As temperatures break records during the recent UK Bank Holiday, Climate change remains centre stage of our social narrative. While the heat and the claims of imminent apocalypse continue to grow, at Quant Foundry we believe that the time is right to apply some cool heads and look at how we can translate the output of climate models into response strategies for decision-makers.

The models around climate change focus primarily on a “tipping point” feedback scenario that results from a thermodynamic imbalance in the atmosphere between the addition CO2 we produce and the surrounding water vapour. The feedback loop accelerates the predicted increases in global temperature from the current 1C to closer to 4C. 

To avoid such a scenario, the IPCC and governments recognise that the world needs to reduce our output of CO2 and migrate to a net-zero paradigm by 2050. The Bank of England (BoE) has picked up the need for insurers and banks to respond appropriately. In their supervisory statement (SS3/19), the BoE is challenging banks and insurers to measure the financial risks that could emerge during the transition to a low carbon future.

Climate change can look like something that is simply a matter of improving corporate governance and social responsibility. Banks and insurers need to avoid the temptation of token market signalling such as buying credits to offset their office and travel carbon footprint and consider their role in financial intermediation within this new world order.

Banks and insurers need to view climate change as a new and long-dated component in their credit framework based on the following new risk factors: –

  • Physical risk where changes in climate create more frequent and extreme events such as flooding impact on assets such as house mortgages and forest fires that dragged PG&E into default
  • Transition Risk where the balance sheet of large producers and consumers comes under strain as they shift away from fossil fuels and adopt renewals

Our purpose at Quant Foundry is to help banks and insurers measure the impact on their balance sheet of the risks associated with climate change. The banks do not have the climate-related data necessary to create the scenarios at a corporate or instrument level. The acquisition, normalisation and integration of the data together with a completely new model approach costly for all firms.

Imperial College Grantham Institute has developed a world-leading model of the global economic transition, which defines decarbonisation pathways in a consistent way across power generation, transport, buildings, and industry.  These can be aligned with physical risk analysis to provide a comprehensive scenario picture for all affected sectors. Our credit model integrates with the Imperial model to achieve the following: –

  • For each path, our credit model measures the revenue and credit quality impact as each corporate executes a multi-year transition strategy
  • Our model estimates the increased likelihood of events from Physical Risk, together with its revenue and cost implications
  • The Quant Foundry aggregates the risks of corporates located in at-risk countries. Physical risk leads to a catastrophic loss of infrastructure, leading to corporate exit that impacts the quality country’s external debt.

Over the summer, we have also been working with Imperial College on a research project that is analysis the exposure of major European generators to transition risk. The prototype we have built highlights the challenges that each management team have in making strategic decisions around transition to renewables within the confines of the capacity of the European economy to absorb the expected disruption. 

We measure the optimal renewables mix for each generator while holding onto their cash to pay down liabilities and to absorb the shocks of assets rolling off. The conclusions from the white paper are due in April 2020, and we expect it to provide insight on the degrees of freedom generators have to adapt their business model to complete the transition to a new low carbon paradigm.