Research On The Optimization Of Electronic Invoice Reimbursement Process In Universities

At present,China has gradually entered the era of comprehensive application of electronic invoices,and the finance department of universities is faced with large-scale electronic invoice reimbursement work.Limited by their own information level,most universities use the printing reimbursement method,resulting in many risk points in the electronic invoice reimbursement work,and the phenomenon of "complicated reimbursement".The rapid development of emerging technologies such as big data and artificial intelligence provides a solid technical guarantee for universities to realize the online,closed-loop management and intelligence of electronic invoice reimbursement work,which helps to reduce the risks in the electronic invoice reimbursement process and improve the efficiency of reimbursement work.This paper takes M University as the case study object,and adopts literature research method,case study method,questionnaire survey method and field research method to optimize its electronic invoice reimbursement process.Through on-the-spot investigation and information collection,it is found that M University adopts the printing and entry method in the electronic invoice reimbursement work,and there are a series of offline transmission and manual operations in the process,which makes the reimbursement work difficult to guarantee the authenticity of electronic invoices,and face problems such as large workload of verification and low satisfaction of teachers and students in reimbursement.Therefore,based on the closed-loop management theory and the perspective of "four-stream matching",this paper sorts out its electronic invoice reimbursement process and finds out the risks in each link.Then,combined with big data and intelligent technology,the electronic invoice reimbursement process of M University is optimized and analyzed,and the expected effect of optimization is analyzed.Finally,this paper will put forward relevant suggestions for the optimal implementation of M University.This paper integrates the "three-stream consistency" of invoices and the "three-stream integration" of ERP system,and builds a "four-stream matching" model,which provides a new idea for sorting out the electronic invoice reimbursement process.And based on the perspective of closed-loop management and "four-stream matching",it sorts out the electronic invoice reimbursement process of M University,finds the links with risks.Combined with big data and intelligent technology to optimize the design of the electronic invoice reimbursement process of M University,it can provide reference for other universities to optimize their own electronic invoice reimbursement process.