WO2022077535A1

WO2022077535A1 - Computer software management financial system and method for using same

Info

Publication number: WO2022077535A1
Application number: PCT/CN2020/122145
Authority: WO
Inventors: 蒋淑清
Original assignee: 垒途智能教科技术研究院江苏有限公司; 无锡科技职业学院
Priority date: 2020-10-15
Filing date: 2020-10-20
Publication date: 2022-04-21
Also published as: CN112016768B; CN112016768A

Abstract

Disclosed in the present invention are a computer software management financial system and a method for using same. The system comprises a login module, a data entry module, a predicting and accounting module, a management module, a database, a display module, and a query module; the login module is communicationally connected to the data entry module; the management module is separately and communicationally connected to the data entry module, the predicting and accounting module, and the database; the predicting and accounting module is further communicationally connected to the data entry module and the database; and the display module is separately and communicationally connected to the database and the query module. The present invention has the following beneficial effects: inputting financial data into the system by means of the data entry module not only can achieve the analysis, operation, classification, and hierarchical management of the financial data under the action of the management module, but also can check the inputted financial data under the action of the predicting and accounting module, thereby being capable of greatly improving the accuracy of the financial data, and being high in working efficiency.

Description

A computer software management financial system and its using method

technical field

The invention relates to the technical field of financial management, in particular, to a computer software management financial system and a method for using the same.

Background technique

Financial management is the management of asset acquisition (investment), capital financing (financing), operating cash flow (working capital), and profit distribution under a certain overall goal. Financial management is an integral part of enterprise management. It is an economic management work that organizes corporate financial activities and handles financial relationships according to financial regulations and the principles of financial management. Simply put, financial management is an economic management work that organizes corporate financial activities and handles financial relationships.

For large enterprises, financial management is very important. Traditional financial management is carried out through common financial management methods such as paper bookkeeping, checkout and audit, which not only wastes time and energy, but also the paper version of financial bookkeeping is not enough. It is easy to copy and store for a long time. Therefore, how to accurately and completely find these financial data from the massive database during financial transactions or subsequent verification is a more troublesome problem. Completing the verification work by manual means and finding relevant financial data in the daily complicated financial vouchers is inefficient, and the data is prone to incomplete or incorrect data, which affects the normal operation of financial management.

For the problems in the related technologies, no effective solutions have been proposed so far.

SUMMARY OF THE INVENTION

In view of the problems in the related art, the present invention proposes a computer software management financial system and a method for using the same, so as to overcome the above-mentioned technical problems existing in the related art.

For this reason, the concrete technical scheme that the present invention adopts is as follows:

According to an aspect of the present invention, a computer software management financial system is provided, which includes a login module, a data entry module, a forecasting and accounting module, a management module, a database, a display module and a query module, wherein the login module is connected in communication with the data entry module, The management module is respectively connected with the data entry module, the forecasting and accounting module and the database in communication, the forecasting and accounting module is also connected in communication with the data entry module and the database, and the display module is in communication with the database and the query module respectively;

Among them, the login module is used for users to log in to the system through digital passwords, fingerprints or facial recognition;

The data entry module is used for the user to input financial data that needs to be stored;

The prediction accounting module is used to predict financial data through a pre-built RNN model, compare the predicted data with the input data, and mark abnormal data at the same time;

The management module is used to analyze, calculate, classify and manage the entered financial data;

The database is used to store the financial data after hierarchical management;

The display module is used to display the financial data of the database in the form of tables or graphs;

The query module is used for the user to view the financial data stored in the database;

The prediction and accounting module includes a data acquisition module, an RNN model establishment module, a data acquisition module, a result output module, a data verification module and a marking module which are sequentially connected in communication;

Among them, the data collection module is used to obtain past financial data;

The RNN model building module is used to build an RNN model through past financial data;

The data acquisition module is used to acquire the entered financial data and input it into the RNN model;

The result output module is used to output the forecast financial data corresponding to the input financial data;

The data checking module is used to compare and account the entered financial data with the forecasted financial data;

The marking module is used to mark abnormal input financial data.

Further, the login module includes a password collection module, a fingerprint collection module and a face recognition module, and the output terminals of the password collection module, the fingerprint collection module and the face recognition module are all connected in communication with the input terminal of the data entry module.

