Mobilisights develops anonymized data services for connected vehicles

Two years ago, Stellantis launched Mobilisights as a data-as-a-service business unit primarily focusing on fleets. Entering its third year, the company is expanding its scope by introducing a new platform that emphasizes the use of anonymized data, utilizing differential privacy techniques to protect driver and vehicle identities. This new direction aims to go beyond their initial fleet customer base, enabling Mobilisights to collect, aggregate, and analyze vehicle data in innovative manners that adhere to strict privacy standards. A critical component of the data processing taking place at Mobilisights involves the anonymization of collected data. While Stellantis remains the data controller with access to raw data, Mobilisights acts as the data processor. Their role includes providing the specifications for the anonymization engine that Stellantis implements and manages. This engine is designed to discard identifiable trip details such as the beginning and end of journeys alongside the vehicle identification number (VIN), ensuring no personally identifiable information can be traced back to individual drivers or vehicles. Randomized, hashed identifiers are assigned to data segments, minimizing the chance of reverse engineering. Mobilisights' approach allows for the collection of combined data segments from the same location within similar time frames, which helps to verify accuracy. However, any inadequate or unreliable data segments are discarded to maintain data integrity. At present, Mobilisights is not generating significant revenue, although the company has secured enough partnerships to sustain its data service expenses. The potential applications for the insights derived from this anonymized data could benefit automakers, aiding in the provision of alerts regarding hazards to drivers on their routes. Currently, Mobilisights is collaborating solely with Stellantis, and their establishment as a separate business unit aims to facilitate partnerships with additional automakers in the future. By bringing more automakers into the fold, the overall quality and robustness of the data could significantly improve, thereby enhancing the utility of the insights generated. Prospective partners will need to implement their own anonymization engines resembling the model set forth by Stellantis, promoting further data privacy and security while expanding Mobilisights' reach.