.ngfs.net/en/about-us/governance/origin-and-purpose.
[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 numbers as of December 2021.
[4] S&P Global Ratings does not contribute to or participate in the creation of credit scores generated by Market Intelligence. Lowercase nomenclature is used to differentiate Market Intelligence credit model scores from the credit ratings issued by S&P Global Ratings.
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