新能源汽车风险评分数据集

风险评分数据集是基于车辆充电行为和车辆状态数据，结合保司现有的承保理赔数据，打破了传统汽车保险的定价方法，用车辆大数据赋能车辆保险经营。大数据风险评分作为保险公司新型核保工具，与传统车险定价相比，增加模型因子的解释维度，提升模型稳定性和区分度。大数据风险评分可以合理反映车辆的风险概率和风险成本，体现保费的公平，改善驾驶行为，促进安全驾驶等。保险公司在应用时通过输入相关车辆数据以及核保数据，通过隐私计算平台技术，由计算模型调用充电行为和车辆行为特征数据，仅返回车辆风险评分结果给到保险公司，达到数据可用不可见的目的，保险公司依据车辆风险评分结果进行核保定价。

The Risk Score Dataset is built upon vehicle charging behavior data, vehicle status data, and the existing underwriting and claims data of insurance companies. It subverts the traditional auto insurance pricing methodology, empowering auto insurance operations with big vehicle data. As a novel underwriting tool for insurers, big data risk scoring expands the explanatory dimensions of model factors and enhances model stability and discriminative power compared to traditional auto insurance pricing. It can reasonably reflect the vehicle's risk probability and risk cost, uphold the fairness of insurance premiums, improve driving behavior, and promote safe driving, among other benefits. When deploying this tool, insurance companies input relevant vehicle data and underwriting data. Leveraging privacy computing platform technologies, the computational model invokes charging behavior and vehicle behavior characteristic data, and only returns the vehicle risk score results to the insurance companies, thereby achieving the goal of "data usable but not visible". Insurance companies then conduct underwriting and pricing based on the obtained vehicle risk score results.