CN115660760A

CN115660760A - Block chain-based value-added tax invoice invoicing prediction method and device

Info

Publication number: CN115660760A
Application number: CN202211421330.9A
Authority: CN
Inventors: 何艳波
Original assignee: Bank of China Ltd
Current assignee: Bank of China Ltd
Priority date: 2022-11-14
Filing date: 2022-11-14
Publication date: 2023-01-31

Abstract

The invention discloses a block chain-based value-added tax invoice invoicing prediction method and a block chain-based value-added tax invoice invoicing prediction device, and relates to a block chain, wherein the method comprises the following steps: acquiring value-added tax transaction data of a customer from a block chain, and performing data cleaning processing and data feature derivation processing to obtain transaction data features; the transaction data characteristics are sent to a billing prediction model of the value-added tax invoice, and the prediction billing time and the prediction billing mechanism corresponding to the value-added tax transaction data are obtained; the billing prediction model of the value-added tax invoice is obtained by training the neural network model through billing historical data of the value-added tax invoice; and before the predicted invoicing time, sending the notification information carrying the value-added tax transaction data of the user and the predicted invoicing time to the predicted invoicing mechanism. The method and the system are used for improving the billing efficiency of the value-added tax invoice of the customer, improving the customer experience, improving the service quality of a website mechanism and improving the service efficiency.

Description

Block chain-based value-added tax invoice invoicing prediction method and device

Technical Field

The invention relates to the technical field of block chains, in particular to a method and a device for forecasting invoicing of a value-added tax invoice based on a block chain.

Background

This section is intended to provide a background or context to the embodiments of the invention that are recited in the claims. The description herein is not admitted to be prior art by inclusion in this section.

For financial institutions, customers usually invoice corresponding to the customers when handling business through some business channels, and for most customers, many customers choose to bill the transactions during the period of time due to various factors, so the customers also need to often go to and from the billing institutions to handle the billing business, but the situations of the customers are different, and business personnel cannot well know the situations of the customers.

For example, after the customer goes to the website, the website does not prepare the invokable transaction data of the customer in advance, so that the customer needs to wait for a long time, the invoicing efficiency of the value-added tax invoice of the customer is reduced, and the customer experience is influenced.

Therefore, how to better assist business personnel to know the billing requirements of customers and push the billing requirements to business personnel of billing organizations is an urgent problem to be solved.

Disclosure of Invention

The embodiment of the invention provides a block chain-based value-added tax invoice billing prediction method, which is used for improving the billing efficiency of a value-added tax invoice of a client, improving the client experience, improving the service quality of a website mechanism and improving the service efficiency, and comprises the following steps:

acquiring value-added tax transaction data of a client from a block chain;

carrying out data cleaning processing and data characteristic derivation processing on the value-added tax transaction data of the client to obtain transaction data characteristics corresponding to the value-added tax transaction data;

transmitting the transaction data characteristics corresponding to the value-added tax transaction data to a billing prediction model of the value-added tax invoice to obtain the predicted billing time and the predicted billing mechanism corresponding to the value-added tax transaction data; the billing prediction model of the value-added tax invoice is obtained by training the neural network model through billing historical data of the value-added tax invoice; the invoicing historical data of the value-added tax invoice comprises the following data: transaction data characteristics of different value-added tax transaction historical data, and historical invoicing time and historical invoicing mechanisms corresponding to the different value-added tax transaction historical data;

before the forecast billing time, sending notice information carrying value-added tax transaction data of the user and the forecast billing time to the forecast billing organization

The embodiment of the invention also provides a block chain-based value-added tax invoice billing prediction device, which is used for improving the billing efficiency of the value-added tax invoice of a client, improving the client experience, improving the service quality of a website mechanism and improving the service efficiency, and the device comprises:

the value-added tax transaction data acquisition module is used for acquiring the value-added tax transaction data of the client from the block chain;

the data cleaning processing and data feature deriving processing module is used for performing data cleaning processing and data feature deriving processing on the value-added tax transaction data of the client to obtain transaction data features corresponding to the value-added tax transaction data;

the forecasting module of the forecasting invoicing time and the forecasting mechanism is used for sending the transaction data characteristics corresponding to the value-added tax transaction data to the invoicing forecasting model of the value-added tax invoice to obtain the forecasting invoicing time and the forecasting invoicing mechanism corresponding to the value-added tax transaction data; the billing prediction model of the value-added tax invoice is obtained by training the neural network model through billing historical data of the value-added tax invoice; the invoicing historical data of the value-added tax invoice comprises the following data: transaction data characteristics of different value-added tax transaction historical data, and historical invoicing time and historical invoicing mechanisms corresponding to the different value-added tax transaction historical data;

and the notification information sending module is used for sending the notification information carrying the value-added tax transaction data of the user and the predicted invoicing time to the predicted invoicing mechanism before the predicted invoicing time.

The embodiment of the invention also provides computer equipment which comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, wherein the processor executes the computer program to realize the method for forecasting the invoicing of the value-added tax invoice based on the block chain.

