SCENARIO ANALYSIS: Assessing Climate Change Transition Risk in Insurer Portfolios
Background. In June 2017, the FSB Task Force on Climate-related Financial Disclosures (TCFD) recommended that financial institutions perform scenario analysis on their portfolios to assess financial risks related to climate change. The TCFD grouped climate-related risks into two categories: transition and physical risks. Transition risks are risks generated by the policy, technology, market, and regulatory changes likely to accompany the transition to a low carbon economy. Physical risks are the weather-related impacts exacerbated by climate change. As part of its supervisory role, the California Department of Insurance engaged the 2° Investing Initiative (2Dii) to undertake a scenario analysis of the investment portfolios of insurance companies operating in California with more than $100 million in premiums.
Goal. The goal of the scenario analysis was to assess California insurers’ exposure to transition risk, individually and as a whole, based on the evolution of production and assets in the real economy. This analysis compares the currently planned production from physical assets allocated to a portfolio (for example, the projected number of barrels of oil produced by an oil well owned by a company that has issued a security held in an insurer’s portfolio) with future production levels defined in a 2°C scenario. To ensure comparability across results, this analysis uses the ‘Energy Technology roadmaps’ published by the International Energy Agency (IEA). See the ‘Important Considerations and Limitations’ section at the end of this page for notes on interpreting these scenarios.
Portfolios. Data on insurers’ investments was taken from the 2017 year-end financial filings of all insurers operating in California with more than $100 million premiums, yielding a sample of over $4 trillion in investments, the bulk of which is held in fixed-income portfolios. This analysis is based on the composition of the insurers’ portfolios at the end of year 2017 assuming no change in portfolio composition.
Scenarios. The scenarios from the International Energy Agency (IEA) have been used throughout this analysis. They define how climate-relevant technologies - essentially energy technologies - must be deployed by 2050 to reach a 50% probability of limiting warming to different temperature ranges. This analysis is based off the Sustainable Development Scenario (SDS) which corresponds to limiting temperature increase to 2°C or 3.6°F by 2100. Additionally included in this analysis are the Beyond 2° Scenario (B2DS), New Policies Scenario (NPS) and Current Policies Scenario (CPS): other technology roadmaps that correspond to a 50% probability of maximum 1.75°C, 2.7°C, and 3.2°C warming, respectively. The SDS (also referred as “2° scenario”), B2DS (“1.75°C scenario”), NPS (“2.7°C scenario”), and CPS (“3.2°C scenario”) all provide forward-looking projections with enough regional detail to perform scenario analysis for 11 technologies in 3 sectors. The analysis, based on the IEA scenarios, is applied to the California Department of Insurance and covers fossil fuel extraction (oil, gas, and coal mining); production of electricity (from coal, gas, hydro, nuclear, and renewables); and, the production of cars (internal combustion engines - gasoline and diesel, hybrid, and electric).
Methodology. The key elements of the analysis are:
Projecting investments and producton. Projected production (for Fossil Fuels and Automotive) and new capacity (for Utilities) for the next 5 years was sourced from commercial business intelligence databases. These data providers collect production capacity, forecasts, and investment data at the most granular level, including barrels of oil by field, cars by model and factory, new capacity by power plant. 2Dii maps these data to their immediate owners, and then their parent company to generate the company’s aggregate ‘current production profile’ for each technology, and links those production plans to the financial securities (stocks and corporate bonds) issued by the company. The asset-level data used for this analysis was retrieved from data providers during the first half of 2017. See the ‘Important Considerations and Limitations’ section at the end of this page for notes on interpreting power sector capacity data.
Allocating physical asset production to financial assets. Based on the share of total equity or debt held in a portfolio, the model allocates a portion of each corporate issuer’s current production plans for each technology to the portfolio. Aggregated to the portfolio level, this is the ‘portfolios’ current production profile’ for a technology. This also defines the insurer’s current ‘exposure’ to each technology.
From macro-level scenario to micro-level targets. To calculate production levels consistent with a climate scenario such as the IEA 2°C scenario, the model uses a ‘fair share’ principle that applies the changes specified by the scenario for a given technology and region equally across all owners of physical assets in that region. It creates a set of alternative production profiles ‘under the scenario’, or consistent with the scenario, for each technology and company. These alternative production profiles are then aggregated to the portfolio level to create the portfolio’s production profile under the scenario. This profile is used to determine the ‘insurer’s target exposure’ to a technology under the scenario. The ‘target exposure’ does not assume any change in the composition of the portfolio: it models the changes in production and investment plans that are required across the different companies held, in order to match the technology deployment roadmap.
Scenario Regionality. For the power sector, the target capacity for each technology is calculated by looking at a specific scenario for different geographies and allocating the required change based off the location of the plant. The targets are based on whether each power plant is in an OECD or Non-OECD country, which then designates what change would be required to meet the scenario for this set of countries. These required changes at plant level are aggregated to the company and then to the portfolio to determine the overall change in production or capacity that is required. The stringency of scenarios for each technology varies between OECD and Non-OECD countries hence it is important to incorporate this breakdown into the calculations. For the fossil fuel and automotive sectors, the global targets are used to determine the target production for each technology. This analysis is limited to the global targets due to the lack of availability of the geographical breakdown for each scenario in the analysis, and the increased integration of these markets globally versus the power sector, which is more regionally distinct.
