CN113537370A - Cloud computing-based financial data processing method and system - Google Patents
Cloud computing-based financial data processing method and system Download PDFInfo
- Publication number
- CN113537370A CN113537370A CN202110829062.3A CN202110829062A CN113537370A CN 113537370 A CN113537370 A CN 113537370A CN 202110829062 A CN202110829062 A CN 202110829062A CN 113537370 A CN113537370 A CN 113537370A
- Authority
- CN
- China
- Prior art keywords
- financial
- information
- data
- feature
- data processing
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
- G06F18/241—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
- G06Q40/12—Accounting
- G06Q40/125—Finance or payroll
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Finance (AREA)
- Accounting & Taxation (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- Data Mining & Analysis (AREA)
- General Physics & Mathematics (AREA)
- Bioinformatics & Computational Biology (AREA)
- Life Sciences & Earth Sciences (AREA)
- General Engineering & Computer Science (AREA)
- Evolutionary Biology (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Artificial Intelligence (AREA)
- Evolutionary Computation (AREA)
- Development Economics (AREA)
- Economics (AREA)
- Marketing (AREA)
- Strategic Management (AREA)
- Technology Law (AREA)
- General Business, Economics & Management (AREA)
- Financial Or Insurance-Related Operations Such As Payment And Settlement (AREA)
Abstract
The invention discloses a financial data processing method and system based on cloud computing, wherein the method comprises the following steps: performing feature classification on the first enterprise business data information according to a financial feature decision tree to obtain first financial feature type information; performing service matching on the first financial characteristic type information and the financial management service cloud platform to obtain first financial application information; calling a corresponding first financial application database according to a first calling instruction; inputting the first financial characteristic type information and the first financial application database into a financial analysis processing model to obtain a first financial data processing result; and integrating and storing the first enterprise business data information, the first financial characteristic type information and the first financial data processing result into a first financial archive. The technical problems that in the prior art, financial data processing workload is large, a large amount of labor cost is needed, and data processing efficiency is low are solved.
Description
Technical Field
The invention relates to the field of data processing, in particular to a financial data processing method and system based on cloud computing.
Background
The financial data processing process is the whole process of continuously, systematically and comprehensively accounting the economic activities of enterprises, is the process of processing, processing and storing the data of economic services, provides useful information for financial information users and has to process the data generated by a large amount of economic services.
However, in the process of implementing the technical solution of the invention in the embodiments of the present application, the inventors of the present application find that the above-mentioned technology has at least the following technical problems:
the financial data processing workload is large, a large amount of labor cost is needed, and the technical problem of low data processing efficiency is caused in the prior art.
Disclosure of Invention
The embodiment of the application provides a financial data processing method and system based on cloud computing, solves the technical problems that in the prior art, financial data processing workload is large, a large amount of labor cost is needed, and data processing efficiency is low, and achieves the technical effects that financial data are processed through cloud computing service, manpower and material resources cost is reduced, data processing efficiency is improved through data sharing, and timely and safe are achieved, so that decision-making management is facilitated.
In view of the above, the present invention has been developed to provide a solution to, or at least partially solve, the above problems.
In a first aspect, an embodiment of the present application provides a cloud computing-based financial data processing method, where the method includes: acquiring first enterprise business data information; performing feature classification on the first enterprise business data information according to a financial feature decision tree to obtain first financial feature type information; constructing a financial management service cloud platform through big data; performing service matching on the first financial characteristic type information and the financial management service cloud platform to obtain first financial application information; obtaining a first calling instruction according to the first financial application information, wherein the first calling instruction is used for calling a corresponding first financial application database; inputting the first financial characteristic type information and the first financial application database into a financial analysis processing model to obtain a first financial data processing result; and integrating and storing the first enterprise business data information, the first financial characteristic type information and the first financial data processing result into a first financial archive.
In another aspect, the present application further provides a cloud computing-based financial data processing system, including: the first obtaining unit is used for obtaining first enterprise business data information; the second obtaining unit is used for carrying out feature classification on the first enterprise business data information according to a financial feature decision tree to obtain first financial feature type information; the system comprises a first construction unit, a second construction unit and a third construction unit, wherein the first construction unit is used for constructing a financial management service cloud platform through big data; a third obtaining unit, configured to perform service matching on the first financial feature type information and the financial management service cloud platform to obtain first financial application information; a fourth obtaining unit, configured to obtain a first call instruction according to the first financial application information, where the first call instruction is used to call a corresponding first financial application database; a fifth obtaining unit, configured to input the first financial feature type information and the first financial application database into a financial analysis processing model, and obtain a first financial data processing result; a first storage unit, configured to store the first enterprise business data information, the first financial feature type information, and the first financial data processing result in a first financial archive in an integrated manner.
In a third aspect, an embodiment of the present invention provides an electronic device, including a bus, a transceiver, a memory, a processor, and a computer program stored on the memory and executable on the processor, where the transceiver, the memory, and the processor are connected via the bus, and when the computer program is executed by the processor, the method for controlling output data includes any one of the steps described above.
In a fourth aspect, the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the steps in the method for controlling output data according to any one of the above.