The embodiment of the invention also provides a computer readable storage medium, wherein a computer program is stored in the computer readable storage medium, and when the computer program is executed by a processor, the method for predicting the invoicing of the value-added tax invoice based on the block chain is realized.

The embodiment of the invention also provides a computer program product, which comprises a computer program, and when the computer program is executed by a processor, the method for predicting the invoicing of the value-added tax invoice based on the block chain is realized.

In the embodiment of the invention, value-added tax transaction data of a client is obtained from a block chain; carrying out data cleaning processing and data characteristic derivation processing on the value-added tax transaction data of the client to obtain transaction data characteristics corresponding to the value-added tax transaction data; transmitting the transaction data characteristics corresponding to the value-added tax transaction data to a billing prediction model of the value-added tax invoice to obtain the predicted billing time and the predicted billing mechanism corresponding to the value-added tax transaction data; the billing prediction model of the value-added tax invoice is obtained by training the neural network model through billing historical data of the value-added tax invoice; the invoicing historical data of the value-added tax invoice comprises the following data: transaction data characteristics of different value-added tax transaction historical data, and historical invoicing time and historical invoicing mechanisms corresponding to the different value-added tax transaction historical data; before the predicted invoicing time, the notification information carrying the value-added tax transaction data of the user and the predicted invoicing time is sent to the predicted invoicing mechanism, so that the predicted invoicing time at which invoicing is possible to be carried out in the future of the client and the predicted invoicing mechanism can be predicted, and the notification information and the client are sent to the predicted invoicing mechanism before the predicted invoicing time, so that service personnel can know which clients are likely to go to the mechanism to handle the invoicing service in time, the problem that in the prior art, the client needs to wait for a long time because the mechanism does not prepare the invoicing transaction data of the client in advance is solved, the invoicing efficiency of the value-added tax invoice of the client is improved, the client experience is improved, the service quality of the mechanism is improved, and the service efficiency is improved.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts. In the drawings:

fig. 1 is a schematic flow chart of a method for predicting invoicing of a value-added tax invoice based on a block chain according to an embodiment of the present invention;

fig. 2 is a diagram illustrating an exemplary method for predicting invoicing of a value-added tax invoice based on a blockchain according to an embodiment of the present invention;

FIG. 3 is a diagram illustrating an exemplary embodiment of a method for predicting invoicing of value-added tax invoices based on block chains according to the present invention;

FIG. 4 is a diagram illustrating an exemplary method for predicting invoicing of value-added tax invoices based on block chains according to an embodiment of the present invention;

fig. 5 is a schematic structural diagram of an apparatus for predicting invoicing of value-added tax invoices based on a blockchain according to an embodiment of the present invention;

fig. 6 is a diagram illustrating an embodiment of a block chain-based apparatus for predicting value-added tax invoice invoicing according to the present invention;

fig. 7 is a diagram illustrating an embodiment of an apparatus for predicting value-added tax invoice invoicing based on a block chain according to the present invention;

fig. 8 is a diagram illustrating an embodiment of an apparatus for predicting value-added tax invoice invoicing based on a block chain according to the present invention;

fig. 9 is a diagram illustrating an exemplary embodiment of a device for predicting value-added tax invoice invoicing based on a block chain according to the present invention;

FIG. 10 is a block diagram illustrating a computer apparatus for forecasting invoicing of value-added tax invoices based on block chains in an embodiment of the present invention.

Detailed Description

In order to make the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the embodiments of the present invention are further described in detail below with reference to the accompanying drawings. The exemplary embodiments and descriptions of the present invention are provided to explain the present invention, but not to limit the present invention.

The term "and/or" herein merely describes an associative relationship, meaning that three relationships may exist, e.g., a and/or B, may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the term "at least one" herein means any one of a plurality or any combination of at least two of a plurality, for example, including at least one of a, B, and C, and may mean including any one or more elements selected from the group consisting of a, B, and C.

In the description of the present specification, the terms "comprising," "including," "having," "containing," and the like are used in an open-ended fashion, i.e., to mean including, but not limited to. Reference to the description of the terms "one embodiment," "a particular embodiment," "some embodiments," "for example," etc., means that a particular feature, structure, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. The sequence of steps involved in the various embodiments is provided to illustrate the practice of the present application, and the sequence of steps is not limited thereto and can be adjusted as needed.

According to the technical scheme, the data acquisition, storage, use, processing and the like meet relevant regulations of national laws and regulations.

For financial institutions, customers usually issue corresponding invoices for the customers when handling business through some business channels, and for most customers, many customers can choose to bill transactions during the period due to various factors, so the customers also need to frequently go to and fro the invoicing institutions to handle the invoicing business, but the situations of the customers are different, business personnel cannot well know the situations of the customers, and therefore how to better assist the business personnel in knowing the invoicing requirements of the customers and push the invoicing requirements to the invoicing institution business personnel is a problem to be solved urgently.

