Intelligent integrated finance and tax invoice management method and device

Abstract

The invention belongs to the field of financial information, and relates to an intelligent integrated finance and tax invoice management method and device. The intelligent integrated finance and tax invoice management comprises the following steps: obtaining tax invoice data; performing reimbursement processing on the tax invoice data to obtain effective invoice data; performing financial accounting processing on the effective invoice data to generate an invoice accounting voucher; carrying out deduction authentication processing on the invoice accounting voucher based on a preset decision model to obtain a deduction authentication result; according to the deduction authentication result, deduction grading processing is carried out to obtain to-be-deducted invoice data; and inputting the to-be-deducted invoice data into a pre-trained decision generation model to generate an optimal deduction strategy, and performing invoice deduction processing on the to-be-deducted invoice data according to the optimal deduction strategy. According to the invention, automatic invoice deduction processing can be effectively carried out according to different invoice data, so that the efficiency of invoice deduction processing is improved.

Description

Technical Field

[0001] The present application relates to the field of financial information, and in particular to an intelligent integrated financial and tax invoice management method and device. Background Art

[0002] In traditional corporate financial management and tax processing, invoice deductions, a key component, have long relied primarily on a combination of manual operations and system support. Specifically, the traditional invoice deduction process typically involves the following steps: First, finance personnel manually import paper or electronic invoices into the financial system; then, they make reimbursements based on the invoice content and verify the consistency of the invoice information with the business transaction; finally, they perform invoice deductions in accordance with tax laws, completing the preparations for tax filing. However, this traditional approach has significant limitations.

[0003] On the one hand, the entire process is highly manual, time-consuming and labor-intensive, and prone to data entry errors or omissions due to human negligence, which in turn affects the accuracy and compliance of invoice deductions. Furthermore, as business volume grows, the need to process large numbers of invoices places an increasing burden on human resources, making it impossible to implement an effective automated deduction process, resulting in a significant waste of valuable human resources.

[0004] On the other hand, while some financial systems with automatic invoice deduction capabilities have emerged, these systems struggle to handle complex and ever-changing invoice scenarios. They often employ fixed processing logic and rules, making it difficult to flexibly adjust to the diversity of invoices (such as invoice type, amount structure, and business scenario). This results in inefficient system processing for special or non-standard invoices, sometimes requiring manual intervention, further reducing the efficiency and quality of overall invoice deduction processing. Summary of the Invention

[0005] The purpose of the embodiments of the present application is to propose an intelligent integrated financial and tax invoice management method and device to solve the problem of inability to automatically perform invoice deduction processing, resulting in low efficiency of invoice deduction processing.

[0006] In order to solve the above technical problems, the present application provides an intelligent integrated fiscal and tax invoice management method, which adopts the following technical solutions:

[0007] Obtain tax invoice data;

[0008] Performing reimbursement processing on the tax invoice data to obtain valid invoice data;

[0009] Perform financial accounting processing on the valid invoice data to generate invoice accounting vouchers;

[0010] Performing deduction authentication processing on the invoice accounting voucher based on a preset decision model to obtain a deduction authentication result;

[0011] Performing deduction grading processing based on the deduction authentication result to obtain invoice data to be deducted;

[0012] The invoice data to be deducted is input into a pre-trained decision generation model to generate an optimal deduction strategy, and the invoice deduction processing is performed on the invoice data to be deducted according to the optimal deduction strategy.

[0013] Furthermore, the step of obtaining tax invoice data specifically includes:

[0014] Download the initial invoice data from the preset invoice data interface;

[0015] The initial invoice data is stored in a local invoice pool, and the stored local invoice pool is used as the tax invoice data.

[0016] Furthermore, the step of performing reimbursement processing on the tax invoice data to obtain valid invoice data specifically includes:

[0017] Reviewing the tax invoice data to obtain reviewed invoice data;

[0018] Extracting payment information from the reviewed invoice data, and performing a payment operation based on the payment information to obtain paid invoice data;

[0019] The paid invoice data is locked to obtain the valid invoice data.

[0020] Furthermore, the step of performing financial accounting processing on the valid invoice data to generate an invoice accounting voucher specifically includes:

[0021] extracting business category and payment information from the valid invoice data;

[0022] A preset accounting mapping table is obtained, and a matching search is performed in the preset accounting mapping table according to the business category and the payment information to obtain the invoice accounting voucher.

[0023] Furthermore, the step of performing deduction authentication processing on the invoice accounting voucher based on the preset decision model to obtain the deduction authentication result specifically includes:

[0024] Obtaining a model extraction identifier, and extracting the preset decision model from a model database according to the model extraction identifier;

[0025] The invoice accounting voucher is input into the preset decision model to perform deduction priority judgment to obtain the deduction certification result.

[0026] Furthermore, the step of performing deduction grading processing according to the deduction authentication result to obtain the invoice data to be deducted specifically includes:

[0027] Determining whether the deduction authentication result is authenticated;

[0028] If the deduction certification result is certified, multi-dimensional feature engineering processing is performed on the certified valid invoice data to obtain multi-dimensional features of the invoice;

[0029] Performing a deduction priority evaluation based on the multi-dimensional features of the invoice to obtain a deduction priority result;

[0030] The valid invoice data is sorted according to the deduction priority score corresponding to the deduction priority result to obtain the invoice data to be deducted.