One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:
the method comprises the steps of obtaining first enterprise business data information; performing feature classification on the first enterprise business data information according to a financial feature decision tree to obtain first financial feature type information; constructing a financial management service cloud platform through big data; performing service matching on the first financial characteristic type information and the financial management service cloud platform to obtain first financial application information; obtaining a first calling instruction according to the first financial application information, wherein the first calling instruction is used for calling a corresponding first financial application database; inputting the first financial characteristic type information and the first financial application database into a financial analysis processing model to obtain a first financial data processing result; and integrating and storing the first enterprise business data information, the first financial characteristic type information and the first financial data processing result into a first financial archive. And then reach through cloud computing service to financial data processing, reduce manpower and materials cost, data sharing improves data processing efficiency, and is timely safe to the technological effect of the decision-making management of being convenient for.
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
Fig. 1 is a schematic flowchart of a cloud computing-based financial data processing method according to an embodiment of the present application;
fig. 2 is a schematic flowchart illustrating a process of adjusting the first enterprise business data information in a cloud computing-based financial data processing method according to an embodiment of the present application;
fig. 3 is a schematic flowchart illustrating a process of obtaining a balance adjustment table of a first business account in a cloud computing-based financial data processing method according to an embodiment of the present application;
fig. 4 is a schematic flowchart illustrating a process of adjusting a first financial data processing result in a cloud computing-based financial data processing method according to an embodiment of the present application;
FIG. 5 is a schematic flowchart illustrating a process of constructing a financial feature decision tree in a cloud computing-based financial data processing method according to an embodiment of the present application;
fig. 6 is a schematic flowchart illustrating the integrated storage of financial information into a first financial archive in a cloud-computing-based financial data processing method according to an embodiment of the present application;
fig. 7 is a schematic flowchart illustrating a process of obtaining a first financial data processing result in a cloud computing-based financial data processing method according to an embodiment of the present application;
FIG. 8 is a schematic structural diagram of a cloud computing-based financial data processing system according to an embodiment of the present application;
fig. 9 is a schematic structural diagram of an electronic device for executing a method of controlling output data according to an embodiment of the present application.
Description of reference numerals: a first obtaining unit 11, a second obtaining unit 12, a first constructing unit 13, a third obtaining unit 14, a fourth obtaining unit 15, a fifth obtaining unit 16, a first storage unit 17, a bus 1110, a processor 1120, a transceiver 1130, a bus interface 1140, a memory 1150 and a user interface 1160.
Detailed Description
In the description of the embodiments of the present invention, it should be apparent to those skilled in the art that the embodiments of the present invention can be embodied as methods, apparatuses, electronic devices, and computer-readable storage media. Thus, embodiments of the invention may be embodied in the form of: entirely hardware, entirely software (including firmware, resident software, micro-code, etc.), a combination of hardware and software. Furthermore, in some embodiments, embodiments of the invention may also be embodied in the form of a computer program product in one or more computer-readable storage media having computer program code embodied in the medium.
The computer-readable storage media described above may take any combination of one or more computer-readable storage media. The computer-readable storage medium includes: an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of the computer-readable storage medium include: a portable computer diskette, a hard disk, a random access memory, a read-only memory, an erasable programmable read-only memory, a flash memory, an optical fiber, a compact disc read-only memory, an optical storage device, a magnetic storage device, or any combination thereof. In embodiments of the invention, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, device, or apparatus.
Summary of the application
The method, the device and the electronic equipment are described through the flow chart and/or the block diagram.
It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer-readable program instructions. These computer-readable program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.
These computer-readable program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing apparatus to function in a particular manner. Thus, the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means which implement the function/act specified in the flowchart and/or block diagram block or blocks.
The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide processes for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.
The embodiments of the present invention will be described below with reference to the drawings.
Practice ofExample one
As shown in fig. 1, an embodiment of the present application provides a cloud computing-based financial data processing method, where the method includes:
step S100: acquiring first enterprise business data information;
as shown in fig. 2, further, after obtaining the first enterprise business data information, step S100 in this embodiment of the present application further includes:
step S110: acquiring first business account change of the first enterprise according to the banking service terminal;
step S120: obtaining a first reconciliation instruction, and comparing the first enterprise business data information with the first business account change according to the first reconciliation instruction to obtain a first comparison result;
step S130: if the difference degree of the first comparison result is not zero, obtaining a first business account balance adjustment table;
step S140: and adjusting the first enterprise business data information according to the first business account balance adjustment table.
Specifically, the first business data information is related accounting information of business to business and business to business, such as financial status, business result and cash flow, and the business data information can reflect the financial status of the business on a specific date and the business result in a certain accounting period, so as to provide a basis for financial data processing.
Further, the banking terminal is a part of banking transaction electronization and automation, and may perform functional services including cash withdrawal, cash deposit and withdrawal, balance inquiry, local or different bank transfer, password modification, and the like. And obtaining a first business account change in a bank account of the first enterprise through the bank service terminal, comparing the first enterprise business data information with the first business account change according to the first reconciliation instruction, namely reconciling with a bank, checking business bills from and to each other one by one, and obtaining a first comparison result after account comparison. If the difference degree of the first comparison result is not zero, namely the business data between the bank and the enterprise are inconsistent, which may be caused by factors such as billing error or time record difference, the business billing data of the enterprise needs to be adjusted to obtain a first business account balance adjustment table according to the adjusted billing after the reconciliation. And adjusting the first enterprise business data information according to the first business account balance adjustment table so as to achieve the technical effect of ensuring the accurate and real business data of the enterprise through the regular checking of business bills.
