The Commercial Modes Practice Of UBI Of The Commercial Vehicles

The internet thinking deeply permeates all aspects of people's life,along with the rapid development of “internet plus” after the concept “internet plus” emerging.Freight industry,a pillar of the national economic advance traditionally,is inevitably involved in the reform.In recent years,the Ministry of Communications has issued a series of regulations and communication treaties(protocol)pointing to Internet of Vehicles.Thanks to the fast advance of the Internet of Vehicles-a member of internet,a number of companies which devote themselves to the reform of vehicles' insurance industry spouted out.This essay will focus on the discussion on a kind of commercial mode aiming at the commercial vehicles' insurance on the background of the Internet of Vehicles.This essay will start with the concepts and contents of commercial mode in order to analyze the advance of the commercial mode in the Internet-of-Vehicles scenario besides the effects of the logistics,finance,petroleum and insurance industries.We will mainly employ commercial cases of the UBI insurance of the commercial vehicles to research the topic,and make some practical analysis according to the elements of the commercial mode.The commercial modes of UBI of the commercial vehicles will proceed as follows.To begin with,integrate the peripheral resources of the Internet of Vehicles,such as upstream hardware manufacturers,vehicle factories,data-gathering service providers,related software-service providers,logistics companies as well as downstream insurance companies.Moreover,collect the data of the vehicle localization and operating status for the sake of building the big data platform by the following ways: explore the driving behaviors through the big-data-mining theory,then extract peripheral driving environments together with the electronic maps,and create the actuarial UBI models of commercial vehicles which suit the vehicles characters.At last,put the model into practices,which help the insurance companies more efficiently predict the loss ratio of the vehicles.