Assessing Alignment with a 2°C Transition Pathway. This analysis assesses the level of alignment with a 2°C transition pathway, using two references:
The portfolio's ‘own’ 2°C target.This is the portfolio’s target production profile ‘under the 2° scenario’: the changes required in the production profile of the companies held in the portfolio, in order to meet the target, based on the above-described methodology. While the 2°C scenario is the focus of this analysis, the target profiles for a 1.75°C, 2.7°C, and a 3.2°C scenario are also calculated to provide further context. Since the securities held and their weight in the portfolio are identical for the portfolio and its alternative versions, comparing them shows how aligned or misaligned the current production profiles of companies held in the portfolio are with each scenario.
The 2°C benchmark.This is the target production profile of a ‘market benchmark’ under the 2° scenario. The same principle as described above is applied to a ‘benchmark portfolio’: the stock market as a whole, or the corporate bond market as a whole. Since the securities and their weight in the market portfolio differ from those in the portfolio, this comparison highlights ‘idiosyncratic’ alignment or misalignment. In other words, it shows how the current composition of the portfolio affects the alignment with the different scenarios, when the first reference only stresses the changes requested from the companies.
The alignment or misalignment of a portfolio’s production and exposure to each technology relative to a scenario is one way to better understand insurers’ exposure to energy transition risk. If policy, technology, market, or regulatory changes occur to bring the global real economy in line with the 2°C scenario, misalignment in a given technology would likely change the financial returns associated with those underlying physical assets. However, this analysis only assesses one dimension of energy transition risks: the assets at risk in the real economy. It does not take into account the financial resilience of the company to those changes and its capacity to adapt, which would require further financial analysis.
Important Considerations and Limitations when Interpreting these Results
Stringency of scenarios. The use of a given scenario (1.75°C, 2°C, 2.7°C, and 3.2°C) does not constitute an assumption that this scenario is more likely to prevail than others. Similarly, the choice of IEA scenarios should not be interpreted as an endorsement of the underlying assumptions by 2Dii or the California Department of Insurance. The IEA historically has, for instance, assumed significant amounts of nuclear power and carbon capture and storage in their scenarios, an assumption that is debated within the energy-climate scientific community. In addition, the international community has accelerated their global target from the 2°C goal to “well below 2°C and towards 1.5°C”. It is important to highlight that each insurer can and may want to take an individual view on the likely decarbonization scenario that may or may not relate to the scenarios modelled by the International Energy Agency.
A snapshot rather than forecasts. The forward-looking production data is based on current ‘revealed’ plans from companies and is subject to change. The estimates should thus not be interpreted as forecasts, but rather as the current plans of companies as estimated from various sources of information by industry-specific business intelligence experts - who might not know everything about the CEOs’ actual plans. Given the 5-year time horizon, it is likely that these plans will change in some way over time. Similarly, insurers are highly likely to alter the composition of their portfolio over time. Bond maturity is usually around 3-7 years. The average holding period of a stock by a fund manager is 20 months on average. However, this analysis seeks to be a point in time assessment of future exposures under current conditions.
Power sector projections. This is a measure of "locked-in" capacity, not a capacity forecast. Distinct from the production data for the Fossil Fuel and Automotive sectors, capacity data for the Power sector does not include information on planned retirements. It should therefore be interpreted as a measure of currently "locked-in" capacity and not as a forecast of future capacity. Retirements are not included for several reasons: First, the availability of planned retirement data is highly variable across jurisdictions and regions, to the extent that including no retirement information was deemed more representative of industry capacity than including partial data. Second, in contrast to the fossil fuel sector where oil wells, gas fields, and coal mines cease production when their resource runs out, it is possible for power plants to be announced as retired or even be retired and then resume production. Given the higher level of uncertainty around planned retirements, they are not included in the power sector projections used for this analysis, and capacity projections should thus be interpreted as the potential maximum “lock-in” from current infrastructure. For technologies projected to decline under the 2° scenario, the gap between current capacity projections and capacity consistent with the 2° scenario should be seen as an estimate of the capacity that would need to be retired to be in alignment with the 2° scenario.
What questions about transition risk does this scenario analysis seek to answer?
Current Exposure: What is the current exposure of the portfolio to economic activities affected by the transition to a low-carbon economy?
Trajectory: Does the portfolio increase or decrease its alignment with a 2°C transition over the next 5 years?
Future Exposure: What is the expected future exposure to high- and low-carbon economic activities?
The combination of 1, Current Exposure, plus 2, Trajectory, determines 3, Future Exposure to energy technologies.
This analysis was done at the individual insurer level as well as at a “macro” level - i.e., for all insurers taken as a whole. For the macro analysis, the debt and equity holdings of all insurers in the sample were combined into two portfolios: an aggregated fixed-income portfolio and an aggregated equity portfolio.
Aggregated fixed income and equity portfolios of all insurers. Complete results (current, trajectory, and future exposure) for the aggregated fixed income and equity portfolios of all insurers included in this assessment can be downloaded. The information on the "Trajectory" and “Trajectory - Fossil Fuels" tabs on this web site are excerpts from the complete results that relate to question 2 above.
Fixed income and equity portfolios of individual insurers. Individual insurer reports, including information addressing questions 1, 2, and 3 will be sent to the top 100 insurance companies by size of their investment portfolio operating in California with more than $100 million in premiums. Additionally, building on the Commissioner’s request to divest from holdings of thermal coal, reports will be sent to insurers outside of the top 100 whose exposure to thermal coal production or coal-fired electricity capacity is beyond the 95% percentile of exposure for all insurers in these technologies. Finally, insurers that are not in either group can request a copy of their individual insurer reports by emailing email@example.com.