T/MSITISA 03-002.04-2021 Big Data Credit Data Description Personal Data Security Level Guide
T/MSITISA 03-002.04-2021 Big Data Credit Data Description Personal Data Security Level Guide
Basic Information
Scope
Main technical content: Data can represent the characteristics of things, and the basic units of these data are called data elements. Big data credit reporting utilizes the advantages of IT technology and risk control models to integrate individuals' fragmented massive data from different credit institutions and consumption scenarios. After a series of processes such as data cleaning, analysis, and verification, the data are processed and integrated into truly useful information. In the context of big data, personal credit reporting currently faces many problems, including the lack of business standards and norms, the serious phenomenon of credit data silos, and the inconsistent security level standards. The Zhongguancun Sifang Modern Service Industry Technology Innovation Strategic Alliance uses the Big Data Credit Reporting Intelligent Evaluation and Service Open Platform to gather credit data from different companies, host credit services from different companies, break down barriers between different credit services, and conduct application demonstrations in typical service scenarios to optimize the social credit environment and promote the construction of a social credit system. After being carefully and rigorously standardized and regulated, the data will greatly enhance their practicality and shareability across systems and environments. Identifying and standardizing the security rating of data elements used for communication through automated information processing systems is an important task. The success of this activity and its application worldwide will play a crucial role in enhancing communication among governments, businesses, and academia.