LexisNexis, which generates consumer risk profiles for the insurers, knew about every trip G.M. drivers had taken in their cars, including when they sped, braked too hard or accelerated rapidly.

Kenn Dahl says he has always been a careful driver. The owner of a software company near Seattle, he drives a leased Chevrolet Bolt. He’s never been responsible for an accident.

So Mr. Dahl, 65, was surprised in 2022 when the cost of his car insurance jumped by 21 percent. Quotes from other insurance companies were also high. One insurance agent told him his LexisNexis report was a factor.

LexisNexis is a New York-based global data broker with a “Risk Solutions” division that caters to the auto insurance industry and has traditionally kept tabs on car accidents and tickets. Upon Mr. Dahl’s request, LexisNexis sent him a 258-page “consumer disclosure report,” which it must provide per the Fair Credit Reporting Act.

What it contained stunned him: more than 130 pages detailing each time he or his wife had driven the Bolt over the previous six months. It included the dates of 640 trips, their start and end times, the distance driven and an accounting of any speeding, hard braking or sharp accelerations. The only thing it didn’t have is where they had driven the car.

On a Thursday morning in June for example, the car had been driven 7.33 miles in 18 minutes; there had been two rapid accelerations and two incidents of hard braking.

  • kbal@fedia.io
    27·
    8 months ago

    It serves as a convenient representative example of the ways in which such systems can go wrong.

    • kbal@fedia.io
      5·
      8 months ago

      I mean, this is the world of software and computer systems. The map is always outdated, the model is always fictional, and the metric is always measuring the wrong thing. Even aside from the obvious privacy problems this kind of big data approach has its limits which are too easily ignored by insurance companies eager to take the average across thousands of mistakes hoping to get something profitable. As is becoming increasingly more obvious to the general public as computer algorithms designed in secret rule more of our lives, quite often the best that can be managed is a system that works adequately well for the purposes of its designers even while it takes decisions that are utterly stupid at the level of the individual people subjected to it.