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The Globetrotter’s Guide to Property Risk: XL Group’s Location Management System
July 15, 2013
The dashboard voice escorts drivers seamlessly through foreign territory to new destinations. You may call it Gloria, or a slightly less charitable name if it guides you to the wrong address.
Global Positioning System (GPS) applications can also highlight popular restaurants, track missing laptops, trace stray children or even chart local singles available for dating.
To do this, the system calculates the overlapping radio spheres from at least three different satellites to track buildings, vehicles, aircraft, sea vessels, and people. But GPS isn't just about end-user applications.
GPS is now lighting up the consoles of underwriters and risk engineers. Not necessarily glamorous, but certainly critical.
The repercussions of climate volatility, catastrophes, and grossly underestimated risk have created an urgent client demand for meticulous and more expansive property risk assessment, and for even more scrupulous insurance pricing.
It's no longer enough to examine a building and the geographical features surrounding it. To truly gauge a property’s risk environment, we want to understand its neighborhood.
The Old Two-Dimensional Standard
Traditional property risk models are based on two dimensions of knowledge: structural elements and immediate environmental factors.
The standard risk picture begins with the client’s self-assessment.
The underwriter works closely together with the risk consultant who then dispatches a field engineer to inspect and photograph the property. Engineers scrutinize the immediate risk arena, including structural soundness, construction materials, safety precautions, building hazards, flood sources, and other environmental dangers.
The risk consultant verifies and supplements the original client information and engineering reports and then the information is passed over for cat modeling to Risk Management Solutions (RMS, catastrophic risk modeling specialists) for scientific calibration. RMS integrates seismic, meteorological, and climatological data to produce the final, enhanced risk models.
This was the best the old world could supply: two-dimensional evaluations of the combined structural and environmental dangers. Based on this, underwriters advised clients on property improvements and procedures to minimize risk exposure, and premiums were set accordingly.
The Third Dimension
Enter GPS, and the dawn of global risk mapping.
What better way to structure this amassed property information than visually on a map? Why stop there?
The third dimension of property risk modeling materializes later this year, with XL Group's Location Management System. Because we collect and manage all location data in a secure database, whether it was quoted, bound or declined, using LMS will be able to shed light on the "dark" or shady places surrounding a property. We want to answer the question: What else is there?
How Does It Work?
LMS makes it possible to map an insured property, placing it in the context of its larger risk neighborhood.
First, we'll geocode properties in pilot countries (UK, Australia, and the US). Two separate geocode engines, similar to Google maps, will plot the latitude and longitude (geocode) of each insured property. These two geocodes are then cross-referenced to map the insured property with the greatest possible accuracy. For further clarification, satellite imagery can be used to drop a pin on a location and re-calculate the geo-codes.
Language can help or hinder geocoding. For example, a Chinese address transcribed into Latin characters loses several degrees of accuracy, before geocoding has even begun.
That means it is easier to pinpoint the helipad on a building in London, than to isolate a factory in China’s Sichuan province to within a 100-kilometer radius. Eventually it may prove useful for clients to supply property geocodes wherever possible, since these are language-independent. A bit like the good old-fashioned postal code, in fact. Just a lot more accurate.
Each geocoded location will be stored in our database under a unique location identifier. Then we will describe it using more than 300 data fields, which will be updated annually for a permanent record, something like a “medical record” of a location over time.
We will be able to link a claim to a specific location, rather than merely to a policy. This will give us new insight into individual locations and the real scope of a policy, and drastically increase the accuracy of our pricing analytics.
This third dimension of location data will result in a new, comprehensive property risk picture.
A New Instrument For Global Underwriters
Most crucially, LMS will become the newest arm of our global underwriting platform (GUP), which intelligently orchestrates the process between LMS, exposure information, pricing, risk modeling, quoting, booking and policy execution.
Click on a property in LMS, and a pop-up window will show the risk reports, claims history, and policy records from the database.
By adding more and more locations into LMS, an aggregate, contextual risk picture emerges. Underwriters can quickly determine the aggregate risk within a defined location perimeter, or simulate an event in a particular area. Of course this does not replace comprehensive, large-scale portfolio control, but gives an underwriter a picture of cumulative exposure in the area.
A mere 300 meters from an insured soft-drinks bottling factory stands a chemical processing plant posing a contamination risk.
The boiler of an old, uninsured shirt factory explodes, setting fire to the insured gasket manufacturer one block away.
Two insured ships are anchored in a harbor. On shore two insured processing plants stand within 100 meters of each other, and an insured hotel lies 200 meters distant. RMS determines that this high-value patch lies in the path of a hurricane. It is clearly a concentrated risk neighborhood. Is it worth knowing that the ships have temporarily created a higher risk accumulation in this port? We believe so.
With LMS, such previously uncharted area risks will be identified, recorded and incorporated into the property risk picture. Underwriters will be able to advise clients on increased protection measures. Policies will better reflect the very real risk factors surrounding a property, guaranteeing sufficient coverage in the event of unavoidable disaster.
The Fourth Dimension: The Sky Is The Limit
Over time, LMS will add the fourth dimension of the risk picture: claims surveyors will use smart phones to interface directly with LMS from property locations. They will upload not only current photographs of the property, but also photographs and information on the other insured and uninsured properties in the vicinity.
We love to dream harder: In future releases we plan to incorporate additional insured objects, such as our onshore energy locations. We also expect to map the relationships between locations, like supply chains. An automobile manufacturer will appear on the map not merely as a central factory with surrounding properties and landscape features; LMS will also highlight the manufacturer's supply chain to include, for example, the inflow of spark plugs and the outflow of finished engine blocks.
LMS could be expanded eventually to include oil rigs, airports, airplanes and ships, since position data is continuously broadcast and publicly available.
Beyond that, we envision a day when every XL employee and client will be able to connect and contribute directly to LMS. On a trip to Barcelona? Remember to snap a shot of that factory you pass on the way from the airport into town. Is it possible to dream too hard?
Ivan Welker is Business Architect for the GUP Global Property Release, and business-side owner of the GENIUS Platform. Mr. Welker is responsible for the operational side of process re-engineering, implementation of new Lines of Business, new branches, and offshoring projects, with underwriting expertise in German Global Program Business.