Accuracy Matters: Gaining Perspective on Risk Using GIS

By Bryon Kenne and Venkat Rachakonda

Insurance companies require statistically sound, accurate, and validated rating data to make well-informed business decisions — and spatial accuracy matters. Geographic information systems (GIS) are a useful and powerful tool for helping insurers gain perspective on and manage the risks and hazards that impact their books of business.

Uncertainty in Risk
Insurers need to trust the risk data used in a GIS. Therefore, it is important to understand how the risk data was collected and delineated, what science and statistical methodologies were used in deriving the risk, and the experience and perspective of the organization that compiled the data. The level of trust can be quantified in terms of uncertainty. Three general types of uncertainty can be introduced into mapped risk data: uncertainty in measurement, changing physical characteristics, and subjectivity.

Uncertainty in measurement can result from a variety of errors, including imprecise methods of data collection and inaccuracies between mapped risk data and the geocoding of a book of business. Therefore, it’s important that GIS users constantly question the accuracy of the data being used.

The physical risk characteristics that users deal with are never static. Changing climate conditions and ocean temperatures affect hurricanes. Socioeconomic conditions, building codes, and the amount of territory that fire stations must cover all affect fire protection. Fuel types, topography, access by firefighters, historical burn patterns, and drought determine wildfire hazards.

Interpretation of data is always subjective. No two individuals view the same data from the same perspective. To ensure field data has fulfilled expectations of accuracy and content quality, it must be fully validated. Standardized scientific methodologies for data collection, interpretation, and validation must be applied when risk data is incorporated into a GIS.

Data Accuracy
When incorporating a book of business into a GIS, it is critical to evaluate the proximity and vulnerability to hazard. Proximity and vulnerability are distinctly different. Proximity is a measure of an asset’s physical distance from a peril within a given boundary, whereas vulnerability is an assessment of the asset’s ability to withstand an event. A well-defined GIS program should offer insight into the relationship between proximity and vulnerability. However, users cannot rely on that relationship without understanding the accuracy of each source of information.

To illustrate how differing levels of accuracy can affect an asset’s proximity to a hazard, consider the process used to geocode a book of business. Depending on point accuracy, some assets can be geocoded to the rooftop level, the parcel level, along streets, or at a ZIP code centroid among a host of other locations. Depend­ing on the sources of geocoders, the placement of the points has an underlying accuracy that may not correspond at all with a floodplain boundary. Figure 1 illustrates how geocoding point placement can inaccurately portray a building’s (asset) proximity to a floodplain (hazard), giving false negative or false positive results.

When evaluating vulnerability, information about the integrity of the asset must be collected using a standardized method. For example, when rating a building’s vulnerability to fire, information on several different modifiers can be collected, such as building materials, sprinkler systems, and architecture. Stan­dardized information gathering enables GIS to portray vulnerability more accurately.

Risk Management
Insurers need tools that provide an understanding of how their assets are impacted by risk and the means to manage those risks. GIS can help quantify the risk exposure to an insurer’s book of business. LOCATION® Analyst, a tool that can be used within a GIS, is one of ISO’s latest innovations for helping insurers manage risk. LOCATION Analyst can determine each asset’s proximity to hazard and the vulnerability of the asset to the hazard, thereby quantifying an insurer’s risk concentration. As an example, Figure 2 illustrates an asset’s proximity to earthquake fault lines. Once high-risk assets are identified using spatial analysis, insurers can use the results to identify areas requiring risk management and formulate the appropriate underwriting policy.

Insurers can use GIS technology to gain valuable perspective on hazards that impose risks to their books of business. GIS allows insurers to correlate the vulnerability of their assets to the surrounding hazards and can assist in the formulation of policies and risk management standards to maintain successful business practices. All GIS users must understand the limits of the data they analyze and use, with accuracy being paramount. Accuracy of the data and of the spatial relationships between data sets is crucial for appropriate interpretation of the information gained through GIS.

Bryon Kenne is project manager of LOCATION Analyst in ISO’s Risk Decision Services (RDS) business unit, and Venkat Rachakonda is GIS architect for LOCATION Analyst.