[0031] Furthermore, after the step of inputting the invoice data to be deducted into the pre-trained decision generation model to generate an optimal deduction strategy, and performing invoice deduction processing on the invoice data to be deducted according to the optimal deduction strategy, the method further includes:

[0032] Obtain the operation log, feature authentication record, and cross-chain transaction hash corresponding to the invoice deduction processing;

[0033] Identifying sensitive fields of the valid invoice data after the invoice deduction processing, and performing homomorphic encryption processing on the identified sensitive fields to obtain encrypted invoice data;

[0034] Extract the operational process links corresponding to invoice deduction processing based on the operation log;

[0035] The feature authentication record, the cross-chain transaction hash, the encrypted invoice data, and the operation process link are sorted to generate a deduction audit data package, and the deduction audit data package is saved to the data table to be audited.

[0036] In order to solve the above technical problems, the embodiment of the present application also provides an intelligent integrated fiscal and tax invoice management device, which adopts the following technical solutions:

[0037] Data acquisition module, used to obtain tax invoice data;

[0038] A data processing module, configured to process the tax invoice data for reimbursement to obtain valid invoice data;

[0039] A voucher generation module is used to perform financial accounting processing on the valid invoice data and generate an invoice accounting voucher;

[0040] A deduction authentication module is used to perform deduction authentication processing on the invoice accounting voucher based on a preset decision model to obtain a deduction authentication result;

[0041] A deduction grading module is used to perform deduction grading processing based on the deduction authentication result to obtain invoice data to be deducted;

[0042] The deduction execution module is used to input the invoice data to be deducted into the pre-trained decision generation model, generate an optimal deduction strategy, and perform invoice deduction processing on the invoice data to be deducted according to the optimal deduction strategy.

[0043] In order to solve the above technical problems, the embodiment of the present application further provides a computer device, which adopts the following technical solution:

[0044] A computer device includes a memory and a processor, wherein the memory stores computer-readable instructions, and when the processor executes the computer-readable instructions, the steps of the intelligent integrated fiscal and tax invoice management method as described in any one of the above items are implemented.

[0045] In order to solve the above technical problems, the embodiment of the present application further provides a computer-readable storage medium, which adopts the following technical solution:

[0046] A computer-readable storage medium having computer-readable instructions stored thereon, wherein the computer-readable instructions, when executed by a processor, implement the steps of the intelligent integrated fiscal and tax invoice management method as described in any one of the above items.

[0047] Compared with the prior art, the embodiments of the present application have the following beneficial effects:

[0048] This embodiment obtains tax invoice data; performs reimbursement processing on the tax invoice data to obtain valid invoice data; performs financial accounting processing on the valid invoice data to generate invoice accounting vouchers; performs deduction authentication processing on the invoice accounting vouchers based on a preset decision model to obtain a deduction authentication result; performs deduction grading processing based on the deduction authentication result to obtain invoice data to be deducted; inputs the invoice data to be deducted into a pre-trained decision generation model to generate an optimal deduction strategy, and performs invoice deduction processing on the invoice data to be deducted based on the optimal deduction strategy. This effectively performs automatic invoice deduction processing based on different invoice data, thereby improving the efficiency of invoice deduction processing. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the solutions in this application, a brief introduction will be given below to the drawings required for use in the description of the embodiments of this application. Obviously, the drawings described below are some embodiments of this application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0050] Figure 1 A flowchart of an embodiment of the intelligent integrated fiscal and tax invoice management method according to the present application;

[0051] Figure 2 yes Figure 1 A flowchart of a specific implementation of step S10;

[0052] Figure 3 yes Figure 1 A flowchart of a specific implementation of step S20;

[0053] Figure 4 yes Figure 1 A flowchart of a specific implementation of step S30;

[0054] Figure 5 yes Figure 1 A flowchart of a specific implementation of step S40;

[0055] Figure 6 yes Figure 1 A flowchart of a specific implementation of step S50;

[0056] Figure 7 This is a structural diagram of an embodiment of an intelligent integrated finance and tax invoice management device according to the present application;

[0057] Figure 8 It is a structural diagram of an embodiment of a computer device according to the present application. DETAILED DESCRIPTION

[0058] Unless otherwise defined, all technical and scientific terms used herein have the same meanings as commonly understood by those skilled in the art to which this application belongs. The terms used in the specification of the application are for the purpose of describing specific embodiments only and are not intended to limit this application. The terms "including" and "having" and any variations thereof in the specification and claims of this application and the above-mentioned drawings are intended to cover non-exclusive inclusions. The terms "first", "second", etc. in the specification and claims of this application or the above-mentioned drawings are used to distinguish different objects, not to describe a specific order.

[0059] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute an independent or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0060] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings.

[0061] Continue to refer Figure 1 , shows a flow chart of an embodiment of a method for speaker production testing according to the present application. The intelligent integrated fiscal and tax invoice management method comprises the following steps:

[0062] Step S10, obtaining tax invoice data;

[0063] In this embodiment, tax invoice data refers to the invoice data collected by the tax system interface. The tax invoice data includes the invoice code, invoice number, invoice date, seller name, seller tax number, buyer tax number, product details, amount, tax amount, etc. The tax invoice data is uploaded by the user to the tax system website and then crawled by the invoice processing system of this embodiment.

