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Close to 100 participants attended the Oasis Conference, hosted by the Swiss Re Institute and Swiss Re's Cat Perils team on July 3, 2018 at the Swiss Re Next Auditorium, Zurich, Switzerland. The 1-day event aimed at sharing and demonstrating the suite of available models, options to deploy Oasis, and how Oasis technology is developing.

The event also provided a venue for model providers to demonstrate their model availability to participants such as Ambiental, Cat Risk Solutions, Fathom, Impact Forecasting, JBA and Kat Risk GmbH. More importantly, the conference discussed key issues in model development, the need for transparency and the future of catastrophe risk modelling.

Paul Henshaw, GEM Director of Technology and Development and one of the keynote speakers at the conference, presented initial findings and considerations in porting a proof-of-concept OpenQuake risk model to OASIS. He is leading GEM’s testing activities on this to better understand the effort and requirements involved. “I believe that OASIS and GEM approaches and offerings are complementary. While this project is still at an early stage, I think our continued collaboration could open interesting possibilities such as the development of open and transparent software and models with support for multi-peril loss estimation and financial module,” Paul remarked after sharing his initial experience on GEM’s model implementation on OASIS loss modeling framework.

Paul also presented the progress of GEM’s global earthquake hazard and risk model (GRM2018). In his presentation, he discussed the open source tools used for hazard and risk analysis and highlighted how GEM’s collaborative regional and national projects around the world contributed to the ongoing development of GRM2018. The GRM2018 is scheduled to be released on 5th December this year in Pavia, Italy.

About OASIS LMF

Oasis Loss Modelling Framework provides an open source modelling platform that eases the exchange of catastrophe models. Among other things, this allows the insurance industry to access models from new model providers, which increases the diversity of models and risk views.