Climate Risk
Classification Standard (CRCS)™

An emerging global standard designed to provide a consistent and transparent methodology for classifying transition and physical risk related to climate change.

The Climate Risk Classification Standard (CRCS™) is designed to consistently classify transition and physical risk related to climate change. CRCS provides a robust, consistent and scalable hierarchy for understanding and comparing exposure to climate-related risk. It is designed to respond to the global financial community’s need for a globally comprehensive, accurate, and auditable approach to defining and classifying climate risk factors and determining their economic impact.

Its universal approach sheds light on both risks and opportunities presented by climate change, climate-related policy, and emerging technologies in a radically uncertain world. 

CRCS defines the causal link between climate regimes, modulators, elements and risks to a Climate Risk Region in a consistent and science driven methodology.

The CRCS structure consists of 

  • 68 Transition Scenarios
  • 33 IPCC Climate Regions
  • 28 Climate Modulators
  • 47 Climate Risks
  • 1,000+ Socio Economic Variables 

Click to view CRCS Methodology Document

Key Features of the CRCS Methodology


CRCS offers objectively defined categories of climate risk that are spatially, categorically, and physically-consistent, enabling the design and execution of effective risk management and portfolio strategies.


The CRCS structure is a robust climate risk taxonomy that standardises measures of risk factors and their associated impacts.


CRCS is underpinned by the world’s leading climate science and macro-economic data, which is further refined through expert analysis and a rigorous structured expert  judgment protocol. Virtually every data point is linked to its source, which ensures auditability and replicability.


The CRCS structure enables analysis and comparison of risks facing individual assets, as well as asset class, group of assets and/or GICS groupings at local, regional and global scales (resolutions down to 0.5 sq meter may be achieved).