In order to solve the above problems, an embodiment of the present invention provides a block chain-based value-added tax invoice invoicing prediction method, so as to improve invoicing efficiency of a value-added tax invoice of a customer, improve customer experience, improve service quality of a website organization, and improve service efficiency, where, referring to fig. 1, the method may include:

step 101: acquiring value-added tax transaction data of a client from a block chain;

step 102: carrying out data cleaning processing and data characteristic derivation processing on the value-added tax transaction data of the client to obtain transaction data characteristics corresponding to the value-added tax transaction data;

step 103: transmitting the transaction data characteristics corresponding to the value-added tax transaction data to a billing prediction model of the value-added tax invoice to obtain the predicted billing time and the predicted billing mechanism corresponding to the value-added tax transaction data; the billing prediction model of the value-added tax invoice is obtained by training the neural network model through billing historical data of the value-added tax invoice; the invoicing historical data of the value-added tax invoice comprises the following data: transaction data characteristics of different value-added tax transaction historical data, and historical invoicing time and historical invoicing mechanisms corresponding to the different value-added tax transaction historical data;

step 104: and before the predicted invoicing time, sending the notification information carrying the value-added tax transaction data of the user and the predicted invoicing time to the predicted invoicing mechanism.

In the embodiment of the invention, value-added tax transaction data of a customer is obtained from a block chain; carrying out data cleaning processing and data characteristic derivation processing on the value-added tax transaction data of the client to obtain transaction data characteristics corresponding to the value-added tax transaction data; transmitting the transaction data characteristics corresponding to the value-added tax transaction data to a billing prediction model of the value-added tax invoice to obtain the predicted billing time and the predicted billing mechanism corresponding to the value-added tax transaction data; the billing prediction model of the value-added tax invoice is obtained by training the neural network model through billing historical data of the value-added tax invoice; the invoicing historical data of the value-added tax invoice comprises the following data: transaction data characteristics of different value-added tax transaction historical data, and historical invoicing time and historical invoicing mechanisms corresponding to the different value-added tax transaction historical data; before the predicted invoicing time, the notification information carrying the value-added tax transaction data of the user and the predicted invoicing time is sent to the predicted invoicing mechanism, so that the predicted invoicing time at which invoicing of the client is possible to be carried out in the future and the predicted invoicing mechanism can be predicted, and the notification information and the client are sent to the predicted invoicing mechanism before the predicted invoicing time, so that service personnel can know which clients are likely to go to the mechanism to handle the invoicing service in time.

At present, the value-added tax is based on the value-added amount, and a chain deduction mechanism of ring collection and layer deduction is formed, so that the value-added tax invoice can be positively charged to a seller in order to be reimbursed or deducted the tax amount to the maximum extent no matter whether the person or the enterprise. The transaction data corresponding to the value-added tax invoice transaction comprises client information (including client numbers, client types, client party tax information (common company clients), account information (information such as account numbers, card numbers and invoicing rows), consumption information of a buyer (information such as consumption areas, goods or tax-responsible labor names, consumption amounts, tax amounts to be paid, tax rates, consumption time, transaction details and the like), seller tax information, billing time of the client, billing mechanisms, billing persons, billing modes (paper tickets, electric tickets and the like) and the like.

In the specific implementation, the value-added tax transaction data of the customer is firstly obtained from the blockchain.

In one embodiment, the value-added tax transaction data is: and the invokable transaction data carries the customer information, the account information and the transaction posting institution information and is used for carrying out transaction by the user.

In one embodiment, the blockchain includes a customer node and a bank node; the customer node stores customer information and account information of the customer; the bank node stores invokable transaction data of a transaction performed in a bank corresponding to the bank node by a customer.

In one embodiment, the value-added tax transaction data of the customer is obtained from the blockchain, as shown in fig. 2, and comprises:

step 201: sending a data request instruction for requesting invokable transaction data of a client in a bank node to different bank nodes in a block chain;

step 202: receiving invokable transaction data of the client fed back by different bank nodes according to the data request instruction;

step 203: and summarizing the invokable transaction data of the client fed back by different bank nodes to obtain the value-added tax transaction data of the client.

In the above embodiment, the value added tax transaction data may be received first. For a bank invoice system, invoiceable transaction data may be received that relates to all transactions upstream involving the need to invoice all lines of the bank. The invoice system needs to receive all transactions of the above systems and contains data of price and tax separation, and the data items need to contain information of customers, account information, transaction posting institution information and the like.

In specific implementation, after the value-added tax transaction data of the customer is obtained from the blockchain, data cleaning processing and data characteristic derivation processing are carried out on the value-added tax transaction data of the customer, and transaction data characteristics corresponding to the value-added tax transaction data are obtained.

In the above embodiment, the billing data may be processed in advance by performing data cleaning processing and data feature derivation processing on the value-added tax transaction data of the customer. When the billing business is handled for the client, information of billing transaction, billing information, billing mode, billing mechanism, billing time and the like of the client is recorded through the blockchain and is used as model training data for subsequently establishing a prediction model.

