Cross-border e-commerce full-process management system and method based on intelligent matching

Abstract

The invention relates to the technical field of cross-border e-commerce informatization systems, in particular to a cross-border e-commerce full-process management system and method based on intelligent matching, and the system comprises an order management module which is used for receiving and processing cross-border e-commerce sales order data; generating an order message; the intelligent matching module is used for receiving the order message sent by the order management module; based on the order message, executing an order closing matching operation; the customs declaration management module is in communication connection with the intelligent matching module and is used for receiving a matching result of the intelligent matching module; generating customs declaration data and submitting customs declaration; the inventory management module is used for updating domestic and overseas inventory information in real time; based on the order data and the customs declaration data, executing inventory adjustment; the financial management module is used for processing cross-border payment and settlement businesses; and financial statements and tax declaration data are generated, so that deep integration of core functions of order management, intelligent matching, customs declaration management, inventory management, financial management and the like is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of cross-border e-commerce information systems, and more specifically, to a cross-border e-commerce full-process management system and method based on intelligent matching. Background Art

[0002] With the acceleration of globalization and the popularization of Internet technology, the cross-border e-commerce industry has shown a booming development in recent years. However, with the rapid growth of the industry, cross-border e-commerce companies are also facing increasingly complex operational management challenges. Traditional cross-border e-commerce management systems are unable to cope with the processing of large orders, intelligent matching, customs declaration management, inventory optimization, and financial processing.

[0003] At present, most cross-border e-commerce management systems on the market adopt a modular design, and each functional module is relatively independent. Although this design improves the flexibility of the system to a certain extent, it also leads to the problem of information islands. For example, there is often a delay in data synchronization between the order management system and the inventory management system, resulting in inaccurate inventory information, which in turn affects the efficiency and accuracy of order fulfillment. In addition, the existing systems have limited capabilities in intelligent matching, and most of them rely on simple rule matching. They cannot effectively handle complex cross-border order scenarios, often require manual intervention, are inefficient and prone to errors.

[0004] In terms of customs declaration management, the existing system can usually only provide basic customs declaration form generation functions, lacking real-time tracking and intelligent application of customs policies, resulting in frequent errors and delays in the customs declaration process. In terms of inventory management, traditional systems often adopt a static inventory management model and cannot be dynamically adjusted according to real-time order conditions and market changes, resulting in inventory backlogs or out-of-stock problems.

[0005] Financial management is another problem that needs to be solved urgently. The existing system often requires a lot of manual operations when processing cross-border payments and foreign exchange settlements, which is not only inefficient but also prone to errors. In addition, due to the lack of intelligent financial analysis tools, it is difficult for corporate managers to grasp the company's financial status in a timely and accurate manner, affecting the timeliness and accuracy of decision-making.

[0006] In the face of these challenges, a cross-border e-commerce system that can achieve full-process intelligent management is urgently needed. The system should be able to organically integrate core functions such as order processing, intelligent matching, customs declaration management, inventory optimization and financial processing, and achieve seamless collaboration between modules, thereby improving the operational efficiency and competitiveness of cross-border e-commerce companies. Summary of the invention

[0007] The present invention aims to solve the technical problems existing in the existing cross-border e-commerce management system, such as information silos, insufficient intelligent matching ability, low customs declaration efficiency, inflexible inventory management, and complex financial processing. Through innovative system architecture design and advanced algorithm application, the present invention provides a cross-border e-commerce full-process management system and method based on intelligent matching, realizing intelligent management of the entire chain from order processing to financial management.

[0008] To solve the above technical problems, the present invention adopts the following technical solutions:

[0009] A cross-border e-commerce full-process management system based on intelligent matching, comprising:

[0010] An order management module, configured to:

[0011] Receive and process cross-border e-commerce sales order data;

[0012] Generate an order message;

[0013] An intelligent matching module, communicatively connected to the order management module, configured to:

[0014] Receive the order message sent by the order management module to which it belongs;

[0015] Perform customs clearance matching operations based on the order message;

[0016] A customs declaration management module, communicatively connected to the intelligent matching module, configured to:

[0017] Receive the matching result of the intelligent matching module;

[0018] Generate customs declaration data and submit it for customs declaration;

[0019] An inventory management module, communicatively connected to the order management module and the customs declaration management module, configured to:

[0020] Real-time update domestic and foreign inventory information;

[0021] Perform inventory adjustment based on the order data and customs declaration data;

[0022] A financial management module, communicatively connected to the customs declaration management module and the intelligent matching module, configured to:

[0023] Process cross-border payment and foreign exchange settlement operations;

[0024] Generate financial statements and tax declaration data.

[0025] Preferably, the order management module includes:

[0026] An order import unit, configured to receive sales order data from multiple e-commerce platforms;

[0027] An order processing unit for validating and collating the sales order data;

[0028] A message generation unit for generating a standardized order message based on the processed order data.

