人工智能在电子商务企业财务风险预警中的应用研究

Research on the Application of Artificial Intelligence in Financial Risk Warning of E-Commerce Enterprises

摘要: 电子商务企业在激烈的竞争环境中财务风险日益增加，传统的财务管理手段已难以应对复杂的风险情境。为了提升电子商务企业财务风险预警能力，以美妆电子商务企业悠可为例，悠可通过引入机器学习、计算机视觉和深度学习等技术，构建了多维度的财务风险评估体系。机器学习模型通过挖掘历史财务数据，实现了对潜在风险的早期识别，计算机视觉技术提高了票据核验的自动化水平，而LSTM神经网络则大幅提升了现金流预测的准确性。研究表明，人工智能的应用显著提高了财务预警系统的效率和准确性，但也暴露出一些问题，如模型可解释性不足、票据识别的泛化能力有限及部分外部因素未纳入预测模型。针对这些问题，本文提出了进一步的优化建议，旨在为电商企业在数字化转型过程中有效管理财务风险提供参考。

Abstract: E-commerce enterprises are facing increasing financial risks in a fiercely competitive environment, and traditional financial management methods are no longer able to cope with complex risk scenarios. In order to enhance the financial risk warning capability of e-commerce enterprises, taking beauty e-commerce enterprise Youke as an example, Youke has constructed a multidimensional financial risk assessment system by introducing technologies such as machine learning, computer vision, and deep learning. Machine learning models achieve early identification of potential risks by mining historical financial data, computer vision technology improves the automation level of bill verification, and LSTM neural networks significantly enhance the accuracy of cash flow forecasting. Research has shown that the application of artificial intelligence has significantly improved the efficiency and accuracy of financial warning systems, but it has also exposed some problems, such as insufficient model interpretability, limited generalization ability of bill recognition, and some external factors not being included in the prediction model. In response to these issues, this article proposes further optimization suggestions aimed at providing reference for e-commerce enterprises to effectively manage financial risks in the process of digital transformation.