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Data Driven Organisation website

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