[0029] Preferably, the intelligent matching module includes:

[0030] A data analysis unit for performing data analysis and feature extraction on the order message;

[0031] A matching rule library for storing and managing matching rules;

[0032] A matching execution unit for performing the customs clearance matching operation according to the rules in the matching rule library;

[0033] A self-learning unit for continuously optimizing the matching rules according to the matching results.

[0034] Preferably, the customs declaration management module includes:

[0035] A customs declaration form generation unit for generating customs declaration form data according to the matching results;

[0036] A declaration interface unit for docking with the customs system and submitting declaration data;

[0037] A status monitoring unit for real-time monitoring of the declaration status and feedback of the results.

[0038] Preferably, the inventory management module includes:

[0039] An inventory information collection unit for real-time collection of inventory data in domestic and foreign warehouses;

[0040] An inventory analysis unit for analyzing the inventory level and turnover situation;

[0041] An inventory adjustment unit for automatically adjusting the inventory according to the order and customs declaration information.

[0042] Preferably, the financial management module includes:

[0043] A payment processing unit for processing cross-border payment operations;

[0044] A foreign exchange settlement management unit for managing foreign exchange settlement operations;

[0045] A report generation unit for generating financial reports;

[0046] A tax declaration unit for preparing and submitting tax declaration data.

[0047] Preferably, it further includes:

[0048] A data analysis module, which is communicatively connected to the order management module, the intelligent matching module, the customs declaration management module, the inventory management module and the financial management module, and is used for:

[0049] Collect and analyze the operation data of each module;

[0050] Generate business insight reports and optimization suggestions.

[0051] Preferably, it further includes:

[0052] A risk control management module, which is communicatively connected to the order management module and the intelligent matching module, and is used for:

[0053] Conduct a risk assessment on the order;

[0054] Adjust the matching strategy according to the assessment results.

[0055] Preferably, the communication connection between the intelligent matching module and the customs declaration management module adopts an encrypted channel to ensure the security of data transmission; it further includes: a tax refund intelligent matching module, which is communicatively connected to the financial management module and is used for:

[0056] Receive the tax refund application data sent by the financial management module;

[0057] Based on the tax refund policy database and historical tax refund data, perform intelligent matching operations;

[0058] Generate an optimal tax refund plan;

[0059] The tax refund intelligent matching module includes: a tax refund data analysis unit for analyzing tax refund application data and historical tax refund data; a policy matching unit for matching tax refund applications with the latest tax refund policies; and a plan generation unit for generating an optimal tax refund plan based on the matching results.

[0060] The cross-border e-commerce full-process management method based on intelligent matching using the system includes the following steps:

[0061] Receive and process cross-border e-commerce sales order data and generate an order message;

[0062] Perform intelligent matching operations on the order message to generate a matching result;

[0063] Generate customs declaration form data based on the matching result and submit it to the customs for declaration;

[0064] Real-time update and adjust inventory information according to order data and customs declaration form data;

[0065] Process cross-border payment and foreign exchange settlement operations to generate financial statements and tax declaration data.

[0066] Compared with the prior art, the beneficial effects of the present invention are reflected in the following aspects:

[0067] The beneficial effects of the present invention are reflected in the innovation of the overall architecture and the synergy among various modules. First of all, the present invention adopts a highly integrated system architecture, breaking the limitation that each functional module in the traditional system is relatively independent. By establishing a unified data center and an intelligent decision-making engine, the deep integration of core functions such as order management, intelligent matching, customs declaration management, inventory management, and financial management is realized. This architecture design not only eliminates the problem of information islands but also greatly improves the response speed and data consistency of the system.

[0068] In terms of intelligent matching, the present invention introduces a multi-dimensional matching algorithm based on machine learning, significantly improving the accuracy and efficiency of matching. This algorithm not only considers traditional factors such as price and quantity but also introduces dimensions of time and commodity characteristics, enabling it to better adapt to complex cross-border order scenarios. Through continuous self-learning and optimization, the matching ability of the system will continuously improve with the increase in usage time, demonstrating strong adaptability and scalability.

[0069] The collaboration between the customs declaration management module and the intelligent matching module greatly improves the efficiency and accuracy of customs declaration. The system can automatically generate customs declaration forms that meet the requirements of the customs according to the matching results, and through real-time policy updates and intelligent optimization algorithms, continuously improve the customs clearance passing rate. This not only reduces the need for manual intervention but also greatly shortens the customs clearance time, saving a large amount of time and labor costs for enterprises.

[0070] In terms of inventory management, the present invention realizes the leap from static management to dynamic optimization. Through close cooperation with the order management and customs declaration management modules, the system can adjust inventory strategies in real time, optimize inventory allocation, and effectively reduce the risks of inventory backlog and out-of-stock. This dynamic inventory management mode not only improves the inventory turnover rate but also significantly improves the cash flow situation of enterprises.

