623 results about "Invoice" patented technology

The invention relates to the technical field of enterprise finance and taxation management, and discloses an enterprise finance and taxation intelligent management system based on data analysis. According to the method, the problems of data islands, response delay and business disjunction in the prior art are solved by constructing a multi-source data real-time access and dynamic knowledge graph and stream calculation analysis engine collaborative architecture. Specifically, deep fusion and real-time perception of enterprise finance and taxation total data are realized, invoice risks and compliance deviations in a business flow can be actively identified, and the conversion from post-event recheck to in-event intervention is completed; through combination of a dynamic knowledge graph and an AI model, an analysis decision deeply accords with a business scene, a tax preferential policy is matched, and the finance and tax planning efficiency is intelligently improved; meanwhile, the system has self-learning and self-adaptive capabilities and can be continuously optimized along with policy and regulation and business changes, the risk control level and compliance capability of an enterprise are enhanced, and the real-time performance, accuracy and intelligent degree of finance and tax management are improved.

Orchestration solutions for agentic automation for artificial intelligence (AI) agents, robotic process automation (RPA) robots, agentic orchestration processes (AOPs), and humans-in-the-loop with self-healing and capabilities to increase autonomy. Agentic orchestration, via a conductor application, enables the automation, modeling, and monitoring of complex business processes from start to finish. A user or an initiating software process requests that a given AOP be run. The AOP defines a business process (e.g., in Business Process Model and Notation (BPMN)), and may utilize one or more RPA robots, one or more AI agents, and / or one or more humans to assist with accomplishing this process, such as resolving invoice discrepancies, onboarding an employee, performing compliance checks, synchronizing order data among multiple backend systems, etc.

The embodiment of the invention provides a bill collaborative management method and system based on multi-source heterogeneous data fusion, and belongs to the technical field of data processing. The method comprises the following steps: performing hash calculation according to standardized bill data to obtain a unique identifier; and obtaining a map node corresponding to the standardized bill data to obtain a target map node. The path from the map root node to the target map node is a target structure path. And obtaining a complete behavior sequence of the standardized bill data according to the unique identifier and the behavior log. And constructing a behavior structure joint sequence according to the target structure path and the complete behavior sequence. And inputting the behavior structure joint sequence into the structure perception embedding model to obtain a sequence embedding vector. And obtaining a structure behavior inconsistency score and an abnormal type label according to the structure behavior consistency evaluation function, the behavior structure joint sequence and the sequence embedding vector. And generating a suggestion text according to the structure behavior inconsistency score and the abnormal type label, and displaying the suggestion text. Accurate identification of abnormal bills is realized.

A system for real-time creditworthiness assessment of small and medium-sized enterprises (SMEs) based on agent-based artificial intelligence (AI), the system includes: a large number of autonomous agents connected to each other via secure communication protocols; a data ingestion processing unit configured to capture and preprocess heterogeneous data streams from structured and unstructured sources, including APIs for financial transactions, tax databases, e-invoicing registers, inventory management systems, social sentiment feeds, and IoT-enabled devices, with preprocessing including schema harmonization, anomaly detection, and encryption-based integrity preservation; an ensemble of scoring control units configured to generate dynamic credit scores, wherein the ensemble includes machine learning models, including gradient-enhanced decision trees, recurrent neural networks, and graph neural networks, the graph neural networks being configured to assess relational dependencies between SMEs, suppliers, and customer nodes in a business ecosystem; an audit controller configured to generate regulatory-compliant justification paths for each credit score; a feedback processing unit configured to update the evaluation control unit ensemble using reinforcement learning signals derived from observed repayment behavior, payment default trends, and fraud detection markers; and a user interface configured to display timestamped credit histories, confidence intervals and explanatory justifications, with the entire system running on a containerized cloud-native infrastructure with blockchain-based ledgers for version control of each point update.

Methods, systems, and computer-readable storage media for providing a set of column pairs, each column pair including a column of a bank statement table, and a column of a super invoice table, each column pair corresponding to a modality, the super invoice table including at least one row including data associated with multiple invoices, for each column pair, determining a feature descriptor based on an operator, a feature vector being provided based on feature descriptors of the set of column pairs, inputting the feature vector to a ML model that processes the feature vector to determine a probability of a match between the bank statement, and a super invoice represented by the super invoice table, and outputting a binary output representing one of a match and no match between the bank statement, and the super invoice based on the probability.

