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Home arrow Marketing Research News arrow Latest Market Research Findings arrow Risk Technology driver behaviour scoring shown to accurately predict likelihood of accidents
Risk Technology driver behaviour scoring shown to accurately predict likelihood of accidents PDF Print E-mail
Written by CAS   
17 Jun 2015

Independent study conducted by CAS highlights the value of telematics technology in reducing the risk of car accidents and insurance claims

A research study undertaken by driver behaviour experts CAS for Risk Technology, has revealed that data collected by automotive telematics devices can accurately predict the likelihood of a motorist having an accident.

CAS carried out the research with 1,291 drivers who were insured by a leading UK insurer and had telematics devices installed in their vehicles. The study examined how driver behaviour affects the chance of a driver being involved in an incident – and, therefore, the potential to make an insurance claim.

CAS concluded that the Risk Technology driver scoring methodology provides very good prediction of a driver’s potential to be involved in accidents than other technologies on the market because of the factors it takes into consideration and the way it does this.

The study investigated the accuracy of five key indicators used by Risk to predict driver behaviour, including: speed of driving, braking force, acceleration speed, whether or not the drive is taking place on an urban road, and or whether it is day or night time.

This information was collected from each driver’s telematics device and compared against the cause of any crashes or damages recorded by the insurer. The main reasons recorded for accidents included a lack of hazard perception, poor basic steering skills, loss of control of the vehicle, and not maintaining a safety envelope (the safe space around the car from other vehicles).

Different crash types are best predicted by different combinations of factors. For example, driver’s braking score was shown to be a very good predictor of loss of control, and is currently the most useful indicator to insurers for predicting this type of crash.

The current scoring methodology already predicts a high proportion of drivers who will be involved in crashes. CAS expects this prediction rate (the ability to identify individuals likely to be involved in crashes) to increase significantly when Risk introduces planned improvements to measure tailgating and poor lane discipline and even more sophisticated driver profiling.

Mark Packman, CEO at Risk Technology said: “This research proves that Risk Technology’s methodology and algorithms work to produce high accuracy predictions for insurance claims and thus help to improve the safety on our roads by reducing crash risk.

“We’re proud that independent research has shown what our insurance partners know already – that our driving performance scores correlate significantly with both the likelihood of being in a crash and the length of time that an individual goes without making a claim on his or her insurance.”

Each of the drivers used in the research had been driving with a telematics device installed in their car for between one month and three years. Of these policy holders, 104 people already had claims made against them for crashes for which they were at fault.

To download a copy of the report on these findings please go to: http://www.risktechnology.com/case-studies/independent-evaluation-of-the-risk-technology-driver-scoring-methodology/.
 
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