[0071] The innovative design of the financial management module provides a comprehensive financial intelligence solution for enterprises. The system integrates multiple international payment channels and introduces an intelligent exchange rate management mechanism, greatly simplifying the cross-border payment and foreign exchange settlement processes. The automated financial statement generation and intelligent tax planning functions provide timely and accurate financial insights for enterprise managers, supporting more scientific decision-making.

[0072] More notably, the functions of these modules are not simply additive. Instead, through in-depth data sharing and collaborative decision-making, the overall efficiency has been multiplied. For example, the high-precision matching results of the intelligent matching module not only improve the order processing efficiency but also provide more accurate demand forecasts for inventory management and optimize the customs declaration process. Such multi-dimensional synergistic effects have greatly enhanced the operating efficiency of the entire system.

[0073] Generally speaking, through the innovative system architecture and advanced algorithm applications, the present invention has successfully solved many technical problems faced by existing cross-border e-commerce management systems. It not only significantly improves the operating efficiency of cross-border e-commerce enterprises but also provides them with more intelligent and accurate decision-making support, effectively enhancing the market competitiveness of enterprises. With the continuous optimization and function expansion of the system, it can be foreseen that the present invention will play an increasingly important role in promoting the intelligent transformation of the cross-border e-commerce industry. BRIEF DESCRIPTION OF THE DRAWINGS

[0074] Figure 1 It is a block diagram of the overall system process of the present invention.

[0075] Figure 2 It is a logic block diagram of the order management module of the present invention.

[0076] Figure 3 It is a logic block diagram of the intelligent matching module of the present invention.

[0077] Figure 4 It is a logic block diagram of the customs declaration management module of the present invention.

[0078] Figure 5 It is a logic block diagram of the inventory management module of the present invention.

[0079] Figure 6 It is a logic block diagram of the financial management module of the present invention.

[0080] Figure 7 It is a logic block diagram of the tax refund intelligent matching module of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0081] As Figure 1-7 shown, the present invention provides a cross-border e-commerce full-process management system and method based on intelligent matching. The system includes an order management module 1, an intelligent matching module 2, a customs declaration management module 3, an inventory management module 4, and a financial management module 6. These modules work together through communication connections to achieve the full-process management of cross-border e-commerce operations.

[0082] First, the order management module 1 is used to receive and process cross-border e-commerce sales order data and generate order messages. In a preferred embodiment of the present invention, the order management module 1 can automatically obtain order data from multiple mainstream e-commerce platforms (such as Amazon, eBay, etc.) through API interfaces or data import methods. The order management module 1 performs preliminary processing on the received order data, including data format standardization, order validity verification, etc. After processing, the order management module 1 generates a standardized order message for subsequent modules to process.

[0083] The intelligent matching module 2 is communicatively connected to the order management module 1 and is used to receive the order message sent by the order management module 1 and perform customs clearance matching operations based on this message. The intelligent matching module 2 of the present invention adopts an innovative multi-dimensional matching algorithm, which can significantly improve the accuracy and efficiency of matching. This algorithm considers multiple-dimensional features such as product information, price, quantity, time, etc., and performs intelligent matching through a machine learning model.

[0084] To further improve the performance and adaptability of the intelligent matching module 2, the present invention introduces a series of innovative algorithms to form a highly collaborative intelligent matching system. These algorithms include multi-dimensional feature vector generation algorithms, dynamic weight adaptive algorithms, non-linear matching degree calculation algorithms, and adaptive threshold optimization algorithms.

[0085] First, a multi-dimensional feature vector generation algorithm is introduced to convert order information into computable feature vectors:

[0086] ,

[0087] where, is the feature vector, is the price factor, is the quantity factor, is the time factor, is the product feature factor. is the corresponding weight coefficient, is the non-linear mapping function. Specifically, the following formulas are used to calculate each factor:

[0088] ,

[0089] ,

[0090] ,

[0091] ,

[0092] where, is the order price, is the average price; is the order quantity, and are the minimum and maximum quantities respectively; is the order time, is the business cycle; is the product feature value, is the reference feature value, is the adjustment coefficient.

[0093] Based on the above feature vectors, a dynamic weight adaptive algorithm is introduced to optimize the feature weights:

[0094] ,

[0095] where is the weight vector at time is the learning rate, is the loss function, is the gradient of the loss function.

[0096] The loss function is defined as:

[0097]

[0098] where is the true label, is the sigmoid function.

[0099] Using the optimized weights, a non - linear matching degree calculation algorithm is designed:

[0100] ,

[0101] where is the matching degree, is the weight vector, is the feature vector, is the bias term, and are the adjustment parameters.

[0102] Finally, an adaptive threshold optimization algorithm is introduced to dynamically adjust the matching threshold:

[0103] ,

[0104] where is the matching threshold at time is the matching degree at time is the historical average matching degree, and are the adjustment coefficients.

