Big Banks Take Part In A Climate Scenario Exercise — The Results Are Unsettling – CleanTechnica

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The US Federal Reserve just released the results of a pilot climate scenario analysis (CSA) exercise they conducted in 2023 to learn about big banks and their climate risk-management practices and challenges. The goal was to highlight the measures that large banking organizations and supervisors will increasingly need to take to identify, estimate, monitor, and manage climate-related financial risks. Those risks arise from a changing climate, concurrent severe weather events, and the transition to an economy less reliant on fossil fuels.

The exploratory pilot climate scenario analysis exercise was conducted with 6 US big banks: Bank of America Corporation; Citigroup Inc; The Goldman Sachs Group, Inc.; JPMorgan Chase & Co.; Morgan Stanley; and Wells Fargo & Company.

The results were unsettling.

These big banks experienced a high degree of uncertainty around the timing and magnitude of climate-related risks and told the Federal Reserve that there are significant data gaps that make it tough for them to properly manage climate-related risks to their businesses. In many cases, participants relied on external vendors to fill in data and modeling gaps.

That means big banks have a big problem determining for themselves how to best account for and oversee climate-related risks on a business-as-usual basis.

What’s the Connection between Big Banks & Climate Risk?

Climate scenario analysis is important as part of a larger need to consider the resiliency of business models to a range of climate scenarios and to explore potential vulnerabilities across short- and longer-term time horizons. Most of the big bank participants in the Federal Reserve “Pilot Climate Scenario Analysis Exercise” relied on existing credit risk models to estimate the impact of physical and transition risks on their portfolios.

Yet the if-it-was-good-enough-for-us-back-then approaches seemed to fall flat for the 6 big banks. Participants assumed that balance sheets remained static over the relevant projection horizon. What became clear was that large banking organizations and the broader financial system are exposed to climate change through macroeconomic and micro-economic transmission channels associated with physical and transition risk drivers.

• Physical risks refer to the harm to people and property arising from acute, climate-related events, such as hurricanes, wildfires, floods, heatwaves, and droughts as well as longer-term chronic phenomena, such as higher average temperatures, changes in precipitation patterns, sea level rise, and ocean acidification.
• Transition risks refer to stresses to certain institutions, sectors, or regions arising from the shifts in policy, consumer and business sentiment, or technologies associated with the changes that would be part of a transition to a lower carbon economy.

The Fed’s physical risk module focused on estimating the effect of common and idiosyncratic shocks of varying levels of severity on residential real estate and commercial real estate loan portfolios over a one-year horizon in 2023. The Federal Reserve set broad parameters around the severity of physical hazards by selecting a future point in time on specific Shared Socioeconomic Pathways or Representative Concentration Pathways presented by the Intergovernmental Panel on Climate Change and a specific return period loss.

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The transition risk module focused on estimating the effect of different transition pathways, as described by the Network of Central Banks and Supervisors for Greening the Financial System, on corporate and CRE loan portfolios over a 10-year horizon from 2023-32.

The Problems that were Revealed in the Climate-Risk Modeling

Because all big banks confront the same types of risk issues, you’d think that they’d approach the detailed physical and transition risk scenarios used in the pilot CSA exercise similarly, and that they’d translate those scenarios into estimates of climate-adjusted credit risk parameters.

Nope.

There were many differences in approach during the analysis exercise, driven largely by participants’ business models, views on risk, access to data, and prior participation in climate scenario analysis exercises in foreign jurisdictions.

They assumed that historical relationships between model inputs and outputs will continue to hold as the climate and the structure of the economy evolve.

Climate-related risks are highly uncertain and proved challenging to measure for these big banks. Participants reported significant data and modeling challenges in estimating climate-related financial risks. For example, participants noted a lack of comprehensive and consistent data related to building characteristics, insurance coverage, and counter-parties’ plans to manage climate-related risks.

What did the Big Banks Learn about Climate Risk?

Participants identified key design choices that meaningfully impacted the insights drawn from the exercise. These included choices related to the scope of the shocks, scenario severity, the starting point of the exercise, insurance assumptions, and balance sheet assumptions.

Participants reported that, in order to manage climate-related financial risks, they will need better understanding and monitoring of indirect impacts and chronic risks.

• Indirect impacts are areas like disruptions to local economies.
• Chronic risks occur because of climate influences like sea level rise.

Participants highlighted the important role that insurance plays in mitigating the risks of climate change for consumers, businesses, and banks. They noted the need to monitor changes across the insurance industry, including changes in insurance costs over time, and the impacts of those changes on consumers and businesses in specific markets and segments.

While not the focus of the pilot CSA exercise, participants’ estimates of climate-adjusted credit risk parameters, such as probability of default (PD), showed significant heterogeneity in impact — across sectors, regions, and counter-parties.

Key Insights from the Pilot CSA Exercise

Participants intend to incorporate climate scenario analysis into their risk-management processes over time. The big banks plan to continue to invest in data, models, and expertise to better identify, estimate, and monitor climate-related financial risks through the use of scenario analysis exercises and other tools. Their specific plans for future investments include acquiring more granular climate and exposure data, enhancing modeling capabilities, designing more customized scenarios that are better suited to test participants’ unique business models and vulnerabilities, and shifting from vendor models to in-house solutions.

Clearly, the high degree of uncertainty inherent to climate risk modeling posed a significant obstacle to the banking organizations. The challenges created by such uncertainty in reliably and consistently quantifying the impact of climate-related risks, as factors impacting how the results of climate scenario analysis exercises, could and should be used going forward.