Step S200: performing feature classification on the first enterprise business data information according to a financial feature decision tree to obtain first financial feature type information;
as shown in fig. 5, further, in the financial characteristic decision tree, step S200 in the embodiment of the present application further includes:
step S210: acquiring a corresponding financial characteristic type information set according to the enterprise business data information set;
step S220: performing principal component analysis on the data features of the financial feature type information set to obtain a first dimension reduction data feature set, wherein the first dimension reduction data feature set comprises a first feature, a second feature and a third feature;
step S230: respectively carrying out information theory coding operation on the first feature, the second feature and the third feature to obtain node feature information of a decision tree;
step S240: and constructing a financial characteristic decision tree according to the node characteristic information.
Specifically, a Decision Tree (Decision Tree) is a Decision analysis method for obtaining a probability that an expected value of a net present value is equal to or greater than zero by constructing a Decision Tree on the basis of known occurrence probabilities of various situations, evaluating a project risk, and judging feasibility thereof, and is a graphical method for intuitively using probability analysis. The financial characteristics can be used as internal nodes of the financial characteristic decision tree, the characteristics with the minimum entropy value can be classified preferentially by calculating the information entropy of the financial characteristics decision tree, the financial characteristic decision tree is constructed recursively by the method until the final characteristic leaf node can not be subdivided, and the classification is finished, so that the financial characteristic decision tree is formed.
Further, according to the enterprise business data information set, a corresponding financial feature type information set is obtained, principal component analysis is performed on the data features of the financial feature type information set, the principal component analysis is the most common linear dimension reduction method, the objective of the principal component analysis is to map high-dimensional data into a low-dimensional space through certain linear projection, and the information amount of the data on the projected dimension is expected to be the largest (the variance is the largest), so that fewer data dimensions are used, and the characteristics of more raw data points are retained. Obtaining a first dimension reduction data feature set after the principal component analysis dimension reduction, wherein the first dimension reduction data feature set comprises a first feature, a second feature and a third feature. The purpose of dimension reduction is to reduce the dimension of the original features under the condition of ensuring that the information content is not lost as much as possible, namely, the original features are projected to the dimension with the maximum projection information content as much as possible, and the original features are projected to the dimensions, so that the loss of the information content after dimension reduction is minimum.
In order to specifically construct the financial characteristic decision tree, information entropy calculation can be performed on the first characteristic, the second characteristic and the third characteristic respectively, that is, the information entropy is specifically calculated through a shannon formula in information theory coding, so that corresponding characteristic information entropy is obtained, further, the information entropy represents uncertainty of information, when the uncertainty is larger, the contained information amount is larger, the information entropy is higher, and the purity is lower, and when all samples in a set are uniformly mixed, the information entropy is maximum, and the purity is lowest. Therefore, the characteristic information entropy is compared with the size value of the characteristic information entropy based on the data size comparison model, then the characteristic with the minimum entropy value, namely the first root node characteristic information, is obtained, the characteristic with the minimum entropy value is preferentially classified, then the node characteristics are sequentially classified according to the sequence of the entropy values from small to large, and finally the financial characteristic decision tree is constructed. Each business is matched with the appropriate financial characteristics, and the technical effect of specifically constructing the financial characteristic decision tree is further realized.
Step S300: constructing a financial management service cloud platform through big data;
step S400: performing service matching on the first financial characteristic type information and the financial management service cloud platform to obtain first financial application information;
step S500: obtaining a first calling instruction according to the first financial application information, wherein the first calling instruction is used for calling a corresponding first financial application database;
specifically, a government service cloud platform with stronger decision making power, insight discovery power and flow optimization capacity is constructed in a big data mode, and the financial management service cloud platform is a financial service management platform which is based on hardware services and provides computing, network and storage capacities. And performing service matching on the first financial characteristic type information and the financial management service cloud platform to obtain first financial application information corresponding to the matching, and performing service voucher application service if necessary. And calling a first financial application database corresponding to the financial application according to the first calling instruction for financial application data processing.
Step S600: inputting the first financial characteristic type information and the first financial application database into a financial analysis processing model to obtain a first financial data processing result;
as shown in fig. 7, further, wherein the inputting the first financial characteristic type information and the first financial application database into a financial analysis processing model to obtain a first financial data processing result, step S600 of this embodiment of the present application further includes:
step S610: inputting the first financial feature type information and the first financial application database as input information to the financial analysis processing model;
step S620: the production line evaluation model is obtained by training a plurality of groups of training data, and each group of training data in the plurality of groups of training data comprises: the first financial feature type information, the first financial application database, and identification information to identify a first financial data processing result;
step S630: obtaining a first output result in the financial analysis processing model, the first output result comprising the first financial data processing result.