[0105] The output of the multi-dimensional feature vector generation algorithm serves as the input of the dynamic weight adaptation algorithm, and the output of the latter serves as the input of the non-linear matching degree calculation algorithm. Finally, the matching degree is used by the adaptive threshold optimization algorithm to adjust the system parameters. This design not only improves the accuracy of matching, but also realizes the adaptive optimization of the system, and can effectively cope with the complex and changeable order matching scenarios in cross-border e-commerce.

[0106] Through this series of innovative algorithms, the present invention has achieved a qualitative leap in intelligent matching, greatly improving the efficiency and accuracy of the cross-border e-commerce full-process management system.

[0107] Preferably, the present invention adopts an improved cosine similarity algorithm to calculate the commodity information similarity I:

[0108] ,

[0109] where and respectively represent the values of the commodity to be matched and the target commodity in the i-th feature dimension.

[0110] The customs declaration management module 3 is communicatively connected to the intelligent matching module 2, and is used to receive the matching result of the intelligent matching module 2, and generate customs declaration form data accordingly, and then submit a customs declaration. In an embodiment of the present invention, the customs declaration management module 3 can automatically fill in various information required for the customs declaration form according to the matching result, such as commodity codes, declared prices, countries of origin, etc. In addition, the customs declaration management module 3 can also perform compliance checks on the generated customs declaration form through preset rules to reduce the customs declaration error rate.

[0111] The system of the present invention further includes a refined structure of the order management module 1. Specifically, the order management module 1 includes an order import unit 11, an order processing unit 12, and a message generation unit 13. The order import unit 11 is used to receive sales order data from multiple e-commerce platforms. In practical applications, the order import unit 11 can support multiple data formats, such as JSON, CSV, etc., to adapt to the data outputs of different platforms.

[0112] The order processing unit 12 is used to verify and sort out the sales order data. This process includes, but is not limited to: checking the integrity of the order information, verifying the validity of the customer address, identifying and marking abnormal orders, etc. In a preferred embodiment of the present invention, the order processing unit 12 can also use natural language processing technology to analyze the order description and extract key information to assist the subsequent intelligent matching process.

[0113] The message generation unit 13 is used to generate a standardized order message based on the processed order data. This standardization process is crucial for ensuring data consistency among various modules of the system. In the present invention, the order message adopts the XML format, and this structured message format facilitates subsequent data analysis and processing by the intelligent matching module 2.

[0114] The refined structure of the intelligent matching module 2 includes a data analysis unit 21, a matching rule library 22, a matching execution unit 23, and a self-learning unit 24. The data analysis unit 21 is used to perform data analysis and feature extraction on the order message. In this process, the data analysis unit 21 extracts key information in the order, such as product SKU, price, quantity, etc., and converts this information into feature vectors that can be used by the matching algorithm.

[0115] The matching rule library 22 is used to store and manage matching rules. These rules can be fixed rules formulated based on expert experience or rules dynamically generated through machine learning algorithms. In an embodiment of the present invention, the matching rule library 22 adopts a graph database storage structure, which can effectively express complex matching rule relationships and support fast rule query and update.

[0116] The matching execution unit 23 is used to perform the order closing matching operation according to the rules in the matching rule library 22. This process involves complex algorithm calculations, such as the multi-dimensional matching algorithm mentioned above. The matching execution unit 23 calculates the matching degree of each order to be matched with potential matching items and selects the item with the highest matching degree as the final matching result.

[0117] The self-learning unit 24 is an innovation point of the present invention. It is used to continuously optimize the matching rules according to the matching results. The self-learning unit 24 adopts a reinforcement learning algorithm and automatically adjusts the parameters of the matching rules by analyzing the accuracy and efficiency of the matching results. For example, if it is found that the matching accuracy of a certain type of product is low, the self-learning unit 24 will appropriately increase the weight of the features of this type of product in the matching algorithm. This adaptive mechanism enables the system to continuously improve the accuracy and efficiency of matching.

[0118] As can be seen from the above detailed description, the system of the present invention has remarkable innovation and practicability in order management and intelligent matching. This system can not only efficiently process a large number of cross-border e-commerce orders, but also achieve accurate customs clearance matching through intelligent algorithms, greatly improving the management efficiency of cross-border e-commerce business. The system of the present invention also includes a refined structure of the customs declaration management module 3. Specifically, the customs declaration management module 3 includes a customs declaration form generation unit 31, a declaration interface unit 32, and a status monitoring unit 33. The customs declaration form generation unit 31 is used to generate customs declaration form data according to the matching results of the intelligent matching module 2. In a preferred embodiment of the present invention, the customs declaration form generation unit 31 adopts an intelligent customs declaration form generation algorithm, which can automatically identify the customs code of goods, calculate the payable tax amount, and adjust the declaration strategy according to the latest customs policies.

[0119] The declaration interface unit 32 is used to connect with the customs system and submit declaration data. The system of the present invention adopts a standardized data exchange interface, supporting multiple customs declaration protocols, such as the single window system of the Chinese customs and the ACE system of the US customs. This flexible interface design enables this system to adapt to the customs declaration requirements of different countries and regions.

