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作 者:李晓楠 LI Xiaonan(Institute of Law,Zhengzhou University,Zhengzhou 450001,China)
出 处:《大连理工大学学报(社会科学版)》2023年第2期65-74,共10页Journal of Dalian University of Technology(Social Sciences)
基 金:国家社会科学基金一般项目“国家安全视域下金融数据跨境流动的法律规制研究”(21BFX121);河南省社会科学界联合会调研课题“算法自动化决策中多元风险的法律治理研究”(SKL-2022-358)。
摘 要:个人征信广泛用于信贷、租赁等经济交易场景,关乎征信主体重大经济利益。从国内外征信业发展看,大数据征信已经成为传统征信的重要补充,并呈现出征信主体多元化、个人信用信息泛化、征信过程智能化和自动化等特征。大数据征信一方面有利于解决缺少信用记录主体获得金融支持的困境,另一方面又可能带来信用歧视和不公,而现有征信监管未能有效回应。基于大数据征信数据驱动的本质,可借鉴数据治理的现有立法实践,在征信监管中一方面坚持和完善大数据征信下数据处理的透明度要求,另一方面夯实大数据征信机构在个人信息准确性和合法性方面的保障义务,并赋予信用主体挑战不公平征信结果的权利,以实现大数据下个人公平信用权益的有效保障。Personal credit investigation is widely used in economic transaction scenarios such as credit and leasing,which is related to the major economic interests of credit investigation subjects.From the development of credit investigation industry at home and abroad,big data credit investigation has become an important supplement to traditional credit investigation,and may reveal diversified credit investigation subjects,generalize personal credit information,and make credit investigation process smart and automatic.On one hand,big data credit investigation is conducive to solving the credit acquisition dilemma of“thin credit”subjects.On the other hand,it may cause credit discrimination and injustice.The existing credit investigation supervision fails to respond effectively to this issue.Based on the data-driven nature of big data credit investigation and the existing legislative practices of data governance,this paper suggests that the transparency requirements of data processing under big data credit investigation should be adhered to and improved,and big data credit investigation institutions should consolidate its guarantee obligations for personal information accuracy and legitimacy,and endow credit subjects the right to challenge unfair credit investigation results so that fair personal credit investigation can be guaranteed.
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