Further, the data input module includes a manual input module and a scan acquisition module, and the manual input module is input by means of a keyboard and a mouse, and the scan acquisition module is scanned by an image scanning device for acquisition.

Further, the management module includes a data definition module, an analysis operation module, a classification management module, and a hierarchical management module that are sequentially connected in communication, wherein the data definition module is used to extract the key features of financial data, automatically generate corresponding financial labels, and analyze financial data. The data and its financial labels are predefined; the analysis operation module is used to analyze and calculate the predefined financial data and its financial labels; the classification management module is used to classify the analyzed and calculated financial data and financial labels; hierarchical management The module is used to grade the classified financial data according to the dynamic data heat table.

Further, an encryption module is arranged inside the database, and the display module includes a table display module and a graphic display module.

Further, the query module includes an identity recognition module, a query authorization module and a query record module that are connected in sequence.

According to another aspect of the present invention, a method for using a computer software management financial system is also provided, and the using method includes the following steps:

S1. Log in to the system through the login module, and enter the financial data to be stored into the system through the data entry module;

S2. Use the RNN model pre-built by the prediction accounting module to predict the financial data, compare the predicted financial data with the input financial data, and mark abnormal financial data at the same time;

S3, analyzing, calculating and classifying the input financial data through the management module, and classifying the classified financial data according to a preset method;

S4. Use the database to store the graded financial data, and use the display module and the query module to view the data in the database.

Further, S2 uses the RNN model pre-built by the prediction accounting module to predict financial data, compares the predicted financial data with the input financial data for accounting, and marks abnormal financial data at the same time, including the following steps:

S21. Obtain past financial data through a data collection module;

S22, using the RNN model building module to build an RNN model based on past financial data;

S23. Use the data acquisition module to acquire the input financial data and input the RNN model;

S24, output the predicted financial data corresponding to the input financial data through the result output module;

S25, using the data checking module to compare and calculate the input financial data and the predicted financial data;

S26. If the input financial data exceeds the threshold of the predicted financial data, use a marking module to mark the abnormal input financial data.

Further, grading the classified financial data according to the preset method in S3 includes the following steps: generating a dynamic data heat table according to the viewing times of different types of data in the past financial data, and performing the input financial data according to the data heat table. Heat rating.

Further, the heat classification includes data migration and data retrieving. The activation of data migration includes the following two situations: the data does not meet the data standard of the heat level or the storage space on the heat level is full or nearly full, and the data is Forced migration; activation of data fetching includes the following two situations: activation based on the user's access request to the data or the data has exceeded the data standard of the heat level within a period of time.

The beneficial effects of the present invention are:

1), the present invention inputs financial data into the system through the data entry module, which can not only realize the analysis, operation, classification and hierarchical management of financial data under the action of the management module, but also can realize the entry under the action of the forecasting and accounting module. The verification of financial data can greatly improve the accuracy of financial data and work efficiently.

2), the present invention compares and calculates the input financial data by constructing an RNN model, considering the time series relationship between the historical financial data, not only can realize the checking of the input financial data, but also can realize the marking of abnormal financial data. , thus effectively ensuring the accuracy of financial data.

3), the present invention performs thermal calculation on historical financial data, and uses the thermal level to perform hierarchical management on the financial data entered by the user, thereby making the present invention more user-friendly for the classification of financial data, which can be better for users. View of financial data.

Description of drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the accompanying drawings required in the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some of the present invention. In the embodiments, for those of ordinary skill in the art, other drawings can also be obtained according to these drawings without any creative effort.

1 is a structural block diagram of a computer software management financial system according to an embodiment of the present invention;

FIG. 2 is a flowchart of a method for using a computer software management financial system according to an embodiment of the present invention.

In the picture:

1. Login module; 101. Password collection module; 102. Fingerprint collection module; 103. Facial recognition module; 2. Data input module; 201. Manual input module; 202. Scanning collection module; 3. Predictive accounting module; 301. Data acquisition module; 302, RNN model building module; 303, data acquisition module; 304, result output module; 305, data checking module; 306, marking module; 4, management module; 401, data definition module; 402, analysis operation module; 403, classification management module; 404, hierarchical management module; 5, database; 501, encryption module; 6, display module; 601, table display module; 602, graphic display module; 7, query module; 701, identification module; 702 , query the authorization module; 703, query the record module.

