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The Role of Scientific Modelling and Insurance in Providing Innovative Solutions for Managing the Risk of Natural Disasters

  • Patrick McSharry
Chapter

Abstract

Scientific modelling and forecasting is rapidly gaining momentum as a way to identify, assess and manage future global risks and extreme events that may threaten our planet. Inadequate modelling of extreme events, such as the earthquakes in Japan and New Zealand, hurricanes in the USA and the floods in Thailand, show that society can no longer afford to assess risk using a retrospective analysis of historical observations. A pressing need exists for the use of improved forward-looking risk analyses. This could be achieved by embracing powerful mathematical modelling and computational simulations. Prospective risk analyses are already being used to understand, manage risk and cope with uncertainty. Areas of shared interest between the insurance sector and society are producing innovative forms of collaboration between re/insurers, governments and the scientific community. There is also an emerging trend of model-based risk assessment by the insurance industry for decision-making, pricing and product creation that looks set to increase in the future. These quantitative models can also be used to support policymakers in making appropriate investments to reduce risks and provide early warning systems. Recommendations include: (1) increasing cooperation between government and industry to better understand risks by constructing open-access models, improving data quality and embracing forward-looking risk forecasting techniques; (2) providing national government funding and official development assistance for IT infrastructure, data collection and independent evaluation of model accuracy and parametric insurance products; and (3) developing education and training programmes for risk management and alternative insurance products.

Keywords

Risk Forecasting Extremes Disasters Insurance Early warning systems Big data Models Public-private partnerships 

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Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  1. 1.Smith School of Enterprise and the Environment, Oxford Man InstituteUniversity of OxfordOxfordUK

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