Our in house data science teams work closely with, actuaries, behavioural psychologists, and operational colleagues to constantly review new and historical data to produce scoring algorithms that are highly predictive of risk and have the ability to detect high risk drives at a very early stage within their cover
We have been and remain advocates of the positive impact of coaching on behavioural change. Working in parrel with Cranfield University, we reviewed decades of scientific research and used this as the foundation of our coaching model.
With billions of miles and hundreds of thousands of crash events recorded, we have a combined social and data science to identify best in class methods of coaching and engagement that have delivered quantifiable improvements in behaviour and reductions in loss ratio.
Cross departmental collaboration between our psychology, data science, and actuarial teams provides a unique environment where by we analysis performance data against actual outcomes, this allows us to refine our behavioural coaching strategies to deliver a specific outcome for our clients.
Through analysing individual trip data, accepting that everyone can have a bad day, we take a holistic approach focusing on trends and dangerous events rather than isolated events, this provides a clearer view of true behaviours and resonates better with policyholders when delivering feedback.
Key data inputs to coaching include harsh braking, harsh acceleration, harsh cornering, speeding, and distracted driving.
Our ultimate goal is to assist to be better drivers and keep people safe on the road.