The present invention discloses a blockchain-integrated financial reputation scoring system designed to assess financial credibility within decentralized ecosystems. The system generates a dynamic accountability score based on blockchain transactions, including escrow payments, invoice completions, smart contract interactions, DeFi transactions, NFT trading, and cross-chain financial activities. A risk-adaptive score weighting system dynamically adjusts the impact of financial behaviors based on transaction risk, counterparty trustworthiness, and historical financial patterns. The score is leveraged for tiered access to financial products, lending, and collateral adjustments. AI-enhanced anomaly detection prevents fraudulent score inflation, while privacy-preserving verification ensures secure reputation authentication. The system further extends into insurance underwriting, compliance verification (AML / KYC), and financial access expansion, allowing traditional institutions to assess blockchain-based creditworthiness. Quantum-resistant cryptographic techniques secure reputation data, ensuring trust and adaptability in both decentralized and traditional financial ecosystems.

The invention discloses an analysis method and system for internet enterprise credit risk assessment, and belongs to the technical field of internet finance, and the method comprises the steps: obtaining multi-source enterprise operation data of a target enterprise and an associated party, the multi-source enterprise operation data comprising payment flow data and tax invoice data; based on the multi-source enterprise operation data, identifying an enterprise association relationship between a target enterprise and an associated party, and constructing a dynamic enterprise relationship graph by using the enterprise association relationship; based on the multi-source enterprise operation data, extracting a time sequence behavior index of the target enterprise; fusing the dynamic enterprise relation graph and the time sequence behavior indexes to generate coupling risk features; and generating a credit risk assessment result according to the coupling risk features. According to the method, a multi-source data fusion mechanism and a dynamic enterprise relation graph construction technology are adopted, coupling risk features can be generated, a risk infection path can be simulated, and panoramic risk portraits and prospective early warning are realized.

The invention belongs to the cross technical field of block chain technology and supply chain finance, and provides a supply chain dynamic risk control method and system based on a smart contract, and the technical scheme is as follows: obtaining node data of each participant in a supply chain; dynamically evaluating the risk of the supply chain in combination with the obtained node data of each participant and the constructed smart contract; wherein in the basic contract, the logistics data and the invoice data are verified respectively, and a verification result is sent to the business contract after verification is passed; in a business contract, according to received enterprise data, introducing a timestamp mechanism, recording creditor's right generation time in a block chain, and realizing multi-level creditor's right splitting and merging through a Merkle tree; in the risk control contract, calculating a risk assessment index based on the on-chain data, the off-chain data and the risk assessment model; and adjusting the credit granting strategy in real time according to the change of the risk assessment index to obtain an adjusted credit granting strategy. Risk control is embedded into contract execution logic, so that the risk loss of the supply chain is reduced.

There is a system for admitting automobiles to a venue comprising: at least one camera for recognizing an automobile, and a license plate. A server is configured for receiving a picture of the automobile and a picture of the license plate of the automobile. Furthermore, there is at least one database for storing, matching and identifying the picture of the automobile and the license plate. In addition, there is at least one screen for allowing a user to identify their automobile taken from a list of automobiles. There is also a process for tracking an automobile within an area which comprises the steps of identifying a pre-defined area and identifying an automobile for screening into the area. Next the auto and its license plate are photographed. This information is stored in a database and then used to generate invoices and track the location of these automobiles. Customer can access the database, enter the license plate of his vehicle, the database recognizes his vehicle, the customer makes payment for his vehicle, and the app places the customer information onto the PAID category list on the database.

The invention relates to the technical field of data processing, in particular to an invoicing, accounting and tax declaration method and system for a supply chain, and the method comprises the following steps: obtaining original data, including purchase order, customs declaration and invoice information, generated in each business link of the supply chain, and synchronizing the original data to a financial data center through a system interface for standardization processing; classifying the standardized data based on a preset rule, generating a to-be-processed receivable bill and a to-be-processed payable bill, and associating corresponding business records; comparing the purchase order, the acceptance record and the invoice information, generating an account checking difference report, and pushing the account checking difference report to a related service terminal; updating the account period state according to the account checking result; extracting tax refund elements in the customs declaration, generating a tax refund application, and tracking an auditing progress until the tax refund application arrives at an account and is filed; the method automatically synchronizes data of links such as customs affair and storage through a system interface and performs standardization processing, solves the problem of lagging of manual data collection, and improves the data synchronization efficiency.

