数智技术在金融科技客户隐私保护中的应用研究

Research on the Application of Intelligent Digital Technologies in Customer Privacy Protection in FinTech

摘要: 目的：在金融科技持续深化的背景下，客户数据呈现高频采集、深度关联化特征，隐私泄露与不当使用风险显著攀升。本研究旨在探讨如何利用数智技术构建系统化、可验证的隐私保护机制，以增强数据治理能力并提升金融业务的安全韧性。方法：基于文献分析、综合技术框架构建、典型场景验证与隐私风险评估，系统梳理差分隐私、联邦学习、区块链可信审计等关键技术的运行逻辑与适配边界，从数据全流程视角提出跨技术协同的综合治理方案。结果：研究发现，多类数智技术协同应用可显著降低数据重识别、越权调用等风险，同时保持模型在关键业务指标上的可用性，并提升数据处理的可控性与审计透明度，具有良好的工程推广潜力。结论：数智技术为金融科技构建隐私保护与业务创新并重的新范式提供可行路径。本研究提出的框架与风险评估体系，可为构建安全、可信、可持续的金融数据治理结构提供理论依据与方法参考。

Abstract: Purpose: As financial technology continues to advance, customer data is increasingly collected and deeply utilized, leading to heightened risks of privacy leakage and improper use. This study aims to explore how intelligent digital technologies can be employed to construct a systematic and verifiable privacy protection mechanism, thereby enhancing data governance capabilities and strengthening security resilience in financial services. Methods: Through literature analysis, an integrated technical framework, scenario-based verification, and privacy risk assessment, this study examines the operational logic and applicability boundaries of key technologies—such as differential privacy, federated learning, and blockchain-based trusted auditing—from a full data-lifecycle perspective. A cross-technology collaborative governance scheme is proposed. Results: The findings show that coordinated deployment of intelligent digital technologies significantly reduces risks of data re-identification and unauthorized access, while maintaining acceptable model performance. These technologies also improve controllability and transparency of data processing, demonstrating strong potential for engineering implementation. Conclusion: Intelligent digital technologies provide a feasible pathway for achieving both privacy protection and business innovation in FinTech. The proposed framework and risk assessment system offer theoretical support and methodological guidance for building a secure, trustworthy, and sustainable data governance structure.