The key problems with big data can be categorised by four V’s: volume; variety of information (drawn from humans and machines); velocity; and variability of quality and value (including where data is sold on to third parties, leading to a loss of control over that data).

Pricing is significantly impacted by new technologies. New market entrants can have a huge competitive advantage simply by having far lower (up to 22%) operating expenses. Big data can help refine prices, though this can create a risk if it spirals out of control and triggers a price war or produces anti-selection. New technologies do, however, offer new value propositions: better assessment of the customer’s risk profile, more interactions with the customer, and better insights of the customer’s needs and preferences.

P&V (Belgium) is about to launch an on-demand “pay-as-you-drive” motor policy. The policy will have dynamic pricing, using telematics to assess risk based on driving conditions which can change the premium (for example terrain and time of day). Data also helps build prevention activities, such as sending warnings (e.g. of black ice) or advising lower driving speeds. It can even advise how to reduce fuel consumption.

Sensors in the connected home also can play a role in dynamic pricing. Water leakage sensors can warn customers of leaks so that they can intervene to address the problem early.

Real-time pricing can also be considered. The data can show if a driver is, for example, speeding, distracted by looking at their mobile phone, or driving in rain. As a result, the premium can be instantly increased.

Dynamic pricing also enables customer retention, as the entire customer base can be assessed for their lifetime value against the likelihood of them leaving the company. Discounts can therefore be applied where required.