CN114581210A - Digital management method and system for enterprise finance based on RPA - Google Patents
Digital management method and system for enterprise finance based on RPA Download PDFInfo
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Abstract
The invention discloses a digital management method and a digital management system for enterprise finance based on RPA, which relate to the field of data processing, wherein the method comprises the following steps: acquiring internal and external financial data of an enterprise by using an ETL data warehouse technology, and constructing an enterprise financial database; acquiring an enterprise financial processing rule set; based on the rule information, determining preset rule information and constructing RPA financial management information; the enterprise financial database is intelligently managed by the enterprise financial database management system, and a financial management report is generated; obtaining optimization demand information; inputting the data into a circulating evaluation model to carry out digital management evaluation to obtain an evaluation result; and performing optimization management on the RPA financial management information according to the evaluation result. The problem of among the prior art to the accuracy of enterprise financial management not high, and then cause the not good technique of effect of enterprise financial management is solved. The method and the device have the advantages that the accuracy and the accuracy of enterprise financial management are improved, and the effect and the quality of the enterprise financial management are improved.
Description
Technical Field
The invention relates to the field of data processing, in particular to a digital management method and a digital management system for enterprise finance based on RPA.
Background
Currently, with the rapid development of economic globalization, the enterprise operating environment is increasingly abundant, and the enterprise financial data is more and more complex. Meanwhile, along with the enlargement of the enterprise scale, the digital requirement on the financial management is higher and higher, and the traditional financial management method cannot meet the requirement on the financial digital management. Financial management influences aspects of enterprise development, and meanwhile, financial management is an important way for enterprise managers to timely master and know information of the enterprise, such as budget control, financial analysis, financial prediction, financial inquiry and the like. The RPA technology is combined with enterprise financial management, and a method for optimizing the enterprise financial management is researched and designed, so that the method has very important practical significance.
In the prior art, the accuracy of enterprise financial management is not high, and then the not good technical problem of effect of enterprise financial management is caused.
Disclosure of Invention
The application provides a digital management method and a digital management system for enterprise financial based on RPA, which solve the technical problem that the accuracy of enterprise financial management in the prior art is not high, and further the effect of enterprise financial management is not good.
In view of the above problems, the present application provides a digital management method and system for enterprise finance based on RPA.
In a first aspect, the present application provides a digital management method for RPA-based enterprise finance, where the method is applied to a digital management system for RPA-based enterprise finance, and the method includes: acquiring internal and external financial data of an enterprise by using an ETL data warehouse technology, and constructing an enterprise financial database; acquiring an enterprise financial processing rule set; determining preset rule information according to the enterprise financial database and the enterprise financial processing rule set; constructing RPA financial management information based on the preset rule information; intelligently managing the enterprise financial database through the RPA financial management information to generate a financial management report;
acquiring optimization demand information based on the financial management report and the preset rule information; inputting the optimization demand information into a cyclic evaluation model for digital management evaluation to obtain an evaluation result; and performing optimization management on the RPA financial management information according to the evaluation result.
In a second aspect, the present application further provides a digital management system for RPA-based enterprise finance, wherein the system includes: the system comprises a first execution unit, a second execution unit and a database management unit, wherein the first execution unit is used for acquiring internal and external financial data of an enterprise by using an ETL data warehouse technology and constructing an enterprise financial database; a first obtaining unit, configured to obtain a set of enterprise financial processing rules; the second execution unit is used for determining preset rule information according to the enterprise financial database and the enterprise financial processing rule set; a third execution unit, configured to construct RPA financial management information based on the preset rule information; the fourth execution unit is used for intelligently managing the enterprise financial database through the RPA financial management information to generate a financial management report; a second obtaining unit, configured to obtain optimization requirement information based on the financial management report and the preset rule information; the third obtaining unit is used for inputting the optimization demand information into a cyclic evaluation model for digital management evaluation to obtain an evaluation result; a fifth execution unit, configured to perform optimized management on the RPA financial management information according to the evaluation result.
In a third aspect, the present application provides a digital management system for RPA-based enterprise finance, comprising a processor coupled to a memory, the memory storing a program that, when executed by the processor, causes the system to perform the steps of the method of any of the first aspects above.
In a fourth aspect, the present application provides a computer-readable storage medium, wherein the storage medium has stored thereon a computer program, which when executed by a processor, implements the steps of the method of any of the first aspects above.
One or more technical solutions provided in the present application have at least the following technical effects or advantages:
acquiring internal and external financial data of an enterprise through an ETL data warehouse technology, and constructing an enterprise financial database; determining an enterprise financial processing rule set; determining preset rule information according to the enterprise financial database and the enterprise financial processing rule set; based on the method, RPA financial management information is constructed; the enterprise financial database is intelligently managed by the enterprise financial database, and a financial management report is generated; obtaining optimization demand information by combining the preset rule information, inputting the optimization demand information into a circulating evaluation model for digital management evaluation, and obtaining an evaluation result; and then performing optimized management on the RPA financial management information. The accuracy and the precision of enterprise financial management are improved, and the effect and the quality of the enterprise financial management are improved; meanwhile, the RPA technology is combined with enterprise financial management, and a method for optimizing the enterprise financial management is designed, so that the waste of resources such as manpower and material resources of the enterprise financial management is avoided, and the cost of the enterprise financial management is reduced; the time of enterprise financial management is saved, and the technical effect of the efficiency of enterprise financial management is improved.