The invention relates to the technical field of invoice risk control management, and discloses an invoice risk control management method and system based on multi-source data linkage. According to the method, multi-source data of the whole invoice business process is collected in real time through a multi-source data fusion gateway. And performing streaming ETL processing and encryption integration on the multi-source data to generate an encrypted unified data view. And based on the view, constructing an association hypergraph by utilizing a dynamic graph association technology, analyzing an entity relationship by virtue of a graph neural network, and identifying false invoice making gang and repeated financing risks. And calculating a dynamic risk score by adopting a risk quantification and traceability technology, and outputting a risk level, a responsibility node identifier and a capital flow thermodynamic diagram. When the risk score exceeds a threshold value, risk gradient information is safely shared among the group headquarters, the molecular companies and the tax-bank institutions, and linkage processing actions such as invoice freezing, red character notification or credit adjustment are triggered. According to a manual reexamination result, the risk model is finely adjusted through a knowledge self-updating technology, and the rule base is hot-updated.

The invention provides a safe short message link invoice generation system and method based on a bank intranet, and belongs to the technical field of data processing, and the method specifically comprises the steps: determining an available invoicing amount interval based on the change condition of a centralized verification risk time period in an effective time interval of an invoicing short message link at a current time period under different invoicing amounts, and when the matching invoice amount is not in the available invoice amount interval, according to the change condition of the matching invoice in different concentrated verification risk time periods and the invoice amount influence condition of the different concentrated verification risk time periods on the future time period, the matching invoice amount is calculated according to the change condition of the matching invoice in the different concentrated verification risk time periods. According to the generation processing method for determining the effective time interval of the short message link invoice of the server of the bank intranet in the current time period, the congestion condition of the server for checking and downloading the invoice is avoided.

The invention discloses a business hall invoice intelligent printing system, which comprises a multi-source data acquisition module used for acquiring equipment state data, user queue data and business attribute data of each printing terminal in a business hall in real time; the dynamic priority evaluation module is used for calculating an invoice issuing emergency degree quantized value E based on the business attribute data; the self-adaptive scheduling engine is used for generating a printing task distribution instruction according to the equipment state data, the user queue data and the emergency degree quantized value E; the predictive maintenance module is used for constructing a consumable consumption prediction model according to the consumable allowance historical data; the execution control module is used for driving the target printing terminal to execute the printing task; wherein the equipment state data comprises the busy and idle states of the printing terminal, the printing rate and the consumable allowance. According to the method, tasks can be intelligently scheduled, the efficiency is improved, the stability is guaranteed, the experience is optimized, and the cost is reduced.

The invention provides a semantic anchor point definition method based on a guide word and a topological structure. The semantic anchor point definition method is used for solving the problem that key fields in structured bills with the same semantic content but large format difference are difficult to position. The method comprises the following steps: constructing a semantic field and guide word dictionary; carrying out OCR identification on the bill image; identifying a matched guide word block in the text block; establishing a spatial adjacency relationship between the guide words; and finally generating an anchor point structure triple containing the semantic field (S), the adjacent structure (N) and the semantic content extraction direction (D). According to the method, the structured representation for expressing the semantic layout of the bills can be constructed, good cross-format adaptability is achieved, stable anchor point support is provided for follow-up format matching and field content extraction, and the method is suitable for processing scenes of multi-type heterogeneous bills such as customs production place certificates, customs declarations and invoices.

Systems and methods are described for executing tenant artificial intelligence pipelines by dynamically selecting service providers based on resource consumption. A server can poll a group of service providers and receive resource information that indicates compute, network, storage, and token requirements to perform an action. When the tenant AI pipeline executes, a pipeline engine can select a service provider to execute the action based on stored resource information. The service providers available in the group can also dynamically change based on terms of service.

The invention relates to the technical field of relation extraction, in particular to an invoice relation extraction method based on natural language analysis, and the method comprises the following steps: analyzing multiple features such as an image seal, a two-dimensional code and a handwritten annotation, matching text and image space information, checking the consistency of the two-dimensional code and a tax-control code, and recognizing the field combination and the abnormality of the amount and a payer. According to the method, detail features such as seals, two-dimensional codes and handwritten marks in invoice images are analyzed through multi-level fusion, space joint judgment of image-text content is achieved, the credibility of information verification is improved through character safety comparison and coding consistency, deep relation mining between payment behaviors and entities is enhanced by means of a context semantic dependency structure, and the payment efficiency is improved. According to the method, elements such as the amount and the payer are dynamically classified and aggregated, automatic identification of a complex transaction relationship is realized, intelligent judgment and real-time label generation of abnormal risk behaviors are further realized through linkage clustering and difference tracking, and the active risk control capability of financial management is improved.