[0064] Step S20, performing reimbursement processing on the tax invoice data to obtain valid invoice data;

[0065] In this embodiment, standard processing includes invoice review, payment processing, and invoice locking. Invoice review involves submitting the tax invoice data for process review based on the business category to verify the invoice's authenticity. Payment processing involves performing invoice payment and reimbursement based on the payment information contained in the approved tax invoice data. Invoice locking involves locking the invoice data after payment is completed to prevent invoices from being reversed after payment and reimbursement.

[0066] Step S30, performing financial accounting processing on the valid invoice data to generate an invoice accounting voucher;

[0067] In this embodiment, financial accounting processing refers to invoice accounting for valid invoice data to generate invoice accounting vouchers. Invoice accounting vouchers are written certificates compiled based on the approved valid invoice data in accordance with accounting standards and tax law requirements to record economic transactions and clarify economic responsibilities. Invoice accounting vouchers include voucher number, voucher date, summary, accounting subject, amount, attachments, etc. By generating invoice accounting vouchers, effective financial accounting of valid invoice data is achieved, which facilitates subsequent inspection and verification.

[0068] Step S40: performing a deduction authentication process on the invoice accounting voucher based on a preset decision model to obtain a deduction authentication result;

[0069] In this embodiment, the preset decision model uses the XGBoost model, an ensemble learning algorithm based on the Gradient Boosting Decision Tree (GBDT). By training the XGBoost model with a sample invoice dataset, a deduction verification result is obtained that effectively verifies whether an invoice is deductible and provides a corresponding deduction priority score.

[0070] Step S50, performing deduction classification processing according to the deduction authentication result to obtain invoice data to be deducted;

[0071] In this embodiment, deduction grading processing is performed based on the characteristics of multiple dimensions of the valid invoice data corresponding to the deduction authentication result, as well as the deduction priority in the deduction authentication result, thereby generating graded and labeled invoice data to be deducted, wherein the invoice data to be deducted includes a deduction priority score and a risk level label, etc.

[0072] Step S60: input the invoice data to be deducted into a pre-trained decision generation model to generate an optimal deduction strategy, and perform invoice deduction processing on the invoice data to be deducted according to the optimal deduction strategy.

[0073] In this embodiment, the decision generation model is used to generate a corresponding deduction strategy based on the input deduction invoice data. In this embodiment, the decision generation model can adopt a gradient boosting model, such as XGBoost or LightGBM, wherein LightGBM (Light Gradient Boosting Machine) is an efficient machine learning algorithm based on the gradient boosting decision tree (GBDT), which effectively realizes the generation of the corresponding optimal deduction strategy based on the deduction invoice data by adopting technical methods such as histogram algorithm, leaf growth strategy, unilateral gradient sampling, and mutually exclusive feature bundling. The deduction strategy may include full deduction, partial deduction, deferred deduction, etc. When the optimal deduction strategy is full deduction, the amount of the invoice data to be deducted is fully deducted. When the optimal deduction strategy is partial deduction, the amount of the invoice data to be deducted is partially deducted. When the optimal deduction strategy is deferred deduction, the amount of the invoice data to be deducted is deferred.

[0074] This embodiment obtains tax invoice data; performs reimbursement processing on the tax invoice data to obtain valid invoice data; performs financial accounting processing on the valid invoice data to generate invoice accounting vouchers; performs deduction authentication processing on the invoice accounting vouchers based on a preset decision model to obtain a deduction authentication result; performs deduction grading processing based on the deduction authentication result to obtain invoice data to be deducted; inputs the invoice data to be deducted into a pre-trained decision generation model to generate an optimal deduction strategy, and performs invoice deduction processing on the invoice data to be deducted based on the optimal deduction strategy. This effectively performs automatic invoice deduction processing based on different invoice data, thereby improving the efficiency of invoice deduction processing.

[0075] Continue to refer Figure 2 In some optional implementations of this embodiment, step S10 includes the following steps:

[0076] Step S101, downloading initial invoice data from a preset invoice data interface;

[0077] In this embodiment, the preset invoice data interface refers to an interface corresponding to the tax system, which can be a website interface of the tax bureau. The website interface of the tax bureau is accessed through a preset digital certificate or access token, thereby effectively downloading the initial invoice data from the tax system.

[0078] Step S102: storing the initial invoice data in a local invoice pool, and using the stored local invoice pool as the tax invoice data.

[0079] In this embodiment, the local invoice pool refers to the invoice data storage center built locally by the system. This invoice data storage center can be an intermediate data layer or a relational database. In this embodiment, initial invoice data is downloaded in batches. The currently downloaded initial invoice data is stored in the local invoice pool, and the saved local invoice pool is used as the tax invoice data. The local invoice pool can perform data cleanup at predetermined intervals to ensure that the invoice data in the local invoice pool is real-time and valid.

[0080] This embodiment downloads initial invoice data from a preset invoice data interface, stores the initial invoice data in a local invoice pool, and uses the stored local invoice pool as the tax invoice data, thereby effectively providing a reliable data source for subsequent invoice deduction process processing.

[0081] Continue to refer Figure 3 In some optional implementations of this embodiment, step S20 includes the following steps:

[0082] Step S201, reviewing the tax invoice data to obtain reviewed invoice data;

[0083] In this embodiment, the review of tax invoice data includes: invoice authenticity verification, invoice integrity check, invoice compliance review, invoice business logic review, and invoice status check. By reviewing tax invoice data through these steps, invoice data that meets the requirements is screened and marked as "approved." Tax invoice data marked "approved" is then processed as approved invoice data.

