09 June 2021 5 min read

Climate risk advisory for Legal & General Investment Management

Enhancing Climate Change scenario modelling capabilities and incorporating climate change transition risk into a risk and investment frameworks

Climate change is unsurprisingly driving revolutionary change in the global and regional energy sectors. Its firms are not only having to adapt and evolve themselves but they are responsible for supporting companies and households to transition towards a lower carbon world.

Given the way this transition will occur over the long-term is dependent on a range of complex, inter-related factors (policy, technology advancements, consumer demand etc.), it is critical to develop scenarios in a consistent and rigourous approach to explore and evaluate the potential impacts to energy companies and therefore, firms that invest in and have financial exposures to these energy companies.


Client challenges

In order to understand the risks and opportunities this transition presents for the energy companies in LGIM’s portfolio, they were seeking a tool to:

  • Generate internally consistent scenarios of the evolution of the global energy system at regional level under different scenario of climate change over the long term (to 2050 and potentially 2100)
  • Assess the potential financial impact of these scenarios on LGIM

Crucially, the scenario analysis capability required the flexibility to:

  • Run scenarios on any GHG emissions pathway specified, incorporating L&G projections for specific firms/parameters while allowing the model to project remaining factors
  • Generate and pivot results flexibly to meet a wide range of internal and regulatory demands, allowing the results to be embedded into risk/investment frameworks


Baringa's role

Baringa designed and developed a framework to model [1] the global energy transition across multiple scenarios. The least-cost optimisation model required an initial data set of 500,000+ data points, drawing from Baringa’s in-depth expertise of decarbonisation across several markets to research and consolidate these inputs. This allowed the optimisation model to be solved up to 2050.

Baringa also passed the model through rigorous testing and validation, for example through benchmarking against published global scenarios (IEA World Energy Balances, IEA Energy Technology Perspectives, etc.).


Outcomes and impact

This enabled LGIM to develop and explore specific scenarios in a fully integrated way, understanding the interactions between different regions and sectors through a completely consistent and rigorous approach.

Through benchmarking against other scenarios, LGIM were able to challenge third party scenarios and interrogate their own underlying assumptions and sensitivities to iteratively improve the accuracy of the model inputs, methodologies and outputs.

The capability to refine inputs/scenarios and analyse the estimated financial impacts at various levels of granularity (global, regional and even down to the individual firm level) created a structured and repeatable approach for translating climate change transition risk into the overall investment framework, driving sustainable financing decisions.

David FitzGerald, Director, Climate Risk, Baringa: "Analysing the climate risk across a portfolio of this size exposes totally unexpected pockets of strength and weakness. A whole new level of decision support comes into play, all the way from the asset level to the strategic direction."

Martin Brookes, Director of Investment Strategy at Legal & General Plc: “We are excited to have worked in partnership with Baringa, one of the leading global energy consultancies, to extend their Climate Change Scenario Model to build one of the market-leading climate change risk management frameworks available today.”

[1] In June 2021, Baringa’s Climate Change Scenario Model was acquired by BlackRock to enhance their Aladdin Climate technology. Baringa and BlackRock have entered a long-term partnership to continue co-developing these models so they remain the market leading solution.

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