Design of a Usage-Based Insurance Platform for Evaluating Driver’s Risk by Big Data Analysis

Abstract

Usage-based insurance (UBI) is a noticeable trend in auto insurance industry over the world The core concept of UBI is offering driver customized premium which based on their predicted driving risk according to realistic driving status Previous research indicated that UBI can effectively eliminate the information asymmetry in auto insurance market and bring benefits for auto insurers customers and the whole society However auto insurers are now lack of resources and funds to establish a complete UBI system since they are suffering from a vicious cycle which is caused by the information asymmetry Therefore this research proposed a novel UBI platform and selected a telecommunication company as operator to solve this problem Recently owing to the rise of OTT (Over-The-Top) services digital transformation is a common trend in telecom industry Moreover with the cost advantage of data communication and possessing experiences of renting devices this study believes that telecom company can play an essential role in manipulating the UBI platform On the other hand due to the limitations and disadvantages of driving risk prediction on current UBI models this work purposed a new driving feature－“Driving Pattern-N” which combined data mining techniques and near crash incidents to predict driver risk Three experiments and two criteria of risk level were designed to evaluate the performance of different driving features (i e “Driving pattern-N” “Driving Pattern” “Behavior-Centric” and “Historical Record”) under different situations

Date of Award	2020
Original language	English
Supervisor	Wei-Hsun Lee (Supervisor)