[0084] Step S202: extracting payment information from the reviewed invoice data, and performing a payment operation based on the payment information to obtain paid invoice data;

[0085] In this embodiment, corresponding payment information is extracted from the audited invoice data through text recognition. The payment information of the audited invoice data includes the payment amount (the amount payable shown on the invoice), payee information (the consumer's name on the invoice, the consumer's tax number, bank account information, etc.), payment method (determined according to the agreement between the enterprise and the supplier or the instructions on the invoice), and payment date (determined according to the enterprise's internal processes or contractual agreements). A payment instruction is generated based on the extracted payment information, and a payment operation is performed according to the payment instruction. The payment result of the payment operation is recorded. When the payment result is successful, the status of the successfully paid audited invoice data is updated to "paid". The audited invoice data with the "paid" status is the paid invoice data.

[0086] Step S203: Lock the paid invoice data to obtain the valid invoice data.

[0087] In this embodiment, the paid invoice data is synchronized to the tax system through an interface. A ticket lock request is initiated through the ticket lock interface provided by the tax system, and the invoice is marked as "used" or "locked". The tax system then receives the ticket lock result returned to confirm whether the invoice is successfully locked. Based on the ticket lock result, the status information in the paid invoice data is updated. If the ticket lock is successful, the invoice status is updated to "valid", and information such as the ticket lock time and the hash value of the ticket lock operation is recorded. If the ticket lock fails, the reason for the failure is recorded, and corresponding exception handling is performed (such as retrying to lock the ticket or issuing a reminder of the abnormality of the ticket lock operation).

[0088] This embodiment reviews the tax invoice data to obtain audited invoice data; extracts payment information from the audited invoice data and performs a payment operation based on the payment information to obtain paid invoice data; and locks the paid invoice data to obtain valid invoice data. This effectively implements the tax invoice data processing steps, including review, payment reimbursement, and locking, to obtain valid invoice data for deduction, facilitating subsequent invoice financial accounting and invoice deduction processing.

[0089] Continue to refer Figure 4 In some optional implementations of this embodiment, step S30 includes the following steps:

[0090] Step S301, extracting business category and payment information from the valid invoice data;

[0091] In this embodiment, the business category refers to the specific business type associated with the valid invoice data, such as "Raw Material Purchase," "Office Supplies Purchase," or "Travel Expense Reimbursement." This business category can be directly read from the business category field. For example, if the "Summary" field in the invoice data is "Purchase of Office Supplies," the business category can be extracted as "Office Supplies Purchase." Payment information includes key information such as the payment amount, payment method, payment date, and payee's bank account. The payment amount can be extracted from the "Amount" field in the invoice data; the payment method can be extracted from the "Payment Method" field, such as "Bank Transfer" or "Cash Payment"; the payment date can be extracted from the "Payment Date" field in the invoice data; and the payee's bank account can be extracted from the "Payee's Bank Account" field in the invoice data. For example, if the "Amount" in the invoice data is 1,000 yuan, the "Payment Method" is "Bank Transfer," the "Payment Date" is April 21, 2025, and the "Payee's Bank Account" is "1234567890123456789," this information will be extracted.

[0092] Step S302: Obtain a preset accounting mapping table, perform a matching search in the preset accounting mapping table according to the business category and the payment information, and obtain the invoice accounting voucher.

[0093] In this embodiment, the preset accounting mapping table is a predefined table used to map business categories and payment information to specific accounting subjects and accounting rules. Based on the extracted business category, the corresponding accounting subject is searched in the preset accounting mapping table. Based on the extracted payment information (such as payment method and payment amount), the corresponding accounting rule is searched in the preset accounting mapping table, thereby implementing the matching and searching steps in the preset accounting mapping table. For example, the business category "Office Supplies Purchase" is matched to the accounting subject "Administrative Expenses - Office Expenses," and the payment method "Bank Transfer" is matched to the accounting rule "Debit: Administrative Expenses - Office Expenses, Credit: Bank Deposits." Based on the matched accounting subjects and accounting rules, accounting entries are generated and entered into an accounting voucher template that includes information such as the voucher number, date, summary, debit account, credit account, and amount, thereby generating an invoice accounting voucher.

[0094] This embodiment extracts the business category and payment information from the valid invoice data; obtains a preset accounting mapping table, and performs a matching search in the preset accounting mapping table based on the business category and payment information to obtain the invoice accounting voucher. This effectively implements financial accounting processing of the valid invoice data, facilitating subsequent verification of the invoice processing flow.

[0095] Continue to refer Figure 5 In some optional implementations of this embodiment, step S40 includes the following steps:

[0096] Step S401, obtaining a model extraction identifier, and extracting the preset decision model from a model database according to the model extraction identifier;

[0097] In this embodiment, the model extraction identifier is a parameter used to uniquely identify a preset decision model. This identifier can be a model name, model number, model version number, etc. This identifier can be input by the user, read from a system configuration file, or obtained through other system interfaces. By using the model extraction identifier as a query condition to perform a traversal query in the model database, the corresponding preset decision model can be effectively found and extracted from the model database.

