Understanding the risk exposures due to Climate Change remains a challenge across the financial services industry given the inherent uncertainties and long-term time horizons. Using a set of event-based scenarios as a translation mechanism can help identify structural exposures in business and operating models and provide a basis to enhance scenario design and forward-looking risk management.
Most current methodological discussions involve some form of long-term scenario analysis, projecting climate and economic variables and modelling the impact on balance sheet, P&L and key risk metrics of financial institutions and their customers. As an output, this produces quantification of losses across various time horizons.
These may happen – or not. Most corporate valuation methodologies apply a terminal value after a 10-year time horizon for a reason. While risk management of banking institutions must pay attention to long-term developments, at a certain point quantifying these becomes spurious given the complexity of the evolving systems under consideration; in particular when considering the medium- to long-term adaptive capacity of society or aspects thereof. In addition, capturing complex relationships between different events remains a challenge even in sophisticated scenarios. This has been highlighted by the current Covid-19 crisis, which has been a challenge for the current risk assessment toolkit due to its complexity and dynamic nature.
Mindful of the importance of climate change to financial stability, regulators are on a similar journey to industry to define expectations and effective supervisory practices. While acknowledging methodological shortcomings, significant emphasis is currently placed on overarching exercises, such as the Bank of England stress test on the financial stability implications of climate change, to provide some initial understanding of financial sector vulnerabilities and support the industry dialogue. However, recent publications by the Basel Committee on Banking Supervision (https://www.bis.org/publ/othp31.pdf) and the European Central Bank (https://www.bankingsupervision.europa.eu/legalframework/publiccons/pdf/climate-related_risks/ssm.202005_draft_guide_on_climate-related_and_environmental_risks.en.pdf) show that thinking is moving beyond stress testing towards a more holistic approach expanding the existing Enterprise Risk Management framework.
Climate change is commonly accepted as a theme interacting with the existing risk taxonomy, amplifying individual risks but not introducing fundamentally new risk types. What is currently missing is a “translation” mechanism to identify how climate change impacts institutions with different business mix, operating model and risk profiles. In this article, we set out what such an approach could look like and briefly discuss how to use this to enhance risk identification and stress testing practices
Thinking outside the box – An approach to mapping climate and environment-related risks into the risk taxonomy
The TCFD recommendations (https://www.fsb-tcfd.org/publications/final-recommendations-report/) provide a classification of climate and environment-related risks commonly adopted across industry. This includes transition and physical risks, which present some interesting methodological challenges as some of the “risk types” (e.g. policy decisions and technology developments) include events that are close to certain to occur (e.g. transition away from fossil fuel-propelled mobility) while other risks such as acute physical risks remain highly probabilistic.
The “transition” risks have a plannable element to it given the rich body of materials on what needs to happen to keep the world on a sustainable pathway. Scientific publications as well as climate objectives that individual countries have committed themselves to provide a means of defining a set of events that could take place as part of a transition pathway, and analyse the potential impact on the institution in question.
The defined set of events can be used to identify how climate change could impact business and operating models across different time horizons. This provides an intuitive way of identifying the risk profile due to climate and environmental risks, as well as provide a view on the materiality of these risks. It also provides a basis to evaluate what would happen if certain events were to be deferred or take place in a different shape – or not at all.
An example of this is structural transitions that will take place in industry and society. In developed countries, the transition to electric mobility and promotion of different mobility concepts are part of the sustainability road maps. This is expected to have a transformational impact on the automotive sector, as it may fundamentally reshuffle industry dynamics and has the potential to lead to significant job losses in a country such as Germany given its strong dependency on its car makers and the surrounding cluster. It is straightforward to identify that this will impact wholesale credit risk, but indirect effects are equally important. Should material job losses occur, this may negatively impact regional economies and in turn have a material impact on an institution with regional concentrations in residential real estate.
A second example could be looking at offshored activities and the exposure to changes in the hospitability of individual regions. Periods of temperatures closing in on 50 degrees centigrade and recurrent water shortages in parts of India can have significant impacts on operating capacities of offshored activities, causing disruptions to important processes of global banking groups. This could contribute to a host of operational risks depending the nature of outsourced operations, including model risk, compliance and timeliness/quality of management information.
Identifying and defining a catalogue of event-based scenarios provides institutions with an intuitive way of understanding where the material risks sit across different time frames. A logical assessment framework can be used to define the likely shape of specified events, and what the expected timeline could be. In the example of the transition to electric mobility, electricity grids need to be able to sustain a much greater and more volatile demand. Combined with the ambition to transition to Carbon-free energy generation, this means that a phase-out on a scale of 60-80% is unlikely to occur before the 2030s even in developed nations – and may not be feasible as such in developing nations.
In the short term, the identified set of scenarios can be used to design better overarching stress tests, including alternative scenarios to test resilience against unexpected abrupt transitions in the global, regional or local socioeconomic system. In the longer-term, the ability to obtain numerically accurate estimates fades into the background to some extent, as it becomes more important to understand where the material exposures in business and operating model sit, and what could cause these to materialise.
It is impossible to predict the future – yet we have a range of tools that help financial institutions to analyse and understand complex systems and prepare for potential undesired events. The financial crisis, the fallout of Covid-19 that we are currently living through and the growing impact of climate change around the world illustrate a need to evolve the current enterprise risk framework to enhance the ability to analyse, prepare for and respond to system-wide shocks and transitions. Warning signs can be there for months or years in advance, but are too often not proactively addressed, with governments and industry scrambling to deal with the fall-out after the incident.
A structured assessment framework combining quantitative data points and expert judgment can help in analysing the event in question and define indicators for changes in expected time frames when the event could materialise. This provides a basis for enhancing current risk appetite concepts to accommodate longer-term time horizons.
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WP Dr. Michael Rönnberg
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