The foregoing description is only an overview of the technical solutions of the present application, and the present application can be implemented according to the content of the description in order to make the technical means of the present application more clearly understood, and the following detailed description of the present application is given in order to make the above and other objects, features, and advantages of the present application more clearly understandable.
Drawings
In order to more clearly illustrate the technical solutions in the present application or prior art, the drawings used in the embodiments or the description of the prior art will be briefly described below, it is obvious that the drawings in the description below are only exemplary, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
FIG. 1 is a schematic flow chart of a digital management method for enterprise finance based on RPA according to the present application;
FIG. 2 is a schematic diagram illustrating a process of constructing an enterprise financial database in the RPA-based digital enterprise financial management method according to the present invention;
FIG. 3 is a schematic flow chart illustrating the process of obtaining a set of enterprise financial processing rules in the RPA-based digital enterprise financial management method according to the present invention;
FIG. 4 is a schematic structural diagram of a digital management system for enterprise finance based on RPA according to the present application;
fig. 5 is a schematic structural diagram of an exemplary electronic device of the present application.
Description of reference numerals: the device comprises a first execution unit 11, a first obtaining unit 12, a second execution unit 13, a third execution unit 14, a fourth execution unit 15, a second obtaining unit 16, a third obtaining unit 17, a fifth execution unit 18, an electronic device 300, a memory 301, a processor 302, a communication interface 303, and a bus architecture 304.
Detailed Description
The application provides a digital management method and a digital management system for enterprise financial based on RPA, and solves the technical problems that in the prior art, the accuracy of enterprise financial management is not high, and the effect of enterprise financial management is poor. The accuracy and the precision of enterprise financial management are improved, and the effect and the quality of the enterprise financial management are improved; meanwhile, the RPA technology is combined with enterprise financial management, and a method for optimizing the enterprise financial management is designed, so that the waste of resources such as manpower and material resources of the enterprise financial management is avoided, and the cost of the enterprise financial management is reduced; the time of enterprise financial management is saved, and the technical effect of the efficiency of enterprise financial management is improved.
Hereinafter, example embodiments according to the present application will be described in detail with reference to the accompanying drawings. It should be apparent that the described embodiments are merely some embodiments of the present application and not all embodiments of the present application, and it should be understood that the present application is not limited to the example embodiments described herein.
According to the technical scheme, the data acquisition, storage, use, processing and the like meet relevant regulations of national laws and regulations.
Currently, with the rapid development of economic globalization, the enterprise operating environment is increasingly abundant, and the enterprise financial data is more and more complex. Meanwhile, along with the enlargement of the enterprise scale, the digital requirement on the financial management is higher and higher, and the traditional financial management method cannot meet the requirement on the financial digital management. Financial management influences aspects of enterprise development, and meanwhile, financial management is an important way for enterprise managers to timely master and know information of the enterprise, such as budget control, financial analysis, financial prediction, financial inquiry and the like. The RPA technology is combined with enterprise financial management, and a method for optimizing the enterprise financial management is researched and designed, so that the method has very important practical significance. In the prior art, the accuracy of enterprise financial management is not high, and then the not good technical problem of effect of enterprise financial management is caused.
In view of the above technical problems, the technical solution provided by the present application has the following general idea:
the application provides a digital management method of enterprise finance based on RPA, wherein, the method is applied to a digital management system of enterprise finance based on RPA, the method includes: acquiring internal and external financial data of an enterprise through an ETL data warehouse technology, and constructing an enterprise financial database; determining an enterprise financial processing rule set; determining preset rule information according to the enterprise financial database and the enterprise financial processing rule set; based on the method, RPA financial management information is constructed; the enterprise financial database is intelligently managed by the enterprise financial database management system, and a financial management report is generated; obtaining optimization demand information by combining the preset rule information, inputting the optimization demand information into a circulating evaluation model for digital management evaluation, and obtaining an evaluation result; and then performing optimized management on the RPA financial management information.
In order to better understand the technical scheme, the technical scheme is described in detail in the following with reference to the attached drawings of the specification and specific embodiments.
Example one
Referring to fig. 1, the present application provides a digital management method for enterprise finance based on RPA, wherein the method is applied to a digital management system for enterprise finance based on RPA, and the method specifically includes the following steps:
step S100: acquiring internal and external financial data of an enterprise by using an ETL data warehouse technology, and constructing an enterprise financial database;
further, as shown in fig. 2, step S100 of the present application further includes:
step S110: acquiring an enterprise financial data source port;
step S120: extracting enterprise financial information based on the enterprise financial data source port;
step S130: performing data parameter analysis according to the enterprise financial information, and converting the data into financial rule data;
step S140: and loading the financial rule data, and constructing the enterprise financial database based on data parameters.