When the method is implemented specifically, after data cleaning processing and data characteristic derivation processing are carried out on value-added tax transaction data of a client to obtain transaction data characteristics corresponding to the value-added tax transaction data, the transaction data characteristics corresponding to the value-added tax transaction data are sent to an invoicing prediction model of a value-added tax invoice to obtain a prediction invoicing time and a prediction invoicing mechanism corresponding to the value-added tax transaction data; the billing prediction model of the value-added tax invoice is obtained by training the neural network model through billing historical data of the value-added tax invoice; the invoicing historical data of the value-added tax invoice comprises the following data: transaction data characteristics of different value-added tax transaction historical data, and historical invoicing time and historical invoicing mechanisms corresponding to the different value-added tax transaction historical data.

In one embodiment, further comprising:

and uploading the value-added tax transaction data, the forecast billing time and the forecast billing mechanism of the user to the client node of the block chain.

In the embodiment, the value-added tax transaction data, the forecast billing time and the forecast billing mechanism of the user can be uploaded to the client node of the block chain, so that the data can be recorded in real time.

In one embodiment, further comprising:

the invoicing prediction model of the value-added tax invoice is trained and verified as follows:

training the neural network model by taking the invoicing historical data of the value-added tax invoice as a training set to obtain a trained invoicing prediction model of the value-added tax invoice;

taking the invoicing historical data of the value-added tax invoice as a verification set, verifying the trained invoicing prediction model of the value-added tax invoice, and obtaining the verified invoicing prediction model of the value-added tax invoice after the verification is passed;

the method comprises the following steps of sending the value-added tax transaction data of a user to a billing prediction model of a value-added tax invoice to obtain a prediction billing time and a prediction billing mechanism corresponding to the value-added tax transaction data, wherein the method comprises the following steps:

and sending the value-added tax transaction data of the user to the verified value-added tax invoice billing prediction model to obtain the predicted billing time and the predicted billing mechanism corresponding to the value-added tax transaction data.

In the embodiment, the billing historical data of the value-added tax invoice can be used as a training set, the neural network model is trained to obtain a trained billing prediction model of the value-added tax invoice, the billing history data of the value-added tax invoice is further used as a verification set, the trained billing prediction model of the value-added tax invoice is verified, and after the verification is passed, the validated billing prediction model of the value-added tax invoice is obtained, so that the training and verification of the billing prediction model of the value-added tax invoice are realized, the information of future billing time, billing mode, billing mechanism, billing transaction type and the like of all clients can be predicted in the subsequent steps, and therefore when the condition of the predicted billing time is met, the block chain is linked to each billing mechanism, and each billing mechanism is assisted in knowing the billing condition of the current day.

In an embodiment, the invoice history data of the value-added tax invoice further includes: transaction data characteristics of different value-added tax transaction historical data, and historical invoicing transaction types and historical invoicing modes corresponding to the different value-added tax transaction historical data;

the method, as shown in fig. 3, further includes:

step 301: and transmitting the transaction data characteristics corresponding to the value-added tax transaction data to the invoicing prediction model of the value-added tax invoice to obtain the predicted invoicing transaction type and the predicted invoicing mode corresponding to the value-added tax transaction data.

In one embodiment, before the predicted invoicing time, sending notification information carrying value-added tax transaction data of the user and the predicted invoicing time to the predicted invoicing mechanism, includes:

and before the predicted invoicing time, sending the notification information carrying the value-added tax transaction data of the user and the predicted invoicing time, the predicted invoicing transaction type and the predicted invoicing mode to the predicted invoicing mechanism together.

In the embodiment, the invoicing prediction model of the value-added tax invoice can be further used for predicting the predicted invoicing transaction type and the predicted invoicing mode, so that the invoicing mechanism can reasonably arrange the work on the same day better, the customer experience is improved, the service quality of a website mechanism is improved, and the service efficiency is improved.

In the embodiment, by establishing an invoicing prediction model of the value-added tax invoice, data cleaning, data characteristic derivation and other processing are carried out through information such as a client type, an invoicing mode, a historical invoicing mechanism of the client, invoicing transactions, invoicing time and the like, marking is carried out according to characteristics such as the type, the interval and the like, the processed data are trained through a decision algorithm, information such as the possible invoicing transaction type, the invoicing mode, the invoicing time, the invoicing mechanism and the like of the client in the future is predicted, results are recorded on a block chain, the data are synchronously sent to a service staff of the invoicing mechanism on the day before the invoicing date or the day of business, and the service staff can timely know the invoicing condition of the client on the day according to the predicted information, timely make work arrangement, or communicate with the client in advance, and whether the client needs to carry out the on-site invoicing or not, so as to better serve the client.

In another embodiment, the method may further include: through a decision algorithm, the future possible invoicing time and the invoicing institution information of all the customers are predicted.

Furthermore, the predicted result is recorded, and meanwhile, the result is synchronously sent to the billing mechanism in advance on the day before or the day when the billing time is predicted, so that service personnel can timely know which clients may go to the mechanism to handle billing services, or can contact whether the clients need to bill, and the clients do not need to go to and from the billing mechanism.

When the method is implemented specifically, after the transaction data characteristics corresponding to the value-added tax transaction data are sent to the invoicing prediction model of the value-added tax invoice, the prediction invoicing time and the prediction invoicing mechanism corresponding to the value-added tax transaction data are obtained, and before the prediction invoicing time, the notification information carrying the value-added tax transaction data of the user and the prediction invoicing time is sent to the prediction invoicing mechanism.

