In this article series, we will explore how new behavioural data is generated and early signs of how this data could be the next wave of predictive power for issues like fraud, and maybe even claims costs. This month we’ll be hosting a live webinar where we will discuss these trends and review a software solution to capture this kind of data. To register, click here.

In our article last week, we showed how the use of a completely new type of data, digital behavioural data, can enhance the fraud models of insurers. This is generally true of any new vector of data with little to any correlation to the conventional data used to build today’s models – and the more novel the data is, the more likely that the data will have predictive power in very unexpected places. The history of credit data predicting motor losses, telematics data predicting non-driving losses, and other novel datasets experience confirms this.

What is the future of digital behavioural data?

We have known from decades of academic research that driving in certain emotional states creates a propensity to dangerous driving and accidents. Several investigations have shown that emotional state has a significant impact on driving ability, with poor driving more likely to occur at both extreme positive and negative moods. We also know that individuals retain habits which were formed at a young age. Normalised for age, income, education, and other factors, people who are more angry, distracted or excitable as young drivers are more likely to exhibit the same traits as older drivers. Therein lies the next frontier of using digital behavioural data.

Key questions to consider:

  • Could it be possible to predict future fortuitous activity with this data?
  • If these are innate traits, can we find this predictive power by somehow testing against a present population with their previous loss experience?
  • If there is predictive power, will a company be willing to maximise their customer selection practices?
  • Should mis-spelling my address increase my rates for car insurance?

It might not end there. Should insurers and lenders re-design their online applications – not to improve the customer experience – but to maximise the power of the emotional data that is captured, is there an intentionally challenging and frustrating drop-down targeted to me because I entered my birth date wrong twice? Intelligent and conditional use of the web experience for behavioural data capture might be on the horizon. Are you ready for it?

In this series of articles, we explored how digital behavioural data is generated with ForMotiv. Read part one here, part two here and part three here.

For further information please contact Linda Bertolissio or Riina Rintanen.