Climate risk refers to the financial risks arising from climate change, including the physical, transition and liability risks. With increasing regulation and changing investor sentiment, it is now more important than ever for organisations to understand the materiality of climate risk to their business.
Physical climate risks refer to the impact of changing climate conditions on asset integrity and business operations. Physical risks can result in lower asset values, defaults on loans, or the increasing price of insurance.
Risk Frontiers has been modelling physical climate risks for the past three decades. We have three tiered products that can help assess physical climate risks at a variety of scales:
ClimateGlobe – our global climate data analytics framework provides seamless downscaled and bias-corrected climate data from 1980 to 2100 anywhere on the globe.
Climate-Enabled Catastrophe (CAT) Loss Models – all our CAT models are now ‘climate-enabled’ allowing for detailed financial loss modelling at the address level for present day (baseline) and a range of future climate scenarios.
ClimateGLOBE
ClimateGLOBE is Risk Frontiers’ global climate data analytics framework, providing seamless downscaled and bias-corrected climate data from 1980 to 2100 anywhere on the globe. If you need quality climate data for your climate risk assessment, ClimateGLOBE is your climate data solution.
Quality-controlled, location-level climate data
Using climate data is unfortunately not as easy as grabbing it direct from the models.
We have developed a proprietary downscale and bias-correction technique that ensures climate model projections are aligned with historical observations at the location of your assets on the ground. We also do the climate model selection for you, based on the best available data in your area and your risk assessment requirements.
Figure 1. Example of the ClimateGLOBE framework. Global or regional climate models of choice are selected, then data are downscaled and bias-corrected to historical observations at the asset locations, to provide a seamless timeseries of climate parameters at the sites of interest for multiple future climate scenarios.
The latest climate model projections
ClimateGLOBE can provide a large range of climate parameters either from the latest CMIP6 round of global climate model simulations, available for each of the new Shared Socioeconomic Pathways (SSP), or from the best-available regional climate model in your area available for select RCPs.
The choice is yours, but we can guide you through this process.
Experts in climate risk
Our staff are experts in climate risk. We are long-term partners of the Australian Research Council Centre of Excellence for Climate Extremes (CLEX) and contributors to the Climate Measurement Standards Initiative (CMSI).
Read more of our insights on climate risk.
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Climate data can be provided direct from our ClimateGLOBE framework and also forms the basis of Risk Frontiers’ global climate risk analyses.
Address-Based Natural Hazards and Climate Risk Rating Database (RRD)
Risk Frontiers’ Natural Hazards and Climate Risk Rating Database (RRD) leverages three decades of catastrophe loss model development, combined with the latest climate science, to take an informed view of natural hazard and climate risk in Australia.
Address-level natural hazard risks rating
The RRD provides a natural hazards risk rating for every address in Australia. This includes ratings for bushfire, flood, cyclone, storm surge, earthquake and convective storms (thunder, lightning and hail).
If you own, operate, or have interests in residential, commercial or industrial property in Australia, the RRD is your solution to understanding natural hazard risk across your portfolio.
Physical climate risk scores
The RRD also contains information on how certain hazards are expected to change with climate change at the address level.
Risk Frontiers’ physical climate risk scores measure the property risk of all the major acute and chronic physical climate risks for both present day and future climate conditions.
Figure 1. Projected changes in climate hazards that influence physical risks for Australian buildings and infrastructure. Confidence estimates are provided in parentheses. Source: modified from CMSI (2020).
Unlike other providers, our scores are based on $ losses from our detailed catastrophe loss models. These models frame risk as a function of the hazard, exposure (using a general asset type) and vulnerability.
Physical climate risk scores can be matched to listed company asset portfolios. Scores can be used for a range of applications include portfolio benchmarking, climate risk identification, due diligence, TCDF reporting and integration into broader ESG analyses.
Figure 2. Example company physical climate risk report generated using Risk Frontiers’ RRD.
Experts in climate risk
Our staff are experts in climate risk. We are long-term partners of the Australian Research Council Centre of Excellence for Climate Extremes (CLEX) and contributors to the Climate Measurement Standards Initiative (CMSI).
Read more of our insights on climate risk.
Contact
Location-level intelligence from the RRD can be delivered by API or in bulk. Licencing can be tailored to your application.</>
Natural catastrophe (CAT) loss models are decision support systems used extensively within (re)insurance to assist in pricing natural hazard risk and aggregate exposure management. These are complex, probabilistic models that comprise a hazard, vulnerability and financial module to calculate $ losses on a portfolio of physical assets.
Figure 1. CAT models comprise a hazard, exposure and vulnerability module to model the financial risk of extreme climate (or seismic) hazards. The output is a set of exceedance probability (EP) curves. EP curves describe the expected losses on a portfolio of physical assets at a range of probability intervals for different climate hazards. ARI = Average Recurrence Interval. Y-axis is estimated losses in AUD. The integral of the curve is the Average Annual Loss (AAL). Shaded areas represent uncertainty related to natural climate variability and model error.
Three decades of development, now climate-enabled
Since 1994, Risk Frontiers has been developing best-in-class CAT models for the global (re)insurance industry, for all the major loss-producing perils in Australia – Flood, Fire, Cyclone, Hail and Earthquake.
Figure 2. Risk Frontiers’ suite of natural catastrophe (CAT) loss models. Ticks show those models that are climate-enabled.
Since 2019, our extreme weather CAT models (Flood, Fire, Hail and Cyclone) are ‘climate-enabled’. This means we can undertake detailed financial loss modelling at the address level for present day (baseline) and a range of future climate scenarios.
Our CAT models have played a crucial role in helping clients across banking, financial services, government, energy and telecommunications understand the materiality of physical climate risk to their business.
Figure 3. Change in the Average Annual Loss (AAL), from present day to 2050 under a high-emissions scenario, on a portfolio of Australian-based assets. Data are aggregated to the postcode level for anonymity but are calculated at the asset level.
Why use CAT models to measure climate risk?
The Geneva Association, and the UK, French and Australian Prudential Regulation Authorities have all identified CAT models as a critical tool to help improve the understanding of financial impacts of physical climate risk.
CAT models have two major advantages over the metric-based climate risk approach – they have been dealing with the ‘problem’ of measuring the financial impacts of extreme weather (tail risk) for several decades, and they include asset vulnerability and exposure aspects into estimates of financial loss.
Experts in climate risk
Our staff are experts in climate risk. We are long-term partners of the Australian Research Council Centre of Excellence for Climate Extremes (CLEX) and contributors to the Climate Measurement Standards Initiative (CMSI).
Read more of our insights and publications on climate risk.
Figure 1. Example of the ClimateGLOBE framework. Global or regional climate models of choice are selected, then data are downscaled and bias-corrected to historical observations at the asset locations, to provide a seamless timeseries of climate parameters at the sites of interest for multiple future climate scenarios.
Figure 1. Example of the ClimateGLOBE framework. Global or regional climate models of choice are selected, then data are downscaled and bias-corrected to historical observations at the asset locations, to provide a seamless timeseries of climate parameters at the sites of interest for multiple future climate scenarios.
