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Q&A: Navigating Climate Risk as a Financial Risk

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Q&A: Navigating Climate Risk as a Financial Risk

Climate change is prompting investors to consider plausible climate-related scenarios and evaluate the potential impact on their portfolios. In our webinar panel on November 12, 2020,[1] we introduced Climate Credit Analytics, the new holistic approach to assess credit risk under a range of climate scenarios developed by S&P Global Market Intelligence and Oliver Wyman[2]. We were joined by Citi who will be utilizing Climate Credit Analytics to support their commitment of a smooth transition to a low carbon economy.[3] Below, two members of our panel – Dr. Giorgio Baldassarri, Global Head of the Analytic Development Group (ADG) and llya Khaykin, Partner, Financial Services, Head of Climate Risk and Sustainable Finance in the Americas at Oliver Wyman – answer a few questions raised in the Q&A.

What are the common practices today for institutions to manage climate risk as a financial risk?

Leaders are pushing to integrate climate considerations comprehensively into their risk management frameworks. They are looking at governance, risk appetite statements, risk measurement, and scenario analysis, as well as at how they can effectively organize their teams around the topic. Firms are also integrating climate issues into their individual risk policies. In many cases, they are doing that in a qualitative manner, but some are starting to work on quantifying metrics in risk appetite, as well. Additionally, they are updating risk frameworks and taxonomies to make sure that they capture climate. Some firms are adding a new category of risk that they call climate, and others are embedding climate across different types of risk. So, there are a range of approaches at the moment across leading global firms.

How do you integrate climate risk in credit risk analysis?

Climate Credit Analytics is a climate scenario analysis and credit analytics model suite developed by S&P Global Market Intelligence and Oliver Wyman. These tools combine S&P Global Market Intelligence’s data resources and credit analytics capabilities with Oliver Wyman’s climate scenario and stress-testing expertise. Climate Credit Analytics enables comprehensive and consistent sector-specific modelling.

Via a highly dynamic, sector-specific approach, Climate Credit Analytics enables counterparty- and portfolio-level analysis of climate-related financial and credit risks for thousands of public and private companies. The capability is designed for risk managers, investment professionals, sustainability teams, and others to assess credit risks related to climate change and the transition to a low-carbon economy.

What scenarios are included in Climate Credit Analytics?

The tool enables analysis of the climate transition reference scenarios published by the Network for Greening the Financial System (NGFS), a group of over 80 central banks and supervisors representing 75% of global GHG emissions. NGFS scenarios are based on integrated assessment models developed by the climate science community and include multiple climate transition pathways over multi-decade time horizons. They comprise scenarios across three integrated assessment models, enabling users to compare impacts across multiple hot house, disruptive, and orderly transition scenarios. In addition, the model includes one short-term, disorderly scenario in which a global carbon tax is phased in over three years with no regulatory lead time.

How does the model work and how would you apply it in practical terms for a bank?

We have integrated climate considerations into a traditional credit risk management framework. Climate Credit Analytics translates climate scenarios into drivers of financial performance tailored to each industry, such as production volumes, fuel costs, and capital expenditure spending. These drivers are then used to forecast complete company financial statements under various climate scenarios.

Users select companies to run through different scenarios. The model then projects adjusted company-level financials, P&L, probabilities of default, and credit scores based on the key scenario drivers. For example, carbon-intensive firms are likely to perform worse under scenarios with higher and more sudden carbon taxes than they are under orderly transition scenarios.

A bank, for example, could choose to run Climate Credit Analytics for the most exposed portion of their loan book, or choose to run it across all companies in their portfolio. The tool supports easy implementation into existing processes and workflows and includes containerized versions where data does not leave the institution.

How does the tool incorporate information on companies’ transition strategies?

The tool will reflect transition strategies to the extent that they are reflected in the company’s business activities, financial statements, industry-specific data, and emissions intensity. For example, a diversified mining firm that has a relatively low current level of coal production and investment due to a strategic shift away from coal will be less affected than a coal mining firm. As companies update their strategies over time, the tool will bring in new baseline information that reflects these strategies. In addition, users can evaluate results under multiple transition strategies. For example, in the power sector, modeling considers the potential for firms to take either a ‘static’ approach where they continue to produce electricity using a similar fuel mix as implied by recent trends, and an ‘adaptive’ approach where firms make the investment to ramp up renewables in line with the overall industry scenario. These strategies can be selected by the user, or both can be considered to understand the range of potential impacts.

What S&P data comes as part of the tool (or is incorporated in the tool)?

The model suite leverages:

  • Financials and industry-specific data – such as oil, gas, or coal production, airline passenger volumes, and electricity capacity – from S&P Capital IQ and S&P Global Market Intelligence
  • Sophisticated quantitative credit scoring methodologies from Credit Analytics
  • Company-level greenhouse gas (GHG) emissions and environmental impact data from S&P Global Trucost

The solution automatically extracts relevant company financials, borrower-level credit scores, and industry-specific data to support a bottom-up modeling approach.

Learn more about Climate Credit Analytics here.


Contributors

llya Khaykin is a Partner based in Oliver Wyman’s New York office and heads the Climate Risk and Sustainable Finance platform in the Americas. He also leads the firm’s engagement with the World Economic Forum on the Financing the Transition to a Net Zero Carbon Economy and is involved in work with clients globally on the topic. Ilya has led Oliver Wyman’s support of the UN Environment Program to develop the industry-leading approach to transition risk scenario analysis for bank portfolios.

Dr. Giorgio Baldassarri is Global Head of the Analytic Development Group (ADG). His team is responsible for the analytical development, maintenance and on-going validation of all credit risk models and products across Risk Services, which are used by financial institutions and corporate companies to measure and manage credit risk, including within regulatory frameworks such as Basel II/III or Solvency II.



[1] Webinar: Navigating Climate Risk as a Financial Risk. S&P Global Market Intelligence. As of November 12, 2020.

[2] Oliver Wyman is a global management consulting firm and is not an affiliate of S&P Global, or any of its divisions.

[3] Press Release: S&P Global Market Intelligence and Oliver Wyman Collaborate with Citi to Support Their Commitment of a Smooth Transition to a Low-Carbon Economy, S&P Global, As of: November 12, 2020.

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