Particularly, when the enterprise finance is managed, the enterprise finance data is widely available, so that the problems of repetition, deletion, inconsistent formats and the like frequently occur to the collected enterprise finance data, and the quality and the efficiency of enterprise finance management are greatly influenced. Preferably, the method and the system utilize ETL data warehouse technology to construct a relatively pure enterprise financial database. The ETL data warehouse technology is a technology for loading data from a data source into a data warehouse, i.e., an extraction (Extract), transformation (Transform), and Load (Load) process of the data. The essence of the ETL data warehouse technology is a data flow process that follows certain rules, flowing from different heterogeneous data sources to a unified target data. Acquiring an enterprise financial data source port in a big data query mode and the like, wherein the enterprise financial data source port is a network port and a data connecting port which are used for establishing connection with a financial data platform, the enterprise financial data source port is used for transmitting internal and external financial data of an enterprise, and the enterprise financial data source port is used for extracting enterprise financial information; and then, the obtained enterprise financial information is converted into financial rule data through data parameter analysis, the data parameters are specific attribute names of the data, namely the financial data, and the financial data are loaded, and the enterprise financial database is constructed by combining the data parameters. Wherein the enterprise financial data source ports comprise internal financial data source ports and external financial data source ports of any enterprise performing intelligent financial management by using the digital RPA-based enterprise financial management system. Illustratively, the corporate financial data source port may be a corporate financial software, a corporate financial applet, a corporate financial web page, or the like. The enterprise financial information comprises data information such as enterprise asset total amount, enterprise liability total amount, enterprise income condition, enterprise profit condition and the like. The data parameter analysis comprises data cleaning, data correction, formatting processing and the like. The financial rule data is clean, standard and correct data information after data parameter analysis is carried out on the obtained enterprise financial information. And the enterprise financial database comprises financial data information which is obtained after loading the financial rule data by utilizing an enterprise financial data source port and is the same as the financial rule data in the aspects of format and the like. The technical effect that a clean enterprise financial database is constructed by utilizing an ETL data warehouse technology, and then the efficiency of subsequent intelligent financial management is improved is achieved.
Step S200: acquiring an enterprise financial processing rule set;
further, as shown in fig. 3, step S200 of the present application further includes:
step S210: obtaining a historical financial statement set;
step S220: classifying the content of the financial statements according to the historical financial statement set to obtain a financial processing classification set;
step S230: performing semantic analysis on financial statements corresponding to various types in the financial processing classification set line by line respectively to obtain statement content specifications, wherein the statement content specifications comprise financial data parameters and parameter processing rules;
step S240: and establishing a mapping relation according to the financial processing classification set, the financial data parameters and the parameter processing rules to obtain the enterprise financial processing rule set.
Specifically, the RPA-based enterprise financial digital management system obtains a historical financial statement set within a certain historical time range through big data, artificial intelligence, cloud computing, Internet of things and other modes, and performs financial statement content classification on the historical financial statement set to obtain a financial processing classification set; based on the method, semantic analysis is carried out on the obtained financial statements corresponding to all types in the financial processing classification set line by line, statement content specifications are obtained, and then the enterprise financial processing rule set is obtained by combining the financial processing classification set. Wherein the historical financial statement set includes a plurality of financial statement data information of a plurality of financial types over a historical time range. The financial processing classification set is data information which can represent the type of the financial statement after the obtained historical financial statement set is subjected to specific financial statement content classification. Such as a collection of assets and liabilities, a collection of profits, a collection of revenues, etc. The report content specification comprises financial data parameters and parameter processing rules. The financial data parameters comprise parameters such as data formats and units of financial statements corresponding to various types in the financial processing classification set. The parameter processing rule is data information used for representing the processing standard of the financial statement corresponding to each type in the financial processing classification set. The enterprise financial processing rule set comprises the financial processing classification set and the report content specification. And the financial processing classification sets correspond to the report content specifications one to one. The enterprise financial processing rule set can be input and updated according to actual condition needs of enterprises and changes of national financial policies, and can also perform intelligent identification on input financial statement samples and financial processing rules according to financial management needs. The method achieves the technical effects of obtaining the enterprise financial processing rule set with higher adaptability and reliability and laying a foundation for subsequently determining the preset rule information.
Step S300: determining preset rule information according to the enterprise financial database and the enterprise financial processing rule set;
step S400: constructing RPA financial management information based on the preset rule information;
step S500: intelligently managing the enterprise financial database through the RPA financial management information to generate a financial management report;
specifically, after the acquired enterprise financial database and the enterprise financial processing rule set are intelligently analyzed by the digital management system of the enterprise financial based on the RPA, preset rule information is acquired, and RPA financial management information is constructed according to the preset rule information; and further, the RPA financial management information is used for screening the information of the enterprise financial database, and finally generating a financial management report intelligently after performing intelligent scanning, automatic calculation and report combination on financial invoices, contracts, bills and the like in the enterprise financial database.
