Case Study — 13 Jul, 2022
A Globally Significant Financial Institution Improves its Capabilities to Assess Climate-Related Credit Risks
It has been widely recognized now that climate change has the potential to adversely affect society and economies. Transition risk (i.e., the risks that arise from the transition to a low-carbon economy), is particularly untested. As a result of this, it has become one of the main topics of discussion among governments and financial regulators due to its potential to slow economic growth, reduce employment and undermine the stability of financial markets.[1] Central banks and regulators across the world are taking steps to ensure that banks are prepared for any shocks to the financial system by having significant financial institutions stress test their counterparty exposures and portfolios under a range of climate scenarios.
Members of the climate team at this GSIFI are responsible for measuring and managing the bank’s exposure to environmental threats. This includes comparing the outcome of internal analysis of the bank’s loan portfolios with an independent challenger model in order to meet regulatory requirements. These exercises require access to robust climate data and analytics to effectively model transition paths to net zero for the bank’s corporate clients.
Pain Points
The bank wanted to select a reliable, holistic bottoms-up approach covering both risks and opportunities, given the limited avenues for validation when it comes to assessing climate related credit risks
The climate team needs to consider stress testing the bank’s loan portfolios to uncover any potential vulnerabilities related to financed emissions. While they’ve built an internal model for this purpose and utilize a number of S&P Global’s environment datasets already as part of their analysis, the climate team wanted to also adopt a challenger model that could help independently assess their approach to quantifying climate related credit risks:
- A sound methodology to evaluate transition paths to net zero under different climate scenarios.
- A standardized yet thorough assessment framework for corporates.
- The ability to estimate impact on credit risk for small- and medium-sized enterprises (SMEs), where information is typically not reported.
- Portfolio-wide analysis of climate-related financial and credit risks.
- Capabilities to easily link internal and external data that use different classification schemes to have one unified database.
- Efficient data access options to support analysis and the development of a company-wide data warehouse.
The team began discussions with S&P Global Market Intelligence (“Market Intelligence”) to learn more about the firm’s offering.
The Solution
Market Intelligence began by discussing Climate Credit Analytics (CCA), a climate stress‑testing framework and scenario analysis model suite, which was launched in 2021. CCA makes the critical link between climate change and credit risk by translating climate scenarios into drivers of financial performance (e.g., production volumes, fuel costs and capex spending) tailored to specific industries. These drivers are then used to forecast complete company financial statements under various climate scenarios, including those published by the Network for Greening the Financial System (NGFS), a group of over 120 central banks, financial authorities, and observers.[2]
Developed through a collaboration between Market Intelligence and Oliver Wyman,[3] CCA includes an automated capability to evaluate more than 1.6[4] million public and private companies, as well as the ability for users to input proprietary information to expand this analysis. CCA covers five carbon-intensive sectors (Airlines, Automotive, Metal & Mining, Oil & Gas and Power Generation) and provides a generalised approach for all other sectors to complete the portfolio analysis.
CCA 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 bank to:
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Conduct climate scenario analysis and stress loan portfolios |
Climate Credit Analytics translates climate scenarios into scenario-adjusted financials and creates credit scores[5] at the company level. CCA enables climate scenario analysis through 2050 by natively incorporating the 2021 scenarios published by NGFS by evaluating both, climate-related risks and opportunities. It also allows for evaluation of user-defined scenario values. |
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Embedded with differentiated data |
CCA automatically extracts relevant company S&P Capital IQ Premium Financials which provides standardized data for over 5,000 financial, supplemental and industry-specific data items for over 150,000 companies globally Private Company Data that covers more than 10 million private with financial statements. allowing users to utilize these datapoints alongside any other proprietary information for the purpose of the analysis SNL Energy 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, hourly Trucost Environmental Data contains information on over 16,000 companies, covering Scope 1, 2 and 3, with metrics on quantities and intensities of carbon-equivalent emissions (tCO2e, tCO2e/US$ revenues) and their estimated damage cost equivalents (US$), along with impact ratios. It includes sector revenue data that gives revenues and percentages of company revenues derived from each of 464 business sectors. For companies where this data is unavailable, the analysis is extended to estimate emissions using industry-specific environmental impact data with quantitative macroeconomic data. Data goes back to 2005, where available. |
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Access to cutting-edge analytics |
Credit Analytics blends cutting-edge models with robust data to help users reliably assess the credit risk of rated and unrated, public, and private companies across the globe.
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Easily integrate internal and external data |
Business Entity Cross Reference Services quickly links the standardized and proprietary IDs for over 28 million entities to the primary key, the S&P Capital IQ Company ID. |
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Deliver data to a centralized warehouse |
The robust Capital IQ Pro desktop is complemented by an API solution that enables clients to receive enterprise-level data securely through RESTful APIs, drawing upon fewer resources than typically required for traditional data feeds. |
Key Benefits
Members of the climate team were impressed with the combination of Market Intelligence’s data resources and credit analytics’ and Oliver Wyman’s climate scenario and stress-testing expertise. The approach provided sufficient transparency and documentation on the approach as is needed for the purposes of a challenger model. The bank also saw immense value in having one well-respected provider of an extensive set of environmental capabilities, given that it was already subscribing to S&P Global’s environmental datasets.
A decision was made to utilize the Climate Credit Analytics offering to provide the bank with:
- A methodology to translate complex climate scenarios into drivers of financial performance that could clearly help challenge their internal modeling approach
- Ability to carry out stress tests, including sophisticated quantitative credit scoring.
- Comprehensive and consistent sector-specific modelling covering key high carbon-emitting sectors, plus others.
- A solution that leverages Market Intelligence’s proprietary datasets, including renowned financials and environmental information.
- Thorough technical and methodology documentation as is needed for audit and regulatory purposes
- Ongoing support to thoroughly understand the underlying data and methodologies.
- Improved workflows with easy integration of internal and external data using cross-referencing capabilities.
- Access to a robust desktop solution with tech-forward productivity tools, plus feeds for seamless data delivery to an internal system paired with an API for interactive forecasting and scoring.
Click here to learn more about Climate Credit Analytics
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[1] “Q&A Credit Risk Perspectives Series: Navigating Climate Scenario Analysis”, S&P Global Market Intelligence, May 5, 2020, Read More.
[2] Source NGFS as of February 14, 2022.
[3] Oliver Wyman is a third-party consulting firm and is not affiliated with S&P Global or any of its divisions.
[4] All coverage numbers as of December 2021.
[5] 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.