Two opposing views:
In our recent ‘Tipping Point’ Newsletter, I stated that one route to mass versus niche market for UBI/Telematics is right data vs any data. I would like to explore what that means in more detail. So, in the words of Oscar Hammerstein II ‘Let’s start at the very beginning’.
Firstly, the quality of data is rooted in the quality of signal from source.
The source is typically (in a device) three sensors: GPS, accelerometer and gyro. If the procurement of those sensors is solely driven by price, the quality of signal will be compromised. Some app-only providers argue that sensor information from a smartphone is as good, but we see issues if the phone is not in a fixed position, increased battery drain and even whether the phone is in the car at all as reasons for concern.
Sampling rate is another feature of signal quality – its frequency. REDTAIL leads the market in its provision of 10Hz – that’s ten cycles per second, in other words ten times the industry standard. This enables us to offer more granular and advanced driver scrutiny and scoring, increasing the normal four parameters fourfold, to include proven high risk signatures such as tail-gating, corner braking, swerving, turning at junctions, roundabouts, queuing traffic. In other words, we are able to detect those high risk driving events, way beyond the regular braking and acceleration metrics.
The second aspect of the right data is its accessibility in the most helpful form and format.
APIs providing raw data for more technically savvy customers; bespoke web portals breaking data into pre-analysed buckets for some less so. For our customer’s end consumers, we have white label apps offering both fleet and vehicle performance tracking and data, and also driver insight combining scoring and gamification to coach and improve safety and eco driving behaviours.
And the final aspect of right data is its value to you, the customer, in making critical business decisions.
A number of TSPs include ‘Actuary’ in their skill sets. Two thoughts:
i) in our experience, each insurer approaches risk differently, and therefore
ii) we prefer our data to inform customer data.
Our data scientists work very closely with your teams (whether in risk or claims or commercial) to maximise the impact of your data relevant to your business, to your book and to your valuable policy holder.
So, in summary, the recommended approach requires a combination of component quality, of information access and of genuinely collaborative data insight. Then, and only then, will the right data deliver the right results.