Research On RPA Financial Automation Process Optimization Based On Process Mining

In recent years,the iterative updates of new generation information technologies such as big data,Robotic Process Automation(RPA),process mining,and artificial intelligence have driven an unstoppable wave of digital transformation and upgrading,becoming a new dimension of enterprise competition and a key driver of the steady progress of the digital economy.As a core department of enterprise operations and a natural data center,the finance department is one of the important areas of enterprise digital transformation.Among many emerging technologies,RPA automates workflow by simulating and enhancing the interaction between humans and computers,empowering finance digital transformation and increasing the demand for RPA implementation in the finance field.To achieve the maximum value of RPA implementation,an excellent RPA financial automation process is crucial.However,the current implementation of RPA financial automation mainly relies on traditional research methods for process optimization,which suffer from problems such as strong subjectivity,high cost,and poor results.Process mining,as an emerging process discovery technology,can objectively visualize the process running process based on event log data in financial information systems,and from a data perspective,help optimize RPA financial automation processes,solve the problems generated by research-based process optimization at the root,promote cost reduction and efficiency enhancement,and achieve enterprise value-added.This article takes the RPA financial automation process optimization based on process mining as the research object.Based on theory and literature support,the principles and goals of RPA financial automation process optimization are used as conditions to construct a process mining-based RPA financial automation process optimization framework,and research is conducted on RPA financial automation process optimization.Firstly,the research status and theoretical basis of process mining,RPA financial automation,process management and optimization are reviewed both domestically and abroad.Then,based on the analysis of the current situation,pain points and the need for implementing RPA financial automation in enterprise financial processes,a closed-loop optimization of financial process decomposition,RPA financial automation process design,and RPA financial automation process optimization is determined using process mining technology.Firstly,for financial process decomposition,the enterprise’s implementation needs for financial automation are obtained based on a bottom-up approach,and the overall event log is exported from the financial information system.Then,the active learning trajectory clustering algorithm is used to decompose the financial process and generate a financial sub-process model.The quality of the clustered financial sub-process is analyzed based on accuracy and complexity indicators,and the financial sub-process event log data required for designing and optimizing RPA financial automation processes is exported.Secondly,for RPA financial automation process design,a financial process discovery model is generated based on the financial subprocess event log obtained from the decomposition process using a highly fitting process discovery algorithm.The financial process model is expanded using a multidimensional analysis algorithm based on analysis requirements,and the financial process bottleneck problem is analyzed from multiple perspectives such as control flow dimension,organizational dimension,and performance dimension.Then,the RPA financial automation process is designed in a targeted manner.Thirdly,for RPA financial automation process optimization,a process discovery model of RPA financial automation is generated using a process discovery algorithm that considers hidden trajectories based on the event log generated during the trial run of RPA financial automation.The consistency check algorithm is used to analyze the consistency and compliance of the real RPA financial automation process with the designed RPA financial automation process based on the fitting degree index,behavioral rationality index,and structural rationality index.The ECRSI method is used to optimize the biased RPA financial automation process,and the net present value is used to analyze the optimization effect of RPA financial automation process to achieve the maximum value of implementing RPA financial automation in enterprises.Building on the shortcomings of traditional research methods for optimizing RPA financial automation processes,this paper proposes solutions by selecting three key stages for optimizing RPA financial automation processes: financial process decomposition,RPA financial automation process design,and RPA financial automation process optimization.Focusing on the pain points encountered during the process optimization,the paper incorporates process mining technology and identifies the requirements for optimizing RPA financial automation implementation by addressing the high repetition,low efficiency,and high volume of financial work.The innovative RPA financial automation process optimization framework developed through process mining technology provides reliable,objective,and effective data support for enterprises to achieve maximum value through RPA automation implementation.This paper hopes to provide theoretical and methodological references for the research and application of process mining technology in the field of RPA financial automation process optimization.