[0098] Step S402: Input the invoice accounting voucher into the preset decision model to determine the deduction priority and obtain the deduction authentication result.

[0099] In this embodiment, the preset decision model uses the XGBoost model. The training steps for the preset decision model include data collection: historical invoice data, including invoice amount, business category, payment information, supplier information, invoice type, etc.; invoice-related financial and tax information, such as whether deductions are available, when deductions are available, and the amount of deductions; and other relevant features, such as supplier reputation scores and the interval between invoice issuance and reimbursement. Data cleaning: deduplication, correction of formatting errors, and filling of missing values. Feature engineering: extracting and constructing features based on business and model requirements. For example: numerical features: invoice amount, payment amount, etc.; categorical features: business category (e.g., office supply procurement, travel expense reimbursement, etc.), payment method (e.g., bank transfer, cash payment, etc.), invoice type (e.g., VAT special invoice, ordinary invoice, etc.); temporal features: invoice issuance date, payment date, etc.; and text features: invoice summary, product details, etc., which can be converted into numerical features using text processing techniques (e.g., TF-IDF, Word2Vec, etc.). Data standardization / normalization: Standardize or normalize numerical features to improve the efficiency and effectiveness of model training. Label generation: Generate labels based on historical data, for example, whether it is deductible (1 means deductible, 0 means non-deductible), or deduction priority score (such as 0-100 points). Configure XGBoost model parameters: Learning rate (learning_rate): Controls the contribution of each tree to the final result, with a value range of 0.01-0.3, and 0.1 in this embodiment. Tree depth (max_depth): Controls the maximum depth of the tree to prevent overfitting, with a value range of 3-10, and 5 in this embodiment. Number of trees (n_estimators): Controls the number of trees in the model, with a value range of 100-1000, and 200 in this embodiment. Regularization parameters (lambda and alpha): Used to control the complexity of the model to prevent overfitting. Other parameters: such as subsample (subsampling ratio), colsample_bytree (column sampling ratio), etc. (the above model parameters can be set and adjusted according to actual conditions, and the model parameters in this embodiment are only examples). The collected data is divided into a training set and a test set, with a ratio of 80% training set and 20% test set. The training set data is then used to train the XGBoost model, and the test set is used to verify the model to obtain a preset decision model that effectively performs deduction priority scoring.

[0100] This embodiment obtains a model extraction identifier and extracts the preset decision model from the model database based on the model extraction identifier; then inputs the invoice accounting document into the preset decision model to determine the deduction priority, thereby obtaining the deduction certification result. This effectively obtains a deduction certification result that includes the invoice deduction status and deduction priority score, facilitating subsequent deduction grading based on the deduction certification result.

[0101] Continue to refer Figure 6 In some optional implementations of this embodiment, step S50 includes the following steps:

[0102] Step S501, determining whether the deduction authentication result is authenticated;

[0103] In this embodiment, the invoice deduction status included in the deduction authentication result can be a label (such as "authenticated" or "unauthenticated"), and by identifying the characters corresponding to the label, it is determined whether the deduction authentication result is authenticated.

[0104] Step S502: If the deduction authentication result is authenticated, multi-dimensional feature engineering is performed on the authenticated valid invoice data to obtain multi-dimensional features of the invoice;

[0105] In this embodiment, the multidimensional features of invoices include invoice amount (the amount on the invoice); business category (the type of business the invoice corresponds to, such as office supply procurement, travel expense reimbursement, etc.); payment information (the payment amount, payment method, payment date, etc.); supplier information (the supplier name, supplier reputation score, etc.); time information (the invoice issuance date, reimbursement date, etc.); time difference feature (the number of days between the invoice issuance date and the reimbursement date); supplier reputation feature (the supplier's reputation score or historical cooperation record); and invoice type feature (the weight or priority of different invoice types). By extracting these features from authenticated valid invoice data, we effectively obtain multidimensional invoice features, providing reliable data support for subsequent deduction priority assessments.

[0106] Step S503: If the deduction authentication result is unauthenticated, the unauthenticated valid invoice data is saved in an unauthenticated invoice dataset, and the unauthenticated invoice dataset is re-processed for financial accounting and authentication and deduction until the deduction authentication result of the unauthenticated invoice dataset is authenticated.

[0107] In this embodiment, the unauthenticated invoice dataset is a pre-created storage dataset. By saving the unauthenticated valid invoice data into the unauthenticated invoice dataset, it is convenient to determine the invoices that need to undergo the financial accounting processing step and the authentication deduction processing step again.

[0108] Step S504: performing a deduction priority evaluation based on the multi-dimensional features of the invoice to obtain a deduction priority result;

[0109] In this embodiment, the deduction priority evaluation can be performed through the XGBoost model. By inputting the multi-dimensional features of the invoice into the pre-trained XGBoost model, the corresponding deduction priority score can be evaluated and obtained. The deduction priority score is the deduction priority result.

[0110] Step S505: sort the valid invoice data according to the deduction priority score corresponding to the deduction priority result to obtain the invoice data to be deducted.

[0111] In this embodiment, the valid invoice data is sorted from high to low according to the deduction priority score to determine the order of invoice deduction. When the sorting is completed, the sorted valid invoice data is output as the deduction invoice data.

