CN112365165A - Cross-border e-commerce wind control management method and system - Google Patents
Cross-border e-commerce wind control management method and system Download PDFInfo
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Abstract
The application discloses a cross-border e-commerce wind control management method and a system, wherein the method comprises the following steps: receiving cross-border service related data, wherein the cross-border service related data comprises enterprise information, commodity information, e-commerce transaction orders, purchase warehousing orders, sale ex-warehouse orders and customs declaration data; calling a correlation database from a data center according to the cross-border service related data; and performing wind control judgment on the cross-border service related data by combining the correlation database and a preset wind control model, and outputting a wind control judgment result of the cross-border service. According to the method and the system, the cross-border business related data are received, the associated database is called from the data center according to the cross-border business related data, the wind control judgment result of the cross-border business is output through the combination of the related data and the preset wind control model, the risk control of the process of import and export trade activities is realized in the whole process, and the risk of the cross-border electric business enterprise is reduced.
Description
Technical Field
The application relates to the technical field of risk management, in particular to a cross-border e-commerce wind control management method and system.
Background
With the explosion of the cross-border e-commerce industry, the agency customs clearance business is one of the key services provided by the cross-border e-commerce enterprise for the enterprise.
At present, for the agency customs clearance business, a related risk management method and a related risk management system are not available, the risk is mainly controlled by the responsibility and the working experience of personnel, so that the risk control is not thorough, and certain risk problems exist for cross-border electric commerce and enterprise, such as the credit worthiness problem of a customer, the execution and control problem of a transaction process and the monitoring and management problem of accounts receivable.
Therefore, how to carry out risk management and control on the import and export trade activity process in the whole process and reduce the risk of the cross-border electric commerce enterprise is urgently needed to be solved by technical personnel in the field.
Disclosure of Invention
The application provides a cross-border electronic commerce wind control management method and system, which realize risk control on the import and export trade activity process in the whole process and reduce the risk of the cross-border electronic commerce enterprise.
In view of the above, a first aspect of the present application provides a cross-border e-commerce wind control management method, including:
receiving cross-border service related data, wherein the cross-border service related data comprises enterprise information, commodity information, e-commerce transaction orders, purchase warehousing orders, sale ex-warehouse orders and customs declaration data;
calling a correlation database from a data center according to the cross-border service related data;
and performing wind control judgment on the cross-border service related data by combining the correlation database and a preset wind control model, and outputting a wind control judgment result of the cross-border service.
Optionally, the invoking of the association database from the data center according to the cross-border service related data specifically includes:
if the cross-border service related data comprises enterprise information, third party platform enterprise credit investigation information data, customs enterprise management credit platform data and national credit platform data are called from the data center;
and if the cross-border service related data comprises commodity information, calling a sensitive word bank, a wild animal directory, an endangered item and a wild plant directory from the data center.
Optionally, the preset wind control model is specifically constructed as follows:
constructing a first-level index and a second-level index, wherein the first-level index corresponds to a plurality of second-level indexes respectively;
constructing a judgment matrix of the first-level index based on an AHP analytic hierarchy process;
calculating the first index weight of the primary index by a standard column average method;
and carrying out consistency check on the first index weight, judging whether the first index weight is reasonable, and calculating a second index weight of the secondary index based on the first index weight when the first index weight is reasonable.
Optionally, the primary indicators include enterprise risk, commodity import risk, commodity export risk, import order risk, export order risk, cross-border e-commerce trade order risk, contract risk, import transportation risk, export letter of credit risk, and exchange rate risk.
Optionally, the wind control determination result includes a customer admission wind control determination result, a commodity admission wind control determination result, a business risk early warning, and a business risk analysis.