The embodiment of the invention discloses a business receipt and invoice data matching method and system, and the method comprises the following steps: accessing original business receipt data and invoice data from a plurality of heterogeneous data sources through a uniform interface, and carrying out the data cleaning according to preset mapping, merging, splitting and conversion rules, generating a standardized matching flow order; adopting streaming data loading and a Worker parallel computing mechanism to carry out multi-dimensional matching on business receipt and invoice data in the standardized flow bill, and generating a relation matrix representing a corresponding relation between the receipt and the invoice based on a matching result; and automatically checking the relation matrix by calling a rule engine and a machine learning model, marking the matching result of the business document and the invoice which are checked to be abnormal, pushing the matching result to manual auditing, and feeding back the manual auditing result to a knowledge base to optimize the subsequent matching and checking rule. According to the embodiment of the invention, the matching efficiency of the business document and the invoice data and the accuracy of the matching result can be improved.

The invention discloses an intelligent expense reimbursement auditing system based on multi-modal identification, and relates to the technical field of artificial intelligence and financial informatization. According to the system, invoice images, structured transaction data and text description information are acquired through a multi-modal data acquisition module, multi-modal feature weighted fusion is realized by using an attention mechanism of a feature fusion module and a tensor fusion technology, and a multi-modal feature fusion model is established by combining Bayesian reasoning of an auditing decision module, Mahalanobis distance of an anomaly detection module and an auto-encoder algorithm. And a rule engine module, an interpretability analysis module and a federal learning architecture, so that the problems of low efficiency, high misjudgment rate, poor rule adaptability, insufficient risk detection capability and the like of a traditional system are solved. The system can shorten the single checking time from 5-10 minutes to a second level, the recognition accuracy rate exceeds 99%, the misjudgment rate is lower than 0.5%, 10 + type high-risk behaviors can be automatically recognized, dynamic policy updating and interpretability analysis are supported, data privacy is guaranteed through federal learning, and the system is suitable for enterprise financial reimbursement checking.

The invention provides an automatic reconciliation method and device, electronic equipment and a storage medium, and the method comprises the steps: carrying out the data preprocessing of a to-be-reconciliated collection / payment voucher and bill, and obtaining a collection / payment voucher set and a to-be-matched bill set which are uniform in format and are normalized in transaction main body; based on a preset first matching condition, performing one-to-one initial matching on the receipt / payment voucher set and the to-be-matched bill set; in response to initial matching failure, expanding the first matching condition to generate a second matching condition; based on a second matching condition, performing one-to-one re-matching on the receipt / payment voucher set and the to-be-matched bill set to obtain a candidate matching pair set; based on a pre-trained confidence evaluation model, evaluating the matching confidence of each candidate matching pair in the candidate matching pair set; and when the matching confidence of the candidate matching pair is greater than a first preset confidence threshold, triggering an automatic entry operation. The account checking efficiency and success rate are improved.

The invention discloses a multi-agent-based accounting business processing method and system. The multi-agent-based accounting business processing method and system comprises the following steps: acquiring a correct invoice number, amount, category, responsible department, principal and the like through the technologies of image acquisition, denoising, enhancement, tilt correction, feature extraction, character correction and the like of an initial voucher; automatically inputting the identified related information into an account book according to the classification of each accounting subject, and generating a total account book and a detail account book; regularly adopting a computer-aided auditing technology, randomly generating a random number according to an importance (such as involved amount or business type risk level) proportion, automatically extracting an account for auditing, and realizing unified calling and checking of an original voucher, a general account book and a detail account book; through integration of deep learning, knowledge graph and other technologies, more complex prediction is realized by using big data, a potential financial trend is identified, detailed risk assessment is carried out, and decision support is provided. The query and scheduling service of the whole business process is realized by using a large language model and adopting a voice interaction mode, unit financial data is preprocessed, and an RAG containing financial statements and related financial knowledge is constructed with related knowledge such as related legal policies, tax policies, financial analysis and bank settlement and is used for retrieval and query, and the financial statement and the related financial knowledge are stored in a database. All modules and execution processes of financial software are fused, and intelligent query and execution based on a large model are achieved.

