The insurance industry represents a large market of USD 4.3 trillion or 6.4 percent of global GDP, while worldwide agricultural insurance markets have a collective premium pool worth €12.5 billion.

Insurance companies are offering various index insurance products that are based on remote sensing. The insurance sector has the potential for increased use of spatial information, particularly in better risk assessment. Remote sensing allows Insurance companies to better analyze and plan for risk if the time ever comes.

One example where remote sensing data is beneficial is during floods. Floods can affect many people concurrently over larger areas and are thus, examples of covariate risks. Covariate risk, by definition, captures the degree of correlation between a peril (event) and economic loss. It is the degree of covariation between an event and a loss that determines an insurable event; not all floods result in economic loss, and not all losses are insurable.

Insurance can be further differentiated according to the criterion used for indemnification. Classical claim-based insurance pays an indemnity following a claim of loss by the insured customer. Index insurance, in contrast, indemnifies the insured customer based on an index related to such losses rather than the claimed loss.

Figures 1 and 2 illustrate an example where Skymap Global used earth observation and GIS to support the insurance industry in managing its business operations in claim-based insurance.

In July 2019, A flood event affected some upstream parts of the Krishna river. Cloud cover impeded the direct observation of the damages caused by the flood.

Spaceborne radar images are capable of imaging the Earth’s surface even during the Monsoon period. The 6-day revisit period of Sentinel-1 allows a detailed and sound understanding of the event. Figure 2 shows a sequence of 3 images acquired respectively on the 10th, 16th, and 22nd July 2019 (Galagali village on the bank of Krishna River in Bijapur District of Karnataka)

The maximum extent of the water is clearly identified. Destructions caused to agriculture can be quantified precisely and accurately. Radar images were acquired respectively on the 10th, 16th, and 22nd July 2019.

Skymap Global is able to pre-process radar data properly. This know-how is a crucial element for the successful application of radar images in such a context. Understanding the maximum flood extent is a fundamental parameter for the insurance companies and the farmers as well.

With this pool of scientific information, Skymap Global is able to provide crucial information during time-sensitive periods like when disasters such as floodings, forest fires, etc. happen. Our ability is to extract information from not only optical data, but also radar data, and compiling information is a key strong point for Skymap Global. Insurance industries around the world can use this knowledge to better manage risks and premiums for their customers, and also use our information for faster claim classification and payouts.