It’s not without reason that the 2020s has been widely labelled ‘the climate decade’. The reality is that if the world is to go close to achieving the 2015 Paris Accord target of a 1.5⁰C global temperature increase above pre-industrial levels, we have to effectively halve greenhouse gas (GHG) emissions by 2030, and achieve net zero or even negative carbon emissions by 2050.
The way the world does many things is going to have to change, but in a way that enables the global economy to carry on functioning through the transition at the same time as dealing with the increased regularity and severity of extreme physical weather events and natural catastrophes seen in recent years.
Life insurers should have a significant interest in how this transition occurs - beyond the pressure placed upon them by regulators and governments in making climate-related financial disclosure mandatory for the industry, or indeed any ESG (Environment, Social, Governance) or reputational considerations.
“...critically, there is the matter of how insurers bind these factors into an integrated asset and liability management (ALM) approach.”
First, there is the matter of how companies can exert their influence and allocate funds as investors to both achieve returns and support transition. Second, there are the consequences that higher levels of projected climate change and less orderly transition would have on health and demography, and thereby future liabilities, products and profitability. And then, critically, there is the matter of how insurers can bind these factors into an integrated asset and liability management (ALM) approach – something that has typically been absent thus far from many companies’ responses to climate risk.
To date, transition risk has been mainly regarded as an asset holding issue – and there are undoubtably challenges ahead on this front.
From an investment point of view, what is very important to realise is that the nature of the investable universe will be very different, particularly where it relates to infrastructure development and the effect on currency denominations of the available opportunities such as localised wind or solar farms. Furthermore, some industries, particularly those associated with higher GHG emissions, may have to be nursed or encouraged to become very different businesses in the future – or potentially face having no future at all.
Asset valuations of equities, debt and sovereign credit will also all be impacted. The starkest demonstration of these impacts comes from some analysis we have done of the effect of a maximum climate transition on the valuation of Europe’s top 50 companies versus market expectations. Willis Towers Watson’s analysis shows up to 60% climate transition value at risk (CTVaR) for some integrated oil and gas companies. Since the transition rate will obviously vary over time (as has happened during the COVID-19 pandemic) and region, this type of analysis also enables the user to track transition risk-adjusted performance against a base index.
As a starting point, we recommend three general ways to look at transition. For investments in the commodity/resources industries, the focus should be on modelling demand curves and the impact of different climate scenarios in tandem with factors such as policy, innovation, regulation and costs of production to assess prices or the longer-term viability of an asset. In manufacturing, the main factor is the impact on the size of the market and margins, while in services the key point of evaluation is the impact of transition on clients and how this would affect things such as the size of the market or market share.
“The importance of modelling a specific asset or portfolio of assets is brought home even stronger by our analysis of the ineffectiveness of existing measures of transition risk.”
So, when thinking about how to address investment transition risk, life insurers will need to look at potential transition paths industry by industry and technology by technology, such as the impact of the rate of adoption of renewables. From there, it’s possible to extrapolate how these paths will affect, for example, margins, prices, cash flows, future market size and finance costs. Also, these provide the basis for assessing what the implications will be for asset values and valuations (the CTVaR) of specific investment opportunities or portfolios based on the projected pace of and reaction to transition and the impact on cash flows.
The importance of modelling a specific asset or portfolio of assets is brought home even stronger by our analysis of the ineffectiveness of existing measures of transition risk. One of these is carbon intensity. Our CTVaR analysis of a sample of European fund mangers’ equity portfolios (Figure 1) has shown a weak correlation between higher carbon intensity and transition risk. Similarly, portfolio ESG scores appear to be misleading, one potential reason being that portfolios that are seen as more exposed to climate and transition risks may be more motivated to display ESG credentials.
Source: Willis Towers Watson analysis (for ‘well below 2⁰C’ scenario).
Therefore, if investors, such as insurers, don’t do more granular analysis, there is certainly potential to get asset selection and mix wrong in the context of climate transition.
But insurers won’t be able to afford to only focus on the asset side of the balance sheet as climate transition occurs. Transition risk brings many potential factors into play that are likely to affect life insurance liabilities and therefore the product design, profitability and asset matching associated with those liabilities.
Figure 2 illustrates how climate change potentially affects the environmental, socio-economic and geopolitical determinants of health and the ability to adequately fund healthcare needs. It underscores the complex relationship between climate change and global health.
So, what does this mean for life insurance liabilities? In this respect, climate change and climate risk are two different things. From a best estimate perspective, insurers need to think of climate change in terms of expected changes in, for example, temperature, precipitation or oceanic currents. This leads on to the expected economic, geopolitical and environmental effects that will arise from those physical climate changes, such as flooding rendering land unusable or uninhabitable. Climate risk on the other hand represents how wrong those estimates could be and the implications for future liabilities under varying climate scenarios.