The invention discloses a smart retail purchase management method and system, and the method comprises the steps: obtaining a multi-supplier order / quoted price and a store demand, carrying out the adaptive analysis, cleaning and verification, and generating a standardized purchase and suggestion list; evaluating risks based on rules and models and automatically selecting an approval link; scanning and collecting bar codes / serial numbers / batches / quantity when goods arrive, and storing according to unique association of suppliers, order numbers, codes and batches; after warehousing, carrying out consistency comparison, abnormity early warning, freezing and closed-loop processing on orders, warehousing, invoices and payment; and in the settlement stage, convergent transaction, bank and billing account checking are carried out, and results are written back to supplier and inventory parameters to drive subsequent suggestion and approval threshold adaptive optimization. According to the technical scheme, the data accuracy and compliance are remarkably improved, the approval and checkout cycle is shortened, and the purchase cost and the operation risk are reduced.

The invention relates to the technical field of bill management, in particular to a retail terminal invoice co-processing method based on multi-service provider interface integration. According to the retail terminal invoice co-processing method based on multi-service provider interface integration, a retail terminal completes collection of consignment data, and an operator initiates a service charge settlement process after data verification is passed; after the store manager audits the consignment data, the dealer issues a value-added tax special invoice, generates an OFD format file through the tax UKey, and uploads the OFD format file to the system; the retail terminal extracts the invoice structured data, verifies the consignment data and the invoice data online, and confirms settlement after confirming that the consignment data and the invoice data are correct; and after the third-party financial system obtains the data, the service fee is settled to the dealer. The retail terminal invoice co-processing method based on multi-service provider interface integration is high in adaptability, human input is reduced, data errors caused by manual input errors are greatly reduced, the business data accuracy is improved, and the business efficiency is improved.

The embodiment of the invention discloses a cross-enterprise invoice risk collaborative identification method and system, and the method comprises the following steps: obtaining a tax policy file, extracting a policy entity and rule logic through an NLP, and constructing and dynamically updating a risk knowledge graph; the updated risk rule is pushed to a federation center, local data features are loaded through the enterprise node, the tax node and the bank node, and local gradient calculation is carried out; homomorphic encryption is carried out on the gradient obtained through local calculation, an encryption result is sent to the federation center through an encryption channel, and aggregation and model updating are completed by the federation center; and carrying out risk identification on real-time invoice data by utilizing the global model obtained by training, marking suspicious invoices and carrying out abnormal type classification. According to the embodiment of the invention, the model precision can be improved, the processing time is shortened, and the processing efficiency is improved.

The invention discloses a cross-border supply chain financial service exit data AI automatic comparison system based on an RPA technology, and the system comprises a data collection module which automatically logs in an electronic port system through the RPA technology and captures exit related data; the document analysis module is used for automatically extracting semi-structured feature information in an unstructured file according to the data acquired by the data acquisition module, and standardizing the semi-structured feature information into a uniform format for subsequent comparison; the AI comparison module is used for intelligently comparing structured and unstructured information through a natural language processing and semantic understanding technology; the rule engine module is used for identifying risk points including field inconsistency, abnormal amount and unmatched terms according to a preset rule; and the risk early warning module is used for automatically generating an audit report and an early warning prompt according to the comparison result. Natural language processing and image recognition technologies are introduced, automatic alignment and comparison with information of receipts such as contracts / orders, waybills and packing lists are achieved, potential abnormity is found, risk early warning is formed, and the problem that in the prior art, deep comparison and automatic processing of semantic content are lacked is solved. And effective linkage with external data sources such as an electronic port system is not formed, so that trade authenticity auditing lags behind, and large operation risks exist.

The invention relates to the technical field of supplier full life cycle technologies, and provides a supplier full life cycle management method based on multi-dimensional evaluation, which comprises the steps of demand source searching, supplier classification and selection, supplier relationship management, contract management, purchase management, order execution, invoice reconciliation and expenditure analysis. According to the method, a whole-process closed-loop management system from demand source searching to expenditure analysis is established, so that information barriers among links are broken, and seamless circulation and sharing of data are realized; a standardized evaluation model and a classification system are adopted, traditional supplier decision-making depending on subjective experience is converted into scientific decision-making based on quantitative data, and the management efficiency and decision-making accuracy are remarkably improved. By establishing a contract performance early warning mechanism and an abnormal order grading processing flow, full-flow dynamic monitoring of contract risks and execution abnormities is realized; based on the risk assessment matrix and the change influence analysis model, various potential risks can be identified and responded in time.

