Latest climate data and tools for insurance and disaster risk reduction
Global climate change and increasingly frequent and severe weather events are impacting lives and livelihoods around the world. Reducing impact requires integrating scientific climate models and catastrophic events risk into insurance/reinsurance schemes. The EU-funded project H2020_Insurance brought together experts from nine European countries, Hong Kong and Kenya to facilitate that process.
Climate science for the insurance industry and beyond
Although insurers and policymakers must rely on science for risk assessment and modelling, the scientists behind the data are rarely at the table themselves. “The H2020_Insurance project brings the insurance sector, the business sector, policymakers, scientists and academics directly into the same conversation,” says project co-coordinator Tracy Irvine. “This enhances insight and accelerates the incorporation of the latest science into risk modelling and, subsequently, into real-world decisions,” adds co-coordinator Fred Hatterman. This unique cooperation has enabled rapid delivery of tools and services for situations ranging from floods in the Danube region and typhoons in China to climate risks to forest resources, agricultural losses of smallholder farmers in Tanzania and even health in central Berlin and Potsdam. The project outcomes improve existing modelling processes and address gaps in risk assessment for regions and hazards. For example, the Danube Flood Model covering a huge area including four major capital cities harnesses some of the latest modelling advances and explicitly integrates climate change scenarios. Irvine and Hatterman explain: “The Future Danube Model can be used for climate risk quantification, support of EU framework directives implementation, climate-informed urban and land use planning, water resources management, and climate-proofing of large-scale infrastructure.” Novi Sad, Serbia is a case point. It is preparing its first wastewater treatment plant (WWTP), a big public investment that must be climate-proof. “We noticed that in the past decade the climate began to change rapidly, which has had a significant impact on our combined sewer system. When we were presented with the idea of the H2020_Insurance project, we decided to participate in order to get a better understanding of future events. The results of the H2020_Insurance project will help us prepare the WWTP and optimise the whole sewer / drainage system,” says Radoica Stefanović, manager at the Public Utility Company for Waterworks and Sewerage of Novi Sad. The Oasis Loss Modelling Framework is an associated non-profit framework that develops and provides free access to its open-source catastrophe modelling platform by the same name. Within H2020_Insurance, it developed a new user interface for non-insurance entities including cities, governmental users and academics available for download on GitHub. “Having an open source loss model is rewarding for all (re)insurance companies, brokers as well as the public sector,” says Marc Wüest SWISS Re natural hazards expert and active member of the project's External Innovation Advisory board.
It takes a (global) village
Oasis HUB is now an independent limited liability company formed to operate the Oasis HUB portal/eMarket. Its global community of over 1 650 members represents sectors including insurance, finance, academia, engineering and consultancy. According to Irvine and Hatterman, “The Oasis HUB provides our members with more than 1 700 free and commercially licensable catastrophe and environmental risk data sets and tools. We also provide innovation and commercialisation assistance to research organisations and SMEs looking to bring new climate risk assessment data, tools and services to market.” Check out the project’s webinar series and get started today on building resilience in our societies for a stronger and more secure tomorrow.
Keywords
H2020_Insurance, climate, risk, insurance, modelling, flood, Oasis HUB, insurers, Danube Flood Model, typhoon, smallholder farmers, Oasis Loss Modelling Framework, catastrophe modelling
