Risk.net convened a panel of three experts from different fields to discuss some of the most pressing and pertinent climate-risk related issues, each offering different insight to the discussion from their respective backgrounds, providing an exchange of ideas on the importance of the financial risks and opportunities of climate change
- Matthew Lightwood, Director, Risk Solutions, Conning
- Nick Stansbury, Head of Climate Solutions, Legal & General Investment Management
- Robert Litterman, Chairman, Climate-related Market, Risk Sub-Committee, Commodity Futures Trading Commission
Averting catastrophic climate change is a big ask for a nascent discipline, yet effective climate risk management could do exactly that. Only by quantifying and repricing risk will the correct price signals be sent out across the economy to channel investments away from polluting activities and into the required clean energy and green technologies.
The myriad ways in which decarbonisation could be achieved, and the countless unknowns that will pop up along the journey, make climate risk management exceedingly challenging. This is why discussion and exchange of ideas on the financial risks and opportunities of climate change is so important. In this Q&A, three experts answer some of the major questions being asked about the discipline today, each bringing a different angle to the debate.
What can be done to improve the level of climate risk disclosure from capital markets participants and mid-sized to large corporations? How important is it that firms follow the guidelines of the Task Force on Climate-related Financial Disclosures (TCFD)?
Matthew Lightwood, Conning: It is essential that governments adopt a consistent global reporting standard for climate disclosures and write these into law. They need to be sufficiently detailed so investors can unambiguously differentiate firms from one another. Also, I see a lot of claims around net-zero ambitions and a need for more rigorous testing of the assumptions around the magnitude of the netting effect of some initiatives. There is a great degree of scepticism among the general public on this issue, and we won’t get a second chance to get it right.
Nick Stansbury, Legal & General Investment Management (LGIM): There are two main routes to improving disclosure: investor pressure and regulatory change.
Disclosure should be a key element of investor engagement with investee companies. Without carbon data, it is difficult for investors to understand their investments’ climate risk exposure and evaluate their climate impact. The TCFD provides best-practice guidance on climate reporting for different sectors, and can be used as a checklist when evaluating investee companies’ disclosure. Investors can set their own minimum standards based on this checklist – a ‘must-have’ list – and impose voting or divestment sanctions where these are not met.
Policy-makers must enshrine their own minimum standards into relevant regulation. This is already happening, with significant regulatory momentum observed across the world. In many jurisdictions, such as the UK, mandatory disclosures will be directly based on the TCFD guidelines. Companies must follow these guidelines as soon as possible if they are to avoid a costly crunch when recommendations become requirements.
What role will voluntary carbon markets play in the energy transition over the next few years, and how will they develop?
Matthew Lightwood: While I think voluntary carbon markets are admirable, there is a risk of them being used by the worst emitters to do less than they could on reduction. The scale of emissions is so much greater than our ability to scale carbon-reduction technologies that I worry we are overestimating the impact these schemes can have on the problem at hand. I think a compulsory cap-and-trade system would have a larger impact. This was highly effective at combatting acid rain in the 1980s and could contribute here too.
Robert Litterman, Commodity Futures Trading Commission: Many climate scientists and conservation experts believe protecting existing forests and regenerating degraded forest lands are the least expensive approaches to increasing the earth’s ability to pull carbon dioxide out of the atmosphere. These critically important activities have not scaled up in recent decades, however, because they require investments that have, to date, been voluntary, with no promise of return. Few investors participate in the voluntary market because, while it may make them feel better, it provides no opportunity for financial returns.
For the forest carbon credit markets to scale, they must provide positive expected returns to investors. This can be achieved by using remote sensing technology to create real, measurable, auditable and high-quality carbon fluxes to which carbon credits can attach ownership rights. By measuring carbon content and flux of landscapes, as well as political jurisdictions, such technology can address the key issues of permanence, additionality and leakage.
Just as financial markets create large, liquid markets for mortgages – which are packages of risky cashflows backed by idiosyncratic properties – those markets can create liquidity and scale for forest carbon credits. To do so, however, these credits cannot be voluntary, but must be investable securities representing insured claims on future carbon fluxes that are expected to have compliance value, and thus generate positive expected returns for investors.
Do you expect an industry-standard climate risk stress test to emerge?
Nick Stansbury: There have been calls for more standardisation in climate risk analysis. It is important to distinguish between three important dimensions along which this could take place: scenarios, methodologies and outputs.
