Climate risk stress testing: From predictions to preparedness

The rising tide of climate risk stress testing

Employing a dual methodology of climate risk stress testing and scenario analysis, is an approach that gains increasing traction within the financial industry. As previously highlighted in ‘Climate risk management: Navigating the heat in a changing world’, this combined methodology offers a robust and comprehensive strategy for managing climate risks across diverse timeframes. A significant catalyst for this growing interest is the European Central Bank (ECB), which mandated the first European Climate Risk Stress Test (CRST) in 2022.

The ECB’s subsequent report sheds light on several key areas. It highlights the significant strides banks have made in enhancing their stress testing capabilities, yet also underscores persisting gaps. Intriguingly, the report indicates that the anticipated losses from both transition and physical risks might underestimate the genuine or projected severity of these challenges. This trend mirrors results from prior voluntary, organisation-driven climate risk stress tests. While limited data access and suboptimal stress testing models are frequently cited reasons for this disparity, it’s equally vital to critically evaluate the stress testing scenarios in use.

Scenario analysis: The backbone of stress testing

Capturing the multifaceted dimensions of climate change within a singular stress testing scenario presents a considerable challenge. For every scenario, it’s essential to project future greenhouse gas emissions, ascertain the rate at which the planet will warm in response to these emissions, evaluate the societal repercussions, interpret economic consequences, and ultimately determine the financial impact on individual firms. Adding to these complexities is the scarcity of relevant historical data to inform models, given the unprecedented scale and urgency of the transition needed to stay within planetary boundaries. Both the inherent challenges of climate change and the difficulties in modelling them ensure that climate risk stress tests possess distinct characteristics:

1. Timescale differences: Climate risks, especially physical ones, manifest over longer periods compared to the immediate financial shocks of traditional stress tests. Thus, climate scenarios often depict gradual shifts rather than sudden changes.

2. Pathway shapes: These smooth pathways tend to be ‘L-shaped’, particularly after climate tipping points have been crossed, implying they form a new baseline. This is a distinct difference compared to the ‘V-Shaped’ scenarios used for traditional stress tests, where a shock event is followed by recovery.

3. Origin of risks: Traditional stress tests typically stem from financial shock events. In contrast, climate risks are more inclined to emerge through the real economy. Given the nuanced relationship between banks and the real economy, predicting shocks and significant loss events becomes inherently more complex.

4. Narrative simplifications: Both traditional and climate risk scenarios offer a condensed narrative of potential futures. However, due to the multifaceted and interconnected nature of climate risks, oversimplifications can have magnified consequences. Often overlooked dynamics, such as the interplay between physical and transition risks, tipping points, and potential disruptive socioeconomic factors like mass migration, are central to understanding the profound threat climate change poses to the financial system and future generations.

The inherent complexities of climate risk scenarios and their foundational models yield interesting results. A recent report of the Institute and Faculty of Actuaries in collaboration with the University of Exeter underscores this: the projected impact of a hot-house world scenario on global GDP by 2100 varies dramatically, ranging from a 73% decline to continued growth, which is counter-intuitive given the severe physical risks anticipated if temperatures continue to rise. Under the NGSF’s hot house ‘current policies’ scenario, which forecasts a temperature rise of 3.2°C, the projected GDP decline by 2100 stands at 18%. Importantly, this projection omits impacts associated with ‘extreme weather, sea-level rise, or broader societal effects from migration or conflict’, as well as the costs of adaptation, which could intensify the overall impact.

Bridging the gap: From scenario analysis to organisational resilience

Given the complexities and uncertainties inherent in the process, from scenario creation to modelling, it’s essential to approach the final quantitative climate risk stress test outcomes with caution rather than as definitive predictions. Nassim Nicholas Taleb insightfully remarked in his renowned book ‘Fooled by Randomness’:

“A model might show you some risks, but not the risks of using it. Moreover, models are built on a finite set of parameters, while reality affords us infinite sources of risks.”

However, this observation doesn’t negate the value of tools like climate scenario analysis and climate risk stress testing. While it’s important to recognise that the current maturity and confidence of climate risk models—and by extension, the outcomes of climate risk stress tests—may not meet the standards traditionally expected for decision-making, these results can act as a springboard for discussions on climate risk within organisations.

At RiskSphere, we firmly believe that these conversations are instrumental in building long-term resilience within financial institutions. Instead of accepting the outcomes of the climate risk stress tests at face value, they should be utilised as a guidebook. This approach helps in identifying and understanding risks and opportunities across various horizons, ensuring they are addressed in a coherent and purpose-driven manner. To facilitate this, RiskSphere has developed an ESG risk management framework. This framework not only encompasses risk identification, climate risk scenario analysis, and stress testing but also emphasises unlocking the deeper insights from these outcomes through interactive brainstorm sessions, ultimately leading to robust climate risk management.