Specifically, the first financial data processing result is a processing result of the business data of the enterprise, and includes a financial data amount processing result, a financial processing analysis result, a processing posting subject result, and the like. The financial analysis processing model is a Neural network model, namely a Neural network model in machine learning, and a Neural Network (NN) is a complex Neural network system formed by widely connecting a large number of simple processing units (called neurons), reflects many basic characteristics of human brain functions, and is a highly complex nonlinear dynamical learning system. Neural network models are described based on mathematical models of neurons. Artificial Neural Networks (ANN), is a description of the first-order properties of the human brain system. Briefly, it is a mathematical model. And inputting the first financial characteristic type information and the first financial application database into a neural network model through training of a large amount of training data, and outputting the first financial data processing result.
More specifically, the training process is essentially a supervised learning process, each set of supervised data includes the first financial feature type information, the first financial application database and identification information for identifying a first financial data processing result, the first financial feature type information and the first financial application database are input into a neural network model, the neural network model performs continuous self-correction and adjustment according to the identification information for identifying the first financial data processing result, and the set of supervised learning is ended until the obtained first output result is consistent with the identification information, and a next set of supervised learning is performed; and when the output information of the neural network model reaches the preset accuracy rate/reaches the convergence state, finishing the supervised learning process. Through the supervised learning of the neural network model, the neural network model can process the input information more accurately, the output first financial data processing result information is more reasonable and accurate, the efficient and accurate financial data processing analysis is achieved, and the system is timely and safe, so that the technical effect of providing basis for decision management is achieved.
Step S700: and integrating and storing the first enterprise business data information, the first financial characteristic type information and the first financial data processing result into a first financial archive.
As shown in fig. 6, further, wherein the integrating and storing the first enterprise business data information, the first financial feature type information, and the first financial data processing result into a first financial archive, step S700 in this embodiment of the present application further includes:
step S710: acquiring first financial processing information, and storing the first enterprise business data information to the first financial processing information;
step S720: obtaining second financial processing information, and storing the first financial feature type information to the second financial processing information;
step S730: obtaining third financial processing information, and storing the first financial data processing result to the third financial processing information;
step S740: and integrally storing the first financial processing information, the second financial processing information and the third financial processing information into a first financial archive through distributed storage.
Specifically, the first financial processing information includes the first enterprise business data information, the second financial processing information includes the first financial characteristic type information, and the third financial processing information includes the first financial data processing result. The first financial archive is used for storing and archiving financial processing data, providing data basis for later calling and checking of enterprise financial data, and integrating the first financial processing information, the second financial processing information and the third financial processing information through distributed storage. The distributed storage is a data storage technology, the disk space of each machine in an enterprise is used through a network, the distributed storage resources form a virtual storage device, data are stored in each corner of the enterprise in a distributed mode, information is stored in a block file in a block chain mode, the safety of stored financial data is guaranteed, and the technical effects that the source tracing cannot be modified and the accuracy is improved are achieved.
As shown in fig. 3, further, step S140 in the embodiment of the present application further includes:
step S141: determining a bank reconciliation accounting period according to the first enterprise business data information;
step S142: obtaining the first business account change in the bank reconciliation accounting period;
step S143: comparing the first enterprise business data information with the first business account change to obtain a first enterprise account number;
step S144: and compiling and obtaining a first business account balance adjustment table according to the first enterprise unachieved account.
Specifically, according to the occurrence time of the first enterprise business data information, a bank reconciliation accounting period, namely business reconciliation accounting dates of enterprises and banks, is determined. And obtaining the first business account change of the enterprise in the bank account checking period, and comparing the first enterprise business data information with the first business account change to obtain an unreachable account of the enterprise, wherein the unreachable account refers to the situation that the accounting time is inconsistent because the actual time for acquiring the certificate is different between the enterprise and the bank, and the settlement certificate is acquired and registered by one party and the account is not acquired by the other party. And compiling and obtaining a first business account balance adjusting table according to the unachieved account of the first enterprise, wherein the first business account balance adjusting table is used for adding the account amounts received by the bank and not received by the enterprise and subtracting the account amounts paid by the bank and not paid by the enterprise so as to adjust the balance of the two parties to make the accounts consistent, thereby ensuring the technical effect of accuracy of financial processing data.
As shown in fig. 4, further, the embodiment of the present application further includes:
step S810: obtaining first accounting amount information of the first enterprise according to the first financial data processing result;
step S820: according to the first account amount information, debit account amount information and credit account amount information are respectively obtained;
step S830: obtaining a first account balance coefficient, wherein the first account balance coefficient is the proportion of the debit account amount information and the credit account amount information;
step S840: if the first account balance coefficient is not 1, obtaining a first adjusting parameter;
step S850: and adjusting the first financial data processing result according to the first adjusting parameter.
Specifically, first accounting amount information corresponding to the first enterprise is obtained according to the first financial data processing result, and debit accounting amount information and credit accounting amount information are respectively obtained according to the first accounting amount information. The enterprise financial accounting adopts a debit and credit keeping method, the debit and credit keeping amount information is the amount of money which is recorded in the debit of an accounting subject during the keeping, the credit keeping amount information is the amount of money which is recorded in the credit of the accounting subject during the keeping, for example, the amount of the debit form of a loss account in an asset class, a cost class and a profit and loss class is increased, the amount of money is reduced by the credit, the amount of money is reduced by the debit of a profit account in a liability class, a right class and a profit class, and the amount of money is increased by the credit. The first account balance coefficient is the proportion of the debit keeping amount information and the credit keeping amount information, and the keeping rule of the debit and credit keeping method can be summarized as follows: borrowing must have the loan, borrowing must equal, and the debit amount of keeping accounts for financial accounts equals the credit amount of keeping accounts for, account amount can only balance correctly. If first account balance coefficient is not 1, and financial account is unbalanced promptly, and the account amount is incorrect, needs carry out the account adjustment, according to the adjustment parameter is right account amount information is adjusted, reaches reasonable adjustment account debit and credit amount, guarantees the balanced technological effect of financial account.