Detailed ways

In order to further illustrate the various embodiments, the present invention provides accompanying drawings, which are part of the disclosure of the present invention, and are mainly used to illustrate the embodiments, and can be used in conjunction with the relevant descriptions in the specification to explain the operation principles of the embodiments. For these, those of ordinary skill in the art will understand other possible implementations and the advantages of the present invention. Components in the figures are not drawn to scale, and similar component symbols are generally used to represent similar components.

According to an embodiment of the present invention, a computer software management financial system and a method for using the same are provided.

The present invention will now be further described with reference to the accompanying drawings and specific embodiments. As shown in FIG. 1, according to an embodiment of the present invention, a computer software management financial system is provided, including a login module 1, a data entry module 2, and a forecasting and accounting module. 3. A management module 4, a database 5, a display module 6 and a query module 7, the login module 1 is connected in communication with the data entry module 2, and the management module 4 is respectively connected with the data entry module 2, the forecast accounting Module 3 and the database 5 are in communication connection, the forecasting and accounting module 3 is also in communication connection with the data entry module 2 and the database 5, and the display module 6 is in communication with the database 5 and the query module 7 respectively. connect;

Wherein, the login module 1 is used for the user to log in to the system by means of digital password, fingerprint or facial recognition;

The data entry module 2 is used for the user to input financial data that needs to be stored;

The prediction accounting module 3 is used to predict financial data through a pre-built RNN model, compare the predicted data with the input data, and mark abnormal data at the same time;

The management module 4 is used to analyze, calculate, classify and manage the entered financial data;

The database 5 is used to store the financial data after hierarchical management;

The display module 6 is used to display the financial data of the database 5 by means of a table or a graph;

The query module 7 is used for the user to check the financial data stored in the database 5;

The forecasting and accounting module 3 includes a data acquisition module 301, an RNN model establishment module 302, a data acquisition module 303, a result output module 304, a data verification module 305 and a marking module 306 that are sequentially connected in communication;

Wherein, the data collection module 301 is used to obtain past financial data;

The RNN model building module 302 is used to build an RNN model through past financial data;

The data acquisition module 303 is used to acquire the entered financial data and input the RNN model;

The result output module 304 is used for outputting predicted financial data corresponding to the entered financial data;

The data verification module 305 is used to compare and account the entered financial data with the predicted financial data;

The marking module 306 is used to mark abnormal input financial data.

In one embodiment, the login module 1 includes a password collection module 101, a fingerprint collection module 102 and a face recognition module 103, and the output of the password collection module 101, the fingerprint collection module 102 and the face recognition module 103 The terminals are all connected in communication with the input terminal of the data entry module 2 .

In one embodiment, the data input module 2 includes a manual input module 201 and a scan acquisition module 202, and the manual input module 201 is input by means of a keyboard and a mouse, and the scan acquisition module 202 scans data by an image scanning device. way to collect.

In one embodiment, the management module 4 includes a data definition module 401, an analysis operation module 402, a classification management module 403, and a hierarchical management module 404 that are sequentially connected in communication, wherein the data definition module 401 is used to extract the data of the financial data. The key feature is to automatically generate corresponding financial labels, and to predefine financial data and financial labels; the analysis and operation module 402 is used to analyze and calculate the predefined financial data and financial labels; the classification management The module 403 is used for classifying the financial data and financial labels after analysis and operation; the classification management module 404 is used for classifying the classified financial data according to the dynamic data heat table.

In one embodiment, an encryption module 501 is provided inside the database 5 , and the display module 6 includes a table display module 601 and a graphic display module 602 .

In one embodiment, the query module 7 includes an identity recognition module 701 , a query authorization module 702 and a query record module 703 that are communicated in sequence.

According to another embodiment of the present invention, as shown in FIG. 2 , a method for using a computer software management financial system is also provided, and the using method includes the following steps:

S1, log in to the system through the login module 1, and enter the financial data that needs to be stored into the system through the data entry module 2;

S2, utilize the RNN model constructed in advance by the forecasting and accounting module 3 to predict financial data, and compare the predicted financial data with the input financial data for accounting, and simultaneously mark abnormal financial data;

Wherein, the S2 utilizes the RNN model pre-built by the forecasting and accounting module 3 to forecast financial data, and compares the forecasted financial data with the input financial data for accounting, and marks abnormal financial data at the same time, including the following steps:

S21, obtaining past financial data through the data collection module 301;

S22, using the RNN model building module 302 to build an RNN model based on past financial data;

S23, use the data acquisition module 303 to obtain the entered financial data and input the RNN model;

S24, outputting predicted financial data corresponding to the entered financial data through the result output module 304;

S25, using the data verification module 305 to compare and calculate the entered financial data and the predicted financial data;

S26. If the entered financial data exceeds the threshold of the predicted financial data, use the marking module 306 to mark the abnormal entered financial data.

