Applied Research on the Development and Design of an Intelligent Early Warning System for Modern Enterprise Operating Indicators: A Case Study

The purpose of this study is to set up an early warning model for operations with the help of big data and artificial intelligence so that it can reach accurate and valid results. In this paper, a comprehensive introduction is made to the intelligent warning mechanism for modern enterprises as well as the related risk index selection and model building. However, some drawbacks can still be found in the current warning system while the key indicators of peer benchmarking are associated with operational risks. A novel warning indicator model is structured to involve aspects of finance, operations, and market based on big data, machine learning, and expert experience. The follow-up empirical analysis is given to get early risk insights for modern companies. What's more, methods and measures to optimize operating strategies are put forward so that companies can be more competitive and risk-resistant in the dynamic market.