The Risks of Hazard

Other than the population of number-crunchers concentrated in lower Manhattan, (a.k.a the stock market), there is no other industry more enamored with — and dependent upon — huge amounts of data than insurance. To run their day-to-day businesses, insurers of all kinds depend upon everything from 100-year-old archives of policies and claims, to predictive analytics producing data for events that haven’t actually happened. 

Specifically, property insurers (as well as brokers and reinsurers) depend on natural catastrophe models, maps, building plans, and industrial machinery profiles, along with their own claims and policy data. The reason everyone needs to use so many datasets is that no single dataset is satisfactory, let alone comprehensive, for predicting the future (which is what every insurer is essentially trying to do every hour of every day).

This blog is the first of five that will explore how InsitePro™, Intermap’s location-based risk software, compares to RiskMeter Online™, the market leading solution from Core Logic. The two solutions serve a very similar purpose, but they do so very differently. Investigating those differences should prove to be interesting.

There are a variety of ways to get location-based risk assessment information, including maps, tables, standard reports, or an interactive combination of the above. There is no “best” way to deliver this type of information, because different users will have different needs. Finding the right solution should be the priority for everyone who uses risk information.

Property insurers and reinsurers all have a dataset that is simultaneously:  

It’s worth exploring how a historical database of claims can be all three things at once.

Geocoding, the attribution of geographic coordinates to a postal address, is a geospatial problem people have been trying to solve since the advent of GIS in the 1960s. Reliable geocoding has always been a concern in the property insurance market: After all, the first step in understanding the risk at a location is to know exactly where that location is. But in the last 15 years it has also become a concern for the consumer market, with Garmin’s perfection of consumer GPS location hardware and the ubiquitous Google Maps platform availability over phone networks. (Personal note: This amazes me. When I studied Geomatics in university in the ‘90s, it required 20 lbs of equipment worth thousands of dollars to match the positioning capability of my cell phone!)

The rapid expansion of available geocoding capabilities brought on by consumer demand has proved to be greatly beneficial to property insurance solutions. With increasingly available geocoding, software for property insurance has been able to grow from databases and paper maps, to GIS systems, and onward to sophisticated spatial tools that provide information to non-technical users. But geocoding remains imperfect. In fact, there are several problems.

Not only is insurance an industry that is based on a general inability to predict what is going to happen, it is a hyper-competitive industry in which the winners are those who can best predict the unknowable…or at least be less wrong than their competition. Insurance underwriting is the actual process of pricing what is unknowable, and is necessarily performed with rigorous processes underpinned with vast amounts of data. However, underwriting is never perfect, and the gap between actual underwriting and perfection is called underwriting leakage.