The preset rule information is data information representing financial management rules of an enterprise, the current financial acquisition data content of the enterprise is matched with the financial rules required by the enterprise to determine results, namely the rules are suitable for the current data to perform financial processing, the financial data parameters corresponding to different financial rules are different, the parameter requirements corresponding to which financial requirements are met in the obtained financial data, and the rules which are met are determined. For example, the preset rule information includes an enterprise reimbursement rule, an enterprise tax rule, an enterprise employee subsidy rule, an enterprise document auditing rule, and the like. And constructing RPA financial management information by utilizing preset rule information, wherein the RPA financial management information is a rule instruction stored in the RPA financial robot, and the RPA financial robot can realize intelligent processing according to the financial requirement with regularity. Rpa (robotic Process automation) means robot Process automation, which is a technology that can imitate human operations or acquire data using a user interface based on rule setting. The RPA does not have self-learning and self-cognition capabilities, like artificial intelligence. RPA financial robot in this application (RPA financial management information promptly) based on preset rule information carries out intelligent management to enterprise's financial database, replaces the loaded down with trivial details part that needs artifical repetitive operation. The RPA financial robot has the advantages that the efficiency and the quality of financial management are improved; the workload of financial staff is reduced, and the satisfaction degree of the staff is improved; and the financial illegal operation risk is reduced. Illustratively, in checking the expense reimbursement invoice in the corporate financial database, the RPA financial robot manually compares the reimbursement standard amount of the reimbursement staff with the actual reimbursement amount in place of the financial staff based on corporate reimbursement rules in the preset rule information. For the flow related to the internal control of the enterprise, the RPA financial robot can perform objective logic analysis based on preset rule information, prevent the communication of financial staff and business staff from the technical level, and strictly prevent financial fraud events affecting the company badly. In addition, when data is interconnected, the API gateway is preferentially selected, but in some old systems or systems which are difficult to develop secondarily, the API interface can not be exposed, and at the moment, data can be obtained in an RPA mode. Therefore, the RPA technology can effectively solve the problem that the data cannot be communicated, and the timeliness and the reliability of data processing are ensured. An RPA financial robot is constructed by using enterprise financial rules matched with enterprise financial data for intelligent processing, so that intelligent management of an enterprise financial database is realized by using RPA financial management information, and a financial management report with higher accuracy and reliability is obtained; meanwhile, the efficiency and the quality of financial management are greatly improved; the waste of resources such as manpower and material resources is avoided, and the cost of financial management is reduced.
Further, step S400 of the present application further includes:
step S410: acquiring new rule information;
step S420: and adding the newly added rule information into the preset rule information, and updating the RPA financial management information.
Specifically, on the basis of obtaining the RPA financial management information, a digital management system for enterprise finance based on RPA obtains new rule information by means of big data query and the like, and adds the new rule information to the RPA financial management information, thereby updating the RPA financial management information. The new rule information can be data information such as new national tax rules, financial processing rules which are in accordance with actual development of enterprises and real-time operation environments of the enterprises and the like. The technical effects of optimizing and updating the RPA financial management information, improving the adaptability of the RPA financial management information and further improving the accuracy of the subsequently generated financial management report are achieved.
Step S600: acquiring optimization demand information based on the financial management report and the preset rule information;
further, step S600 of the present application further includes:
step S610: obtaining report feedback information based on the financial management report;
step S620: performing financial data parameter matching according to the report feedback information and the preset rule information to obtain a matching parameter processing rule;
step S630: and performing difference analysis according to the matching parameter processing rule and the report feedback information to obtain rule difference information, and taking the rule difference information as the optimization demand information.
Specifically, on the basis of the acquired financial management report, the digital management system of the enterprise financial based on the RPA carries out scientific analysis on the report, acquires report feedback information, and carries out financial data parameter matching by combining with the preset rule information to acquire a matching parameter processing rule; further, difference analysis is carried out on the matching parameter processing rule and the report feedback information to obtain rule difference information, and the rule difference information is determined as the optimization demand information. The report feedback information is data information which is obtained through the financial management report and feeds back the financial condition of the enterprise visually and clearly, wherein the report feedback information can determine the deviation with the rule through intelligent analysis and comparison, and can also be fed back through a client, and is determined according to the satisfaction given by the client and the feedback opinion provided, and the direction of optimization and improvement needed subsequently is determined according to the feedback opinion, for example, the report feedback information is that the liability rate of the enterprise is reduced, the profit rate is increased, the balance condition is good, and the like. Meanwhile, the report feedback information can also be feedback opinions of enterprise managers, new policy rules and the like. The matching parameter processing rule is data information representing the financial data parameter matching condition of the report feedback information and the preset rule information. The rule difference information is data information representing the difference between the matching parameter processing rule and the report feedback information. The technical effects of obtaining the optimization demand information and providing data support for subsequently obtaining the evaluation result are achieved.
Further, step S700 of the present application further includes:
step S640: monitoring the processing process of the RPA financial management information based on the preset rule information to obtain process processing information;
step S650: performing management evaluation according to the process processing information and the financial management report to obtain management evaluation information;
step S660: acquiring a demand optimization direction according to the management evaluation information and the optimization demand information;
step S670: optimizing the preset rule information according to the demand optimization direction;
step S680: and constructing the circulation evaluation model based on the circulation relationship of the preset rule information, the process processing information, the management evaluation information, the demand optimization direction and the preset rule information.
