AI驱动的银行运营风险智能监测体系研究

Research on AI-Driven Intelligent Monitoring System for Bank Operational Risks

摘要: 为破解金融科技时代银行运营风险管理的困境，本研究构建了一套AI技术驱动的智能化监测体系。该体系以“四维四引擎”为核心架构，通过智能感知、动态计量、自动处置与迭代优化四大引擎，覆盖风险识别、评估、应对与监控全流程。研究重点阐述了体系的技术实现路径，包括云原生架构、多源异构数据融合、机器学习与知识图谱的混编应用，并提出了组织架构重塑、流程再造与工具集成的实施保障。该体系可为银行实现运营风险的实时、精准与自动化管控提供系统性解决方案，为行业风险管理转型提供理论与实践参考。

Abstract: To address the challenges of bank operational risk management in the fintech era, this study constructs an AI-driven intelligent monitoring system. Centered on the “Four-Dimension and Four-Engine” core architecture, the system covers the entire risk management lifecycle—including risk identification, assessment, response, and monitoring—through four engines: intelligent perception, dynamic measurement, automatic disposal, and iterative optimization. The research focuses on elaborating the technical implementation path of the system, such as cloud-native architecture, multi-source heterogeneous data fusion, and the hybrid application of machine learning and knowledge graphs. Additionally, it proposes implementation guarantees including organizational restructuring, process reengineering, and tool integration. This system provides a systematic solution for banks to achieve real-time, accurate, and automated operational risk control, and offers theoretical and practical references for the transformation of risk management in the industry.