S3, analyzing, calculating and classifying the entered financial data through the management module 4, and grading the classified financial data according to a preset method;

The grading of the classified financial data according to the preset method in the S3 includes the following steps: generating a dynamic data heat table according to the viewing times of different types of data in the past financial data, and classifying the entered data according to the data heat table. Financial data for heat classification.

Specifically, the heat classification includes two types of data migration and data retrieval, wherein the activation of the data migration includes the following two situations: the data does not meet the data standard of the heat level or the storage space on the heat level is full or the If the data is full, the data is forced to be migrated; the activation of the data fetch includes the following two situations: activation based on the user's access request to the data or the data has exceeded the data standard of the heat level within a period of time.

S4. Use the database 5 to store the graded financial data, and use the display module 6 and the query module 7 to view the data in the database 5.

In order to facilitate the understanding of the above technical solutions of the present invention, the RNN model of the present invention will be described below.

Recurrent Neural Networks (RNN), also known as Recurrent Neural Networks, is one of the hottest technologies in the field of deep learning in recent years. It has achieved great success in the fields of machine translation, speech recognition and image recognition. In traditional neural networks, it is usually assumed that all input layers and output layers are independent of each other, but for many tasks, this is not a good way. Taking the financial data of an enterprise as an example, the future financial data situation depends on the situation value at the historical moment.

The purpose of RNN is to process sequence data. The specific manifestation is that the network will memorize the previous information and apply it to the calculation of the current output, that is, the nodes between the hidden layers are no longer unconnected but connected, that is to say, the input of the hidden layer not only includes the input layer The output of also includes the output of the hidden layer at the previous moment. In theory, RNN can process sequence data of any length. In RNN, each input step, each layer shares parameters U, V, W. It reflects that each step in the RNN is doing the same thing, but the input is different, so the parameters that need to be learned in the network are greatly reduced, and the key point of the RNN is the hidden layer, which can capture the information of the sequence.

To sum up, with the help of the above technical solutions of the present invention, the present invention can input financial data into the system through the data input module, which can not only realize the analysis, calculation, classification and hierarchical management of financial data under the action of the management module, but also The verification of the input financial data can be realized under the action of the forecasting accounting module, so that the accuracy of the financial data can be greatly improved, and the work efficiency is high.

In addition, the present invention compares and calculates the input financial data by constructing an RNN model, considering the time series relationship between historical financial data, not only can check the input financial data, but also can realize the marking of abnormal financial data, This effectively ensures the accuracy of financial data.

In addition, the present invention performs grading management on the financial data entered by the user by performing heat calculation on the historical financial data and using the heat level to manage the financial data entered by the user, thereby making the grading of the financial data more humanized in the present invention, which can be more convenient for the user to classify the financial data. Viewing financial data.

The above descriptions are only preferred embodiments of the present invention, and are not intended to limit the present invention. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the scope of the present invention. within the scope of protection.

Claims

A computer software management financial system, characterized in that it comprises a login module (1), a data entry module (2), a forecast accounting module (3), a management module (4), a database (5), a display module (6) and Inquiry module (7), the login module (1) is connected in communication with the data entry module (2), and the management module (4) is respectively connected with the data entry module (2) and the forecasting and accounting module (3) ), the database (5) is communicatively connected, the forecasting and accounting module (3) is also communicatively connected with the data entry module (2) and the database (5), and the display module (6) is respectively connected with the The database (5) is connected in communication with the query module (7);

Wherein, the login module (1) is used for the user to log in to the system by means of digital password, fingerprint or facial recognition;

The data entry module (2) is used for the user to input financial data that needs to be stored;

The predictive accounting module (3) is used to predict financial data through a pre-built RNN model, compare the predicted data with the input data, and mark abnormal data at the same time;

The management module (4) is used to analyze, calculate, classify and manage the entered financial data;

The database (5) is used to store the financial data after hierarchical management;

The display module (6) is used to display the financial data of the database (5) in a form or a graph;