[0120] The status monitoring unit 33 is used to monitor the declaration status in real time and feedback the results. Preferably, the status monitoring unit 33 adopts a real-time notification mechanism based on message queues, which can notify relevant personnel in a timely manner when the declaration status changes. In addition, the status monitoring unit 33 also has an intelligent analysis function, which can automatically identify abnormal declaration statuses and give handling suggestions.

[0121] In the system of the present invention, the inventory management module 4 is communicatively connected with the order management module 1 and the customs declaration management module 3, and is used to update the domestic and foreign inventory information in real time, and perform inventory adjustment based on order data and customs declaration form data. The refined structure of the inventory management module 4 includes an inventory information collection unit 41, an inventory analysis unit 42, and an inventory adjustment unit 43.

[0122] The inventory information collection unit 41 is used to collect the inventory data of domestic and foreign warehouses in real time. In an embodiment of the present invention, the inventory information collection unit 41 adopts a distributed data collection architecture, and can obtain real-time inventory data from multiple warehouse management systems simultaneously. To ensure the accuracy and timeliness of the data, this system adopts a data verification mechanism based on blockchain technology, effectively preventing the tampering and loss of inventory data.

[0123] The inventory analysis unit 42 is used to analyze the inventory level and turnover situation. The system of the present invention introduces advanced predictive analysis algorithms in this link. For example, for seasonal goods, the inventory analysis unit 42 adopts a time series analysis method, which can accurately predict the inventory demand in the future for a period of time. Specifically, the prediction algorithm can be expressed as:

[0124] ,

[0125] Among them, is the predicted value at time t, is the actual demand at time t - 1, is the smoothing coefficient (0 < < 1). By dynamically adjusting , this system can adapt to the demand characteristics of different types of commodities.

[0126] The inventory adjustment unit 43 is used to automatically adjust the inventory according to the order and customs declaration information. Preferably, the inventory adjustment unit 43 adopts an intelligent inventory allocation algorithm, which can perform optimal inventory allocation among multiple warehouses. This algorithm takes into account multiple factors such as transportation costs, inventory holding costs, and shortage costs, and solves the optimal inventory allocation plan through a linear programming model.

[0127] Preferably, this system also introduces a dynamic key management mechanism. This mechanism can automatically update the encryption key regularly, greatly reducing the risk of the key being cracked. Specifically, the system will automatically generate a new key pair every certain period (such as 24 hours) and synchronize it among modules through a secure key exchange protocol. This dynamic key management method significantly improves the security of the system, so that even if the key at a certain moment is obtained by an attacker, the system data cannot be accessed for a long time.

[0128] In addition, the system of the present invention also integrates digital signature technology in the encryption channel. Each message transmitted through the encryption channel will be attached with the digital signature of the sender, and the receiver can ensure the authenticity and integrity of the message by verifying the signature. This mechanism effectively prevents security threats such as man-in-the-middle attacks and message tampering.

[0129] The system of the present invention also includes a tax refund intelligent matching module 5, which is communicatively connected to the financial management module 6 and is used to optimize the tax refund process of cross-border e-commerce enterprises. The tax refund intelligent matching module 5 mainly includes a tax refund data analysis unit 51, a policy matching unit 52, and a solution generation unit 53.

[0130] The tax refund data analysis unit 51 is responsible for receiving and analyzing the tax refund application data from the financial management module 6, and will also conduct in-depth analysis of historical tax refund data to identify tax refund patterns and trends. This unit adopts advanced data mining technology and can extract valuable features and rules from a large amount of tax refund data.

[0131] The policy matching unit 52 maintains a real-time updated tax refund policy database. This unit can intelligently match the tax refund application with the latest tax refund policies to ensure that the tax refund application complies with the latest regulatory requirements. To improve the accuracy and efficiency of the matching, the present invention introduces an innovative policy matching algorithm:

[0132] ,

[0133] wherein, is the policy matching degree, is the i-th feature of the tax refund application, is the i-th element of the policy, is the similarity function, is the weight coefficient, is the policy novelty function, is the adjustment parameter.

[0134] The solution generation unit 53 generates an optimal tax refund solution based on the analysis of the tax refund data and the result of the policy matching. This unit adopts a multi-objective optimization algorithm, considering both maximizing the tax refund amount and minimizing the compliance risk:

[0135] ,

[0136] ,

[0137] wherein, is the tax refund amount function, is the compliance risk function is the constraint condition.

[0138] By introducing the tax refund intelligent matching module 5, the system of the present invention can significantly improve the tax refund efficiency and accuracy of cross-border e-commerce enterprises, effectively reduce the tax refund risk, and create more value for enterprises. The seamless integration of this module with other modules further enhances the advantages of the present invention in the whole process management of cross-border e-commerce.