In summary, the cloud computing-based financial data processing method and system provided by the embodiment of the application have the following technical effects:
the method comprises the steps of obtaining first enterprise business data information; performing feature classification on the first enterprise business data information according to a financial feature decision tree to obtain first financial feature type information; constructing a financial management service cloud platform through big data; performing service matching on the first financial characteristic type information and the financial management service cloud platform to obtain first financial application information; obtaining a first calling instruction according to the first financial application information, wherein the first calling instruction is used for calling a corresponding first financial application database; inputting the first financial characteristic type information and the first financial application database into a financial analysis processing model to obtain a first financial data processing result; and integrating and storing the first enterprise business data information, the first financial characteristic type information and the first financial data processing result into a first financial archive. And then reach through cloud computing service to financial data processing, reduce manpower and materials cost, data sharing improves data processing efficiency, and is timely safe to the technological effect of the decision-making management of being convenient for.
Example two
Based on the same inventive concept as the cloud computing-based financial data processing method in the foregoing embodiment, the present invention further provides a cloud computing-based financial data processing system, as shown in fig. 8, the system includes:
a first obtaining unit 11, where the first obtaining unit 11 is configured to obtain first enterprise business data information;
a second obtaining unit 12, where the second obtaining unit 12 is configured to perform feature classification on the first enterprise business data information according to a financial feature decision tree, so as to obtain first financial feature type information;
a first building unit 13, wherein the first building unit 13 is used for building a financial management service cloud platform through big data;
a third obtaining unit 14, where the third obtaining unit 14 is configured to perform service matching on the first financial feature type information and the financial management service cloud platform to obtain first financial application information;
a fourth obtaining unit 15, where the fourth obtaining unit 15 is configured to obtain a first call instruction according to the first financial application information, where the first call instruction is used to call a corresponding first financial application database;
a fifth obtaining unit 16, wherein the fifth obtaining unit 16 is configured to input the first financial feature type information and the first financial application database into a financial analysis processing model, and obtain a first financial data processing result;
a first storage unit 17, wherein the first storage unit 17 is configured to integrally store the first enterprise business data information, the first financial feature type information, and the first financial data processing result into a first financial profile.
Further, the system further comprises:
a sixth obtaining unit, configured to obtain, according to a banking service terminal, a first business account change of the first enterprise;
a seventh obtaining unit, configured to obtain a first reconciliation instruction, compare the first enterprise business data information with the first business account change according to the first reconciliation instruction, and obtain a first comparison result;
an eighth obtaining unit, configured to obtain a first service account balance adjustment table if the difference degree of the first comparison result is not zero;
and the first adjusting unit is used for adjusting the first enterprise business data information according to the first business account balance adjusting table.
Further, the system further comprises:
the first determining unit is used for determining the bank reconciliation accounting period according to the first enterprise business data information;
a ninth obtaining unit, configured to obtain the first business account change in the bank reconciliation accounting period;
a tenth obtaining unit, configured to compare the first enterprise business data information with the first business account change, and obtain a first enterprise unacknowledged account;
an eleventh obtaining unit, configured to compile and obtain a first business account balance adjustment table according to the first enterprise unaccounted item.
Further, the system further comprises:
a twelfth obtaining unit, configured to obtain first accounting amount information of the first enterprise according to the first financial data processing result;
a thirteenth obtaining unit, configured to obtain debit account amount information and credit account amount information according to the first account amount information;
a fourteenth obtaining unit, configured to obtain a first account balance coefficient, where the first account balance coefficient is a ratio between the debit account amount information and the credit account amount information;
a fifteenth obtaining unit configured to obtain a first adjustment parameter if the first account balance coefficient is not 1;
and the second adjusting unit is used for adjusting the first financial data processing result according to the first adjusting parameter.
Further, the system further comprises:
a sixteenth obtaining unit, configured to obtain a corresponding financial feature type information set according to the enterprise business data information set;
a seventeenth obtaining unit, configured to perform principal component analysis on the data features of the financial feature type information set to obtain a first dimension-reduced data feature set, where the first dimension-reduced data feature set includes a first feature, a second feature, and a third feature;
an eighteenth obtaining unit, configured to perform information theory encoding operations on the first feature, the second feature, and the third feature, respectively, to obtain node feature information of a decision tree;
and the second construction unit is used for constructing a financial characteristic decision tree according to the node characteristic information.
Further, the system further comprises:
a nineteenth obtaining unit, configured to obtain first financial processing information, and store the first enterprise business data information to the first financial processing information;
a twentieth obtaining unit configured to obtain second financial processing information, to which the first financial feature type information is stored;
a twenty-first obtaining unit, configured to obtain third financial processing information, and store the first financial data processing result in the third financial processing information;
and the second storage unit is used for integrally storing the first financial processing information, the second financial processing information and the third financial processing information into a first financial archive through distributed storage.