Specifically, the preset rule information is utilized to monitor the processing process of the RPA financial management information to obtain process processing information, and management evaluation is carried out in combination with the financial management report to obtain management evaluation information; further, based on the management evaluation information and the optimization demand information, a demand optimization direction is obtained, and the preset rule information is optimized by using the demand optimization direction; further, the loop evaluation model is constructed through a loop relation of the preset rule information, the process processing information, the management evaluation information, the demand optimization direction and the preset rule information. The process processing information is data information such as specific steps and methods for representing the intelligent management process of the RPA financial management information on the enterprise financial database. The management evaluation information is data information representing the process processing information and the management evaluation of the financial management report. The demand optimization direction is data information representing an optimization direction of financial management. The circulation evaluation model is an intelligent model for carrying out digital management evaluation according to the circulation relationship of the preset rule information, the process processing information, the management evaluation information, the demand optimization direction and the preset rule information. The method and the device have the advantages that the processing requirements are determined by the rules, the processing results are obtained by processing according to the processing requirements, the processing results are evaluated, the requirements are determined according to the evaluation differences and the problems left over, then the cyclic processing relation for improving the rules according to the requirements is constructed to form the cyclic evaluation model, the management state of the system is evaluated, the processing rules and the running state of the whole system can be continuously optimized and improved according to the evaluation results, and the technical effect of laying a foundation for subsequent digital management evaluation and optimization management is achieved.
Further, step S650 of the present application further includes:
step S651: acquiring a processing flow and a data processing relation according to the flow processing information;
step S652: processing parameter analysis is carried out on the data processing relation based on the processing flow, and processing process evaluation parameters are obtained;
step S653: acquiring a report data mapping relation according to the data processing relation and the financial management report;
step S654: performing content parameter analysis on the financial management report and the report data mapping relation to obtain report evaluation parameters;
step S655: inputting the processing process evaluation parameters and the report evaluation parameters into an evaluation model to obtain the management evaluation information, wherein the evaluation model is a neural network model obtained by training a plurality of groups of training data, embedding the evaluation model into the cyclic evaluation model, monitoring the management evaluation information in the cyclic evaluation model, and outputting the management evaluation information as the evaluation result.
Specifically, on the basis of the acquired flow processing information, a processing flow and a data processing relation are acquired; further, processing parameter analysis is carried out on the data processing relation according to the processing flow, and processing process evaluation parameters are obtained; further, based on the data processing relation and the financial management report, a report data mapping relation is obtained, and content parameter analysis is carried out in combination with the financial management report, so that report evaluation parameters are obtained. And further, inputting the processing process evaluation parameters and the report evaluation parameters into an evaluation model by taking the processing process evaluation parameters and the report evaluation parameters as input information to obtain the management evaluation information. The processing flow is data information representing flow nodes, flow steps and the like in the flow processing information. The data processing relation is data information representing specific data conversion, calculation modes and the like in the process processing information. The processing procedure evaluation parameters are data information of static parameters such as calculation efficiency, accuracy and error rate of the representation processing procedure. The report data mapping relation is data information representing the corresponding relation between the data processing relation and the financial management report. The report evaluation parameter is data information representing the processing result of the financial management report data. The report evaluation parameters comprise data information such as whether the structure sequence of the financial management report is correct or not, whether report data position errors exist in the financial management report or not and the like. The evaluation model is a neural network model obtained by training a plurality of groups of training data, the evaluation model is embedded into the cyclic evaluation model, management evaluation information in the cyclic evaluation model is monitored, the management evaluation information is output as an evaluation result, the evaluation result obtained by the cyclic evaluation model in the cyclic process is output, the evaluation requirement is met, the reliability of evaluation is improved, in addition, the evaluation result is continuously input into the cyclic evaluation model for cyclic analysis processing, and the rule and the evaluation result of the system are continuously perfected. Management evaluation information with higher accuracy is obtained; meanwhile, the evaluation model is embedded into the circular evaluation model, so that the technical effect of evaluation accuracy is improved.
Step S700: inputting the optimization demand information into a cyclic evaluation model for digital management evaluation to obtain an evaluation result;
step S800: and performing optimization management on the RPA financial management information according to the evaluation result.
Specifically, the obtained optimization demand information, namely, the direction content which needs to be optimized and is determined according to the feedback information is used as input information, a cyclic evaluation model is input, an evaluation result is output, and the RPA financial management information is subjected to optimization management under the condition that the evaluation result is not good. Wherein, the evaluation result includes data information such as feasibility and adaptability of the optimization demand information, if the evaluation result is not good, it is judged that the rule for improving the current demand does not meet the requirement of system operation, the demand needs to be adjusted to ensure the management level of the system, the demand information can be managed in a targeted manner, such as adjusting the demand direction, increasing the adjustment parameters, adjusting the parameter requirement in the demand, and the like, if the optimization demand information is the necessary direction proposed by the customer, the requirement of the optimization demand information can be met by adjusting the preset rule information, the evaluation is performed again through the circular evaluation model, and the process is repeated until the optimization requirement and the management requirement of the system are met, so as to realize the requirement of the optimization requirement, ensure the reliability of the operation management result of the system, and can define the current management level of the system, to ensure the management effect. The technical effects that the optimization demand information is subjected to digital management evaluation by using the cyclic evaluation model, then the RPA financial management information is subjected to optimization management, and the accuracy and the precision of the RPA financial management information are improved are achieved.