The query module (7) is used for the user to check the financial data stored in the database (5);

The forecasting and accounting module (3) includes a data acquisition module (301), an RNN model building module (302), a data acquisition module (303), a result output module (304), a data verification module (305) and a tag that are sequentially connected in communication module(306);

Wherein, the data acquisition module (301) is used to acquire past financial data;

The RNN model establishment module (302) is used to establish an RNN model through past financial data;

The data acquisition module (303) is used to acquire the entered financial data and input the RNN model;

The result output module (304) is used for outputting predicted financial data corresponding to the entered financial data;

The data verification module (305) is used to compare and account the entered financial data with the predicted financial data;

The marking module (306) is used for marking abnormal input financial data.
A computer software management financial system according to claim 1, wherein the login module (1) comprises a password collection module (101), a fingerprint collection module (102) and a face recognition module (103), and the The output terminals of the password collection module (101), the fingerprint collection module (102) and the face recognition module (103) are all connected in communication with the input terminal of the data entry module (2).
A computer software management financial system according to claim 2, wherein the data input module (2) comprises a manual input module (201) and a scan acquisition module (202), and the manual input module (201) ) is input by means of a keyboard and a mouse, and the scanning and acquisition module (202) performs acquisition by means of scanning by an image scanning device.
A computer software management financial system according to claim 3, characterized in that, the management module (4) comprises a data definition module (401), an analysis and operation module (402), and a classification management module (403) which are sequentially connected in communication ) and a hierarchical management module (404), wherein the data definition module (401) is used to extract key features of financial data, automatically generate corresponding financial labels, and predefine financial data and financial labels; the analysis The operation module (402) is used to analyze and calculate the predefined financial data and its financial labels; the classification management module (403) is used to classify the analyzed and calculated financial data and financial labels; the hierarchical management The module (404) is used for grading the classified financial data according to the dynamic data heat table.
A computer software management financial system according to claim 4, characterized in that, an encryption module (501) is provided inside the database (5), and the display module (6) includes a table display module (601) and a graph Display module (602).
A computer software management financial system according to claim 5, characterized in that, the query module (7) comprises an identity recognition module (701), a query authorization module (702) and a query record module (703) which are sequentially connected in communication ).
A kind of use method of computer software management financial system, is used for the described computer software management financial system of claim 7, it is characterized in that, this use method comprises the following steps:

S1, log in to the system through the login module (1), and enter the financial data that needs to be stored into the system through the data entry module (2);

S2, utilize the RNN model constructed in advance by the forecasting and accounting module (3) to forecast financial data, compare the forecasted financial data with the input financial data, and mark abnormal financial data at the same time;

S3, analyzing, calculating and classifying the input financial data through the management module (4), and grading the classified financial data according to a preset method;

S4. Use the database (5) to store the graded financial data, and use the display module (6) and the query module (7) to view the data in the database (5).
The method for using a computer software management financial system according to claim 7, wherein the S2 uses the RNN model pre-built by the forecasting and accounting module (3) to forecast the financial data, and compares the forecasted financial data with the forecasted financial data. Entering financial data for comparison and accounting, and marking abnormal financial data at the same time includes the following steps:

S21, obtaining past financial data through the data collection module (301);

S22, using the RNN model building module (302) to build an RNN model based on past financial data;

S23, use the data acquisition module (303) to obtain the entered financial data and input the RNN model;

S24, output predicted financial data corresponding to the entered financial data through the result output module (304);

S25, using the data checking module (305) to compare and calculate the input financial data and the predicted financial data;

S26. If the entered financial data exceeds the threshold of the predicted financial data, use a marking module (306) to mark the abnormally entered financial data.
The method for using computer software to manage a financial system according to claim 8, wherein the grading of the classified financial data according to a preset method in S3 comprises the following steps: according to different types of data in the past financial data The number of viewings is generated, a dynamic data heat table is generated, and the entered financial data is classified according to the data heat table.
The method for using a computer software management financial system according to claim 9, wherein the heat classification includes two types of data migration and data recall, wherein the activation of the data migration includes the following two situations: The data does not meet the data standard of the heat level or the storage space at the heat level is full or about to be full, and the data is forced to be migrated; the activation of the data fetch includes the following two situations: activation based on the user's access request to the data or The data has exceeded the data standard of the heat level for a period of time.