Fund Management Audit Alert Based On Machine Learning Under Big Data

In the era of big data,the operation mode of enterprises has begun to move towards intelligence and information technology,and the market competition has gradually turned into the competition of information technology.In modern enterprise management,capital management is the key,in all business activities,its operation can not lack of financial support,if the lack of sufficient funds for security,it is difficult for the enterprise to survive.Therefore,if an enterprise wants to gain an advantage in the brutal market competition,it must improve its fund management level.Internal audit is indispensable in fund management.Internal audit is conducive to the fund management of an enterprise,and it is one of the most important means in the development and growth of an enterprise,as well as the core strategy of enterprise management.Facing the background of The Times and the rapid development of intelligent technology,machine learning algorithm provides technical supervision for enterprise internal audit,but also provides new ideas for internal audit methods.ABC Company is a provincial subsidiary of a large central enterprise engaged in the sale of oil and non-oil products.It has 15 prefecture-level city branches.Under the design of strategic financial control system,ABC Company continues to promote the digital transformation of audit and realize the construction of intelligent management.However,after reviewing the audit practice of fund management,it is found that ABC company has deficiencies in fund management audit.The data volume brought by business multiplication and data intellectualization transformation presents exponential growth.However,the existing audit methods are more traditional,the audit means are not scientific,and the authenticity and reliability of audit results cannot be guaranteed,resulting in a substantial reduction in audit efficiency.This directly leads to the loss of value of ABC’s internal audit department,which is not conducive to the realization of audit objectives and corporate strategies.In this paper,ABC company is taken as the case study object,aiming at the problems in fund management audit,intelligent information technology is integrated with fund management,and an early-warning framework of fund management audit is constructed,and ABC company is taken as the implementation object for verification.Firstly,this paper summarizes the research status of fund management audit,audit early warning and machine learning at home and abroad,and introduces the related concepts,theories and technical basis of fund management audit,audit early warning,big data and machine learning.Secondly,it summarizes the current situation of ABC Company’s fund management audit through investigation and analysis,and finds the existing problems in ABC Company’s fund management audit after data collation and analysis.At the same time,according to the analysis of the current situation of ABC company’s fund management audit,the problems existing in fund management audit are summarized,the method of audit early warning is put forward,and the necessity of using machine learning algorithm for audit early warning is explained according to the fit analysis.The fund management audit framework is designed and constructed,and according to the logic of the framework,the fund management audit data warehouse is first designed.From the data warehouse data preparation,structure design,construction process and other aspects of detailed analysis.Then,the audit early warning scheme was designed based on the two specific processes of rolling budget and fund control of ABC company.The audit early warning model of rolling budget of funds was constructed by using decision tree algorithm,and the unreasonable or relatively unreasonable budget was further audited to improve the accuracy and efficiency of audit results.BP neural network is used to classify the risk levels of the approval process of the fund control link,and timely alert the problematic fund control nodes.Then,on the basis of the above algorithm process and under the condition of big data,the machine learning-based ABC company fund management audit early warning is realized.The paper also compares and evaluates the results of several algorithms,and gives implementation suggestions and safeguard measures through analysis.Finally,the whole paper carries out research conclusions and research prospects.This paper innovates the audit methods and processes,improves the efficiency and accuracy of internal auditors in the audit of fund management,and provides new ideas for the audit research of other companies in the industry in the aspect of fund management under the downward trend of big data.The early warning framework of fund management audit based on machine learning is designed to indicate the work flow of internal audit of fund management.Through the simulation and implementation,it helps ABC company solve the problems existing in the fund management audit,improves the audit quality,guides ABC company to quickly implement the audit early warning process,and provides reference for promoting the intelligent transformation of the company.