Further, the system further comprises:
a first input unit for inputting the first financial feature type information and the first financial application database as input information to the financial analysis processing model;
a twenty-second obtaining unit, configured to obtain, by training the production line evaluation model through multiple sets of training data, each set of training data in the multiple sets of training data including: the first financial feature type information, the first financial application database, and identification information to identify a first financial data processing result;
a twenty-third obtaining unit to obtain a first output result in the financial analysis processing model, the first output result comprising the first financial data processing result.
Various changes and specific examples of the cloud-computing-based financial data processing method in the first embodiment of fig. 1 are also applicable to the cloud-computing-based financial data processing system in the present embodiment, and a person skilled in the art can clearly know the implementation method of the cloud-computing-based financial data processing system in the present embodiment through the foregoing detailed description of the cloud-computing-based financial data processing method, so for the brevity of the description, detailed descriptions are omitted here.
In addition, an embodiment of the present invention further provides an electronic device, which includes a bus, a transceiver, a memory, a processor, and a computer program stored in the memory and capable of running on the processor, where the transceiver, the memory, and the processor are connected via the bus, and when the computer program is executed by the processor, the processes of the method for controlling output data are implemented, and the same technical effects can be achieved, and are not described herein again to avoid repetition.
Exemplary electronic device
Specifically, referring to fig. 9, an embodiment of the present invention further provides an electronic device, which includes a bus 1110, a processor 1120, a transceiver 1130, a bus interface 1140, a memory 1150, and a user interface 1160.
In an embodiment of the present invention, the electronic device further includes: a computer program stored on the memory 1150 and executable on the processor 1120, the computer program, when executed by the processor 1120, implementing the various processes of the method embodiments of controlling output data described above.
A transceiver 1130 for receiving and transmitting data under the control of the processor 1120.
In embodiments of the invention in which a bus architecture (represented by bus 1110) is used, bus 1110 may include any number of interconnected buses and bridges, with bus 1110 connecting various circuits including one or more processors, represented by processor 1120, and memory, represented by memory 1150.
The bus 1110 may also connect various other circuits such as peripherals, voltage regulators, or power management circuits to provide an interface between the bus 1110 and the transceiver 1130, as is well known in the art. Therefore, the embodiments of the present invention will not be further described.
The transceiver 1130 may be one element or may be multiple elements, such as multiple receivers and transmitters, providing a means for communicating with various other apparatus over a transmission medium. For example: the transceiver 1130 receives external data from other devices, and the transceiver 1130 transmits data processed by the processor 1120 to other devices. Depending on the nature of the computer system, a user interface 1160 may also be provided, such as: touch screen, physical keyboard, display, mouse, speaker, microphone, trackball, joystick, stylus.
It is to be appreciated that in embodiments of the invention, the memory 1150 may further include memory located remotely with respect to the processor 1120, which may be coupled to a server via a network. One or more portions of the above-described network may be an ad hoc network, an intranet, an extranet, a virtual private network, a local area network, a wireless local area network, a wide area network, a wireless wide area network, a metropolitan area network, the internet, a public switched telephone network, a plain old telephone service network, a cellular telephone network, a wireless fidelity network, and a combination of two or more of the above. For example, the cellular telephone network and the wireless network may be a global system for mobile communications, code division multiple access, global microwave interconnect access, general packet radio service, wideband code division multiple access, long term evolution, LTE frequency division duplex, LTE time division duplex, long term evolution-advanced, universal mobile communications, enhanced mobile broadband, mass machine type communications, ultra-reliable low latency communications, etc.
It is to be understood that the memory 1150 in embodiments of the present invention can be either volatile memory or nonvolatile memory, or can include both volatile and nonvolatile memory. Wherein the nonvolatile memory includes: read-only memory, programmable read-only memory, erasable programmable read-only memory, electrically erasable programmable read-only memory, or flash memory.
The volatile memory includes: random access memory, which acts as an external cache. By way of example, and not limitation, many forms of RAM are available, such as: static random access memory, dynamic random access memory, synchronous dynamic random access memory, double data rate synchronous dynamic random access memory, enhanced synchronous dynamic random access memory, synchronous link dynamic random access memory, and direct memory bus random access memory. The memory 1150 of the electronic device described in the embodiments of the invention includes, but is not limited to, the above and any other suitable types of memory.
In an embodiment of the present invention, memory 1150 stores the following elements of operating system 1151 and application programs 1152: an executable module, a data structure, or a subset thereof, or an expanded set thereof.
Specifically, the operating system 1151 includes various system programs such as: a framework layer, a core library layer, a driver layer, etc. for implementing various basic services and processing hardware-based tasks. Applications 1152 include various applications such as: media player, browser, used to realize various application services. A program implementing a method of an embodiment of the invention may be included in application program 1152. The application programs 1152 include: applets, objects, components, logic, data structures, and other computer system executable instructions that perform particular tasks or implement particular abstract data types.
In addition, an embodiment of the present invention further provides a computer-readable storage medium, where a computer program is stored, and when the computer program is executed by a processor, the computer program implements each process of the above method for controlling output data, and can achieve the same technical effect, and in order to avoid repetition, details are not repeated here.