A second aspect of the present application provides a cross-border e-commerce wind control management system, the system comprising:
the system comprises a receiving unit, a processing unit and a processing unit, wherein the receiving unit is used for receiving cross-border service related data, and the cross-border service related data comprises enterprise information, commodity information, e-commerce transaction orders, purchase warehousing orders, sale ex-warehouse orders and customs declaration data;
the calling unit is used for calling a correlation database from a data center according to the cross-border service related data;
and the wind control unit is used for carrying out wind control judgment on the cross-border service related data by combining the correlation database and a preset wind control model and outputting a wind control judgment result of the cross-border service.
Optionally, the invoking unit is specifically configured to:
if the cross-border service related data comprises enterprise information, third party platform enterprise credit investigation information data, customs enterprise management credit platform data and national credit platform data are called from the data center;
and if the cross-border service related data comprises commodity information, calling a sensitive word bank, a wild animal directory, an endangered item and a wild plant directory from the data center.
Optionally, the preset wind control model is specifically constructed as follows:
constructing a first-level index and a second-level index, wherein the first-level index corresponds to a plurality of second-level indexes respectively;
constructing a judgment matrix of the first-level index based on an AHP analytic hierarchy process;
calculating the first index weight of the primary index by a standard column average method;
and carrying out consistency check on the first index weight, judging whether the first index weight is reasonable, and calculating a second index weight of the secondary index based on the first index weight when the first index weight is reasonable.
Optionally, the primary indicators include enterprise risk, commodity import risk, commodity export risk, import order risk, export order risk, cross-border e-commerce trade order risk, contract risk, import transportation risk, export letter of credit risk, and exchange rate risk.
Optionally, the wind control determination result includes a customer admission wind control determination result, a commodity admission wind control determination result, a business risk early warning, and a business risk analysis.
According to the technical scheme, the embodiment of the application has the following advantages:
the application provides a cross-border electricity and commerce wind control management method, which comprises the following steps: receiving cross-border service related data, wherein the cross-border service related data comprises enterprise information, commodity information, e-commerce transaction orders, purchase warehousing orders, sale ex-warehouse orders and customs declaration data; calling a correlation database from a data center according to the cross-border service related data; and performing wind control judgment on the cross-border service related data by combining the correlation database and a preset wind control model, and outputting a wind control judgment result of the cross-border service.
According to the method and the system, the cross-border business related data are received, the associated database is called from the data center according to the cross-border business related data, the wind control judgment result of the cross-border business is output through the combination of the related data and the preset wind control model, the risk management and control of the process of import and export trade activities in the whole process is realized, and the risk of the cross-border electric business enterprise is reduced.
Drawings
FIG. 1 is a flowchart illustrating a method for cross-border electricity business wind control management in an embodiment of the present application;
fig. 2 is a schematic structural diagram of a cross-border e-commerce wind control management system in an embodiment of the present application.
Detailed Description
In order to make the technical solutions of the present application better understood by those skilled in the art, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments that can be derived by a person skilled in the art from the embodiments given in the present application without making any creative effort shall fall within the protection scope of the present application.
The application designs a cross-border electronic commerce wind control management method and system, which realize the risk control of the business activity process of the entrance and exit in the whole process and reduce the self risk of the cross-border electronic commerce enterprise.
For convenience of understanding, please refer to fig. 1, in which fig. 1 is a flowchart illustrating a method for cross-border power grid wind control management according to an embodiment of the present disclosure, and as shown in fig. 1, the method specifically includes:
101. receiving cross-border service related data, wherein the cross-border service related data comprises enterprise information, commodity information, e-commerce transaction orders, purchase warehousing orders, sales ex-warehouse orders and customs declaration data;
it should be noted that, first, cross-border service related data is received, the cross-border service covers service ranges such as cross-border enterprise admission, large cargo delivery and admission declaration, in-zone cross account book allocation, and inter-zone goods circulation, and according to specific matters of the cross-border service, different cross-border service related data will be received, for example, cross-border service related data of enterprise information will be received by the cross-border enterprise admission service, and large cargo delivery and admission declaration data will be received by the cross-border enterprise information, commodity information, purchase warehousing orders, and customs declaration data.
