The Global Risk Institute hosted the Bank of Canada to discuss the bank’s report on “Scenario Analysis and the Economic and Financial Risks from Climate Change”. Guest speakers included the report’s authors, Erik Ens and Craig Johnston, as well as an industry expert, Eli Angen from Ontario Teacher’s Pension Plan (OTPP). The webinar was hosted by GRI’s Senior Director of Sustainable Finance, Alyson Slater.

The work completed by the Bank of Canada was the first of its kind globally to use scenario analysis to assess the potential risks of climate change to financial system stability. Ens and Johnston presented two key takeaways from their work on scenario analysis:

1. Climate change and transition pose serious economic and financial risks in the short, medium and long term, and
2. Scenario analysis is a key tool for the financial sector, but it will take time for data and methodologies to mature.

The Bank of Canada’s aim was to forecast what could happen to the macroeconomic landscape if certain climate risks were, or were not, mitigated. The scenarios assessed the impacts of both physical and transitional risks. Physical risks were described as damage or destruction from extreme weather events, which could result in economic disruption and losses to the financial system. Transition risks were defined as costs that could be incurred as the economy transitions to a low carbon economy.

The Bank of Canada conducted a 5-step process to complete its scenario analysis work:

Step 1. Address the goals and objectives

The Bank of Canada described the goals of the work as: assess the financial system risks, and analyze the macroeconomic impacts.

Step 2. Choose tools to assess the risks

The Bank of Canada used two tools:

1. The Integrative Assessment Model – a model that connects the economy to climate, and is usually used on a global scale rather than a regional scale. This model was used for physical risk assessment.
2. Computable General Equilibrium Model – a model that doesn’t necessarily connect the economy to climate, however provides a high degree of sectoral and regional data that can be attributed to transition risks. This model was used for transition risk assessment.

Step 3. Choose climate scenarios

Existing climate scenarios provided by the Intergovernmental Panel on Climate Change (IPCC) and other scientific sources were used but had to be modified to assess the financial impacts of climate risks. The Bank of Canada developed four scenarios, outlined below.

Step 4. Assess the economic and financial impacts

This step involves the interpretation of the results from the scenarios performed:

1. Business as usual – this scenario posed no transition risk, as no measures were assumed to be taken to mitigate climate risk. However, the physical risks posed a 45 per cent loss of GDP due to physical damages.
2. 2-degree Celsius consistency – meeting the Paris Agreement by 2050 showed that there would be an increase in transition risk such as oil production falling sharply by 2035.
3. 2-degree Celsius disorderly transition – with emissions reduction action starting in 2030, there is extreme transition risk toward 2050.
4. Technology shock – with the assumption that technology would be developed to extract greenhouse gas emissions from the atmosphere in time to avoid the worst physical risks, there was low physical and transition risk.

Step 5. Integration into strategy and risk assessment

The Bank of Canada is using these scenarios to perform more research, and understand how these results can be integrated into business strategy. Some examples discussed were how these results could be used to inform monetary policy, using it as a basis for system-wide stresses, and being able to understand more detailed risks around the financial sector.

Presenters noted that climate scenario work is still in its infancy, and there is a need for skills such as conceptual thinking, and economic and risk modelling; adapting already developed climate tools to fit specific needs; lack of available data; and translating climate data into economic and financial variables.

Eli Angen followed up with a perspective from the private sector and shared three motivating factors for financial institutions to use scenario analysis:

1. Forthcoming regulation
2. Stakeholder demands
3. Financial institutions’ own self interest

Angen highlighted the complexity of scenario analysis and explained three approaches to tackling the process: qualitative and narrative based approaches, a top down approach assessing macroeconomic and financial sector impacts, and a combination of macro and bottom up details – resulting in complex and firm-specific information leading to value-at-risk output. Furthermore, Angen pointed out success factors such as the need for an executive champion, internal skills and knowledge, and a longer-term vision for the continuous development and updating of scenarios.

In conclusion, panelists agreed that scenario analysis is a collaborative effort from everyone, and with more data, variables, and knowledge of scenario analysis, models will become more accurate and more usable to inform business strategy for the financial sector.