When it comes to claims handling, many insurers don’t know how to get the best out of their telematics data or sometimes don’t even know where to begin. This can lead to incorrect liability decisions, fraud cases slipping under the radar, and major injury cases not rearing their head until potentially much later on in the claim’s lifecycle, meaning valuable strategic opportunities have already been lost.
Even those insurers who routinely use telematics data in claims, report that doing so is a highly manual and time-consuming process for those claims staff who have the expertise to visualise and interpret raw telematics data.
That is where DWF’s new product TIA comes in.
TIA stands for ‘Telematics Interpretation Automation’ and it is designed to make interpreting telematics data simple, fast, and effective. With as little as 3 clicks it can generate on any given telematics claim:
- Crash Analysis Report (CAR) – an 8-page PDF containing 12 visuals and 12 key metrics to give an instant data-centric view of the collision that can be easily shared.
- A file that can be uploaded to Google Earth for a 360° view of the car’s journey, with any of the key metrics able to be displayed on each placemark, such as speed or acceleration at that point.
- A 3D simulation of the car’s journey from the driver’s perspective, again within Google Earth, allowing the handler an understanding of the car’s movements leading up to the collision that metrics and graphs alone cannot convey.
This means uncovering the story hidden in telematics data is now incredibly straightforward, with some of the measurable benefits being:
- Fewer paid non-fault claims, quicker settling fault claims, and lower litigation rates, all as a consequence of more accurate liability decision making.
- Improved hard-fraud and LVI repudiation rates.
- Reduced time to correctly identify and route major injury claims
These all ultimately translate to reduced indemnity spend, greater fraud deterrence, lower litigation rates, shorter claim lifecycles and earlier strategy implementation.
Let us take a look at a ‘Key Metrics’ section of a CAR, for a more detailed view of what TIA can produce:
Key Metrics
The Key Metrics Section is page 1 of the CAR PDF. It provides lots of useful information to the handler in just a matter of a few seconds, which would otherwise be very difficult and time consuming to calculate manually. There is a lot of physics and maths incorporated into TIA’s algorithm to calculate these metrics, and a full breakdown and guide to each one is provided within the product itself.
One particularly useful metric is the Peak ‘XYZ’ Acceleration. This is the highest G-force the vehicle experienced and is highly correlated to the severity of the occupant’s injuries, much more so than even the speed of the collision. This, combined with other metrics such as the direction of collision, is what primarily enables the early major injury detection.
Let us also take a look at an example simulation of a car’s journey leading up to the collision.
The simulation puts you in the shoes of the driver, travelling along the same roads at the same speeds and same directions. The placemarks ahead of you trace out your path and can be configured in a couple of clicks to show any useful information you would like (here it is speed in MPH and G-force when available). The placemarks are colour-coded, with a particularly key one to watch out for being the pink placemark which denotes the predicted site of the collision, which TIA calculates by interpolating between neighbouring GPS coordinates based on the milliseconds of the time of the collision.
The simulation makes it clear that the vehicle did not pause at all before entering the roundabout and was involved in a collision shortly after as a result. Toggling to street view allows you to see the road and roundabout as if you were there in person, but with the added benefit of being able to toggle back to the 3D view at any time to see placemarks and data overlayed on top.
Overall, TIA is a powerful tool that unlocks the potential buried in your telematics data while remaining easy to use for all handlers. It reduces indemnity spend, deters fraud, mitigates risk, produces operational handling efficiencies and in so doing, creates measurable value for insurers – which is the purpose of innovation.
If you are interested in discussing this further, please contact Simon White or Ryan Lysaght.