102. Calling a correlation database from a data center according to the cross-border service related data;
it should be noted that, after receiving the cross-border service related data, the correlation database is called from the data center according to the cross-border service related data, specifically:
if the cross-border business related data comprises enterprise information, third-party platform enterprise credit investigation information data, customs enterprise management credit platform data and national credit platform data are called from the data center;
and if the cross-border service related data comprises commodity information, calling a sensitive word bank, a name list of the wild animals, endangered items and a name list of the wild plants from the data center.
103. And performing wind control judgment on the cross-border service related data by combining the correlation database and a preset wind control model, and outputting a wind control judgment result of the cross-border service.
The construction of the preset wind control model provided by the embodiment of the application specifically comprises the following steps:
constructing a first-level index and a second-level index, wherein the first-level index corresponds to a plurality of second-level indexes respectively;
constructing a judgment matrix of a first-level index based on an AHP analytic hierarchy process;
calculating the first index weight of the primary index by a standard column average method;
and carrying out consistency check on the first index weight, judging whether the first index weight is reasonable, and calculating a second index weight of the secondary index based on the first index weight when the first index weight is reasonable.
The primary indicators include enterprise risk, commodity import risk, commodity export risk, import order risk, export order risk, cross-border e-commerce trade order risk, contract risk, import transportation risk, export letter of credit risk, and exchange rate risk.
The preset wind control model constructed in the embodiment of the application is divided into three layers, wherein the highest layer is a target layer A and represents the risk of enterprise cross-border business, and the middle layer is a criterion layer B and represents each link of purchasing agency business division; the bottom layer is a scheme layer P which represents various refined risk factors in each link, and therefore a preset wind control model is built.
First, first-level indexes of a criterion layer B and second-level indexes of a scheme layer P are established, each first-level index corresponds to at least one second-level index, the established first-level indexes in the embodiment of the application comprise enterprise risks, commodity import risks, commodity export risks, import order risks, export order risks, cross-border e-commerce trade order risks, contract risks, import transportation risks, export letter of credit risks and exchange rate risks, and the corresponding second-level indexes are more refined, for example, the second-level indexes corresponding to the enterprise risks comprise: 1. the tax administration is listed in an abnormal list, 4, the foreign exchange administration is listed in an abnormal list and the like. The increase and decrease of the secondary index can be changed at any time according to the actual condition.
After the first-level index and the second-level index are constructed, a judgment matrix of the first-level index is constructed based on an AHP analytic hierarchy process, and the judgment matrix is a square matrix formed by quantitative evaluation values obtained by pairwise comparison of all elements of the same level to a certain element of the previous level. The judgment matrix is a judgment value for indicating the relative importance of each index element at the same level. The evaluation scale of AHP analytic hierarchy process is 1-9 scale method. Firstly, dividing every two importance comparison values into five grades, and sequentially reducing and dividing the importance comparison values into five grades; absolutely important, very important, relatively important, slightly important and equally important. And these five grades are given in turn a W score of: 9. 7, 5, 3 and 1. In addition, scores of 2, 4, 6, and 8 are given to represent four basic levels between W, respectively. As shown in the following table:
| serial number | Importance level | FijAssignment of value |
| 1 | i, j two elements are equally important | 1 |
| 2 | The i element is slightly more important than the j element | 3 |
| 3 | The i element is significantly more important than the j element | 5 |
| 4 | The i element is more strongly important than the j element | 7 |
| 5 | The i element is extremely important than the j element | 9 |
| 6 | The i element is less important than the j element | 1/3 |
| 7 | The i element is significantly less important than the j element | 1/5 |
| 8 | i is more strongly insignificant than j | 1/7 |
| 9 | i elements are extremely less important than j elements | 1/9 |
According to the risk evaluation model diagram and the scale of the AHP method, experts relatively compare the importance of each first index in the criterion layer B, and the comparison structure is represented by a judgment matrix B, which is shown as an example in the following table.
| B | B1 B2 B3…………………………………………Bm |
| B1 | B11 B12 B13…………………………………………B1m |
| B2 | B21 B22 B23…………………………………………B2m |
| B3 | B31 B32 B33…………………………………………B3m |
| ……… | ………… |
| Bm | Bm1 Bm2 Bm3…………………………………………Bmm |
And judging each element ij in the matrix B, wherein the element ij represents the proportional scale of the relative importance of the row index i to the column index j, namely the pairwise comparison of the importance degrees of the risk factor indexes.
