摘要
互联网金融业务的飞速发展向个人征信领域提出了更大的需求和更高挑战,不同于基于电商、社交、网贷平台的征信数据来源,文章提出运用电信运营商通讯数据建立个人征信评分模型进行信贷结果预测,匹配信贷机构借贷及坏账样本数据,运用逻辑回归方法进行实证研究。验证表明电信运营商通讯数据与信贷结果具有强关联性,依据电信运营商通讯数据建立的个人征信评分模型可以在借贷坏账预测方面起到很好的效果。
The rapid development of Internet financial business has brought greater demands and challenges to the field of personal credit.It is different from the credit data sources based on e-commerce,social networking and online lending platforms.This paper uses telecommunication operators'communication data to establish a personal credit scoring model to predict credit results,matches loan and bad debts sample data of credit institutions.This paper uses logistic regression method to carry out credit scoring.The validation shows that there is a strong correlation between telecom operators'communication data and credit results.The personal credit scoring model based on telecommunication operators'communication data can play a good role in forecasting bad debts.
作者
韩勇
范若愚
康旗
魏永吉
毕朝晖
Han Yong;Fan Ruoyu;Kang Qi;Wei Yongji;Bi Zhaohui(School of Economics and Management,Beijing University of Posts and Telecommunications,Beijing 100876,China;Shanghai Lucheng Data Services Co.,Ltd.,Shanghai 200436,China;China Unicom Research Institute,Beijing 100176,China;Unicom Information Navigation Co.,Ltd.,Beijing 100032,China)
出处
《信息通信技术》
2019年第3期69-75,共7页
Information and communications Technologies
关键词
个人征信
电信运营商
通讯数据
评分模型
Personal Credit
Telecommunication Operator
Communication Data
Scoring Model