In summary, the digital management method for enterprise finance based on RPA provided by the present application has the following technical effects:
1. acquiring internal and external financial data of an enterprise through an ETL data warehouse technology, and constructing an enterprise financial database; determining an enterprise financial processing rule set; determining preset rule information according to the enterprise financial database and the enterprise financial processing rule set; based on the method, RPA financial management information is constructed; the enterprise financial database is intelligently managed by the enterprise financial database management system, and a financial management report is generated; obtaining optimization demand information by combining the preset rule information, inputting the optimization demand information into a circulating evaluation model for digital management evaluation, and obtaining an evaluation result; and then performing optimized management on the RPA financial management information. The accuracy and the precision of enterprise financial management are improved, and the effect and the quality of the enterprise financial management are improved; meanwhile, the RPA technology is combined with enterprise financial management, and a method for optimizing the enterprise financial management is designed, so that the waste of resources such as manpower and material resources of the enterprise financial management is avoided, and the cost of the enterprise financial management is reduced; the time of enterprise financial management is saved, and the technical effect of the efficiency of enterprise financial management is improved.
2. When the enterprise financial management is carried out, the enterprise financial data are wide in source, so that the problems of repetition, loss, inconsistent formats and the like of the collected enterprise financial data often occur, and the quality and the efficiency of the enterprise financial management are greatly influenced. Preferably, the method and the system utilize ETL data warehouse technology to construct a relatively pure enterprise financial database. The ETL data warehouse technology is a technology for loading data from a data source into a data warehouse, i.e., an extraction (Extract), transformation (Transform), and Load (Load) process of the data. The essence of the ETL data warehouse technology is a data flow process that follows certain rules, flowing from different heterogeneous data sources to a unified target data.
3. The RPA financial management information is an RPA financial robot. Rpa (robotic Process automation) means robot Process automation, which is a technology that can imitate human operations or acquire data using a user interface based on rule setting. The RPA does not have self-learning and self-cognition capabilities, like artificial intelligence. RPA financial robot in this application (RPA financial management information promptly) based on preset rule information carries out intelligent management to enterprise's financial database, replaces the loaded down with trivial details part that needs artifical repetitive operation. The RPA financial robot has the advantages that the efficiency and the quality of financial management are improved; the workload of financial staff is reduced, and the satisfaction degree of the staff is improved; and the financial illegal operation risk is reduced.
4. The evaluation model is a neural network model obtained by training a plurality of groups of training data, the evaluation model is embedded into the cyclic evaluation model, management evaluation information in the cyclic evaluation model is monitored, and the management evaluation information is output as the evaluation result. Management evaluation information with higher accuracy is obtained; meanwhile, the evaluation model is embedded into the circular evaluation model, so that the technical effect of evaluation accuracy is improved.
Example two
Based on the digital management method for the enterprise finance based on the RPA in the foregoing embodiment, the present invention also provides a digital management system for the enterprise finance based on the RPA, referring to fig. 4, where the system includes:
the first execution unit 11 is used for acquiring internal and external financial data of an enterprise by using an ETL data warehouse technology and constructing an enterprise financial database;
a first obtaining unit 12, wherein the first obtaining unit 12 is configured to obtain a set of enterprise financial processing rules;
a second executing unit 13, where the second executing unit 13 is configured to determine preset rule information according to the corporate financial database and the corporate financial processing rule set;
a third executing unit 14, where the third executing unit 14 is configured to construct RPA financial management information based on the preset rule information;
a fourth executing unit 15, where the fourth executing unit 15 is configured to perform intelligent management on the enterprise financial database through the RPA financial management information, and generate a financial management report;
a second obtaining unit 16, where the second obtaining unit 16 is configured to obtain optimization requirement information based on the financial management report and the preset rule information;
a third obtaining unit 17, where the third obtaining unit 17 is configured to input the optimization requirement information into a cyclic evaluation model for digital management and evaluation, so as to obtain an evaluation result;
a fifth executing unit 18, where the fifth executing unit 18 is configured to perform optimized management on the RPA financial management information according to the evaluation result.
Further, the system further comprises:
a fourth obtaining unit, configured to obtain an enterprise financial data source port;
a sixth execution unit, configured to extract enterprise financial information based on the enterprise financial data source port;
the seventh execution unit is used for performing data parameter analysis according to the enterprise financial information and converting the data into financial rule data;
an eighth execution unit, configured to load the financial rule data, and construct the enterprise financial database based on data parameters.
Further, the system further comprises:
a fifth obtaining unit to obtain a set of historical financial statements;
a sixth obtaining unit, configured to perform financial statement content classification according to the historical financial statement set, and obtain a financial processing classification set;
a seventh obtaining unit, configured to perform semantic analysis on the financial statements corresponding to each type in the financial processing classification set line by line, respectively, to obtain a statement content specification, where the statement content specification includes financial data parameters and parameter processing rules;
an eighth obtaining unit, configured to establish a mapping relationship according to the financial processing classification set, the financial data parameters, and parameter processing rules, and obtain the enterprise financial processing rule set.
Further, the system further comprises:
a ninth obtaining unit, configured to obtain report feedback information based on the financial management report;
a tenth obtaining unit, configured to perform financial data parameter matching according to the report feedback information and the preset rule information, and obtain a matching parameter processing rule;
an eleventh obtaining unit, configured to perform difference analysis according to the matching parameter processing rule and the report feedback information, obtain rule difference information, and use the rule difference information as the optimization demand information.
