大数据背景下个人信用评估体系建设和评估模型构建

Construction of Personal Credit Evaluation System and Evaluation Model Construction under the Background of Big Data

大数据和云计算等信息技术的飞速发展为金融行业开展征信业务提供了海量数据与先进技术。基于传统个人征信和现有互联网金融征信体系,从个人特征、经济能力、消费偏好、社交网络、信用情况和风险信息六个维度构建基于大数据的个人信用评估体系,尽可能涵盖影响信用主体行为的主要因素,减少主观评价信息。与此同时,基于大数据和信用评估体系特征,对信用评估进行数量化建模,运用层次模型、熵权法和汇总评估方法,对个人信用评估体系各个维度以及最后得分进行评估,期望充分利用主观数据和客观数据的优势,确保信用评估的准确性和科学性。

With the rapid development of big data, cloud computing and other computer technologies, the emergence of massive data provides data and technical support for the financial industry to carry out credit reporting business. Based on traditional personal credit and the current Internet financial credit system, from the six dimensions of personal characteristics, economic capacity, consumer preferences, social networks, credit status and risk situation, the paper presents a big data-based individual credit evaluation system, which covers as much as possible the main factors influencing credit subject behavior so as to reduce subjective evaluation information. At the same time, based on big data and characteristics of credit evaluation system, numerical modeling of credit evaluation, by making full use of hierarchical model, the entropy weight method and summary evaluation method, the paper makes evaluation on the dimensions of individual credit evaluation and the final scoring, expecting to realize the accurate and scientific credit evaluation by taking the full advantage of subjective and objective data.