The first element that could be standardised are the scenarios companies consider. This is, in effect, the ‘input’ of the stress test. For example, the Network for Greening the Financial System (NGFS) provides a standard set of scenario narratives, which it says provides a point of reference for climate risk analysis. These may come close to representing an industry standard. Standardising scenarios could ensure some degree of comparability across analyses from different companies. It could ensure companies don’t only stress-test against scenarios designed to be less disruptive for their business model. However, given the degree of uncertainty around future climate outcomes and the pathways of getting there, complete standardisation would do more harm than good.
The second element would be the methodology with which companies analyse their exposure. The same scenario could represent different levels of risk depending on the method of quantification. Given the complexity of these analyses, numerous assumptions are needed to arrive at a climate risk number. As companies often disclose only a limited number of these assumptions, comparisons across different climate risk numbers can be challenging for third parties. Especially if the third element – outputs – also differs across analyses.
The best outcome could be a mixture of standardisation and freedom: ensuring companies stress test against a set of standard scenarios, given a specific methodology, and producing a specific set of outputs and allowing them to explore their own specifications in addition to this.
Matthew Lightwood: Yes and no. I think some standardisation is likely because most of what we have seen so far has been based on the NGFS framework in some way. However, what we are seeing more and more is a move away from highly prescriptive stress tests and towards a more interpretative approach. For example, the Bank of England’s (BoE’s) Climate Biennial Exploratory Scenario (CBES) defines a very wide range of financial, economic, transitional and physical climate risk scenarios, and it is very much up to the insurer or bank to make use of those and think about what it means to their business. This is very deliberate; regulators want risk departments and boards to put some effort in to understanding their particular exposures to the risk.
How should firms incorporate climate risk within their strategic and risk management frameworks?
Matthew Lightwood: This is the third pillar of climate risk reporting from a regulatory perspective. First, insurers have to size the risk, understand the impact on their firm’s business model and, finally, management needs to decide how to use this information to inform future strategic decisions. This third step is extremely challenging in practice because, until there is firm action from governments on the cost of carbon, it is difficult to see what management actions might be appropriate today that would also align with their basic fiduciary duties. There are perhaps some exceptions to this on the liability side and also when we start to consider reputational risk, but I don’t see markets realigning themselves without some policy action as a trigger.
What have been the most important developments in the field of financial climate risk modelling in recent years? What are the key challenges to modelling climate risk exposure in a portfolio?
Nick Stansbury: Climate risk modelling is a relatively new discipline, but it has evolved considerably since 2017 when the TCFD first recommended climate scenario analysis for risk management purposes.
First, the diversity of climate scenarios has grown significantly. There are now many more organisations and companies providing possible pathways to a given climate outcome, not least the NGFS. There are also more destinations being considered – especially around the 1.5° Celsius outcome, which rose to prominence following a special report from the Intergovernmental Panel on Climate Change (IPCC) in 2018.
Second, climate science has evolved. Climate change and associated risks can be modelled with greater certainty than before. New carbon budgets indicating the amount of carbon humanity can emit before reaching a certain temperature outcome by the end of the century have been provided by the IPCC, most recently in August 2021.
Third, companies have developed their modelling capacities. Taking climate scenarios and translating them into financial impacts – or indeed quantifying the impacts of companies on the climate – were not common practice prior to 2017 outside of the energy sector. Now, many companies – especially investors – have internal modelling capabilities specialising in their individual interests.
The key challenge for investors when modelling portfolio risk exposure is to capture the individual investment context while enabling big-picture conclusions. The transition will not affect all companies in a sector in the same way: a company’s financial situation, carbon performance, asset locations and many more factors play important roles in determining risk. Yet the amount of data required to evaluate company-specific risk is very large, and can be patchy, especially around issues like Scope 3 emissions and physical assets. Collecting all available data on an entity and filling any gaps is time-intensive, but as much of a portfolio as possible must be captured to arrive at a meaningful high-level conclusion. Therefore, the key challenge is the balancing act of capturing investment-level detail and providing meaningful high-level results.
Robert Litterman: It is important to separate the growing specific climate risks that threaten individuals, companies, cities and regions from the longer-term aggregate systemic risk that faces humanity globally. The former are mostly local, measurable impacts of extreme weather events or sea-level rise, and can be adapted to, mitigated and insured against, whereas the latter are difficult to quantify and can be addressed only through urgent aggregate collective action to reduce global emissions.
The explosion in the availability of public data, analytic approaches and experience in addressing specific extreme weather impacts means corporations are much better able to address, measure and disclose specific climate risks. Public and private climate risk analysis and understanding has increased greatly in recent years.
