The Future of Estimating

June 1, 2015
Sunil Nayak, director of product management at Mitchell International, explains why 3-D scanning technology could change the estimating process

Today’s vehicles incorporate the newest technologies and require highly accurate information in order to repair them back to pre-accident condition. The future of that technology could include 3-D scanners, which have the power to transform the estimating process. Mitchell recently opened a Technical Research Center with the goal to leverage that technology. Sunil Nayak, director of product management at Mitchell International, recently discussed the technology and what it means for the collision repair industry.

Why is 3-D scanning an important new technology for the industry?

With today’s auto insurance claims, repair shops and claims departments rely on vehicle data 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.

3-D scanning collects measurements of a car’s frame and chassis, and provides the most detailed and accurate automotive information. Some high potential areas identified for use include deformation-based estimating, fraud detection and consumer self-service.

What does deformation-based estimating look like?

With 3-D scanning technology, an insurer could take 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 is able to 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 re-inspection. Today, this type of analysis is often accomplished through an initial teardown of the vehicle, which can create extra expense or vendor issues if the claim is eventually totaled. 

How can this technology help with fraud detection?

In addition to helping ensure estimates are right from the start, this type of technology could be used to prevent incidences of fraud or overpayment. A 3-D 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 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.  

What is the benefit for consumers?

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 a smartphone. From there, the insurer could compare the uploaded image to the 3-D scan of the vehicle available in the 3-D 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.

How is Mitchell leveraging this technology? Where are we at right now?

We recently opened a technical research center that allows us to collect automotive frame measurements and chassis diagram data to provide to repair shops, collision and body shop centers. The center is equipped with 3-D scanning technology from FARO. Mitchell authors a lot of its own editorial content itself, meaning that we get raw OEM data from most of the automobile manufacturers in the US. We take that data and distill it down to data that’s consumable for the collision estimating industry. 

As a part of that process, it’s very useful to have a technical research center to bring in vehicles to understand how they’re built or how the parts are assembled onto those vehicles to facilitate creation of this content for collision estimating. We also supplement the data by doing some additional frame dimension analysis on those vehicles that we bring in. Intrinsically, we author our own data. We don’t license it from a third party. As a result of that, it’s very useful when we get this raw OE data to bring in the corresponding vehicle and create the content for that vehicle and really analyze how that vehicle is constructed to generate that content. 

As the industry continues to demand increasingly accurate information to restore vehicles to pre-accident condition, the future of 3-D data collection is extremely bright. This advanced technology to collect automotive frame measurements and chassis diagram data from most original equipment manufacturers worldwide and deliver to insurers and collision repairer through estimating solutions would be an important step forward. While there are current identified use-cases for this next-generation 3-D database, new technology always transcends its original intended application. The most exciting, game-changing applications for this data have not even been imagined. 

What is the benefit of authoring your own data?

It’s more quality, accuracy and control of what goes into the collision estimating software. As opposed to purchasing it from a third party, where you don’t know how they’re authorizing the data or actually coming up with the values or labor rates that are going into the software. If we have the technical research center and we author our own editorial content, we basically control the collision estimating process in our software end to end, from the data through to the output.

Why is building up the data set an important step?

The data collection is essential for the collision estimating software. Basically that software is just a collection of parts, labor times and other information that when a vehicle is damaged, the software can call upon that data to create the estimate for what it would take to repair the damage. Ultimately, the accuracy and quality of the estimate is based on the accuracy and quality of the data that goes into that system. By controlling not only the way the software draws on the data to create the estimate, but also controlling the content that goes into that software, those are the reasons why we author our own software and have our technical research center to aid in that process. Shops need to ensure they repair based on accurate information, so we’re trying to build up data to help our customers do that. 

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