Affiliations: School of Management, Jilin University, Changchun, China
Correspondence:
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Corresponding author. Yaona Liu, School of Management, Jilin University, Changchun, China. Yaona Liu, E-mail: liuyaona815@163.com.
Abstract: By integrating business processes, financial intelligent management system can provide effective data information with high quality and low cost for strategic decision-making. In this paper, the authors analyze the intelligent financial management of company based on neural network and fuzzy volatility evaluation. With the help of the development and support of information technology, the construction of financial intelligent management center realizes the efficient and standardized business process by building the information system center platform. It is the basis for the smooth operation of process reengineering and can guarantee the successful and safe operation of financial intelligent management center. The correlation dimension information reflecting the financial data abnormal feature is extracted to construct discrimination statistic and test criterion. The abnormal feature of financial data is mined according to the significant difference of discrimination statistic to realize anomaly analysis of financial data. The results show that the accuracy of financial data anomaly mining with this method is better. It has good application value in the financial audit and economic investigation and other fields.
Keywords: Neural network, volatility assessment, corporate finance, intelligent
management system
