Identified and validated behaviours that complemented customers' risk profile
Social media based risk profiler

A major global insurance company wanted to complement their thinking in risk assessment in motor insurance business and consider social data to help define additional parameters in the risk pricing model
The challenge
How PA helped
Identifying behavioural factors which can complement the accuracy of the client's current predictive models used in underwriting and pricing motor insurance; 5 factors were confirmed by the client
Benefit for the clients
These behavioral factors, which were not known to the insurance company prior to the project, can be used alongside the hard-data to better profile and segment the customers. This has major implications on customer communications, pricing and marketing activities