In the embodiment of the invention, value-added tax transaction data, invoice data, billing information and the like can be recorded on a block chain, through the historical data, the possible future billing time and billing mechanism information of all clients can be predicted through a neural network algorithm, the predicted result is recorded, meanwhile, the predicted billing time is synchronously sent to a billing mechanism in advance on the day before or on the day before the predicted billing time, and business personnel can timely know which clients are likely to go to the mechanism to handle billing services or can contact whether the clients need to bill, the clients do not need to go to and from the billing network, the client experience is improved, the service quality of the mechanism is improved, and the service efficiency is improved.

In one embodiment, the block chain includes: a transaction base data storage node; the transaction basic data storage node stores interest rate information, quotation information and exchange rate information;

the method further comprises the following steps:

acquiring interest rate information, quotation information and exchange rate information from a transaction basic data storage node in a block chain;

before the predicted invoicing time, sending notification information carrying value-added tax transaction data of a user and the predicted invoicing time to the predicted invoicing mechanism, wherein the notification information comprises:

before the predicted invoicing time, the notification information carrying the value-added tax transaction data of the user and the predicted invoicing time, the interest rate information, the quotation information and the exchange rate information are sent to the predicted invoicing mechanism together.

In the above embodiment, the basic data of interest rate, bid price, exchange rate, etc. of the core may be received. Since various transactions, financing and the like involve information such as interest rate, quotation, exchange rate and the like of the basic data of the core, basic data such as daily interest rate, quotation, exchange rate and the like of the core are recorded through the block chain.

In one embodiment, the transaction basic data storage node in the block chain is used for updating the stored interest rate information, the stored quotation price information and the stored exchange rate information every day.

A specific embodiment is given below to illustrate a specific application of the method of the present invention, and in this embodiment, as shown in fig. 4, the following may be included:

1. and receiving the value-added tax transaction data. For a bank invoice system, invoiceable transaction data relating to all transactions upstream involving invoicing is received throughout the bank. The invoice system needs to receive all transactions of the above systems and contains data of price and tax separation, and the data items need to contain information of customers, account information, transaction posting institution information and the like.

2. And receiving basic data of interest rate, quotation, exchange rate and the like of the core. Since various transactions, financing and the like involve information such as interest rate, quotation, exchange rate and the like of the basic data of the core, basic data such as daily interest rate, quotation, exchange rate and the like of the core are recorded through the block chain.

3. Processing billing data. When the billing business is handled for the client, information of billing transaction, billing information, billing mode, billing mechanism, billing time and the like of the client is recorded through the blockchain and is used as model training data for subsequently establishing a prediction model.

4. And establishing an invoicing prediction model. Through the data recorded in the steps, a client billing prediction model is established, data cleaning, data characteristic derivation and other processing are carried out through information such as client types, billing modes, historical billing mechanisms of clients, billing transactions, billing time and the like, marking is carried out according to the characteristics such as types, intervals and the like, the processed data are trained through a decision algorithm, information such as the possible future billing transaction types, billing modes, billing time, billing mechanisms and the like of the clients is predicted, the result is recorded on a block chain, the result is synchronously sent to business personnel of the billing mechanisms on the day before the billing date or the day of business, and the business personnel can timely know the billing conditions of the clients on the day according to the predicted information, timely make work arrangement, or communicate with the clients in advance, and whether the clients need to bill on-site, so as to better serve the clients.

According to the specific embodiment, data such as billing information of the client can be recorded through the block chain, the historical data is processed to be used as training data of a client billing prediction model, information such as future billing time, billing mode, billing mechanism and billing transaction type of all the clients can be predicted, the results are synchronized and recorded on the block chain, when the condition of predicting the billing time is met, the prediction results recorded on the block chain are synchronized to each billing mechanism, each billing mechanism is assisted to know the billing condition of the current day, or the clients can be contacted to whether billing needs to be carried out, the clients do not need to go to and go to the billing mechanism, the current day work is reasonably arranged, client experience is improved, the service quality of the website mechanism is improved, and the service efficiency is improved.

Of course, it is understood that other variations of the above detailed flow can be made, and all such variations are intended to fall within the scope of the present invention.

In the embodiment of the invention, value-added tax transaction data of a customer is obtained from a block chain; carrying out data cleaning processing and data characteristic derivation processing on the value-added tax transaction data of the client to obtain transaction data characteristics corresponding to the value-added tax transaction data; transmitting the transaction data characteristics corresponding to the value-added tax transaction data to a billing prediction model of the value-added tax invoice to obtain the predicted billing time and the predicted billing mechanism corresponding to the value-added tax transaction data; the billing prediction model of the value-added tax invoice is obtained by training the neural network model through billing historical data of the value-added tax invoice; the invoicing historical data of the value-added tax invoice comprises the following data: transaction data characteristics of different value-added tax transaction historical data, and historical invoicing time and historical invoicing mechanisms corresponding to the different value-added tax transaction historical data; before the predicted invoicing time, the notification information carrying the value-added tax transaction data of the user and the predicted invoicing time is sent to the predicted invoicing mechanism, so that the predicted invoicing time at which invoices are likely to be made in the future of the client and the predicted invoicing mechanism can be predicted, and the notification information of the client are sent to the predicted invoicing mechanism before the predicted invoicing time, so that service personnel can know which clients are likely to go to the mechanism to handle the invoicing service in time, the problem that the client needs to wait for a long time because the mechanism does not prepare the invoicing transaction data of the client in advance in the prior art is solved, the invoicing efficiency of the value-added tax invoice of the client is improved, the client experience is improved, the service quality of a website mechanism is favorably improved, and the service efficiency is improved.