[0139] The present invention also provides a cross-border e-commerce whole process management method based on intelligent matching, and this method includes the following steps:

[0140] First, receive and process the cross-border e-commerce sales order data to generate an order message. In this step, the system will automatically obtain the sales order information from major e-commerce platforms, and after data cleaning and standardization processing, generate an order message in a unified format. Preferably, this method adopts an intelligent data processing algorithm, which can automatically identify and correct the abnormal data in the order, such as incorrect address formats, unreasonable commodity quantities, etc.

[0141] Next, perform an intelligent matching operation on the order message to generate a matching result. This step is the core of the method of the present invention and adopts an innovative multi-dimensional matching algorithm. This algorithm not only considers traditional price and quantity factors, but also introduces time dimension and commodity feature dimension, greatly improving the accuracy of matching. In an embodiment of the present invention, the core of the matching algorithm can be expressed as:

[0142] ,

[0143] where S is the final matching score, , , and represent price similarity, quantity similarity, time similarity and feature similarity respectively, , , and are the corresponding weight coefficients. These weight coefficients can be dynamically adjusted through machine learning algorithms to adapt to different types of commodities and market conditions.

[0144] Subsequently, generate customs declaration form data based on the matching result and submit it for customs declaration. An intelligent customs declaration form generation mechanism is introduced in this step of the method. The system will automatically fill in the information required for the customs declaration form according to the matching result, such as commodity code, declared price, country of origin, etc. Preferably, the system will also optimize the generated customs declaration form according to the latest customs policies and historical declaration data to improve the customs clearance efficiency. For example, if the inspection rate of a certain type of commodity is relatively high recently, the system will automatically increase the detail level of the declaration information for this type of commodity.

[0145] Then, update and adjust the inventory information in real time according to the order data and the customs declaration form data. The method adopts an advanced inventory management algorithm, which can perform intelligent inventory allocation among multiple warehouses. Specifically, the system will calculate the optimal inventory allocation plan according to multiple factors such as order situation, customs declaration status, transportation time, etc. This algorithm can be expressed as:

[0146] ,

[0147] where Z is the total cost, is the unit transportation cost from warehouse i to destination j, is the transportation quantity from warehouse i to destination j, is the unit inventory holding cost of warehouse i, is the initial inventory of warehouse i. By solving this optimization problem, the system can obtain the inventory allocation plan with the lowest cost.

[0148] Finally, process cross-border payment and foreign exchange settlement operations, and generate financial statements and tax declaration data. In this step, this method integrates multiple international payment channels and introduces an intelligent exchange rate management mechanism. The system automatically executes foreign exchange settlement operations based on real-time exchange rates and preset rules, optimizing the enterprise's exchange rate earnings. In addition, the system can automatically generate various financial statements and tax declaration materials, greatly reducing the workload and error rate of manual operations.

[0149] The system of the present invention further includes a financial management module 6, which is communicatively connected to the customs declaration management module 3 and the intelligent matching module 2, and is used to process cross-border payment and foreign exchange settlement operations, and generate financial statements and tax declaration data. The detailed structure of the financial management module 6 includes a payment processing unit 61, a foreign exchange settlement management unit 62, a statement generation unit 63, and a tax declaration unit 64.

[0150] The payment processing unit 61 is used to process cross-border payment operations. In a preferred embodiment of the present invention, the payment processing unit 61 integrates multiple international payment channels, such as PayPal, Stripe, etc., and can automatically select the optimal payment path to reduce transaction costs. In addition, the payment processing unit 61 also has a risk control function, which can monitor abnormal transactions in real time and prevent cross-border payment risks.

[0151] The foreign exchange settlement management unit 62 is used to manage foreign exchange settlement operations. The system of the present invention introduces an intelligent exchange rate management mechanism in this link. The foreign exchange settlement management unit 62 can obtain real-time exchange rate information of various currencies and automatically execute foreign exchange settlement operations according to preset rules. For example, when the exchange rate of a certain currency reaches a preset threshold, the system will automatically trigger the foreign exchange settlement process to optimize the enterprise's exchange rate earnings.

[0152] The statement generation unit 63 is used to generate financial statements. The system of the present invention adopts a modular statement design and can flexibly generate various financial statements, such as balance sheets, income statements, cash flow statements, etc. Preferably, the statement generation unit 63 also has a data visualization function and can generate intuitive charts to help managers quickly understand the financial status of the enterprise.

[0153] The tax declaration unit 64 is used to prepare and submit tax declaration data. In an embodiment of the present invention, the tax declaration unit 64 adopts an intelligent tax planning algorithm, which can formulate an optimal tax plan for the enterprise on the premise of being legal and compliant. This algorithm takes into account multiple factors such as the tax policies of different countries and the business conditions of the enterprise, and obtains the optimal solution through a complex calculation model.

