Problem: ForMotiv engaged with the Data Science and Modeling team at a Property and Casualty Insurer that sells primarily through the direct-to-consumer channel with eCommerce representing 85% of their transaction volume. Like most insurers, the client was looking to add additional datasets to their fraud, pricing, and underwriting models. The carrier has done studies where they concluded that 17% of their policies are misrepresented.

Solution: Prior to the launch of ForMotiv’s Behavioral Intelligence solution, the carrier was blind to customer behavior inside of their web application. While they were analyzing Quote Iteration data, the carrier had nothing that viewed user behavior during the application process. From experience, they felt (and later confirmed) this data could provide meaningful insights to understand both “safe” and “bad” risks.