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The costs of developing better parametric models are also likely to significantly decrease as enabling data and software are increasingly shared as an open resource. The Oasis Loss Modelling Framework is one example of an open source catastrophe loss modelling platform. NASA’s Global Flood Monitoring System provides real- time satellite data and hydrological runoff analysis as an online resource and the OpenQuake Platform allows modelling analysts to share datasets and tools to assess earthquake risk.
These are insurance products which have a parametric trigger allowing for immediate emergency funding to be released to a policyholder combined with a normal indemnity function that tops up any additional loss after adjusting. Such hybrid models are increasingly available and can assist in reducing basis risk and building regulatory and consumer trust for parametric insurance whilst such products are in their infancy. This is particularly the case where there is a strong indemnity principle under local law and losses must eventually be quantified or evaluated. The CCRIF startedwith a simple parametric index, which allowed the scheme to be up and in place quickly. After three years, and after more research and model building, it switched to a modelled loss basis that enabled new hazard modules and a variety of exposure database formats to be added. The FONDEN scheme in Mexico consists of a parametric catastrophe bond to provide immediate post-disaster funding combined with an indemnity-based insurance to cover local governmental assets.
LEVERAGING MIXED MODELS
For simplicity and to build trust, parametric insurers might also start off by using simple single datasets as the basis for a parametric trigger instead of more detailed and complex models. Another possible solution to the basis risk issue is the creation of mixed models.
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