While these specific impacts will grow, they will differ by location and business sector, and aggregate portfolio climate risk exposure will likely emerge more slowly over time as individual specific impacts increase in size and frequency. Aggregate risk will increase to the extent that specific climate impacts deplete aggregate financial resources. Though less understood – and perhaps less likely – the most dangerous long-term climate risks may well be caused by non-linear responses to impacts that emerge suddenly and had not even been recognised ahead of time.
Matthew Lightwood: The availability of data and the development of some freely available detailed scenario sets have made the task of defining climate stress tests much simpler. Then there has been the development of software solutions that help make those scenarios implementable and to turn them into analytics. This has been key – seeing systems becoming available to make the process practicable.
One of the main challenges is centred around the fact there is no really robust way of pinning economic and financial market effects on a particular climate scenario. Trying to understand the distribution of possible outcomes is key. A transition to a low-carbon economy, for instance, may have the potential for upside as well as downside – spurring innovation and fiscal stimulus, perhaps. A deterministic stress test doesn’t really tell you anything about that, so we’ve been developing techniques that model the range of outcomes using the stochastic modelling techniques in which we already have expertise. This really helps to capture the uncertainty in the future market impacts of climate risk and avoid the pitfalls of false precision.
How are developments in technology and analytics helping with climate risk management?
Robert Litterman: Climate risk is an emerging scientific field with an explosion of data gathered through remote sensing and satellite imagery, large-scale modelling and forecasting abilities. As a simple example, the science of rapid attribution of extreme weather events to climate change, based on climate simulations with and without changes in atmospheric greenhouse gases, has emerged in the past decade, allowing the public to make the connection between local impacts and climate change. This increased public understanding supports appropriate government policy as well as private adaptation and mitigation strategies. Another example is the ability to project sea-level rise at very fine granularity, which allows homeowners and businesses to gauge the adequacy of their mitigation efforts.
Matthew Lightwood: We have seen a big spike in companies looking for technological solutions to help them make sense of the emerging regulatory requirements around climate risk. Within insurance this has centred around the Own Risk and Solvency Assessment and the type of scenario analysis requirements the BoE and the UK’s Prudential Regulatory Authority released as part of its CBES exercise earlier this year. We have been working with a number of clients to develop a cloud-based stochastic scenario analysis tool, which enables them to assess the impact of climate scenarios on the asset side of the balance sheet in a more quantitative way. Having a pre-packaged and implementable solution to these standardised stress tests is proving very popular, particularly for mid-sized insurers that maybe don’t have the resources to have a dedicated climate or environment, social and governance (ESG) risk person.
What are the most important metrics for measuring climate risk? Can it be quantified in a similar way to market risk or do factors such as sentiment and reputation make it a ‘soft’ rather than ‘hard’ discipline?
Matthew Lightwood: I think it is both. We are seeing the types of quantitative analysis we are doing with clients is being used to feed into those softer qualitative discussions. Climate is definitely a branch of market risk, whereas ESG is more a governance issue with climate as a related topic.
Nick Stansbury: LGIM believes it important to consider climate risk from two angles: first, the risk that climate change and any policy response represent to companies; and second, the risk that companies represent to climate change. We see asset valuation risk as capturing the first dynamic, and temperature alignment as capturing the second.
Climate risk can and should be quantified in a similar way to market risk. That is the only way the results of climate risk stress-testing will be taken seriously by market participants. Of course, there are weaknesses in this approach: not all elements of climate risk can be meaningfully quantified, and even those we can quantify carry an unusually high level of uncertainty.
Areas with potential climate-related risks that are difficult to quantify in a meaningful way are reputation and litigation risk. As the impacts of climate change worsen, firms that do not align with a low-carbon transition could lose their social licence to operate and see consumers shift demand elsewhere. For high emitters, there is an additional question: will they one day be held to account for the climate risk they contributed to through historical emissions? The science around attribution of individual climate-related events such as hurricanes and flooding to specific emitters provides insufficient grounds for such lawsuits – but this could change in the future, with significant financial consequences.
Even elements that can be quantified are likely to carry a much higher amount of uncertainty than typical market risk metrics. There are many reasons for this, including the unprecedented nature of the risks and the unusually lengthy time horizons considered. Yet they provide invaluable insights into the significance of climate risk and must be quantified, despite shortcomings. Over time we can work on adding capacity to quantify the ‘softer’ parts of climate risk previously mentioned, as the science and sentiment around climate change are constantly evolving.
The panellists’ responses to our questionnaire are made in a personal capacity, and the views expressed herein do not necessarily reflect or represent the views of their employing institutions
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