[0154] From the above detailed description, it can be seen that the system of the present invention has significant innovation and practicality in customs declaration management, inventory management, and financial management. This system can not only efficiently handle all aspects of cross-border e-commerce business but also achieve precise decision support through intelligent algorithms, greatly improving the operation efficiency and competitiveness of cross-border e-commerce enterprises. The communication connection between the intelligent matching module 2 and the customs declaration management module 3 in the system of the present invention adopts an encrypted channel to ensure the security of data transmission. This design takes into account the sensitive information involved in cross-border e-commerce business, such as customer information, transaction amounts, etc., which requires a high level of security protection. In a preferred embodiment of the present invention, the encrypted channel adopts the Advanced Encryption Standard (AES) algorithm, specifically using a 256-bit key, ensuring the confidentiality and integrity of the data transmission process.

[0155] From the above detailed description, it can be seen that the method of the present invention has significant innovation and practicality in the full-process management of cross-border e-commerce. Through intelligent algorithms and automated processing, this method realizes the full-process optimization from order processing to customs declaration, inventory management, and financial processing, and can effectively improve the operation efficiency and competitiveness of cross-border e-commerce enterprises. To verify the superiority of the cross-border e-commerce full-process management system and method based on intelligent matching of the present invention, the following key indicators are selected for testing by the present invention: order processing efficiency, intelligent matching accuracy rate, customs declaration passing rate, inventory turnover rate, and financial processing efficiency. These indicators comprehensively reflect the core performance of the cross-border e-commerce management system.

[0156] In the actual test, the present invention selects a medium-sized cross-border e-commerce enterprise as the test object. This enterprise mainly deals in electronic products and household goods and processes approximately 10,000 cross-border orders per month. The test period is 3 months, and the system of the present invention (Example 1) and the original traditional management system of this enterprise (Comparative Example 1) are used for comparison respectively.

[0157] Example 1 adopts the full set of systems of the present invention, including an intelligent matching module, a customs declaration management module, an inventory management module, and a financial management module. This system makes full use of artificial intelligence and big data technologies to achieve highly automated and intelligent cross-border e-commerce management.

[0158] Comparative Example 1 uses the original traditional management system of this enterprise, mainly relying on manual operations and simple data processing tools, lacking intelligent and automated functions.

[0159] Table 1. Comparison of the detection results between Example 1 and Comparative Example 1

[0160] Index Detection method Example 1 Comparative Example 1 Order processing efficiency (orders / hour) Count the number of orders processed per unit time 450 120 Intelligent matching accuracy rate (%) Sample and check the correctness of the matching results 98.5% 85% Customs declaration passing rate (%) Count the proportion of first declarations that pass 96% 78% Inventory turnover rate (times / month) Calculate the ratio of monthly cost of sales to average inventory 4.2 2.8 Financial processing efficiency (hours / month) Count the time required for monthly financial settlement 24 96

[0161] From the detection results in Table 1, it can be seen that the system of the present invention is significantly superior to the traditional management system in all key indicators. The specific analysis is as follows:

[0162] 1. Order processing efficiency: The system of the present invention can process 3.75 times as many orders per unit time as the traditional system. This is mainly due to the high degree of automation of the system, which can quickly process and classify order information.

[0163] 2. Intelligent matching accuracy: The intelligent matching module of the present invention has increased the matching accuracy to 98.5%, which is 13.5 percentage points higher than that of the traditional system. This means that the system can more accurately match orders with corresponding inventory, customs declaration information, etc., greatly reducing the need for manual intervention.

[0164] 3. Customs declaration passing rate: After adopting the system of the present invention, the first-time declaration passing rate has increased to 96%, which is 18 percentage points higher than that of the traditional system. This shows that the present system can better adapt to customs policies and generate more accurate and compliant customs declarations.

[0165] 4. Inventory turnover rate: The system of the present invention has increased the monthly inventory turnover rate to 4.2 times, which is 50% higher than that of the traditional system. This reflects the advantage of the system in inventory management, which can better predict demand and optimize inventory.

[0166] 5. Financial processing efficiency: After using the system of the present invention, the monthly financial settlement time has been reduced from 96 hours to 24 hours, and the efficiency has been increased by 75%. This is due to the automated financial processing and report generation functions of the system.

[0167] These test results fully demonstrate the significant advantages of the system of the present invention in improving the operation efficiency of cross-border e-commerce. The system not only greatly improves the efficiency of order processing and financial processing, but also improves the accuracy of business through intelligent matching and optimized customs declaration processes. It is particularly worth noting that the increase in inventory turnover rate reflects the contribution of the system to the capital utilization efficiency, which is of great significance to the cash flow management of cross-border e-commerce enterprises.

[0168] Considering all indicators comprehensively, it can be considered that Example 1 represents the best implementation mode of the present invention. It gives full play to the advantages of core functions such as intelligent matching, automated customs declaration, intelligent inventory management and efficient financial processing, and has achieved remarkable results in practical applications. This comprehensive performance improvement can not only help cross-border e-commerce enterprises reduce operating costs, but also improve customer satisfaction and enhance the market competitiveness of enterprises.

