The Risks of Hazard

Underwriting property insurance is a very complex operation, with limitless variety on methods of management. I tend to concentrate on the risk associated with natural catastrophes damaging a location, but that is actually just a small part of the overall process. How an underwriter receives requests for quotes, builds quotes, and sends them out (not to mention how that quote affects a book’s accumulation) is an intricate process. What is so interesting to me is how software solutions are solving the inherent problems associated with underwriting as a whole.

The Risks of Hazard blog is devoted to the exploration of natural catastrophe risk, and how to better understand it for insurance. An important aspect of the topic is how the analytics can be delivered. The software that delivers the analytics is as important as the analytics themselves.

Cloud computing is driving a software revolution as astonishing as any other computing revolution of the past 40 years. With the processors and memory moved to the cloud, along with the advance in both of those aspects of computing, it is now possible to build software solutions that would have been impossible 5 years ago. Platform-as-a-Service (PaaS) and Software-as-a-Service (Sass) are the only ways in which innovative software products are being built now. And they are being built to work on the next generation of IT infrastructure being installed by forward-thinking companies everywhere, like Allianz.

Next week I will be heading to Asia to try and find out how insurers, brokers, and reinsurers are handling their risk assessment, particularly for flood risk. Asia is an exciting market for property insurers, with economies growing quickly and property values becoming valuable enough to stimulate thriving markets for insurance — especially for natural catastrophe coverages. It is also a breeding ground for innovation right now, as everyone is working hard to ensure they have the necessary tools to understand risk from all natural catastrophes (and Asia gets them all!). This article by James Nash (of Guy Carpenter) summarizes the situation in Asia and their response to it very well.

The use of risk models and maps to predict the likelihood and intensity of flooding has an inherent, although not immediately apparent, flaw: dependability. Flood maps and models are relatively static, updated every few years (maybe), while weather and climate are extremely dynamic. So how can static models predict dynamic events dependably? A recent study suggests they really can’t.

One of the things that make natural catastrophes inherently unpredictable is the ever-changing nature of the natural world. This is a trivial observation, but it is fundamental to understanding how peril models work and what their limitations are. This post will discuss flood specifically, but the case is the same for all natural catastrophic phenomena.

Here in Colorado, where Intermap is based, one of the most dramatic fires in recent memory was the Waldo Canyon fire, which engulfed some of the western suburbs of Colorado Springs in 2012. It was an intense wildfire that stormed down the front range incredibly fast and consumed almost 350 homes. However, most of those houses weren’t behind the fire-line — they were ignited by embers blown by the same winds that blew the fire down the mountains.