The above description is only a specific implementation of the embodiments of the present invention, but the scope of the embodiments of the present invention is not limited thereto, and any person skilled in the art can easily conceive of changes or substitutions within the technical scope of the embodiments of the present invention, and all such changes or substitutions should be covered by the scope of the embodiments of the present invention. Therefore, the protection scope of the embodiments of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. A cloud computing-based financial data processing method, wherein the method comprises:
acquiring first enterprise business data information;
performing feature classification on the first enterprise business data information according to a financial feature decision tree to obtain first financial feature type information;
constructing a financial management service cloud platform through big data;
performing service matching on the first financial characteristic type information and the financial management service cloud platform to obtain first financial application information;
obtaining a first calling instruction according to the first financial application information, wherein the first calling instruction is used for calling a corresponding first financial application database;
inputting the first financial characteristic type information and the first financial application database into a financial analysis processing model to obtain a first financial data processing result;
and integrating and storing the first enterprise business data information, the first financial characteristic type information and the first financial data processing result into a first financial archive.
2. The method of claim 1, wherein after obtaining the first business data information, the method is applied to a financial data processing system, the system being communicatively coupled to a banking terminal, comprising:
acquiring first business account change of the first enterprise according to the banking service terminal;
obtaining a first reconciliation instruction, and comparing the first enterprise business data information with the first business account change according to the first reconciliation instruction to obtain a first comparison result;
if the difference degree of the first comparison result is not zero, obtaining a first business account balance adjustment table;
and adjusting the first enterprise business data information according to the first business account balance adjustment table.
3. The method of claim 2, wherein the method comprises:
determining a bank reconciliation accounting period according to the first enterprise business data information;
obtaining the first business account change in the bank reconciliation accounting period;
comparing the first enterprise business data information with the first business account change to obtain a first enterprise account number;
and compiling and obtaining a first business account balance adjustment table according to the first enterprise unachieved account.
4. The method of claim 1, wherein the method comprises:
obtaining first accounting amount information of the first enterprise according to the first financial data processing result;
according to the first account amount information, debit account amount information and credit account amount information are respectively obtained;
obtaining a first account balance coefficient, wherein the first account balance coefficient is the proportion of the debit account amount information and the credit account amount information;
if the first account balance coefficient is not 1, obtaining a first adjusting parameter;
and adjusting the first financial data processing result according to the first adjusting parameter.
5. The method of claim 1, wherein the financial feature decision tree comprises:
acquiring a corresponding financial characteristic type information set according to the enterprise business data information set;
performing principal component analysis on the data features of the financial feature type information set to obtain a first dimension reduction data feature set, wherein the first dimension reduction data feature set comprises a first feature, a second feature and a third feature;
respectively carrying out information theory coding operation on the first feature, the second feature and the third feature to obtain node feature information of a decision tree;
and constructing a financial characteristic decision tree according to the node characteristic information.
6. The method of claim 1, wherein said integrating storage of said first enterprise business data information, said first financial characteristic type information, and said first financial data processing result into a first financial archive comprises:
acquiring first financial processing information, and storing the first enterprise business data information to the first financial processing information;
obtaining second financial processing information, and storing the first financial feature type information to the second financial processing information;
obtaining third financial processing information, and storing the first financial data processing result to the third financial processing information;
and integrally storing the first financial processing information, the second financial processing information and the third financial processing information into a first financial archive through distributed storage.
7. The method of claim 1, wherein said entering the first financial feature type information and the first financial application database into a financial analytics processing model, obtaining a first financial data processing result, comprises:
inputting the first financial feature type information and the first financial application database as input information to the financial analysis processing model;
the production line evaluation model is obtained by training a plurality of groups of training data, and each group of training data in the plurality of groups of training data comprises: the first financial feature type information, the first financial application database, and identification information to identify a first financial data processing result;
obtaining a first output result in the financial analysis processing model, the first output result comprising the first financial data processing result.
8. A cloud computing-based financial data processing system, wherein the system comprises:
the first obtaining unit is used for obtaining first enterprise business data information;
the second obtaining unit is used for carrying out feature classification on the first enterprise business data information according to a financial feature decision tree to obtain first financial feature type information;
the system comprises a first construction unit, a second construction unit and a third construction unit, wherein the first construction unit is used for constructing a financial management service cloud platform through big data;
a third obtaining unit, configured to perform service matching on the first financial feature type information and the financial management service cloud platform to obtain first financial application information;
a fourth obtaining unit, configured to obtain a first call instruction according to the first financial application information, where the first call instruction is used to call a corresponding first financial application database;
a fifth obtaining unit, configured to input the first financial feature type information and the first financial application database into a financial analysis processing model, and obtain a first financial data processing result;
a first storage unit, configured to store the first enterprise business data information, the first financial feature type information, and the first financial data processing result in a first financial archive in an integrated manner.
9. Cloud computing based financial data processing system comprising a bus, a transceiver, a memory, a processor and a computer program stored on and executable on said memory, said transceiver, said memory and said processor being connected via said bus, characterized in that said computer program realizes the steps in the method of controlling output data according to any of claims 1-7 when executed by said processor.
