CLIMATE RISK
We help our clients develop or validate
transition and physical risk models
Given the growing understanding that non-financial –Environmental, Social and Governance– related risk drivers have an impact on credit risk (incl. asset/collateral value) – it was essential for us to build our ESG modelling capacity, with a particular attention to climate-related and environmental risk modelling.
We therefore decided on a significant R&D investment – to learn by doing and experimenting with relevant use cases.
We started our R&D with a thorough review of literature. Collecting and shortlisting papers from: academics, practitioners, and supervisors. With special attention to the new regulatory expectations and timeline.
Open-Source Models
Following our review of literature, we prioritized our appropriation of the following open-source models –and required data inputs– to start-with:
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PACTA: for transition risk
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CLIMADA: for physical risk
PACTA: for transition risk modelling
PACTA stands for Paris Agreement Capital Transition Assessment.
It is an open-source model who enables to assess the alignment of a portfolio to climate scenario benchmarks (per sector or per technology) – including net-zero pathways. It is a bottom-up model compiling counterparties' asset-level alignment rates (i.e. effective investments in production assets - which goes beyond communicated transition plans).
The model is developed in R. The project started in 2014 and was initiated by the 2° Investing Initiative (2DII) with as main contributors: University of Zurich, Frankfurt School of Finance, and Principles for Responsible Investment.
The sectors covered by PACTA are:
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Power,
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Auto manufacturing,
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Aviation,
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Shipping,
Collectively, these sectors account for about 75% of global greenhouse gas emissions.
PACTA relies on 5-year forward-looking asset-based production pathways.
5. Coal mining,
6. Oil & gas upstream,
7. Cement, and
8. Steel.
Overview of PACTA inputs and outputs:
Physical assets in the real economy and their corresponding production values are mapped to loans, equities and bonds.
The alignment of loans books, or investment portfolios is assessed against climate change scenarios and market benchmarks.
PHYSICAL ASSETS
IN THE REAL ECONOMY
FINANCIAL INSTITUTIONS PORTFOLIOS
CLIMATE
SCENARIOS
METRICS
PACTA outputs a number of metrics, for example:
production trajectory alignment, technlogy mix, emission intensity. They can be accessed in a number of tools, for example software packages, interactive reports and meta-reports.
Source: https://pacta.rmi.org
PACTA has been used by over 3,000 financial institutions worldwide (source: RMI), and by supervisors and central banks to assess their regulated entities – e.g.:
CLIMADA: for physical risk modelling
CLIMADA stands for CLIMate ADAptation. It is an open-source probabilistic model enabling the assessment of the loss distributions of geolocalized assets – conditional on Representative Concentration Pathways (‘RCP’, i.e. future greenhouse gas concentrations and hence global warming scenarios).
The model is developed in Python (and MATLAB) and was initially developed by the Weather and Climate Risks Group at the Federal Institute of Technology (ETH) Zürich.
The natural risks covered by CLIMADA are:
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European winter storms,
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River floods,
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Wildfires,
All at 4km spatial resolution. Historical data are provided – and allow to generate RCP-dependent probabilistic events, with a stochastic (Wiener) process, at distinct time horizons.
4. Agro droughts, and
5. Tropical cyclones.
Overview of CLIMADA inputs and outputs:
Resilience measures
(for example: prevention, spatial planning, building codes...)
Climate scenarios
Development scenarios
Exposure
Weather
Hasard
Vulnerability
Intensity
Impact
Outputs:
+ Risk analysis
+ High-res risk mapping
+ Impact warninings...
+ Appraisal of resilience measures / options (effectiveness of options, cost/benefit...)
+ Quantification of uncertainty
Climada
probabilistic event-based simulation
open-source
CLIMADA has been used/recommended notably by supervisors and central banks – e.g.: