Insurance Assessment Based on the Big Data of Driver Historical Timeline and Car Accident Occurrence

Whether you are a novice or a veteran, driving a luxury car or an ordinary domestic car, car insurance is necessary, especially for people who often need to drive for a long time to commute, the importance of car insurance is even more important; after all, car incident is unexpected and always caught off guard. Most of the current mobile phones have a GPS function, but in the mobile phone settings, you can manually turn off or turn it on, and continuously turning on the GPS can record the motion paths. Meanwhile, most countries statistic the car accident occurrences and stored them as open data for all relevant agencies to improve traffic transportation safety and policy formulation. In this paper, we utilize the historical timeline big data recorded in the Cloud to evaluate the driver's road dangerous level by driver's road habit and the car accident occurrence hot zones which can be the partial factor to determine the insurance premiums. Here, we acquire the car accident hot zone data from Tainan City Transportation Bureau, Taiwan, and the driver's Google timeline data to analyze his road habit dangerous level. If the dangerous level is high, we can remind him to change his road habit and taking a safer path to drive. The insurance company can charge the driver's insurance premiums according to the dangerous level he owns as well. During the research process, we discussed with the manager of the auto insurance company, and he also said that the results are of a reference value.