Anylasis on Personal Data Protection from the Perspective of Credit Investigation
Yao Jia
Abstract
Yao Jia
Abstract
With the booming of the credit economy, the improper use of personal credit data and the infringement of person’s rights are becoming more and more serious during the process of conducting credit investigation due to the absence of relevant laws and regulations protecting personal credit data currently in China. Personal credit data will have the legitimacy of credit investigation, the theory construction of protecting privacy and the limitation of public interests as the base of ideals of values. Based on the study about the above legal ideals, it appears urgent to construct the corresponding legal rules, especially to establish the provisions concerning the protection of the Right to Controlling Credit Data, Right to Be Informed, and the Right of Indemnity of the person whose credit is investigated. In addition, the credit agencies and the credit data users shall perform the obligations and bear the liabilities therewith.
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With the booming of the credit economy, the improper use of personal credit data and the infringement of person’s rights are becoming more and more serious during the process of conducting credit investigation due to the absence of relevant laws and regulations protecting personal credit data currently in China. Personal credit data will have the legitimacy of credit investigation, the theory construction of protecting privacy and the limitation of public interests as the base of ideals of values. Based on the study about the above legal ideals, it appears urgent to construct the corresponding legal rules, especially to establish the provisions concerning the protection of the Right to Controlling Credit Data, Right to Be Informed, and the Right of Indemnity of the person whose credit is investigated. In addition, the credit agencies and the credit data users shall perform the obligations and bear the liabilities therewith.
Key concepts: Credit reference, Business, Credit enhancement, Indemnity, Construct (python library), Credit history, Legitimacy, Law and economics