Oasis conference

3 July 2018

Location: Zurich, Switzerland


Driving innovation together

Developing "your own view of risk" is a common mandate for natural catastrophe modelling teams and experts around the world. In the past, they used validation and adjustment of third party models to achieve their "own view"; only a few companies like Swiss Re built proprietary models. The Oasis Loss Modelling Framework (Oasis LMF) facilitates model building and adds transparency for model validation.

At the third annual Oasis conference, hosted by Swiss Re Institute and Swiss Re's Cat Perils team, participants learned that Oasis is a powerful framework to build a cost efficient "view of risk" by building proprietary models or by accessing multiple models from various providers via the marketplace of cat models from Oasis.

Today, the Oasis framework is widely used for probabilistic natural catastrophe modelling and provides an alternative to traditional model vendor solutions.

"Rising cost pressures in the insurance industry are boosting the willingness to join forces to reach common goals in model validation, increased model transparency, and interoperability of cat models, which companies used to address independently in the past," Beat Aeberhardt, Swiss Re's Head R&D Cat Perils, said during his introduction.

"Oasis brings together the three key elements of readiness: open source software, a marketplace of models and a community," said Oasis CEO Dickie Whitaker. "Taken together, they give the insurance industry and its R&D partners the means to stay on top of latest developments in risk modelling and tackle the challenges we all face."





Beat Aeberhardt, Head Cat Perils R&D, Swiss Re      
Dickie Whitaker, Chief Executive, Oasis LMF


Oasis Technology and Interoperability - Getting Models into Oasis
Mark Pinkerton, Chief Technology Officer, Oasis LMF


Global Earthquake Model (GEM) - applicability to the insurance industry and collaboration with Oasis
Paul Henshaw, Director of Technology and Development, GEM Foundation

Claire Souch, Director, AWHA Consulting


Networking break


Switching Cat Models, regulatory approval, challenges and success stories
Junaid Serai, Global Head of Cat Model R&D and Governance, SCOR P&C
Peter Zimmerli, Peril Lead, Swiss Re


Validating cat models with event loss data
Rick Thomas, Managing Director, Beach & Associates


Standing lunch


Introduction to afternoon session
Martin Bertogg, Head Catastrophic Perils & Managing Director, Swiss Re


A short overview of (flood) loss modelling relevant research at the Mobiliar Lab for Natural Risks
Olivia Romppainen-Martius, Associate Professor, University of Bern


What do recent historical events teach us about risk and cat models
Ellen Cousins, Chief Science Officer, Weather Analytics

Peter Geissbuehler, Senior Vice President, Tokio Millennium Re


Networking break


Options for deployment
James Lay, Commercial Director of ModEx, Simplitium


Future of Cat Modelling - Science and Operations
Claire Souch, Director, AWHA Consulting
Marc Rierola, Senior Risk Manager & Cat Modeling, Qatar Re
Rick Thomas, Managing Director Zurich, Beach


Closing remarks


Farewell drinks and networking


Photos by: Rafael Haegi

About the event

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.

At the Oasis Conference, hosted by the Swiss Re Institute and Swiss Re's Cat Perils team, participants will learn more about the suite of available models, options to deploy Oasis, and how Oasis technology is developing. This one-day event also offers stands to many model providers who will be able to demonstrate their model availability to participants. These include: Ambiental, Cat Risk Solutions, Fathom, Impact Forecasting, JBA and Kat Risk GmbH. Lastly there will be a focus on key issues in models, the need for transparency and the future of catastrophe risk modelling.