[0112] This embodiment determines whether the deduction authentication result is authenticated; if the deduction authentication result is authenticated, multi-dimensional feature engineering is performed on the authenticated valid invoice data to obtain the invoice multi-dimensional features; if the deduction authentication result is unauthenticated, the unauthenticated valid invoice data is saved in the unauthenticated invoice data set, and the unauthenticated invoice data set is re-processed for financial accounting and authentication and deduction until the deduction authentication result of the unauthenticated invoice data set is authenticated; a deduction priority evaluation is performed based on the invoice multi-dimensional features to obtain a deduction priority result; the valid invoice data is sorted according to the deduction priority score corresponding to the deduction priority result to obtain the invoice data to be deducted. This effectively determines the invoice data to be deducted that requires subsequent invoice deduction operations, so as to facilitate the subsequent acquisition of the optimal deduction strategy.

[0113] In some optional implementations of this embodiment, after step S60, the following steps are further included:

[0114] Obtain the operation log, feature authentication record, and cross-chain transaction hash corresponding to the invoice deduction processing;

[0115] In this embodiment, the operation log records every step of the invoice deduction process, such as reimbursement processing, financial accounting processing, deduction authentication processing, deduction classification processing, and generation of the optimal deduction strategy. Feature authentication records refer to the identity authentication record information corresponding to the invoice data, such as fingerprints and identity images. The cross-chain transaction hash is a unique string generated by hashing cross-chain transaction data (such as the addresses of both parties to the transaction, the amount, and the timestamp), which is used to identify a specific cross-chain transaction. In this embodiment, when the invoice deduction process does not include a cross-chain transaction, the corresponding cross-chain transaction hash value is empty.

[0116] Identifying sensitive fields of the valid invoice data after the invoice deduction processing, and performing homomorphic encryption processing on the identified sensitive fields to obtain encrypted invoice data;

[0117] In this embodiment, the sensitive fields of valid invoice data after invoice deduction processing are identified by pre-set sensitive field information (such as name, ID number, bank account number, etc.), and then the sensitive fields are encrypted using a homomorphic encryption algorithm to ensure that the data can still be calculated in an encrypted state. Among them, the homomorphic encryption algorithm is an encryption technology that allows calculations to be performed directly on ciphertext data, and the calculation results, after decryption, are consistent with the results calculated directly on the plaintext. In this embodiment, by performing homomorphic encryption on the sensitive fields of the valid invoice data, the encryption of the valid invoice data is simply and effectively achieved, and the corresponding encrypted invoice data is obtained.

[0118] Extract the operational process links corresponding to invoice deduction processing based on the operation log;

[0119] In this embodiment, the operation steps, system response time, operation objects and other information corresponding to the invoice deduction processing can be extracted from the operation log, and the time sequence and step flow can be sorted based on the above operation steps, system response time, operation objects and other information to obtain the corresponding operation flow link.

[0120] The feature authentication record, the cross-chain transaction hash, the encrypted invoice data, and the operation process link are sorted to generate a deduction audit data package, and the deduction audit data package is saved to the data table to be audited.

[0121] In this embodiment, by associating feature authentication records, cross-chain transaction hashes, encrypted invoice data, and operational process links, a deduction audit data package containing a series of invoice deduction operational processes and encrypted information is generated. This deduction audit data package is then saved in the audited data table to facilitate subsequent audit verification, effectively improving the security and confidentiality of the invoice deduction process.

[0122] This embodiment obtains the operation log, feature authentication record, and cross-chain transaction hash corresponding to the invoice deduction process; identifies sensitive fields of the valid invoice data after the invoice deduction process, and performs homomorphic encryption on the identified sensitive fields to obtain encrypted invoice data; extracts the operation process link corresponding to the invoice deduction process based on the operation log; organizes the feature authentication record, the cross-chain transaction hash, the encrypted invoice data, and the operation process link to generate a deduction audit data packet, and saves the deduction audit data packet to the data table to be audited. In this way, an auditable data table to be audited is effectively generated based on the operation status and link process status of the invoice deduction process, so as to facilitate subsequent audit and verification operations and effectively improve the process security and confidentiality of the invoice deduction process.

[0123] Those skilled in the art will appreciate that all or part of the processes in the above-described method embodiments can be implemented by instructing related hardware via computer-readable instructions. The computer-readable instructions can be stored in a computer-readable storage medium, and when the program is executed, it can include the processes in the above-described method embodiments. The aforementioned storage medium can be a non-volatile storage medium such as a magnetic disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM).

[0124] It should be understood that although the steps in the flowcharts of the accompanying drawings are shown in sequence as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some of the steps in the flowcharts of the accompanying drawings may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be executed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

[0125] Further references Figure 7 , as a response to the above Figure 1 The present application provides an embodiment of an intelligent integrated tax invoice management device. Figure 1 Corresponding to the method embodiment shown, the device can be specifically applied to various electronic devices.

