机器学习在企业运营风险管理中的应用——基于电商平台交易数据的分析

Application of Machine Learning in Enterprise Operation Risk Management—Analysis Based on E-Commerce Platform Transaction Data

摘要: 电商平台规模扩张导致运营风险剧增，传统人工风控难以满足动态需求，基于机器学习构建智能预警系统，采用随机森林深度神经网络分析某电商平台三年交易数据，系统提取32个核心风险特征，通过SHAP值LIME方法增强可解释性，预警系统识别准确率达92.3%，响应时间低于50毫秒，模型保留80%特征时准确率维持85%以上，3个月内预测效果稳定。智能客服解决率达85%，差评率降低32%。

Abstract: The expansion of e-commerce platforms has led to a surge in operational risks, while traditional manual risk control cannot meet dynamic demands. An intelligent early warning system based on machine learning was built using random forest and deep neural networks to analyze e-commerce platform data over three years. The system extracts 32 core risk features and enhances interpretability through SHAP values and LIME methods. The warning system achieves 92.3% identification accuracy with response time under 50 ms. Model accuracy remains above 85% with 80% features available, maintaining stability within 3 months. The intelligent customer service achieves 85% resolution rate and reduces negative feedback by 32%.