The key point is that life insurers can’t start to quantify climate risk in mortality and morbidity assumptions without knowing what the best estimate assumptions imply about a view of climate change and how wrong it could be.
“Put bluntly, many life insurers have no idea how climate change is reflected in their best estimate mortality and morbidity assumptions.”
Right now, however, we would say the bulk of the industry doesn’t consider the expected future impacts of climate change but instead ignores them, assuming that extrapolative models of mortality improvements (for instance, the CMI_20xx models) based on data containing the past effects of climate change will include a suitable implicit, albeit unquantified, allowance for the future effects of climate change. Put bluntly, many life insurers have no idea how climate change is reflected in their best estimate mortality and morbidity assumptions.
So, what can life insurers do about it? How can insurers model climate risk as it relates to future life insurance liabilities?
Using a fairly standard approach of breaking down a complex problem into many smaller problems, academic studies have looked at a variety of the health, socio-economic and demographic impacts of climate change. From these, it’s possible to parameterise and aggregate them in a driver-based model – an example being the effect of extreme rises or falls in temperature or increases in air pollution on excess deaths.
However, not all climate effects have been researched in this way. Future effects such as sea level rise, threats to food security and mass migration are less easy to quantify. For those risks, the way forward is a scenario-based approach to arrive at a range of plausible impact estimates and their effect on economic activity and healthcare provision. Without this level of analysis, it’s likely that climate change best estimates and climate risk assumptions will be too narrow and simplistic.
Scenarios are useful for many reasons, but two reasons in particular:
In essence, they provide a tool to encourage risk awareness and action.
Developing those scenarios will involve asking a number of questions. The first step is to think about what defines different scenarios in the sense of the physical climate impacts and the nature and timing of policy, regulation and mitigation actions. Next comes an evaluation of the consequences other than for health of a specific scenario, such as the economic and geopolitical impacts. And then the last step is to make an assessment of the health implications, such as increases in disease, a rise in health inequity or the potential public health response.
“[Scenario analysis] offers a route to a more complete understanding of climate risk inherent in best estimate assumptions.”
By way of illustration, take a scenario where people choose or are forced to switch to a largely plant-based diet in the future. Potential actions of interest would include taxation, removal of meat products and consumer behaviours. Consequences to consider would include a reduction in carbon emissions from reduced livestock farming, a slowing or reversal of deforestation and, potentially, changes in international trade. And finally, health impacts to analyse for assumption setting would be likely to include changes in diabetes rates and cardiovascular disease but also the health and employment implications, including healthcare provision, for different socio-economic groups.
Nonetheless, these questions only skim the surface of those that could be investigated. But, scenario analysis, whilst complex and reliant upon expert judgement, offers a route to a more complete understanding of climate risk inherent in best estimate assumptions. Techniques such as Bayesian network models can help to combine judgements to form an overall view of the potential impact. This improved understanding of how climate risk alters best estimate assumptions of liabilities is also likely to be a key tool in informing future pricing, capital and risk management (see Figure 3) in what is, by its very nature, is a complex and uncertain issue.
| Pricing | Capital | Risk Management | |
|---|---|---|---|
| Properly understand best-estimate | ...then assess uncertainty... | maintain and display understanding | |
| Protection | Short-term volatility Extreme events Changing risk of future pandemics |
Add scenarios to mortality / morbidity and catastrophe risks Capture volatility associated with extreme events |
Monitor climate sciences and direction of political action Update BE projections and associated assumptions regularly |
| Annuities | Reflect long-term trends Impact of mitigation strategies (policies and lifestyles changes) |
Consider new information risk scenarios with extreme mitigation strategies and behavioural changes | Include liability-side risk in climate risk disclosures Consider information requirements of providers of capital |
What we can say with certainty though is that climate change and the transition risk it implies for life insurance is going to impact all parts of the business. The traditional view of transition risk as almost exclusively an asset issue will increasingly be too narrow. Similarly, basing the assessment of climate risk arising from transition simply upon the experience of climate impacts to date will leave companies at a disadvantage.
By bringing an enhanced understanding of physical climate and transition risk to both the assets and liabilities sides of the balance sheet, while concurrently advancing asset stewardship and climate-awareness in their own organisations, insurers should improve their chances of effectively adapting to the changing market and the climate-related regulatory, legal, economic, consumer, geopolitical and healthcare factors that will increasingly shape it.
Richard Marshall is a Director in WTW’s Insurance Consulting and Technology business and leads the development of mortality and demographic risk models for our UK business.
