There exists a distinct synergy between enterprise financial sharing and internal control systems. From the perspective of big data intelligence, the present research designs an optimization model for enterprise financial sharing center, combining the application of robotic process automation (RPA), with the aim of making the optimal intelligent internal control system of financial operation and management of industrial enterprises. This financial management optimization model includes three key aspects, namely, (1) enterprise credit risk evaluation through system clustering and factor analysis; (2) employee disciplinary prediction through C4.5 decision tree algorithm; and (3) enterprise financial management risk prediction through BP neural network algorithm. In the empirical study, the researchers find out that the 75 sampled industrial enterprises fall into six groups, while there are three main components in relation to their enterprise credit risk. Moreover, the employee disciplinary prediction model is found effective in recognizing the employee disciplinary behavior, thus helping in enterprise safety management. In addition, compared to the LPM risk prediction model, the new risk prediction model using BP neural network algorithm offers a better fitting effect and accuracy. In summary, the optimization model of enterprise financial management successfully lowers the cost of the financial sharing center operations and management, optimizes the intelligent internal control system of finance, and raises the quality and level of enterprise financial management.
