Embracing Climate Risk
Our climate risk solution extracts dynamically downscaled global and regional climate change models and combine these with global and local data sets, applying bespoke probabilistic algorithms to produce decision-ready financial and risk metrics.
We use mathematical-based models to assess exposure and vulnerability of the financial firm balance sheet to understand the likely impact on credit and market risks caused by extreme weather and climate change hazards. Results are expressed in a range of financial metrics to inform decision-making at all scales.
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climate undertaking and adaptation . carbon analytic
Incorporate Industry Standards In Climate Scenarios
- A short-term scenario of 5-year, featuring both climate-related shocks and a macroeconomic downturn
- Long-term scenarios that project until 2050 based on global best practices, namely orderly transition, disorderly transition and limited transition
Methodologies In Translating Climate Factors To Financial Loss
- Proprietary functional forms that are robust in the propagation of climate shocks to financial sector outcomes
- Climate risk models that capture the building blocks of CRST such as economic vulnerability, financial vulnerability and stress test modeling
Impact Analysis Due To Climate Related Shocks And Net-Zero Plan
- Discover and understand how climate change impacts balance sheet risk and portfolio investments
- Assist in preparation of decarbonisation scenarios to set long-term and intermediate targets that are aligned with net-zero by 2050 goal
Climate Risk
CUACA is curated to match the needs of a range of use cases in the finance sector. Assess financial risk to investment and lending portfolios using different climate scenarios, timeframes and asset types. Report material climate-related physical risk and transition risk through Climate VaR, in line with market practices.
CUACA provides an operational framework to support the critical steps of CRST by providing metrics as inputs to Probability of Default, Loss Given Default and Expected Credit Losses.
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