Research On Accounts Receivable Management Optimization Based On Big Data Intelligentization Under Financial Sharing Mode

At present,relying on advanced science and technology,the financial sharing agement mode achieves a breakthrough for the improvement of enterprise's inancial anagement ability.The Financial Sharing Center serves the financial personnel from many spects,strengthens the quality management of enterprises,and provides effective support for decision-making.However,the problems such as the management process is not concise and the labor cost is too high in the Financial Sharing Center are still not effectively solved.Cost reduction and efficiency improvement have always been one of the goals of the financial sharing center.Through the integration and connection of various process systems,the deep integration and automation of the system can be realized.However,the receivable business of Z enterprise still has many problems on the way of financial sharing development in the past ten years,such as how tontegrate and connect various process systems based on existing systems,and how to realize deep integration and automation of the system.With the emergence of cloud accounting and big data,it marks the arrival of the era of financial intelligence.Intelligence of big data has become one of the important characteristics of financial management model,which brings new ideas for the optimization of financial work.In this paper,under the background of the era of financial intelligence,Z enterprise accounts receivable management as a case for analysis.Firstly,this paper gives a theoretical overview of the impact of Financial Sharing mode,robotic process automation and big data on receivable business,value chain management theory,K-Means clustering algorithm to establish credit rating standards and BP neural network algorithm to predict the risk of bad debts.Then,it gives a theoretical overview of the construction of Z enterprise sharing center,the quality of Z enterprise's current assets and so on.Based on the analysis of the current situation of the receivable business of Z enterprise under the mode of financial sharing,this paper sums up three optimization points in the receivable management: strengthening the risk management of receivables,cross-system automatic withdrawal,and automatic prompting of accounts.Therefore,according to the current situation and new requirements of accounts receivable management in Z enterprise,and based on the theory of value chain management and the existing business processes of accounts receivable management in Z enterprise,this paper puts forward the optimization design of accounts receivable management based on big data intellectualization,and designs the optimization framework of accounts receivable management based on big data intellectualization based on the existing information system.How to optimize the business process of accounts receivable management with robotic process automation technology and how to use K-Means clustering algorithm and BP neural network to carry out risk management of accounts receivable are elaborated in detail.The two optimization contents are illustrated and analyzed by case studies.Then specific implementation suggestions are put forward in three aspects: information resources integration,large data technology and financial team transformation.Finally,the paper summarizes and prospects for the future.It is expected that this paper can provide theoretical basis and practical reference for the intelligent transformation of Z enterprise financial sharing center.