The embodiment of the invention also provides a device for predicting the invoicing of the value-added tax invoice based on the block chain, which is expressed in the following embodiment. The principle of the device for solving the problems is similar to the block chain-based value-added tax invoice invoicing prediction method, so the implementation of the device can refer to the implementation of the block chain-based value-added tax invoice invoicing prediction method, and repeated parts are not repeated.

The embodiment of the present invention further provides a block chain-based value-added tax invoice billing prediction apparatus, which is used to improve billing efficiency of a value-added tax invoice of a customer, improve customer experience, improve service quality of a website organization, and improve service efficiency, as shown in fig. 5, the apparatus includes:

the value-added tax transaction data acquisition module 501 is configured to acquire value-added tax transaction data of a customer from a blockchain;

the data cleaning processing and data feature derivation processing module 502 is used for performing data cleaning processing and data feature derivation processing on the value-added tax transaction data of the client to obtain transaction data features corresponding to the value-added tax transaction data;

the forecast billing time and forecast billing mechanism forecast module 503 is used for sending the transaction data characteristics corresponding to the value-added tax transaction data to the billing forecast model of the value-added tax invoice to obtain the forecast billing time and forecast billing mechanism corresponding to the value-added tax transaction data; the billing prediction model of the value-added tax invoice is obtained by training the neural network model through billing historical data of the value-added tax invoice; the invoicing historical data of the value-added tax invoice comprises the following data: transaction data characteristics of different value-added tax transaction historical data, and historical invoicing time and historical invoicing mechanisms corresponding to the different value-added tax transaction historical data;

and the notification information sending module 504 is configured to send the notification information carrying the value-added tax transaction data of the user and the predicted invoicing time to the predicted invoicing mechanism before the predicted invoicing time.

In one embodiment, the value-added tax transaction data is: and the invokable transaction data carries the customer information, the account information and the information of the transaction posting institution for the user to carry out transaction.

In one embodiment, the blockchain includes a customer node and a bank node; the customer node stores customer information and account information of a customer; the bank node stores invoicing transaction data of a customer for conducting transaction in a bank corresponding to the bank node.

In one embodiment, the value-added tax transaction data acquisition module is specifically configured to:

sending a data request instruction for requesting invokable transaction data of a client in a bank node to different bank nodes in a block chain;

receiving invokable transaction data of the customer fed back by different bank nodes according to the data request instruction;

and summarizing the invokable transaction data of the client fed back by different bank nodes to obtain the value-added tax transaction data of the client.

In one embodiment, as shown in fig. 6, further includes:

a data uploading module 601, configured to:

In one embodiment, the block chain comprises: a transaction base data storage node; the transaction basic data storage node stores interest rate information, quotation information and exchange rate information;

the apparatus, as shown in fig. 7, further includes:

an interest rate information, quotation price information and exchange rate information obtaining module 701 is configured to:

the notification information sending module is specifically configured to:

and before the predicted invoicing time, sending the notification information carrying the value-added tax transaction data of the user and the predicted invoicing time, as well as interest rate information, quotation information and exchange rate information to the predicted invoicing mechanism.

In one embodiment, as shown in fig. 8, further includes:

a model training verification module 801 configured to:

training and verifying the invoicing prediction model of the value-added tax invoice as follows:

taking the invoicing historical data of the value-added tax invoice as a training set, and training the neural network model to obtain a trained invoicing prediction model of the value-added tax invoice;

the forecast billing time and forecast billing mechanism forecast module is specifically used for:

In one embodiment, the invoicing history data of the value-added tax invoice further comprises: transaction data characteristics of different value-added tax transaction historical data, and historical invoicing transaction types and historical invoicing modes corresponding to the different value-added tax transaction historical data;

the apparatus, as shown in fig. 9, further includes:

a predicted invoicing transaction type and predicted invoicing mode module 901 configured to:

and transmitting the transaction data characteristics corresponding to the value-added tax transaction data to the invoicing prediction model of the value-added tax invoice to obtain the prediction invoicing transaction type and the prediction invoicing mode corresponding to the value-added tax transaction data.

In one embodiment, the notification information sending module is specifically configured to:

and before the predicted invoicing time, sending the value-added tax transaction data carrying the user, the notification information of the predicted invoicing time, the predicted invoicing transaction type and the predicted invoicing mode to the predicted invoicing mechanism.

