3D Scanning Technology: The Future of Auto Estimating?

The next generation of auto estimating takes accuracy and interactive vehicle data to a whole new level by using 3D scanning.

By Sunil Nayak , Paul Rosenstein

With today’s auto insurance claims, repair shops and claims departments rely on vehicle data in order to help accurately assess the cost of a vehicle repair. For most appraisers, the data is sourced from the three major estimating software providers that either collect the data themselves or license the data from third parties. At least one provider of vehicle information is in the process of building a repository to house the next generation of accurate, interactive vehicle data using 3D scanning.

To obtain extremely precise data, cutting-edge 3D scanners, such as the devices offered to the aerospace industry, measure the car to a fraction of a millimeter. 3D scanning collects the measurements of a car’s frame and chassis and provides very detailed and accurate automotive information. You do not need to be an appraiser to appreciate the difference that level of precision will mean to the future of physical damage estimating.

How 3D Scanners Work

The process is a bit like watching an episode of Star Trek. An infrared laser scans the entire vehicle and generates a 3D point cloud. By moving the scanner around the vehicle, the laser can take several scans, with each one collecting 84 pictures as well as millions of points, each one two millimeters apart. The scanner has a range from half a meter (1.5 feet) up to 120 meters (over 300 feet). The complete 3D point cloud gives the ability to measure virtually anywhere on the vehicle. When this technology is leveraged, the potential it brings to the claims and repair process skyrockets. Some high-potential areas identified for use include deformation-based estimating, fraud detection, and consumer self-service.

Deformation-Based Estimating

Currently, it is sometimes difficult to detect damage during an initial inspection, especially when there may be only millimeters of deformation. With 3D scanning technology, an insurer could capture an image of a damaged vehicle and then view a color map that would highlight the extent of the impact. In effect, a damaged vehicle could be compared to a “clean,” undamaged vehicle that is in the database in order to identify impacted areas. Since the system can detect even the smallest dent, an appraiser would be able to identify hidden damage before writing the estimate—potentially preventing the need for a supplement or reinspection. Today, this type of analysis often is accomplished through an initial tear-down of the vehicle, which can create extra expense or vendor issues if the claim is eventually totaled.

Fraud Detection

In addition to helping ensure that estimates are right from the start, 3D technology could be used to prevent incidences of fraud or overpayment. Similar to a crime-scene investigator who can identify exactly how a transgression occurred, a 3D scan of the vehicle could identify if the vectors of damage match the facts of loss reported to the insurer. If the damage does not match, an alert could be sent to the desk reviewer or special investigation unit (SIU) department with a notification of the potential for fraud on the claim. Also, a desk reviewer could look at a photo comparison to identify prior damage on the vehicle, helping to prevent overpayment on the claim.

Consumer Self-Service

Another potential area for this technology is in the use of photo-based estimating. A consumer could take a picture of his vehicle and upload it to his insurer via smartphone. From there, the insurer could compare the uploaded image to the 3D scan of the vehicle available in its database to see how much damage occurred. If the damage is under $1,500, the insurer could opt to place the claim on a fast-track settlement path with an automated value or photo-based estimate in order to reduce loss adjustment expense. This type of fast-track settlement, if severity can be accurately controlled, has great potential to produce major loss adjustment expense savings.

The 3D Future

As the industry continues to demand increasingly more accurate information to restore vehicles to pre-accident condition, the future of 3D data collection is extremely bright. The ability to collect automotive frame measurements and chassis diagram data from most original equipment manufacturers worldwide and deliver it to insurers and collision repair facilities through estimating solutions would be an important step forward.

While there are identified uses for this next-generation 3D database, new technology always transcends its original intended application. The most exciting, game-changing applications for this data have not yet been imagined.

Sunil Nayak is director, product management, for Mitchell International, www.mitchell.com. He has been a CLM Fellow since 2014.

Paul Rosenstein is vice president, product management, for Mitchell International, www.mitchell.com. He has been a CLM Fellow since 2014.

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