Abstract: Described herein are systems and methods for applying machine learning to telematics data to generate a unique driver fingerprint for an individual by periodically receiving telematics data generated at a plurality of sensors of a vehicle; standardizing the telematics data; aggregating the standardized telematics data; applying a trained machine learning model to embed the aggregated telematics data into a low-dimensional state; and generating a unique driver fingerprint for the individual, the driver fingerprint comprising a static component, a dynamic component, or both a static component and a dynamic component; including iterative repetition to update the dynamic component of the driver fingerprint.

Abstract: Described herein are systems and methods for applying machine learning to telematics data to generate a unique vehicle fingerprint by periodically receiving telematics data generated at a plurality of sensors of a vehicle; standardizing the telematics data; aggregating the standardized telematics data; applying a trained machine learning model to embed the aggregated telematics data into a low-dimensional state; and generating a unique vehicle fingerprint, the vehicle fingerprint comprising a static component, a dynamic component, or both a static component and a dynamic component; including iterative repetition to update the dynamic component of the vehicle fingerprint.