The embodiment of the present invention provides an embodiment of a computer device for implementing all or part of contents in the method for predicting invoicing of a value-added tax invoice based on a block chain, where the computer device specifically includes the following contents:

a processor (processor), a memory (memory), a communication Interface (Communications Interface), and a bus; the processor, the memory and the communication interface complete mutual communication through the bus; the communication interface is used for realizing information transmission between related devices; the computer device may be a desktop computer, a tablet computer, a mobile terminal, and the like, but the embodiment is not limited thereto. In this embodiment, the computer device may be implemented with reference to the embodiment of the method for implementing the method for predicting invoicing of a value-added tax invoice based on a blockchain and the embodiment of the device for predicting invoicing of a value-added tax invoice based on a blockchain in the embodiments, and the contents of the method and the device are incorporated herein, and the repeated parts are not described again.

Fig. 10 is a schematic block diagram of a system configuration of a computer apparatus 1000 according to an embodiment of the present application. As shown in fig. 10, the computer apparatus 1000 may include a central processing unit 1001 and a memory 1002; the memory 1002 is coupled to the cpu 1001. Notably, this fig. 10 is exemplary; other types of structures may also be used in addition to or in place of the structure to implement telecommunications or other functions.

In one embodiment, the block chain based value added tax invoice invoicing prediction function may be integrated into the central processor 1001. The cpu 1001 may be configured to perform the following control:

acquiring value-added tax transaction data of a client from a block chain;

and before the predicted invoicing time, sending the notification information carrying the value-added tax transaction data of the user and the predicted invoicing time to the predicted invoicing mechanism.

In another embodiment, the billing prediction apparatus for the block chain-based value-added tax invoice may be configured separately from the central processing unit 1001, for example, the billing prediction apparatus for the block chain-based value-added tax invoice may be configured as a chip connected to the central processing unit 1001, and the billing prediction function for the block chain-based value-added tax invoice may be implemented by the control of the central processing unit.

As shown in fig. 10, the computer apparatus 1000 may further include: a communication module 1003, an input unit 1004, an audio processor 1005, a display 1006, a power supply 1007. It is noted that the computer device 1000 does not necessarily include all of the components shown in FIG. 10; furthermore, the computer device 1000 may also comprise components not shown in fig. 10, which can be referred to in the prior art.

As shown in fig. 10, the cpu 1001, which is sometimes referred to as a controller or operation control, may include a microprocessor or other processor device and/or logic device, and the cpu 1001 receives input and controls the operation of the components of the computer device 1000.

The memory 1002 may be, for example, one or more of a buffer, a flash memory, a hard drive, a removable media, a volatile memory, a non-volatile memory, or other suitable device. The information relating to the failure may be stored, and a program for executing the information may be stored. And the cpu 1001 can execute the program stored in the memory 1002 to realize information storage or processing, or the like.

The input unit 1004 provides input to the cpu 1001. The input unit 1004 is, for example, a key or a touch input device. The power supply 1007 is used to supply power to the computer apparatus 1000. The display 1006 is used for displaying display objects such as images and characters. The display may be, for example, but is not limited to, an LCD display.

The memory 1002 may be a solid state memory such as Read Only Memory (ROM), random Access Memory (RAM), a SIM card, or the like. There may also be a memory that holds information even when power is off, can be selectively erased, and is provided with more data, an example of which is sometimes called an EPROM or the like. The memory 1002 may also be some other type of device. Memory 1002 includes buffer memory 1021 (sometimes referred to as a buffer). The memory 1002 may include an application/function storage part 1022, the application/function storage part 1022 being used for storing application programs and function programs or a flow for executing the operation of the computer device 1000 by the central processing unit 1001.

The memory 1002 may also include a data store 1023, the data store 1023 being used to store data such as contacts, digital data, pictures, sounds and/or any other data used by the computer device. Driver storage 1024 of memory 1002 may include various drivers for the computer device for communication functions and/or for performing other functions of the computer device (e.g., messaging applications, directory applications, etc.).

The communication module 1003 is a transmitter/receiver 1003 that transmits and receives signals via an antenna 1008. The communication module (transmitter/receiver) 1003 is coupled to the cpu 1001 to provide an input signal and receive an output signal, which may be the same as in the case of a conventional mobile communication terminal.

Based on different communication technologies, a plurality of communication modules 1003, such as a cellular network module, a bluetooth module, and/or a wireless local area network module, may be provided in the same computer device. The communication module (transmitter/receiver) 1003 is also coupled to a speaker 1009 and a microphone 1010 via an audio processor 1005 to provide audio output via the speaker 1009 and receive audio input from the microphone 1010 to implement general telecommunications functions. The audio processor 1005 may include any suitable buffers, decoders, amplifiers and so forth. In addition, the audio processor 1005 is also coupled to the central processor 1001, so that sound can be recorded locally through the microphone 1010, and so that locally stored sound can be played through the speaker 1009.

As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, 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 specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are only exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.

Claims

1. A block chain-based method for forecasting invoicing of a value-added tax invoice is characterized by comprising the following steps:

acquiring value-added tax transaction data of a customer from a block chain;

and before the forecast billing time, sending the notice information carrying the value-added tax transaction data of the user and the forecast billing time to the forecast billing organization.

