Allstate used GasBuddy and other apps to track driving behavior: lawsuit

Original Article ↗ Hacker News Discussion ↗

Allstate is being sued in Texas for allegedly using data from third‑party apps like GasBuddy and automaker telematics systems to secretly track drivers’ behavior and adjust insurance risk profiles. Commenters weigh the trade-offs between sharing detailed driving data for potentially lower premiums, the reliability and fairness of insurers’ scoring models, and the broader shift toward pervasive surveillance in cars and phones. The thread also delves into how insurers make money (often via investing premium “float” rather than underwriting profit) and whether mandatory insurance should be restructured or nationalized to reduce perverse incentives.

Scope of Data Collection

  • Discussion centers on Allstate/Arity using data from third‑party apps (e.g., GasBuddy) and automakers (Toyota, Mazda, etc.) to infer driving behavior.
  • Some note that GasBuddy’s detailed tracking was tied to an opt‑in “Trips” feature, not default use.
  • Car telematics (OnStar-style modules, OEM “connected services”) are seen as a bigger, harder‑to-avoid source of data than apps; disabling modules may be technically possible in some older cars.

Privacy, Consent, and Surveillance

  • Many see this as covert mass surveillance: unclear or buried consent, data repurposed for insurance and sold to brokers.
  • Strong sentiment that location and behavior tracking should be illegal unless clearly opt‑in, with meaningful alternatives.
  • Some worry about broader patterns: apps and cars building detailed profiles, including in‑car cameras and attention monitoring; Mozilla’s survey of car privacy is cited as alarming.
  • A minority argue that more monitoring is acceptable or desirable if it deters dangerous driving, especially given rising pedestrian deaths; others counter that this normalizes pervasive surveillance and should be replaced by conventional traffic enforcement.

Insurance Economics and Fairness

  • Debate on whether “good drivers subsidize bad drivers.”
    • One side: yes, because high‑risk drivers can’t practically be charged their full actuarial cost, so low‑risk drivers are priced up.
    • Other side: bad drivers already pay higher premiums; insurance is inherently a shared‑risk pool.
  • Extensive argument over whether property/casualty insurers lose money on underwriting and profit only via investing “float.”
    • One view: combined ratios often exceed 100% over long periods; underwriting is effectively a loss leader.
    • Counterview: core operations must be and often are profitable; recent climate‑related losses are exceptional, prompting exits and price hikes.
  • Discussion on telematics scoring:
    • Concerns that metrics like “hard braking” and night driving lack context and can punish safe drivers or those with unusual schedules.
    • Fear that shared data will mostly be used to raise rates or deny coverage, with limited and temporary discounts.

Policy and Structural Proposals

  • Suggestions include: government‑run non‑profit insurance where coverage is mandatory, or a single risk pool funded via fuel/charging taxes.
  • Others note public or mutual insurance already exists in some regions but is not necessarily better.

Practical Workarounds and Unclear Points

  • Some recommend:
    • Using web versions of fuel‑price tools instead of apps.
    • Avoiding OEM connected services or apps (e.g., for remote start) that require broad data‑sharing consent.
  • Technical questions remain:
    • How reliably insurers can distinguish drivers vs. passengers from phone data.
    • How exactly third‑party app identifiers are matched to specific insurance customers.