For insurers looking to expand into new areas of recall, finding the right data to make pricing decisions can be difficult.

In this case study, we look at how unstructured web data, such as news articles and reports from regulatory bodies, can be used to unlock rating attributes for automotive recall that are powerfully predictive of loss frequency and severity.

To download the case study, please enter your details below.

Name *