信贷领域中信用评分算法技术的法律规制研究

Legal Regulation of Credit Scoring Algorithm Technology in the Credit Sector

摘要: 信贷领域中算法技术与信用评分的深度融合，改变了传统的信用评分工作机制，在提高了信贷服务效率的同时，也衍生了算法偏见、个人信息泄露、数据滥用等风险。我国现有法律体系已初步形成算法规制框架，但在实践中仍面临针对信贷领域中信用评分算法模型审查缺乏明确标准、动态监管缺位，审查主体分散，传统侵权规则适配不足等困境。为防范、化解信用评分中风险，可建立“准确性–公平性–可解释性”的算法模型审查机制，明确以央行为主的监管主体。界定多元主体责任范围，针对信贷领域信用评分算法涉及的多元责任主体，差异化适用无过错责任原则和过错责任原则，补齐救济制度短板。为信用评分算法技术的发展提供良好的法治保障。

Abstract: The deep integration of algorithmic technology with credit scoring in the credit sector has transformed traditional credit scoring mechanisms, enhancing the efficiency of credit services while simultaneously giving rise to risks such as algorithmic bias, personal information leakage, and data misuse. Although China’s existing legal framework has preliminarily established a regulatory structure for algorithms, practical challenges persist, including the lack of clear standards for model review of credit scoring algorithms, the absence of dynamic supervision, fragmentation among regulatory authorities, and insufficient adaptation of traditional tort rules. To prevent and mitigate these risks in credit scoring, it is advisable to establish an algorithmic model review mechanism based on the triad of “accuracy-fairness-explainability”, with the central bank designated as the primary regulatory authority. It is also necessary to delineate the scope of liability for the multiple responsible parties involved, and to apply the principles of no‑fault liability and fault liability differentially to these parties, thereby addressing the shortcomings of the existing redress system. These measures will provide robust legal safeguards for the development of credit scoring algorithm technologies.