SYSTEMS AND METHODS FOR DRIVER SCORING WITH MACHINE LEARNING

Systems and methods for using machine learning classifiers to identify anomalous driving behavior in vehicle driver data obtained from vehicle telematics devices are provided. In one example, a vehicle telematics device receives vehicle driver data from sensors, identifies anomalies in the vehicle driver data by using an unsupervised machine learning process, calculates a driver risk score by using the anomalies identified in the vehicle driver data, and transmits the risk score to a remote server system. In another example, a server system receives vehicle driver data from a plurality of vehicle telematics devices, identifies anomalies in the vehicle driver data by using an unsupervised machine learning process, and calculates a driver risk score by using the anomalies identified in the vehicle driver data.