Further, the system further comprises:
a twelfth obtaining unit, configured to monitor a processing procedure of the RPA financial management information based on the preset rule information, and obtain flow processing information;
a thirteenth obtaining unit, configured to perform management evaluation according to the process processing information and the financial management report, and obtain management evaluation information;
a fourteenth obtaining unit, configured to obtain a demand optimization direction according to the management evaluation information and the optimization demand information;
a ninth execution unit, configured to optimize the preset rule information according to the demand optimization direction;
a tenth execution unit, configured to construct the loop evaluation model based on a loop relationship among the preset rule information, the process processing information, the management evaluation information, a demand optimization direction, and preset rule information.
Further, the system further comprises:
a fifteenth obtaining unit, configured to obtain a processing flow and a data processing relationship according to the flow processing information;
a sixteenth obtaining unit, configured to perform processing parameter analysis on the data processing relationship based on the processing flow to obtain a processing procedure evaluation parameter;
a seventeenth obtaining unit, configured to obtain a report data mapping relationship according to the data processing relationship and the financial management report;
an eighteenth obtaining unit, configured to perform content parameter analysis on the financial management report and the report data mapping relationship to obtain a report evaluation parameter;
a nineteenth obtaining unit, configured to input the processing procedure evaluation parameters and the report evaluation parameters into an evaluation model, and obtain the management evaluation information, where the evaluation model is a neural network model obtained through training multiple sets of training data, embed the evaluation model into the cyclic evaluation model, monitor the management evaluation information in the cyclic evaluation model, and output the management evaluation information as the evaluation result.
Further, the system further comprises:
a twentieth obtaining unit configured to obtain new addition rule information;
and the eleventh execution unit is used for adding the newly added rule information into the preset rule information and updating the RPA financial management information.
In the present specification, the embodiments are described in a progressive manner, and each embodiment focuses on differences from other embodiments, and the foregoing digital management method for RPA-based enterprise finance and the specific example in the first embodiment of fig. 1 are also applicable to the digital management system for RPA-based enterprise finance of the present embodiment, and through the foregoing detailed description of the digital management method for RPA-based enterprise finance, those skilled in the art can clearly know the digital management system for RPA-based enterprise finance in the present embodiment, so for brevity of description, detailed description is not repeated here. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Exemplary electronic device
The electronic device of the present application is described below with reference to fig. 5.
Based on the same inventive concept as the digital management method of the enterprise finance based on the RPA in the previous embodiment, the application also provides a digital management system of the enterprise finance based on the RPA, which comprises: a processor coupled to a memory, the memory to store a program that, when executed by the processor, causes a system to perform the method of any of the embodiments.
The electronic device 300 includes: processor 302, communication interface 303, memory 301. Optionally, the electronic device 300 may also include a bus architecture 304. Wherein, the communication interface 303, the processor 302 and the memory 301 may be connected to each other through a bus architecture 304; the bus architecture 304 may be a peripheral component interconnect standard bus, an extended industry standard architecture bus, or the like. The bus architecture 304 may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, only one thick line is shown, but this does not mean that there is only one bus or one type of bus.
The memory 301 is used for storing computer-executable instructions for executing the present application, and is controlled by the processor 302 to execute. Processor 302 is configured to execute computer-executable instructions stored in memory 301, thereby implementing a digital RPA-based enterprise finance management method provided in the present application.
Alternatively, the computer executable instructions may also be referred to as application code, and the application is not limited thereto.
The application solves the technical problem that in the prior art, the accuracy of enterprise financial management is not high, and then the effect of enterprise financial management is poor. The accuracy and the precision of enterprise financial management are improved, and the effect and the quality of the enterprise financial management are improved; meanwhile, the RPA technology is combined with enterprise financial management, and a method for optimizing the enterprise financial management is designed, so that the waste of resources such as manpower and material resources of the enterprise financial management is avoided, and the cost of the enterprise financial management is reduced; the time of enterprise financial management is saved, and the technical effect of the efficiency of the enterprise financial management is improved.
Those of ordinary skill in the art will understand that: the various numbers of the first, second, etc. mentioned in this application are for convenience of description and are not intended to limit the scope of this application nor to indicate the order of precedence. "and/or" describes the association relationship of the associated objects, meaning that there may be three relationships, e.g., a and/or B, which may mean: a exists alone, A and B exist simultaneously, and B exists alone. The character "/" generally indicates that the former and latter associated objects are in an "or" relationship. "at least one" means one or more. At least two means two or more. "at least one," "any," or similar expressions refer to any combination of these items, including any combination of item(s) or item(s). For example, at least one (one ) of a, b, or c, may represent: a, b, c, a b, a c, b c, or a b c, wherein a, b, c can be single or multiple.
In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the procedures or functions described in accordance with the present application are generated, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another computer readable storage medium, for example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center by wire or wirelessly. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device including one or more available media integrated servers, data centers, and the like. The usable media may be magnetic, optical, or semiconductor media, among others.
The various illustrative logical units and circuits described in this application may be implemented or operated through the design of a general purpose processor, a digital signal processor, an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof. A general-purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing devices, e.g., a digital signal processor and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a digital signal processor core, or any other similar configuration.
The steps of a method or algorithm described in this application may be embodied directly in hardware, in a software element executed by a processor, or in a combination of the two. The software cells may be stored in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, a removable disk, a CD ROM, or any other form of storage medium known in the art. For example, a storage medium may be coupled to the processor such that the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium may be integral to the processor. The processor and the storage medium may reside in an ASIC, which may be disposed in a terminal. In the alternative, the processor and the storage medium may reside in different components within the terminal. These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Although the present application has been described in conjunction with specific features and embodiments thereof, it will be evident that various modifications and combinations can be made thereto without departing from the spirit and scope of the application.