Compared with other methods for determining index weight coefficients, the AHP method has the greatest advantage of ensuring consistent expert panel concept logic through consistency check. The consistency of thought and logic, as the name suggests, means that when the expert evaluation group judges the importance, the inconsistency when more than three indexes are compared with each other is avoided, for example, when the indexes a, b and c are compared pairwise, a is slightly more important than b, and when b is slightly more important than c, if c is slightly more important than a, the thinking of the expert evaluation group is called as inconsistency. The contradiction of such inconsistencies generally occurs on multi-index matrices. And after a judgment matrix is given, carrying out consistency check by an expert evaluation group, and integrating the opinions of average experts to obtain a judgment matrix B of the first index.
After listing the importance judgment matrix B of the first index, the corresponding weight of each first index needs to be calculated, and the embodiment of the present application uses a canonical column average method for calculation, which specifically includes the following steps:
assuming that expert groups of the group are discussed consistently, the following risk factor index judgment matrix B is established:
normalizing the elements B according to columns, namely dividing the sum of all ratios of the columns in the judgment matrix B by each ratio, and then replacing the original ratio with a new ratio to obtain a new judgment matrix B', wherein the formula is as follows:
then, a new judgment matrix is obtained
The first column of the new decision matrix B' is calculated as follows:
B’1＝1/(1+1/2+1/3+1)＝0.353
B’2＝1/2/(1+1/2+1/3+1)＝0.176
B’3＝1/3/(1+1/2+1/3+1)＝0.118
B’4＝1/(1+1/2+1/3+1)＝0.353；
averaging the rows of the decision matrix B
Then vector
A weight vector being a first index;
and carrying out the data of the judgment matrix B, and calculating as follows:
the vector w (0.351,0.189,0.109,0.351) is the resulting order processing index weight.
Since the elements of the two-by-two comparison matrix are obtained by manually scoring and comparing the two elements, in order to prevent the occurrence of inconsistency, it is necessary to perform consistency check, and since complete consistency has certain difficulty, certain deviation is allowed.
Firstly, calculating the maximum characteristic value of a judgment matrix B of a first index of order processing:
by passing
Calculating the index consistency;
by passing
Calculating an average random consistency index;
the average random consistency index r.i is the average of consistency indexes and is calculated from a plurality of judgment matrices that occur randomly. The values of R.I in stages 1-9 are shown in the table:
and judging whether the C.R is less than 0.1. If true, the consistency of the judgment matrix can be accepted, otherwise, the judgment matrix needs to be corrected. In conjunction with the above data c.r.0.003/0.89 0.004 < 0.1 was tested. Therefore, it is reasonable that w ═ (0.351,0.189,0.109,0.351) is the weight of each vendor to select the primary index.
After the weight of each primary index of the criterion layer B is obtained, the weight of the secondary index of the lower level can be calculated, the calculation process is consistent with the process of calculating the weight of the primary index, and the weight of the criterion layer B is assumed to be
And the second-level index weight of the scheme layer P is as follows:
then
According to the method and the system, the cross-border business related data are received, the associated database is called from the data center according to the cross-border business related data, the wind control judgment result of the cross-border business is output through the combination of the related data and the preset wind control model, the risk management and control of the process of import and export trade activities in the whole process is realized, and the risk of the cross-border electric business enterprise is reduced.
