Climate-related events are occurring with increased frequency and severity across Canada.
As such, in a recent report titled “Navigating Uncertainty in Climate Change”, the Office of the Superintendent of Financial Institutions Canada (OSFI) outlines that as part of their mandate they are making this complex topic relevant to Canada’s financial institutions.
Having access to climate risk data* at a property level assists financial institutions in assessing and quantifying their portfolios’ resiliency to natural disasters such as floods, wildfires, hurricanes, tornadoes, tsunamis, earthquakes, volcanoes, and heat waves.
Historical climate events assist in evaluating the past, but with climate change, there is an increasing need for predictive climate risk data. Teranet’s ability to connect with data partners to aggregate and agglomerate accurate data, allows us to offer predictive climate risk data* per property.
Quantifying climate risk is now possible with a wide variety of our climate risk metrics such as:
- Probability of climate events
- Expected damage to assets
- Probability of defaults
- Tail losses for portfolio stress testing
- Climate ratings
- Climate scores and much more
Additionally, predictive climate risk data is also available:
- Across the lending life cycle of a property from one to 30 years and
- Across a variety of carbon emission scenarios, such as those set out in the Paris Agreement
Climate-related risk can quickly transition into operational risk, credit risk, market risk, liquidity risk and reputation risk. Testing portfolio resiliency with our climate risk data assists in identifying assets that require action and others that are safe for the long run.
Our goal is to assist our customers with their risk management processes of assessing, mitigating, monitoring and reporting of risks from climate-related events. If you’d like to learn more about climate risk data per property, please contact your account manager.
*Includes natural hazards that are not climate-related events, i.e., earthquakes.
