基于机器学习的企业安全风险识别与预警机制研究  

Research on Enterprise Security Risk Identification and Early Warning Mechanism Based on Machine Learning

作　　者：蔡玲琪 CAI Lingqi(Beijing Shouwei Security Service Co.,Ltd.,Beijing 100080,China)

机构地区：[1]北京首卫保安服务有限公司,北京100080

出　　处：《移动信息》2025年第4期320-322,共3页Mobile Information

摘　　要：随着经济环境的日益复杂,企业面临的风险因素更加多样化。文中利用机器学习技术,构建了一个多维度的企业风险识别框架,并基于某上市企业的财务及经营数据,应用AdaBoost、Hist Gradient Boosting等机器学习算法建立了风险识别模型。实证研究表明,该风险特征指标体系能全面刻画企业的风险状态;AdaBoost模型在风险识别准确率上达到96.09%,显著优于其他模型;通过SHAP方法识别供应链需求风险和经营风险是关键影响因素,为企业风险预警机制的建立和风险防范提供了方法指导。With the increasingly complex economic environment,enterprises face more diverse risk factors.This paper uses machine learning technology to build a multi-dimensional enterprise risk identification framework,and uses machine learning algorithms such as AdaBoost and Hist Gradient Boosting to establish a risk identification model based on the financial and operating data of a listed enterprise.Empirical research shows that the risk characteristic index system can comprehensively describe the risk status of enterprises;the risk identification accuracy of the AdaBoost model reaches 96.09%,which is significantly better than other models;the SHAP method identifies supply chain demand risk and operational risk as key influencing factors,providing methodological guidance for the establishment of enterprise risk early warning mechanism and risk prevention.

关 键 词：机器学习 风险识别 供应链风险 预警机制 

分 类 号：TP399[自动化与计算机技术—计算机应用技术]