Fleets face missing out on the benefits of behavioural telematics, because some systems do not provide the information needed to manage risk.
Measuring the relevant driver behaviours and then understanding underlying root causes, as part of a wider road risk strategy, will help improve fuel efficiency and lead to a safer fleet.
However, Zurich says that all too often fleets are investing in systems billed as behavioural telematics, but they are failing to deliver the desired results.
Nick List, fleet intelligence proposition manager at Zurich, said: “Too many times we have seen organisations that have invested in what they believe to be driver behaviour telematics but, through no fault of their own, they are not achieving the reductions in risk and the other benefits telematics can bring.”
Zurich argues the key behaviours a system should measure are braking, acceleration, cornering and lane changing, speed versus posted speed limit and fatigue. However, not all systems provide this information - a system may record vehicle speed but not the posted speed limit, for example.
As a result, Zurich is calling for providers to develop a standard set of driver metrics for behavioural telematics to help fleets improve their risk rating.
List explained: “Unfortunately, there is no standard definition of what behaviours when measured with a telematics device will help the purchaser achieve their expected results in terms of improving driver behaviour.
“Zurich would like to see the introduction of the measures we’ve highlighted as being the standard set of criteria recognised as telematics driver behaviour metrics by all telematic service providers.”
However, List also the stressed the need for companies to act on the data, with line managers giving regular feedback to drivers. This could include praising the driver for good driving, as well as understanding where the business may be at fault for poor driver behaviour, and taking steps to reduce and ultimately eliminate that type of driving.
Real time in-vehicle feedback to a driver, either visual and or audible may also reinforce line manager messaging.
Zurich’s appeal comes as a study suggests that telematics data can accurately predict the likelihood of a motorist having an accident.
Competence Assurance Solutions (CAS) carried out the research for Risk Technology with 1,291 drivers who 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.
It investigated the accuracy of the five key indicators used by Risk Technology 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.
The information was collected from each driver’s telematics device and compared against the cause of any crashes or damages recorded by the insurer.
However, while the metrics were slightly different to those suggested by Zurich, CAS concluded that the risk technology driver scoring methodology provides a very good prediction of a driver’s potential to be involved in accidents, because of the factors it takes into consideration and the way it does this.
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, a 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.
Each of the drivers participating in the research had been driving with telematics 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.
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Gareth has more than 20 years’ experience as a journalist having started his career in local newspapers in the 1990s. Prior to joining Fleet News in 2008, he worked in the public sector as a media advisor and is currently news editor at Fleet News.
Greg Bayley - 01/07/2015 21:03
Being involved in the driver behavior area has let me see how preconceived notions regarding a topic like, what predicts bad driving and accidents have evolved. I have run across a group of drivers that have had no tickets and no accidents that most people would consider to be maniacs behind the wheel. If this group has low incidents of accidents and citations, do we rely on factors that have no basis in fact? It will take time to learn the factors that are related to accident causation. We have the tools to collect the data. Insurance companies have the claims and accident information. We have to let those numbers tell us what the predictors are of drivers that are involved in accidents. Then their is the issue of where do you draw the line separating bad from good. Most that I have seen are arbitrary and qualitative not quantitative. Early statistical applications use to cut off the normal distribution at plus or minus 3 standard deviations. Non-normal driving behavior should linked to a statistical distribution and a a level where the behaviors are considered not to be a part of a normal distribution. I'm an engineer. I think by statistician colleagues have even more quantitative ways to draw lines that are fair.