Accordingly, the specification and figures are merely exemplary of the application and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of the application. It will be apparent to those skilled in the art that various changes and modifications may be made in the present application without departing from the scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the present application and its equivalent technology, it is intended that the present application include such modifications and variations.
Claims (10)
1. A digital management method for enterprise finance based on RPA, which is characterized in that the method comprises:
acquiring internal and external financial data of an enterprise by using an ETL data warehouse technology, and constructing an enterprise financial database;
acquiring an enterprise financial processing rule set;
determining preset rule information according to the enterprise financial database and the enterprise financial processing rule set;
constructing RPA financial management information based on the preset rule information;
intelligently managing the enterprise financial database through the RPA financial management information to generate a financial management report;
acquiring optimization demand information based on the financial management report and the preset rule information;
inputting the optimization demand information into a cyclic evaluation model for digital management evaluation to obtain an evaluation result;
and performing optimization management on the RPA financial management information according to the evaluation result.
2. The method of claim 1, wherein said collecting internal and external financial data of the enterprise using ETL data warehouse technology, building an enterprise financial database, comprises:
acquiring an enterprise financial data source port;
extracting enterprise financial information based on the enterprise financial data source port;
performing data parameter analysis according to the enterprise financial information, and converting the data into financial rule data;
and loading the financial rule data, and constructing the enterprise financial database based on data parameters.
3. The method of claim 1, wherein the obtaining a set of corporate financial processing rules comprises:
obtaining a historical financial statement set;
classifying the content of the financial statements according to the historical financial statement set to obtain a financial processing classification set;
respectively carrying out line-by-line semantic analysis on financial statements corresponding to various types in the financial processing classification set to obtain statement content specifications, wherein the statement content specifications comprise financial data parameters and parameter processing rules;
and establishing a mapping relation according to the financial processing classification set, the financial data parameters and the parameter processing rules to obtain the enterprise financial processing rule set.
4. The method of claim 2, wherein obtaining optimization requirement information based on the financial management statement and the preset rule information comprises:
obtaining report feedback information based on the financial management report;
performing financial data parameter matching according to the report feedback information and the preset rule information to obtain a matching parameter processing rule;
and performing difference analysis according to the matching parameter processing rule and the report feedback information to obtain rule difference information, and taking the rule difference information as the optimization demand information.
5. The method of claim 1, wherein inputting the optimization requirement information into a cyclic evaluation model for digital management evaluation comprises, before obtaining an evaluation result:
monitoring the processing process of the RPA financial management information based on the preset rule information to obtain process processing information;
performing management evaluation according to the process processing information and the financial management report to obtain management evaluation information;
acquiring a demand optimization direction according to the management evaluation information and the optimization demand information;
optimizing the preset rule information according to the demand optimization direction;
and constructing the circulation evaluation model based on the circulation relationship of the preset rule information, the process processing information, the management evaluation information, the demand optimization direction and the preset rule information.
6. The method of claim 5, wherein performing management evaluation according to the process processing information and the financial management report to obtain management evaluation information comprises:
acquiring a processing flow and a data processing relation according to the flow processing information;
processing parameter analysis is carried out on the data processing relation based on the processing flow, and processing process evaluation parameters are obtained;
acquiring a report data mapping relation according to the data processing relation and the financial management report;
performing content parameter analysis on the financial management report and the report data mapping relation to obtain report evaluation parameters;
inputting the processing process evaluation parameters and the report evaluation parameters into an evaluation model to obtain the management evaluation information, wherein the evaluation model is a neural network model obtained by training a plurality of groups of training data, embedding the evaluation model into the cyclic evaluation model, monitoring the management evaluation information in the cyclic evaluation model, and outputting the management evaluation information as an evaluation result.
7. The method of claim 1, wherein the method further comprises:
acquiring new rule information;
and adding the newly added rule information into the preset rule information, and updating the RPA financial management information.
8. A digital management system for RPA-based corporate finance, the system comprising:
the system comprises a first execution unit, a second execution unit and a database management unit, wherein the first execution unit is used for acquiring internal and external financial data of an enterprise by using an ETL data warehouse technology and constructing an enterprise financial database;
a first obtaining unit, configured to obtain a set of enterprise financial processing rules;
the second execution unit is used for determining preset rule information according to the enterprise financial database and the enterprise financial processing rule set;
a third execution unit, configured to construct RPA financial management information based on the preset rule information;
the fourth execution unit is used for intelligently managing the enterprise financial database through the RPA financial management information to generate a financial management report;
the second obtaining unit is used for obtaining optimization demand information based on the financial management report and the preset rule information;
the third obtaining unit is used for inputting the optimization demand information into a cyclic evaluation model for digital management evaluation to obtain an evaluation result;
a fifth execution unit, configured to perform optimized management on the RPA financial management information according to the evaluation result.
9. A digital management system for RPA based corporate finance, comprising a processor coupled to a memory, the memory storing a program which, when executed by the processor, causes the system to perform the steps of the method of any one of claims 1 to 7.
10. A computer-readable storage medium, characterized in that the storage medium has stored thereon a computer program which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 7.
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