Over 2% of flood insurance assignments are incorrectly underwritten
Why are you still using a dot to do flood determination?
Geocoding is an essential part of property underwriting. Inaccurate geocoding could result in a carrier taking on risk it shouldn’t, passing on acceptable risks, pricing a policy too high, or pricing a policy too low. In essence, inaccurate geocoding injects more uncertainty and missed opportunity into a portfolio.
In flood determination, the current standard in geocoding is Address Point. Address Points are approximations for locations. It essentially takes you to the streetside portion of the parcel, and not on the buildings or structures themselves. Because a geocoding error of feet or inches can result in an incorrect determination of whether a building is in a flood zone or not, Address Point geocoding results in many false positives and false negatives.
Building footprint data is available nationwide and is the most accurate representation of a building’s address. The centroid of a building is the most accurate point representation of the structure’s location. The outline of the building is the most dynamic input for analyzing risk to any part of the structure. A small portion of the structure could be in a flood zone, or a building could overlap multiple zones.
Neither the building centroid nor the footprint are being used in the insurance industry today. Why not? In the era of high definition data, why is standard definition accuracy considered “good enough”? We can demonstrate that in Suffolk County, NY, over 2% of homes are assigned to incorrect flood zones when using standard definition accuracy data.
At BuildingFootprintUSA, we appreciate how our highly accurate spatial data can solve hard problems across industries. We have innovative clients who have been using our data to enhance the accuracy of the flood insurance determination process. This process determines which houses require flood insurance and which don’t. You take in an address, get the most accurate location for the building and do a spatial comparison against government defined flood plains.
In the current era of Flood Insurance Privatization and climate change-driven disasters, companies looking for a competitive edge need to be searching for “secret ingredients” that they can use to make better decisions. We believe that BuildingFootprintUSATM data is one such secret ingredient. How would address point-based flood zone determinations compare against determinations made using BuildingFootprintUSA data?
What is the crux of the challenge? In flood determination, if your address is located imprecisely in an incorrect floodplain designation you could either be paying for flood insurance that you don’t need, or not having flood insurance that you require.
What causes these problems? Address points are point approximations of a given address and are used to identify a single flood zone for the address. These approximations may be wrong – they may be hundreds of yards from the actual location of the structure. These approximations may also fail to make clear that an address (and multiple buildings associated with that address) may fall within several different flood zones. Can BuildingFootprintUSA data solve both of these problems?
We conducted two analyses. First, we wanted to understand if building footprint-based analysis could help us understand when an address is located in two or more different flood designations. Secondly, we analyzed the frequency of when an address point had a different flood designation than building footprint-based determination.
For those new to flood determination, a quick primer on flood analysis. Broadly there are two types of zones that convey that a property carries risk:
Special Zones are any flood zone designation that begins with A (any area) or V (coastal areas) means there is a 1% greater annual chance of flooding which means a potential 1 in 4 chance of flooding during a 30-year mortgage in high risk areas. All home and business owners in Special Zones who have mortgages from federally regulated or insured lenders are required to buy flood insurance.
Non-Special Zones are any flood zone designation that begins with an X (yellow) on this map indicates a moderate-to-low risk of flooding. The risk is reduced, but not completely removed. Flood insurance isn’t federally required in Non-Special Zones, but it is recommended for all property owners and renters.
This image demonstrates how complex the flood zones can be. The blue and red zones (top left and most of the middle respectively) are Special Zones, where one would need flood insurance, while the yellow (small circle in the middle and bottom left/right) is a Non-Special Zone, meaning that an individual is not required to purchase flood insurance.
Structures in Multiple Zones
As mentioned above, simplistic address point-based analysis associates an address with a single flood hazard area. We first studied how frequently addresses and their associated structures fall in multiple flood zones in Suffolk County, NY.
We anticipated that this would happen frequently but we were surprised that 5,803 out of the 469,510 buildings in Suffolk County (1.2%) have multiple flood zone designations. As an example the following map shows three different flood zones intersecting a neighborhood. The light blue VE (bottom right) and red AE (top right) areas are high risk flood zones that require flood insurance. The yellow X (left) area is Non-Special and does not require flood insurance. Address point assignment of the addresses to flood zones is straightforward, however it fails to reveal that several buildings fall on multiple zones. Home owners whose properties fall on multiple flood zones would benefit from higher accuracy studies to determine if their property really requires flood insurance.
Higher Accuracy Decisions
We also studied the number of times an address point and a building footprint yield different flood zones determinations. 1.1% of all houses fell in different flood zones when comparing an address point- versus a building footprint-based result. For example, an address point with a generalized location might fall in an Non-Special (lower risk) zone while a building footprint might fall completely within an Special Zone (higher risk) zone.
Sometimes these differences were relatively harmless, meaning the address point and the building footprint location both fell in Special Zones or Non-Special Zones. However, nearly 65% of the time one determination was in a Special Zone and the other was in a Non-Special Zone.
You may be asking yourself, are the differences in the results material? Do they matter? Absolutely! Imagine putting a monetary value on the properties that have potentially incorrect flood assessments. If the average home price in Suffolk County is over $420,000, and if there are over 10,000 buildings that have potentially incorrect flood zone determination, over 4 billion dollars of property are potentially at risk from poor flood analysis determinations.
Let’s examine a specific example; picture this house on Harvey Rd. You see two buildings, a large home and a garage underneath the tree cover. The home is near a small marina, but would be considered to be on higher ground. At 24 Harvey Road, the flood zone designation would be X or a Non-Special zone if determined with an address point. The address point and front of the house are coded accordingly, requiring no flood insurance. However, maybe it would be best to check and see if the rest of the building is near any other flood zones.
The image shows a closer look at the home on Harvey Rd. Using BuildingFootprintUSA’s high accuracy building outlines we can analyze the entire set of structures associated with the address. A garage and even a portion of the home falls in a Special zone.
We knew that building footprint data can provide higher accuracy, yet we were surprised that in our Suffolk County study over 2% of the time a property could be mislabeled for flood determination. These are missed opportunities in underwriting. By implementing building footprints, you will more properly rate the risks, reduce surprises in future claims, and have confidence in the accuracy of your portfolio level of risk. By misassigning flood risk, you could be making avoidable mistakes — declining good business or accepting bad business. Gauging by the extent of the return period, you could be improperly pricing the risk as well. Further down the policy value-chain, using greater location accuracy in flood models will help in reducing the uncertainty in those results as well.
Whether you use an automated process for flood determinations, or you yourself look at the flood maps, it is always going to be more responsible to use the most accurate and informative information. Even in an automated system, using high accuracy building outlines could still flag multiple flood zones for someone’s property.
Want to know how our data can work for you? Feel free to contact us!
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