[0169] It should be noted that although this test was carried out in a specific enterprise and a specific period, considering the representativeness of the test samples and the rationality of the test cycle, these results largely reflect the general applicability and superiority of the system of the present invention.

[0170] The above are only the preferred specific embodiments of the present invention; however, the protection scope of the present invention is not limited thereto. Any person familiar with the art, within the scope disclosed by the present invention, making equivalent substitutions or changes according to the solution and improved concept of the present invention, shall be covered by the protection scope of the present invention.

Claims

1. Cross-border e-commerce full-process management system based on intelligent matching, characterized in that including: an order management module, configured to: receive and process cross-border e-commerce sales order data; generate order messages; an intelligent matching module, communicatively connected to the order management module, configured to: receive the order messages sent by the order management module; perform customs clearance matching operations based on the order messages; a customs declaration management module, communicatively connected to the intelligent matching module, configured to: receive the matching results of the intelligent matching module; generate customs declaration data and submit it for customs declaration; an inventory management module, communicatively connected to the order management module and the customs declaration management module, configured to: update domestic and foreign inventory information in real time; perform inventory adjustment based on the order data and customs declaration data; a financial management module, communicatively connected to the customs declaration management module and the intelligent matching module, configured to: handle cross-border payment and foreign exchange settlement operations; generate financial statements and tax declaration data.

2. The cross-border e-commerce full-process management system based on intelligent matching according to claim 1, wherein, The order management module includes: an order import unit, configured to receive sales order data from multiple e-commerce platforms; an order processing unit, configured to verify and sort out the sales order data; a message generation unit, configured to generate standardized order messages according to the processed order data.

3. The cross-border e-commerce full-process management system based on intelligent matching according to claim 1, characterized in that The intelligent matching module includes: a data analysis unit, configured to perform data analysis and feature extraction on order messages; a matching rule library, configured to store and manage matching rules; a matching execution unit, configured to perform customs clearance matching operations according to the rules in the matching rule library; a self-learning unit, configured to continuously optimize the matching rules according to the matching results.

4. The cross-border e-commerce full-process management system based on intelligent matching according to claim 1, characterized in that The customs declaration management module includes: a customs declaration form generation unit, configured to generate customs declaration data according to the matching results; a declaration interface unit, configured to interface with the customs system and submit declaration data; a status monitoring unit, configured to monitor the declaration status in real time and feedback the results.

5. The cross-border e-commerce full-process management system based on intelligent matching according to claim 1, characterized in that The inventory management module includes: an inventory information collection unit, configured to collect inventory data of domestic and foreign warehouses in real time; an inventory analysis unit, configured to analyze inventory levels and turnover situations; an inventory adjustment unit, configured to automatically adjust inventory according to order and customs declaration information.

6. The cross-border e-commerce full-process management system based on intelligent matching according to claim 1, characterized in that, The financial management module includes: a payment processing unit, configured to handle cross-border payment operations; a foreign exchange settlement management unit, configured to manage foreign exchange settlement operations; a statement generation unit, configured to generate financial statements; a tax declaration unit, configured to prepare and submit tax declaration data.

7. The cross-border e-commerce full-process management system based on intelligent matching according to claim 1, characterized in that, It further includes: a data analysis module, communicatively connected to the order management module, intelligent matching module, customs declaration management module, inventory management module and financial management module, configured to: collect and analyze the operation data of each module; generate business insight reports and optimization suggestions.

8. The cross-border e-commerce full-process management system based on intelligent matching according to claim 1, characterized in that, It further includes: a risk control management module, communicatively connected to the order management module and the intelligent matching module, configured to: perform risk assessment on orders; adjust the matching strategy according to the assessment results.

9. The cross-border e-commerce full-process management system based on intelligent matching according to claim 1, characterized in that, The communication connection between the intelligent matching module and the customs declaration management module adopts an encrypted channel to ensure the security of data transmission; it further includes: a tax refund intelligent matching module, communicatively connected to the financial management module, configured to: receive the tax refund application data sent by the financial management module; perform intelligent matching operations based on the tax refund policy database and historical tax refund data; generate an optimal tax refund plan; The tax refund intelligent matching module includes: a tax refund data analysis unit for analyzing tax refund application data and historical tax refund data; a policy matching unit for matching tax refund applications with the latest tax refund policies; and a solution generation unit for generating an optimal tax refund solution based on the matching results.

10. A cross-border e-commerce full-process management method based on intelligent matching, and a cross-border e-commerce full-process management system based on intelligent matching using the system according to any one of claims 1-9, characterized in that, It includes the following steps: Receiving and processing cross-border e-commerce sales order data to generate an order message; Performing an intelligent matching operation on the order message to generate a matching result; Generating customs declaration data based on the matching result and submitting it for customs declaration; Real-time updating and adjusting inventory information according to order data and customs declaration data; Processing cross-border payment and foreign exchange settlement operations to generate financial statements and tax declaration data.

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