2. The method of claim 1, wherein the value-added tax transaction data is: and the invokable transaction data carries the customer information, the account information and the transaction posting institution information and is used for carrying out transaction by the user.

3. The method of claim 2, wherein the blockchain includes a customer node and a bank node; the customer node stores customer information and account information of a customer; the bank node stores invoicing transaction data of a customer for conducting transaction in a bank corresponding to the bank node.

4. The method of claim 3, wherein obtaining value-added tax transaction data for the customer from the blockchain comprises:

receiving invokable transaction data of the client fed back by different bank nodes according to the data request instruction;

5. The method of claim 1, further comprising:

and uploading the value-added tax transaction data, the predicted billing time and the predicted billing mechanism of the user to the client node of the block chain.

6. The method of claim 1, wherein the blockchain comprises: a transaction base data storage node; the transaction basic data storage node stores interest rate information, quotation information and exchange rate information;

the method further comprises the following steps:

acquiring interest rate information, quotation information and exchange rate information from transaction basic data storage nodes in a block chain;

before the forecast billing time, sending notification information carrying value-added tax transaction data of a user and the forecast billing time to the forecast billing organization, wherein the notification information comprises:

7. The method of claim 6, wherein the blockchain trading base data stores nodes are configured to update stored interest rate information, bid price information, and exchange rate information on a daily basis.

8. The method of claim 1, further comprising:

taking the billing historical data of the value-added tax invoice as a training set, and training the neural network model to obtain a trained billing prediction model of the value-added tax invoice;

9. The method of claim 1, wherein the billing history data of the value-added tax invoice further comprises: transaction data characteristics of different value-added tax transaction historical data, and historical invoicing transaction types and historical invoicing modes corresponding to the different value-added tax transaction historical data;

the method further comprises the following steps:

10. The method of claim 9, wherein sending a notification message carrying the value-added tax transaction data of the user and the predicted invoicing time to the predicted invoicing authority prior to the predicted invoicing time comprises:

11. The utility model provides a prediction unit that invoices of value-added tax invoice based on block chain which characterized in that includes:

the value-added tax transaction data acquisition module is used for acquiring the value-added tax transaction data of the customer from the block chain;

the data cleaning processing and data characteristic derivation processing module is used for carrying out data cleaning processing and data characteristic derivation processing on the value-added tax transaction data of the client to obtain transaction data characteristics corresponding to the value-added tax transaction data;

the forecasting module of the forecasting billing mechanism is used for sending the transaction data characteristics corresponding to the value-added tax transaction data to a billing forecasting model of the value-added tax invoice to obtain the forecasting billing time and the forecasting billing mechanism corresponding to the value-added tax transaction data; the billing prediction model of the value-added tax invoice is obtained by training the neural network model through billing historical data of the value-added tax invoice; the invoicing historical data of the value-added tax invoice comprises the following data: transaction data characteristics of different value-added tax transaction historical data, and historical invoicing time and historical invoicing mechanisms corresponding to the different value-added tax transaction historical data;

12. The apparatus of claim 11, wherein the value-added tax transaction data is: and the invokable transaction data carries the customer information, the account information and the information of the transaction posting institution for the user to carry out transaction.

13. The apparatus of claim 12, wherein the blockchain includes a customer node and a bank node; the client node stores client information and account information of a client; the bank node stores invoicing transaction data of a customer for conducting transaction in a bank corresponding to the bank node.

14. The apparatus of claim 13, wherein the value-added tax transaction data acquisition module is specifically configured to:

15. The apparatus of claim 11, further comprising:

a data upload module to:

16. The apparatus of claim 11, wherein the block chain comprises: a transaction base data storage node; the transaction basic data storage node stores interest rate information, quotation information and exchange rate information;

the device, still include:

the interest rate information, quotation price information and exchange rate information acquisition module is used for:

the notification information sending module is specifically configured to:

17. The apparatus of claim 16, wherein the block chain comprises a trade base data storage node configured to update the stored interest rate information, bid price information, and exchange rate information on a daily basis.

18. The apparatus of claim 11, further comprising:

a model training verification module to:

the forecasting module for forecasting the billing time and forecasting the billing mechanism is specifically used for:

19. The apparatus of claim 11, wherein the billing history data of the value-added tax invoice further comprises: transaction data characteristics of different value-added tax transaction historical data, and historical invoicing transaction types and historical invoicing modes corresponding to the different value-added tax transaction historical data;

the device, still include:

the prediction billing transaction type and prediction billing mode module is used for:

and transmitting the transaction data characteristics corresponding to the value-added tax transaction data to the invoicing prediction model of the value-added tax invoice to obtain the predicted invoicing transaction type and the predicted invoicing mode corresponding to the value-added tax transaction data.

20. The apparatus of claim 19, wherein the notification message sending module is specifically configured to:

21. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method of any one of claims 1 to 10 when executing the computer program.

22. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program which, when executed by a processor, implements the method of any one of claims 1 to 10.

23. A computer program product, characterized in that the computer program product comprises a computer program which, when being executed by a processor, carries out the method of any one of claims 1 to 10.