Research on combining modelling and satellite data for flooding for parametric insurance

Location: Global, with testing applied to Southeast Asia
Client: World Bank – Global Facility for Disaster Reduction and Recovery (GFDRR)

Myanmar

A technical assistance research and development (R&D) project to improve the calculation methodologies used in parametric and index-based insurance programmes.

Challenge

The World Bank-GFDRR Disaster Risk Financing and Insurance Program (DRFIP) – a partnership of the World Bank’s Finance & Markets Global Practice and the Global Facility for Disaster Reduction and Recovery (GFDRR) – has supported many countries over the past decade, pioneering innovative financial tools and strategies to manage the financial impacts of catastrophes. Example initiatives include the Pacific Catastrophe Risk Assessment and Financing Initiative (PCRAFI) insurance program and the South East Asia Disaster Risk Insurance Facility (SEADRIF). The primary aim of these programs is to provide a quick injection of cash to help participating governments deliver relief efforts as quickly as possible after a disaster.

Satellite-derived data can provide direct, objective observations of where disaster events are in progress as well as showing post-event damage and calculating impacts. Over the past decade, DRFIP has supported many developing countries in setting up financial tools and strategies to manage the financial impacts of natural disasters. The use of satellite imagery could help DRFIP innovate the way that insurance products are used, particularly in response to extreme flood events. However, there are limitations to the use of satellite imagery.

This project undertook R&D to develop methodologies that complement the use of satellite imagery with data derived from flood model simulations and ground-based measurements.

Solution

Research on combining modelling and satellite data for flood for parametric insurance
Communities living near Inle Lake, Myanmar

The World Bank commissioned us to carry out research to propose methodologies for combining multiple estimates of post-event loss into a robust single value which could be used in parametric or index-based flood insurance instruments.

As a result of research, we proposed four potential methodologies for combining satellite-derived data with data from telemetered gauges and hazard data models to estimate population affected by flooding.  To ensure the robustness of the post-event loss index based on population affected, a manual verification process was introduced to identify and address potential issues with input data sources. A repeatable, pre-defined set of rules was proposed to verify the index calculation and mitigate the risk of large discrepancies between estimated and actual population affected.

 

Elements of this research have been adopted in subsequent operational phases of index-based insurance programmes.

Benefit

We have extensive experience in insurance, catastrophe modelling and disaster risk financing mechanisms, as well as specialist technical skills in hydrological modelling, remote sensing, GIS and software development. This expertise allowed us to take an objective view on the options available to DRFIP and propose options that could realistically be deployed in future operational phases. Our client benefited from a highly customised set of solutions developed to meet their specific needs during a very short, time intensive project.

Want to know more?

Email John Bevington (JBA Consulting) or Paul Maisey (JBA Risk Management) for more information on our services and products that can support parametric insurance. You can also discover more of our projects on our International Development webpage.



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