For many, buying a home is both a major life milestone and a significant financial burden.
Homeowners, who must contend with all manner of accidents, decay, natural disasters and wildlife, look to insurance providers to protect their investments.
Thus far, the 2016 Atlantic hurricane season is the most active and costly since Hurricane Sandy in 2012, responsible for more than $8.65 billion in damages. For insurance providers, understanding the dynamics of a storm and the geography of the projected impact zone is essential to fundamental business operations during the hurricane season.
For example, home insurance providers need to know which of their insured properties, commercial and residential, exist in the path of a hurricane to determine whether the provider has enough reserves to offset potential losses. In the case of Hurricane Matthew, over 5.5 million homes and $1.4 trillion worth of property lay in the cone of the storm, according to Pitney Bowes geolocation data.
As Hurricane Matthew rolled toward Florida earlier this week, the meteorologists at Verisk Analytics were tracking its every move.
Location intelligence, or the enrichment and analysis of location data for enhanced business insight, allows insurance providers to access the necessary data to make these critical business decisions before, during and after a hurricane hits.
The calm before the storm
From a business standpoint, insurance companies examine prospective new customers closely for their proximity to a forthcoming tropical storm. Specifically, they are looking to ensure a reasonable amount of payments will occur to offset any potential damages in any specific timeframe.
Keeping accurate data on policyholders helps to validate claims after a storm and enable the insurer to deliver more efficient service. How does it work in practice?
Homeowners will typically reach out to one or more insurance companies to answer a series of questions on a new property. These companies will then utilize location intelligence technology and data to examine the property using high precision geocoding and through appending descriptive attributes to a specific property location.
Insurance providers evaluate a series of spatial queries combined with historical data to quantify the potential risk that the property exposes them to (e.g. the property is on the water, has a high risk of flooding or resides in an area prone to earthquakes). In a normal course of business, that data is used to develop a risk profile which directly informs insurance rates.
While the fire is hot
During the hurricane, insurance providers turn to location intelligence to track the impending damage in real-time. Location intelligence allows providers to continuously update their damage assessment based on risk datasets that feed into a high-quality model of the storm’s path.
Information-based models better assess the risk of hurricane damage by neighborhood, so insurance companies can price products correctly to avoid unnecessary risk and yet still serve policyholders. The accuracy of the data feeding into these models is of the utmost importance: The difference between several thousands of dollars in over or underpriced premiums could boil down to the exact borders of a particular flood zone.
The model is primarily used to forecast the hurricane’s intensity, track, storm surge and projected rainfall, however, other factors contribute to the overall damage assessment. Insurance companies can then use these real-time models to make timely, actionable decisions to minimize its risk exposure, pre-position resources and reduce unnecessary expenditures.
As Hurricane Matthew rolled toward Florida earlier this week, the meteorologists at Verisk Analytics were tracking its every move.
The aftermath
Ultimately, in the aftermath of a hurricane, location intelligence can be key when calculating the return-on-investment. For example, Florida Farm Bureau Insurance operates in a state statistically likely to sustain damage from 50 percent of all hurricanes that occur in the United States.
When projecting the potential costs incurred from a storm, Florida Farm Bureau uses geocoding to efficiently and accurately determine rates for its customers, as well as decrease the amount of time and effort involved in the underwriting process. The result is reduced operating expenses and greater profitability — specifically, a 900 percent return-on-investment in the first 10 months following the implementation of location intelligence technology.
Because Florida Farm Bureau was able to ensure the accuracy of the information in its databases, they retained more customers through the policy renewal process. Florida Farm Bureau is also realizing fewer fines and criticisms from regulatory agencies, while eliminating many of the manual processes that agents previously used to validate policyholder information, according to a Pitney Bowes Florida Farm Bureau case study.
To the everyday homeowner, during hurricane season, insurance rates are an afterthought to immediate safety concerns. Human Resource departments can even use location intelligence to track their employees and send contextually relevant communications prior to or during a major storm event. However, to insurance companies, hurricanes represent an unpredictable business liability that can be managed through the use of this innovative technology.
Clarence Hempfield is vice president of product management, location intelligence for Pitney Bowes Software. Connect with him on LinkedIn.
Source: Pitney Bowes Risk Data Suite
Source: PropertyCasualty360