About the Client
Client started in 2008 by aggregating dispersed building permit data from
across the United States and providing it to other businesses, such as
insurance companies, building inspectors, and economic analysts. Today it
provides solutions tailored to those professions along with a variety of
services, including indices that track trends like housing remodels and new
commercial construction. The company is based in Asheville, N.C.
The Challenge
-
Customer core customer base is insurance companies, which spend billions of
dollars annually on roof losses. The company provides estimates on the age
and condition of roofs to help its customers establish policies and
-
Customer initially built predictive models based on ZIP codes and other
general data using Python and R languages, but building the models was
complex and the results did not provide enough differentiators to boost the
-
Customer needed a solution that was easier to use and would support faster,
more accurate modeling for property-specific
Solution
-
Turned to
Amazon Machine Learning for predictive
-
Uses Amazon Machine Learning to provide roof-age and job-cost estimations
for insurers and builders, with property-specific values that don’t need to
rely on broad, ZIP code-level
- Uses data sets from public sources and from customers to build
Benefits
-
The best practices and ease of use built into Amazon Machine Learning
dramatically streamline the process of building predictive
-
Models that previously took six months or longer to create are now complete
in four weeks or
-
Customer can provide customers with easy, programmatic access to predictions
through
-
Creates opportunities for new data analytics services that Customer can
offer to customers, such as text analysis in Amazon ML to estimate job costs
with 80 percent
