| At the Fifth Session of the Thirteenth National People’s Congress,the government strongly advocated enterprises to improve their asset management arrangements,and encouraged enterprises to complete digital transformation as soon as possible to release the potential of data elements to prevent and defuse risks and stimulate the enthusiasm of enterprises for endogenous development.At the same time,the deterioration of the economic and trade situation caused by the global epidemic has become a major obstacle to the sustainable development of enterprises.Coupled with the escalation of Sino-US trade frictions and the increasing downward pressure on the domestic economy,enterprises are facing severe challenges for stable,healthy and orderly operation.At the same time,with the improvement of the development stage of the enterprise,the scale of its own assets,management chain,hierarchical entities and business process volume have increased rapidly,which can easily lead to rough budget preparation data,expansion of forecast errors,deviation of the execution process from decision-making goals,delay in the discovery of hidden dangers,and Insufficient monitoring prompts and other problems will reduce the efficiency of capital use and affect the stable,orderly and healthy development of enterprises.With the rapid development of artificial intelligence technology,digital intelligence will gradually empower the capital budget of enterprises.In the face of government requirements and the impact of reality,the use of artificial intelligence-related technologies to achieve scientific and lean control of capital budgets will promote stability,quality and stability of enterprises.Seeking progress is of great benefit.On the basis of fully sorting out the relevant research at home and abroad,this paper first analyzes the problems and new demands around the current situation of capital budget control,and designs a capital budget control process framework that integrates artificial intelligence technology.Then,in view of the problems and new demands,the technical methods applicable to the three main links of data management extraction,fund forecasting and fund monitoring in the process of capital budget service are analyzed and selected,and the specific processes of data management and extraction,fund prediction and fund monitoring are elaborated by using knowledge graph,big data mining and support vector machine algorithms,and the fund prediction and monitoring model is constructed.Finally,in the case study part,in view of the existing problems and new demands of the capital budget of A power generation enterprises,the above process and model are applied to the actual capital budget control process,and the advantages of the model in this paper compared with the original prediction and monitoring methods of the enterprise in precision,efficiency,real-time multi-dimensionality are compared,which verifies the feasibility and applicability of the theoretical research of capital budget control,and reflects the practicality and important value of artificial intelligence technology in optimizing the capital budget control method and improving the effect of capital budget control.This paper adopts the research idea of "status quo analysis-demand traction-theoretical research-case application",according to the current situation of capital budget control and the analysis of new demands,innovatively integrates artificial intelligence-related technologies into the capital budget control process framework,enriches and expands capital budget The relevant theoretical and method research on management and control provides reference value for realizing the overall goal of optimal allocation of corporate funds and sustainable development. |
