Insurers and reinsurers alike are always on the lookout for tools that can provide them better predictive analysis and modeling of risk exposure, for example when faced with upcoming hurricanes, floods or other natural disasters. How will their policy portfolio be affected by a hurricane? Where should they dispatch local agents after a natural disaster? What level of reinsurance should they get when faced with new risk? All these decisions can make or break a company's bottom line as well as their customer service. Insurers use sophisticated modeling and forecasting tools to make decisions, but these tools are usually only accessible by trained analysts and getting reports takes hours if not days to receive.
With SpatialKey's SaaS platform, insurers can now finally bring together and analyze *on-the-fly* - not in hours or days as with other tools- a variety of data coming from different sources, and make immediate business decisions accordingly.
Take tropical storm Alex, expected to turn into a hurricane (thankfully heading away from the Gulf of Mexico oil spill) this Wednesday as an example. Since some of the predictive hurricane models are proprietary, we decided to use publicly available datasets of the hurricane's path at http://www.hurricanezone.net/#01l, as well as a mock sample of insurance policy to showcase how easy it was to import and analyze information using SpatialKey.
After downloading a shapefile containing the Tropical Storm ALEX 5-Day Track here, we easily imported it into SpatialKey and created a new report showing the potential 72 and 120 hour paths of the storm.
Next we added our fictitious insurance company's policy data and overlayed it with the predictive hurricane's path. This allowed us to see in minutes, not days or hours, which policies in which geographies might be affected by Alex. Minutes vs days make a big difference- the quicker the information gets in the hands of decision makers within the insurance company, the quicker they can adjust their plans- for example where to dispatch local agents after a natural disaster.
SpatialKey shines by making complex data analysis simple and available to the people who need it the most.
Within just a few minutes, no programming or analysts required, we imported the insurance policy data from a spreadsheet, shape files from the NOAA site and used the capabilities of SpatialKey to filter which policies could potentially be affected by the path of the storm. We could take this analysis further and forecast the impact of the storm on commercial vs home policies or per construction type. We could even import additional datasets, for example local demographics, for further insight. The analysis capabilities are endless. And the other benefit of SpatialKey is that the information (for example which policies are at the highest risk) can easily then be exported out of SpatialKey and shared within the organization for follow up. Or interactive reports containing the information above can be shared so that others on the team can further slice and dice it according to their analysis needs.