“The last ten years have seen a dramatic rise in the wireless transmission and use of automotive sensor data — commonly known as “telematics”. UPS, an early pioneer in telematics for delivery fleet management, collects over 1.25 billion telematics records per week, and through analysis of this data, is able to save nearly one million gallons of gasoline a year, as well as improve delivery times. (History and Evolution of Telematics, 2015).

With the expectation of more and more new cars to be produced with integrated global telematics over the next years, new business models are emerging to take advantage of this growing technology. Insurance companies, for example, now have several forms of telematic insurances, such as Pay-As-You-Drive (PAYD) and Pay-How-You-Drive (PHYD) and utilize collected vehicle-monitoring parameters for their insured drivers. The telematics transmitting devices typically monitor GPS location, speed, acceleration and time of day, amongst other parameters. Insurance premiums can then be set based on a specific driver’s driving habits…

…Building on IBM-lead work on adding encryption to Apache Parquet files (https://github.com/apache/parquet-format/blob/encryption/Encryption.md) and our work on the European Union sponsored Horizon 2020 project, RestAssured (https://restassuredh2020.eu/), we have implemented a prototype of how an end-to-end, Cloud-based PHYD system leveraging the power of Apache Spark analytics while protecting the privacy rights of the data subjects, can be securely implemented.

The basic use-case scenario and implemented architecture can be seen in Figure 1.”

Figure 1: Architecture of the Telematics Insurance Use case

The full article by Eliot Salant and Gidon Gershinsky  of IBM continues here.