[0126] like Figure 7As shown, the intelligent integrated fiscal and tax invoice management device 700 of this embodiment includes: a data acquisition module 701, a data processing module 702, a voucher generation module 703, a deduction authentication module 704, a deduction classification module 705, and a deduction execution module 706. Among them:

[0127] Data acquisition module 701, used to obtain tax invoice data;

[0128] Data processing module 702, used to perform reimbursement processing on the tax invoice data to obtain valid invoice data;

[0129] The voucher generation module 703 is used to perform financial accounting processing on the valid invoice data and generate an invoice accounting voucher;

[0130] The deduction authentication module 704 is used to perform deduction authentication processing on the invoice accounting voucher based on a preset decision model to obtain a deduction authentication result;

[0131] A deduction grading module 705 is configured to perform deduction grading processing based on the deduction authentication result to obtain invoice data to be deducted;

[0132] The deduction execution module 706 is used to input the invoice data to be deducted into the pre-trained decision generation model, generate an optimal deduction strategy, and perform invoice deduction processing on the invoice data to be deducted according to the optimal deduction strategy.

[0133] This embodiment obtains tax invoice data; performs reimbursement processing on the tax invoice data to obtain valid invoice data; performs financial accounting processing on the valid invoice data to generate invoice accounting vouchers; performs deduction authentication processing on the invoice accounting vouchers based on a preset decision model to obtain a deduction authentication result; performs deduction grading processing based on the deduction authentication result to obtain invoice data to be deducted; inputs the invoice data to be deducted into a pre-trained decision generation model to generate an optimal deduction strategy, and performs invoice deduction processing on the invoice data to be deducted based on the optimal deduction strategy. This effectively performs automatic invoice deduction processing based on different invoice data, thereby improving the efficiency of invoice deduction processing.

[0134] To solve the above technical problems, the present application also provides a computer device. Figure 8 , Figure 8 This is a basic structural block diagram of the computer device in this embodiment.

[0135] The computer device 8 includes a memory 81, a processor 82, and a network interface 83 that are interconnected through a system bus. It should be noted that the figure only shows a computer device 8 with components 81-83, but it should be understood that it is not required to implement all the components shown, and more or fewer components can be implemented instead. Among them, those skilled in the art can understand that the computer device here is a device that can automatically perform numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes but is not limited to microprocessors, application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), digital signal processors (DSPs), embedded devices, etc.

[0136] The computer device may be a desktop computer, notebook computer, PDA, cloud server, etc. The computer device may interact with the user via a keyboard, mouse, remote control, touchpad, or voice control device.

[0137] The memory 81 includes at least one type of readable storage medium, including flash memory, hard disk, multimedia card, card-type memory (e.g., SD or DX memory), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 81 can be an internal storage unit of the computer device 8, such as the hard disk or memory of the computer device 8. In other embodiments, the memory 81 can also be an external storage device of the computer device 8, such as a plug-in hard disk equipped on the computer device 8, a smart memory card (SMC), a secure digital (SD) card, a flash card, etc. Of course, the memory 81 can also include both the internal storage unit of the computer device 8 and its external storage device. In this embodiment, the memory 81 is generally used to store the operating system and various application software installed on the computer device 8, such as the computer-readable instructions of the intelligent integrated fiscal and tax invoice management method. In addition, the memory 81 can also be used to temporarily store various types of data that have been output or are to be output.

[0138] In some embodiments, the processor 82 may be a central processing unit (CPU), a controller, a microcontroller, a microprocessor, or other data processing chip. The processor 82 is generally used to control the overall operation of the computer device 8. In this embodiment, the processor 82 is used to execute computer-readable instructions or process data stored in the memory 81, such as computer-readable instructions for executing the intelligent integrated fiscal and tax invoice management method.

[0139] The network interface 83 may include a wireless network interface or a wired network interface. The network interface 83 is generally used to establish a communication connection between the computer device 8 and other electronic devices.

[0140] By using the aforementioned computer device, this embodiment can obtain tax invoice data; perform reimbursement processing on the tax invoice data to obtain valid invoice data; perform financial accounting processing on the valid invoice data to generate an invoice accounting voucher; perform deduction authentication processing on the invoice accounting voucher based on a preset decision model to obtain a deduction authentication result; perform deduction grading processing based on the deduction authentication result to obtain invoice data to be deducted; input the invoice data to be deducted into a pre-trained decision generation model to generate an optimal deduction strategy, and perform invoice deduction processing on the invoice data to be deducted based on the optimal deduction strategy. This effectively performs automatic invoice deduction processing based on different invoice data, thereby improving the efficiency of invoice deduction processing.

[0141] The present application also provides another embodiment, namely, providing a computer-readable storage medium, which stores computer-readable instructions, and the computer-readable instructions can be executed by at least one processor to enable the at least one processor to perform the steps of the intelligent integrated financial and tax invoice management method as described above.

[0142] By using the computer-readable storage medium, this embodiment can obtain tax invoice data; perform reimbursement processing on the tax invoice data to obtain valid invoice data; perform financial accounting processing on the valid invoice data to generate an invoice accounting voucher; perform deduction authentication processing on the invoice accounting voucher based on a preset decision model to obtain a deduction authentication result; perform deduction grading processing based on the deduction authentication result to obtain invoice data to be deducted; input the invoice data to be deducted into a pre-trained decision generation model to generate an optimal deduction strategy, and perform invoice deduction processing on the invoice data to be deducted based on the optimal deduction strategy. This effectively performs automatic invoice deduction processing based on different invoice data, thereby improving the efficiency of invoice deduction processing.

[0143] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus the necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for enabling a terminal device (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in each embodiment of the present application.