The invention discloses an intelligent monitoring method and system for enterprise tax receipt risk early warning, and relates to the technical field of intelligent tax risk control. Comprising the following steps: S1, processing a tax policy file through structured preprocessing, and determining a policy feature vector; s2, obtaining transaction network characteristics through the space-time transaction graph and the enterprise invoice data; s3, determining a violation probability and a judgment threshold according to the policy feature vector and the transaction network feature; and S4, determining a risk level according to the violation probability and a final judgment threshold, and generating a risk report. According to the method, policy feature vectors are extracted through BERT, the judgment threshold is dynamically adjusted in combination with the similarity between new and old policies, so that the model can be adaptively optimized along with policy changes, the misjudgment of the model is reduced, meanwhile, the rule violation probability and the abnormal type label are generated through the CVAE model, weighting is performed in combination with the industry risk coefficient, and the probability of rule violation is reduced. And the sensitivity to a few abnormal samples is enhanced.

The invention provides an intelligent management and control system for enterprise finance and taxation risks. Invoice data, enterprise finance data and industry tax data of a target enterprise are acquired through a data acquisition module; through a data fusion module, performing distributed cleaning on abnormal data in the invoice data, the enterprise financial data and the industry tax data based on the established data mapping rule base, and performing real-time fusion to obtain a dynamic data pool; using a risk diagnosis module to extract compliance rules from enterprise finance and taxation legal provisions as conditions, using the trained random forest regression model to predict the dynamic data pool to obtain a reasonable tax threshold value, and determining a risk diagnosis result according to the reasonable tax threshold value; the risk diagnosis result is analyzed through the early warning module, the weight of each risk index is obtained and used for early warning the enterprise finance and taxation risk and generating the risk report of the target enterprise, the island problem of enterprise finance and taxation data is solved, and the finance and taxation management efficiency is improved.

The invention discloses a financial flow situation awareness system and method based on a multi-modal large model, and relates to the technical field of supply chain financial risk control. Aiming at the problems of data isolation, high processing delay and risk perception lagging in the existing storage pledge financing scene, the method comprises the following steps: obtaining a storage digital planar graph, dividing logic sub-regions, collecting and processing multi-source data of each sub-region in parallel, and extracting pledge stock time sequence data and warehouse receipt information by utilizing a visual and text model respectively; constructing a sub-region association map by taking the cargo identifier as a node and fusing the fund flow; and fusing all the sub-maps to construct a global association map, performing cross-regional consistency verification and anomaly recognition, generating a dynamic risk judgment result, and outputting hierarchical situation awareness information. According to the invention, accurate association and panoramic risk perception of the "object-bill-money" state are realized, and the real-time performance and accuracy of risk identification and the expandability of the system are improved.

The invention relates to the technical field of information intelligent processing, and discloses an accounting document information intelligent processing system, which comprises the steps of collecting bill characteristics, bill two-dimensional codes, business persons, business names and business amounts of enterprise bills based on laser scanning; and judging whether the bill characteristics are qualified or not according to whether the positions, colors and fonts of the special invoice seals, the tax control codes and the two-dimensional codes in the bill characteristics are consistent with the tax department filing template or not. According to the invention, the physical characteristics of the bill are automatically compared with the filing template of the tax department through the laser scanning technology, and the invoice state of the database of the tax bureau is checked through real-time networking; according to the double verification mechanism of physical characteristics and dynamic tax data, the problems that traditional manual verification is low in efficiency and prone to missing detection are solved, the risks of false bills and repeated reimbursement are completely eradicated from the source, and a high-credibility data basis is provided for subsequent processes.

The invention discloses a risk identification method and device based on invoice information, equipment, a storage medium and a product, and relates to the technical field of data processing, and the method comprises the steps: extracting field information and remark information of an invoice through a large model, the large model comprises a visual encoder, a layout understanding module, a text encoder, a multi-modal fusion module and an information structured decoder; performing risk verification on the invoice based on the field information and the remark information to obtain a risk verification result; and determining a risk level according to the risk verification result, and determining a target processing strategy according to the risk level. According to the method and the device, the potential risk in the invoice can be accurately identified.