May 12, 2017

Auto Database Fills Recall Gap

George Leopold

(saravuth sawasdee/Shutterstock)

As the massive Takata airbag scandal illustrates, it has become nearly impossible to track down affected consumers who must bring cars to dealerships for repairs. One problem is that government watchdogs do not collect data on the soaring number of auto recalls or how dealerships handle them.

A data startup is attempting to address the gap between the growing number of recalls and fixing auto defects using machine-learning techniques. Recall Masters said it has amassed a database of more than 63 million vehicles in “open recall.” Applying a “digital forensics” approach, the company claims it has helped get hundreds of thousand of vehicle into dealerships for repairs.

Another addition to the database came Friday (May 12) when Fiat Chrysler recalled more than 1 million pickup trucks to fix faulty software.

The startup’s approach includes wrangling unstructured recall data from more then 50 data sources to construct a comprehensive recall database. The data is then organized into various categories such as “Don’t Drive” and “Stop Sale” that is loaded into its API and batch processing platforms.

The startup claims to have so far signed up more than 1,000 U.S. dealerships to its service.

The scale of the disconnect between auto recalls and the lack of hard data on repairing defects continues to widen. The National Highway Traffic recently told the web site Entrepreneur is does not collect or retain data on auto recalls or how dealerships resolve issues.

Meanwhile, Recall Masters estimates that more than 60 million vehicles were recalled in 2016 alone. At least four automakers were pulled into the defective airbag scandal involving Japanese manufacturer Takata. The company recently pleaded guilty to attempting to conceal defects in its airbags, which have been shown to shoot shrapnel when their airbags inflated, killing several drivers.

Along with its database, Recall Masters, Laguna Hills, Calif., has developed a proprietary “recall scoring methodology” that rates auto recalls based on five criteria. The result is an overall rating based on the level of safety risk to consumers. The approach also helps drum up profitable repair business for dealerships by determining the “repair profitability” for car dealerships.

The startup’s forensic approach “identifies open recall owners in a dealer’s service area, even if the vehicle has been resold multiple times,” according to the startup’s web site.

The service drills down to determine car ownership—even if a vehicle has been sold—and whether it qualifies for a recall. It then connects the owners of recalled vehicles with the appropriate dealership to repair defects. It also is pitched as helping carmakers and dealerships build customer relationships.

Recall Masters’ approach builds on earlier data efforts designed to glean consumer data such as warranty details and correlate it with public databases maintained by state motor vehicle agencies that track vehicle identification numbers and car titles. Marketers also use data generated by auto telematics to gauge customer preferences.

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