When Telematics Meets AI Image Analysis: The Transformation of Damage Claims

Traffic accidents are always a mess - for drivers, insurance companies, and police. Sorting out what damages need to be paid for; what the traffic conditions were; if the brakes working properly; whether there was a sufficient gap between vehicles; if the weather was a factor, is a long and complex process. But all of these factors and more need to be assessed in order to determine who is responsible, who needs to pay for the damage, and whether the driver needs to be cited or even prosecuted for negligence.

Fortunately, there are increasingly accessible tools that can help insurance adjusters, claims managers and drivers cope with the damage, the loss, and the aftermath of an accident. Mobile scanning of damage and automated AI-based analysis of these images, combined with telematics data retrieved from vehicle computers is an especially powerful combination that can help augment traditional post-accident investigations and police reports. These tools can help insurance adjusters understand how extensive and costly the damage is; reconstruct what happened, and determine fault, ensuring that the responsible party’s insurance company is the one that foots the bill. This is important even in states with no-fault insurance, as the insurance company will want to recover settlement money paid to their customers if it turns out that another party was at fault.

Typically, after accidents, police will examine the scene, determining the direction of the vehicles and where exactly the collision or incident took place, as well as estimating the speed of the vehicles involved, based on visual assessment of the vehicles or available roadside radar and speed detection systems. Police can also examine footage from highway or road cameras. In addition to relying on these police reports, insurance companies will assess the damage and conduct their own investigations, documenting damage, evidence from the scene, speaking with witnesses and trying to piece it all together.   

To help make these investigations quicker and more accurate, insurance adjusters, and even drivers themselves can use a mobile phone app to scan and take photos of the damage of the car and from the scene, as soon as an accident happens—and upload these images to a database. AI helps analyze the images for details regarding the damage, and compares them to billions of stored images to determine exactly what the damage is, how much it will cost to repair it, and even, by examining the angle, severity, and type of damage, could help determine who is responsible for the accident. This system is more objective than human visual assessment, and more comprehensive as it can see details beyond what an expert adjuster can even imagine as it accesses a huge image library for its analysis, taking into account every detail about damage.

In addition to speed and accuracy, AI image analysis can also help prevent fraud and inaccurate claims. Some drivers may try to take advantage of an accident to fix previous dings and dents – costing the insurance company more money. AI image analysis systems, including Ravin’s system, can determine whether damage is current – or was there before the accident. 

Along with post-accident AI-assisted scans of vehicles, telematics can help adjusters determine responsibility and evaluate claims. Over 70% of late model cars worldwide (and over 90% in the US) include telematics systems. These systems collect data from vehicle sensors and keep track of data like location (GPS), speed, braking power, fuel consumption, vehicle performance, and engine data. This can all be very useful in helping insurance adjusters understand whether an accident was caused by a driver, a vehicle that needed repairs, or any icy road. Many insurance companies offer drivers discounts for allowing them to access this telematics data, and although drivers are not required to provide telematics data to insurance companies (or police, for that matter), studies show that telematics makes the claims process faster, smoother, and easier for everyone - benefitting the consumer, who gets their settlement more quickly, as well as the insurer, who gets credit from the consumer for handling their claim efficiently.  

The combination of AI image analysis and telematics can also be very useful to police, if an investigation is deemed necessary. Although drivers are not required to allow them to access vehicle telematics or other data like that from dashcams (police can seize data or images if there is cause), drivers who do so may find themselves more quickly exonerated in accidents where they are not at fault.

As traumatic as they are when they happen, traffic accident investigations don’t have to be something to lose (too much) sleep over. With advanced AI imaging tools, and in-vehicle data, insurance companies can more quickly and efficiently determine responsibility and how much it will cost to fix a vehicle. Ultimately, this leads to cost-savings and better customer service.. Advanced AI imaging and telematics - along with the skills and expertise of experienced adjusters - can ensure that drivers can come to a quicker, more transparent resolution of liability issues, and ensure that the rights of everyone involved are preserved.