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Along with the continuous socioeconomic growth, more capital injection is needed to meet the daily operating cash flow demand compared to the traditional development model, so it is necessary to study the digital capability of enterprise financial management. Based on the evolutionary logic of financial risk identification, evaluation, and control, this paper summarizes the most suitable feature processing algorithm process for enterprise financial management systems by visual processing technology; for the visual guidance system, it needs to be able to identify artifacts quickly and accurately and compare different visual recognition algorithms experimentally. Considering the accuracy and real time of the visual guidance system, the efficiency of the algorithm is improved as much as possible under the condition of ensuring the accuracy, including the collection of work area features and the filtering preprocessing of data features, edge detection, and feature extraction, and, finally, the coordinate conversion can be carried out effectively to meet the requirements of the system for speed and accuracy. The digital platform for enterprise financial management built in this paper gives risk management strategies and implementation plans in six aspects, including improving the internal environment for risk management, setting control objectives in line with the development of the company, focusing on the response and control of major risks, ensuring efficient communication of information, and strengthening supervision. In terms of profitability risk, we propose to improve asset utilization, establish additional investment risk management departments, enhance capital utilization efficiency, and create core mobile products; in terms of asset operation, we propose to increase asset risk management, expand product sales scale, standardize cash flow system, and use centralized bank accounts.

Construction of a Digital Platform for Enterprise Financial Management Based on Visual Processing Technology