Tag Archives: GIS

Flood warning: Working to provide better coverage

Flood is one of the most devastating catastrophic perils, in which a single event can create tens of billions of dollars of loss. It is also one of the least insured perils, affecting people in every part of the United States. Advanced risk models now provide granularity, assessing flood risk at local levels. Such technological development presents insurers the opportunity to offer affordable, risk-based coverage within a private insurance market. Milliman colleagues Nancy Watkins, Matt Chamberlain, Andrei Stoica, and Garrett Bradford offer perspective in this video.

To learn more about Milliman’s flood expertise, click here.

Reading list: Florida’s private flood insurance market

Advances in catastrophe models and new state insurance regulations have opened the door for an affordable, risk-based private insurance market in Florida. This reading list highlights articles focusing on various issues and implications related to the market. The articles feature Milliman consultants Nancy Watkins and Matt Chamberlain, whose knowledge and experience is helping insurers to understand and price flood risk more precisely.

Forbes: “The private flood insurance market is stirring after more than 50 years of dormancy
The reemergence of private flood insurance has piqued the interest of carriers seeking to enter the market. Some catastrophe (CAT) modeling companies are creating flood models to help insurers price policies. Here’s an excerpt:

Nancy Watkins, a principal consulting actuary for Milliman, likened the current level of interest from insurers to enter the private flood insurance market to popcorn.

“We are at that stage where you can hear the space between pops. You can hear one kernel at a time,” she said. “What I think is going to happen is, in one to two years, there’s going to be a lot more going on.”

Bradenton Herald: “Important for homeowners to compare flood insurance options
Florida homeowners must consider the issues related to the National Flood Insurance Program (NFIP) and private flood policies. Private insurers can use predictive modeling technology to determine a home’s distinct flood risk.

Tampa Bay Times: “Remember the flood insurance scare of 2013? It’s creeping back into Tampa Bay and Florida
Real estate and insurance experts comment on the possible effects that high flood insurance rates may have on homeowners. Insurers express interest in the granular modeling of flood-prone territories.

Tampa Bay Business Journal: “Why some Tampa Bay property insurers are offering flood coverage and others are not” (subscription required)
Insurers need to weight the risks and rewards associated with the underwriting of flood insurance. A few carriers have already decided to participate in Florida’s private flood insurance market.

Geographic information systems can help insurers price flood risk

Insurers have been cautious about reentering the homeowners flood insurance market, which is due to high risks related to floods. In his Best Review’s article “High water mark,” Milliman’s Matt Chamberlain discusses the reasons behind the industry’s trepidation. He also provides perspective on how geographic information systems (GIS) can help insurers develop granular rating plans. Here is an excerpt:

There are several reasons why flood has been considered an uninsurable risk. First, flood is a localized peril; a distance of a few hundred feet, or less, can make a large difference in risk. This produces an information asymmetry, because the insured has a clear understanding of the local topography, while the insurer does not. The insured knows how far the house is from water, and whether it is on the top of a hill or if it is in a depression.

Insurers, on the other hand, typically use large rating territories for homeowners insurance, in some cases larger than a county. If these territories were to be used for flood insurance, it would create the potential for adverse selection. Insureds that were at highest risk of a flood would be most likely to want the coverage, and if insurance companies do not have a means of distinguishing higher-risk from lower-risk policies, anti-selection would result….

Geographic Information Systems, when coupled with the new flood catastrophe models to provide a very granular rating plan, may help insurance companies overcome these risks. Territories can be based on “hydrological units,” or watersheds, so that areas that water is not likely to flow between are not grouped together. Within a territory, appropriate rating factors are distance-to-coast (relating to storm surge risk), distance-to-river/stream (relating to river flood risk), and elevation (because all else being equal, there is lower flood risk at higher elevations).

Using all of these rating factors produces a rating plan that is able to distinguish different levels of risk even among points that are near each other. This produces true risk-based pricing that is likely to be sustainable in the long run. The top map at right shows this approach and compares it to the traditional method of rating flood insurance used by the NFIP, shown at bottom.

The video below presents an example of how GIS can improve pricing strategy.