[0144] Obviously, the embodiments described above are only some of the embodiments of the present application, rather than all of the embodiments. The preferred embodiments of the present application are given in the accompanying drawings, but they do not limit the patent scope of the present application. The present application can be implemented in many different forms. On the contrary, the purpose of providing these embodiments is to make the understanding of the disclosure of the present application more thorough and comprehensive. Although the present application has been described in detail with reference to the aforementioned embodiments, for those skilled in the art, it is still possible to modify the technical solutions described in the aforementioned specific embodiments, or to make equivalent replacements for some of the technical features therein. Any equivalent structure made using the contents of the present application specification and the accompanying drawings, directly or indirectly used in other related technical fields, is also within the scope of patent protection of the present application.

Claims

1. An intelligent integrated fiscal and tax invoice management method, characterized by: include: Obtain tax invoice data; Performing reimbursement processing on the tax invoice data to obtain valid invoice data; Perform financial accounting processing on the valid invoice data to generate invoice accounting vouchers; Performing deduction authentication processing on the invoice accounting voucher based on a preset decision model to obtain a deduction authentication result; Performing deduction grading processing based on the deduction authentication result to obtain invoice data to be deducted; The invoice data to be deducted is input into a pre-trained decision generation model to generate an optimal deduction strategy, and the invoice deduction processing is performed on the invoice data to be deducted according to the optimal deduction strategy.

2. The intelligent integrated fiscal and tax invoice management method according to claim 1 is characterized in that: The steps of obtaining tax invoice data specifically include: Download the initial invoice data from the preset invoice data interface; The initial invoice data is stored in a local invoice pool, and the stored local invoice pool is used as the tax invoice data.

3. The intelligent integrated fiscal and tax invoice management method according to claim 1 is characterized in that: The step of reimbursing the tax invoice data to obtain valid invoice data specifically includes: Reviewing the tax invoice data to obtain reviewed invoice data; Extracting payment information from the reviewed invoice data, and performing a payment operation based on the payment information to obtain paid invoice data; The paid invoice data is locked to obtain the valid invoice data.

4. The intelligent integrated fiscal and tax invoice management method according to claim 1 is characterized in that: The step of performing financial accounting processing on the valid invoice data to generate an invoice accounting voucher specifically includes: extracting business category and payment information from the valid invoice data; A preset accounting mapping table is obtained, and a matching search is performed in the preset accounting mapping table according to the business category and the payment information to obtain the invoice accounting voucher.

5. The intelligent integrated fiscal and tax invoice management method according to claim 1 is characterized in that: The step of performing deduction authentication processing on the invoice accounting voucher based on the preset decision model to obtain the deduction authentication result specifically includes: Obtaining a model extraction identifier, and extracting the preset decision model from a model database according to the model extraction identifier; The invoice accounting voucher is input into the preset decision model to perform deduction priority judgment to obtain the deduction certification result.

6. The intelligent integrated fiscal and tax invoice management method according to claim 1 is characterized in that: The step of performing deduction grading processing according to the deduction authentication result to obtain the invoice data to be deducted specifically includes: Determining whether the deduction authentication result is authenticated; If the deduction certification result is certified, multi-dimensional feature engineering processing is performed on the certified valid invoice data to obtain multi-dimensional features of the invoice; Performing a deduction priority evaluation based on the multi-dimensional features of the invoice to obtain a deduction priority result; The valid invoice data is sorted according to the deduction priority score corresponding to the deduction priority result to obtain the invoice data to be deducted.

7. The intelligent integrated fiscal and tax invoice management method according to claim 1 is characterized in that: After the steps of inputting the invoice data to be deducted into the pre-trained decision generation model to generate an optimal deduction strategy, and performing invoice deduction processing on the invoice data to be deducted according to the optimal deduction strategy, the method further includes: Obtain the operation log, feature authentication record, and cross-chain transaction hash corresponding to the invoice deduction processing; Identifying sensitive fields of the valid invoice data after the invoice deduction processing, and performing homomorphic encryption processing on the identified sensitive fields to obtain encrypted invoice data; Extract the operational process links corresponding to invoice deduction processing based on the operation log; The feature authentication record, the cross-chain transaction hash, the encrypted invoice data, and the operation process link are sorted to generate a deduction audit data package, and the deduction audit data package is saved to the data table to be audited.

8. An intelligent integrated fiscal and tax invoice management device, characterized by: include: Data acquisition module, used to obtain tax invoice data; A data processing module, configured to process the tax invoice data for reimbursement to obtain valid invoice data; A voucher generation module is used to perform financial accounting processing on the valid invoice data and generate an invoice accounting voucher; A deduction authentication module is used to perform deduction authentication processing on the invoice accounting voucher based on a preset decision model to obtain a deduction authentication result; A deduction grading module is used to perform deduction grading processing based on the deduction authentication result to obtain invoice data to be deducted; The deduction execution module is used to input the invoice data to be deducted into the pre-trained decision generation model, generate an optimal deduction strategy, and perform invoice deduction processing on the invoice data to be deducted according to the optimal deduction strategy.

9. A computer device, characterized in that: It includes a memory and a processor, wherein the memory stores computer-readable instructions, and when the processor executes the computer-readable instructions, it implements the steps of the intelligent integrated fiscal and tax invoice management method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer-readable instructions, which, when executed by a processor, implement the steps of the intelligent integrated fiscal and tax invoice management method according to any one of claims 1 to 7.

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