10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method of controlling output data according to any one of claims 1-7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110829062.3A CN113537370A (en) | 2021-07-22 | 2021-07-22 | Cloud computing-based financial data processing method and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110829062.3A CN113537370A (en) | 2021-07-22 | 2021-07-22 | Cloud computing-based financial data processing method and system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113537370A true CN113537370A (en) | 2021-10-22 |
Family
ID=78120389
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110829062.3A Pending CN113537370A (en) | 2021-07-22 | 2021-07-22 | Cloud computing-based financial data processing method and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113537370A (en) |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113988666A (en) * | 2021-11-01 | 2022-01-28 | 常州天晟紫金自动化设备有限公司 | Intelligent quantitative packaging method and system for organic silicon rubber compound |
| CN114510735A (en) * | 2022-04-01 | 2022-05-17 | 国网浙江省电力有限公司 | Role management-based intelligent shared financial management method and platform |
| CN114708080A (en) * | 2022-06-06 | 2022-07-05 | 湖南涉外经济学院 | Distributed financial data online processing method |
| CN115587898A (en) * | 2022-10-14 | 2023-01-10 | 南昌工学院 | Cloud service-based financial data secure sharing method and system |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111667225A (en) * | 2019-03-05 | 2020-09-15 | 阿里巴巴集团控股有限公司 | Financial data processing method and device and computer system |
| CN112508671A (en) * | 2020-12-29 | 2021-03-16 | 广州广电运通信息科技有限公司 | Enterprise financial data processing method, system, device and medium |
-
2021
- 2021-07-22 CN CN202110829062.3A patent/CN113537370A/en active Pending
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111667225A (en) * | 2019-03-05 | 2020-09-15 | 阿里巴巴集团控股有限公司 | Financial data processing method and device and computer system |
| CN112508671A (en) * | 2020-12-29 | 2021-03-16 | 广州广电运通信息科技有限公司 | Enterprise financial data processing method, system, device and medium |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113988666A (en) * | 2021-11-01 | 2022-01-28 | 常州天晟紫金自动化设备有限公司 | Intelligent quantitative packaging method and system for organic silicon rubber compound |
| CN113988666B (en) * | 2021-11-01 | 2022-08-09 | 常州天晟紫金自动化设备有限公司 | Intelligent quantitative packaging method and system for organic silicon rubber compound |
| CN114510735A (en) * | 2022-04-01 | 2022-05-17 | 国网浙江省电力有限公司 | Role management-based intelligent shared financial management method and platform |
| CN114510735B (en) * | 2022-04-01 | 2022-07-19 | 国网浙江省电力有限公司 | Role management-based intelligent shared financial management method and platform |
| CN114708080A (en) * | 2022-06-06 | 2022-07-05 | 湖南涉外经济学院 | Distributed financial data online processing method |
| CN115587898A (en) * | 2022-10-14 | 2023-01-10 | 南昌工学院 | Cloud service-based financial data secure sharing method and system |
| CN115587898B (en) * | 2022-10-14 | 2023-10-03 | 河北湛泸软件开发有限公司 | Financial data secure sharing method and system based on cloud service |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN113537370A (en) | Cloud computing-based financial data processing method and system | |
| EP3889829A1 (en) | Integrated clustering and outlier detection using optimization solver machine | |
| CN110796399B (en) | Resource allocation method and device based on block chain | |
| Firmansyah et al. | The influence of efficacy, credibility, and normative pressure to M-banking adoption level in Indonesia | |
| CN110415123B (en) | Financial product recommendation method, device and equipment and computer storage medium | |
| CN111090780A (en) | Method and device for determining suspicious transaction information, storage medium and electronic equipment | |
| US20200265514A1 (en) | Recording medium recording communication program and communication apparatus | |
| CN111639690A (en) | Fraud analysis method, system, medium, and apparatus based on relational graph learning | |
| CN113806350B (en) | Management method and system for improving security of big data transaction platform | |
| WO2021012906A1 (en) | Product pricing method and device | |
| US20230360124A1 (en) | Recurrent neural networks with gaussian mixture based normalization | |
| CN112446777A (en) | Credit evaluation method, device, equipment and storage medium | |
| CN116150200A (en) | Data processing method, device, electronic equipment and storage medium | |
| CN114240599A (en) | Loan calculation method and device, computer equipment and storage medium | |
| CN113191877A (en) | Data feature acquisition method and system and electronic equipment | |
| CN115221663A (en) | Data processing method, device, equipment and computer readable storage medium | |
| CN111882294B (en) | Method and device for flow approval | |
| UA139735U (en) | HARDWARE AND AUTOMATIC COMPLEX FOR AUTOMATED DECISION-MAKING ON ON-LINE LOANS | |
| US20240331037A1 (en) | Management of custodian-held securities based on conversion scores | |
| US20230359884A1 (en) | Training a neural network model across multiple domains | |
| Sewe et al. | Credit Quality Evaluation on a Dynamic Network with Latent Variables | |
| CN118313625A (en) | Financial service resource allocation method, device, equipment and storage medium | |
| CN117891713A (en) | Test data construction method and device, electronic equipment and storage medium | |
| CN112785207A (en) | Model construction method, output prediction method, device and computing equipment | |
| CN115619444A (en) | Combination method of prediction models, traffic prediction method, device, and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20211022 |