Geocoding coastlines and rate-making

Determining a “coastline” is not as easy as some would think. The following excerpt from an Insight article by Matt Chamberlain discusses the challenge of defining a coastline:

Although it may seem like defining the “coastline” is clear-cut, it is actually quite ambiguous when considering a property’s exposure to a hurricane. Does the coastline follow bays, such as Tampa Bay? Does it follow barrier islands? Does it follow rivers and, if so, how far?

After a company decides that it should organize its territories based on distance to the coast, that company’s first instinct may be to use an existing coastline. However, such a coastline may not be suitable for the purpose. Off-the-shelf coastlines, such as the one in the map in Figure 4, may follow many small-scale features that do not, in fact, affect hurricane risk.4 The coastline in Figure 4 even follows inland features, such as Lake Okeechobee. A considerable amount of preprocessing work is required to create a coastline that matches the expectation of risk. It is even possible that different coastlines could be used for different purposes.

Different hurricane model vendors may have designed their models using different coastlines. If a company wants to calibrate its rating structure to a particular hurricane model, it should use a coastline that matches its preferred model vendor’s interpretation. If the company wants to understand the relationship between risk and storm surge, it makes sense to use a coastline that captures the more finely detailed features that are relevant to storm surge risk. If the company is concerned about wind risk, it makes sense to use a coarser coastline that more closely corresponds to the hurricane peril.

Once a coastline is defined, an insurance company can begin geocoding territories to rate policies. Chamberlain outlines the process of geocoding in this excerpt:

In order to rate a policy, it must be “geocoded.” This requires the location’s address to be entered into a “geocoder,” which returns the location’s latitude and longitude. A geographic information system (GIS) program can use that latitude and longitude to determine which territory it is in. This provides the ability to determine the risk at a location much more precisely. Instead of rating the location based on the average risk in a territory, which in turn is based on counties or ZIP codes, this method allows the company to estimate the risk for that specific location. In practice, a company may still choose to create territories that group together similar risks, but the territories can be made as small as necessary, ensuring that each one is homogeneous.

To read Matt Chamberlain’s article on geocoding hurricane risk in Florida, click here.

Geocoding can produce more precise homeowner coverage in Florida

A one-size-fits-all approach to rating hurricane coverage in Florida can be inexact for insurers taking on these risks.

In a new paper, Matt Chamberlain discusses the benefits of utilizing geocoding models to define more granular territories that provide companies the ability to more accurately determine the risk at a specific location. Current practices consist of grouping territories on county boundaries or ZIP codes.

This excerpt addresses the shortcomings of both current practices:

• The number of territories is inadequate to accurately differentiate the risk. Simply placing a property on one side of a line or the other results in discontinuities. While wind risk varies continuously, premiums varies vary discontinuously, meaning there are areas that are overpriced and others that are underpriced.

• The dividing line between coastal and inland territories is not usually based on a fixed distance from the coast, but rather on geographic features such as the Intracoastal Waterway. Because those features may vary in their distance from the coast, locations that are the same distance from the coast could be assigned to an inland territory or a coastal territory depending on their position relative to this geographic feature. This creates nonhomogeneous territories and provides more sophisticated competitors with marketing opportunities by offering lower rates for risks that have been overpriced.

• ZIP codes are defined for the convenience of the post office and have no relation to property causes of loss. They are irregularly shaped, meaning that locations at different points within the same ZIP code may be different distances from the coast. They are too big, resulting in locations with very different risk levels being grouped together. The post office changes ZIP codes over time, introducing new ZIP codes or merging existing ZIP codes for its convenience, but such ZIP code updates do not change, or reflect, the underlying risk of property loss.

This excerpt provides insight into Chamberlain’s recommended practice:

…Companies should adopt wind territories that are defined based on their distance to the coast, instead of being defined based on ZIP codes or the Intracoastal Waterway. Using the coast as a reference point can pool similar risks together. It is possible to create as many territories as desired by using many different distance-to-coast dividing lines. Utilizing many different dividing lines instead of one can create a greater gradation in premium from one territory to another, meaning that the variation between any two adjacent territories will be small.

To read the entire paper, click here.