Referring to fig. 2, fig. 2 is a schematic structural diagram of a cross-border e-commerce wind control management system according to an embodiment of the present application, and as shown in fig. 2, the system includes:
the receiving unit 201 is configured to receive cross-border service related data, where the cross-border service related data includes enterprise information, commodity information, e-commerce transaction orders, purchase warehousing orders, sales ex-warehouse orders, and customs declaration data;
the retrieval unit 202 is configured to retrieve the association database from the data center according to the cross-border service related data;
and the wind control unit 203 is configured to perform wind control determination on the cross-border service related data by combining the association database and a preset wind control model, and output a wind control determination result of the cross-border service.
Further, the invoking unit 202 is specifically configured to:
if the cross-border business related data comprises enterprise information, third-party platform enterprise credit investigation information data, customs enterprise management credit platform data and national credit platform data are called from the data center;
and if the cross-border service related data comprises commodity information, calling a sensitive word bank, a name list of the wild animals, endangered items and a name list of the wild plants from the data center.
Further, the construction of the preset wind control model specifically comprises:
constructing a first-level index and a second-level index, wherein the first-level index corresponds to a plurality of second-level indexes respectively;
constructing a judgment matrix of a first-level index based on an AHP analytic hierarchy process;
calculating the first index weight of the primary index by a standard column average method;
and carrying out consistency check on the first index weight, judging whether the first index weight is reasonable, and calculating a second index weight of the secondary index based on the first index weight when the first index weight is reasonable.
Further, the primary indicators include enterprise risk, commodity import risk, commodity export risk, import order risk, export order risk, cross-border e-commerce trade order risk, contract risk, import transportation risk, export letter of credit risk, and exchange rate risk.
Further, the wind control judgment result comprises a client admission wind control judgment result, a commodity admission wind control judgment result, a business risk early warning and a business risk analysis.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
The terms "first," "second," "third," "fourth," and the like in the description of the application and the above-described figures, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the application described herein are, for example, capable of operation in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover non-exclusive inclusions, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
It should be understood that in the present application, "at least one" means one or more, "a plurality" means two or more. "and/or" for describing an association relationship of associated objects, indicates that there may be three relationships, for example, "a and/or B" may indicate: only A, only B and both A and B are present, wherein A and B may be singular or plural. The character "/" generally indicates that the contextual objects are in an "or" relationship. "at least one of the following" or similar expressions refer to any combination of these items, including any combination of single item(s) or plural items. For example, at least one (one) of a, b, or c, may represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", wherein a, b, c may be single or plural.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical functional division, and in actual implementation, there may be other divisions, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a hardware form, and can also be realized in a software functional unit form.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be substantially implemented or contributed to by the prior art, or all or part of the technical solution may be embodied in a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The above embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions in the embodiments of the present application.
Claims (10)
1. A cross-border e-commerce wind control management method is characterized by comprising the following steps:
receiving cross-border service related data, wherein the cross-border service related data comprises enterprise information, commodity information, e-commerce transaction orders, purchase warehousing orders, sale ex-warehouse orders and customs declaration data;
calling a correlation database from a data center according to the cross-border service related data;
and performing wind control judgment on the cross-border service related data by combining the correlation database and a preset wind control model, and outputting a wind control judgment result of the cross-border service.
2. The cross-border e-commerce wind control management method according to claim 1, wherein the retrieving of the association database from the data center according to the cross-border business related data specifically comprises:
if the cross-border service related data comprises enterprise information, third-party platform enterprise credit investigation information data, customs enterprise management credit platform data and national credit platform data are called from the data center;
and if the cross-border service related data comprises commodity information, calling a sensitive word bank, a wild animal directory, an endangered item and a wild plant directory from the data center.
3. The cross-border electricity business wind control management method according to claim 1, wherein the preset wind control model is specifically constructed by:
constructing a first-level index and a second-level index, wherein the first-level index corresponds to a plurality of second-level indexes respectively;
constructing a judgment matrix of the first-level index based on an AHP analytic hierarchy process;
calculating the first index weight of the primary index by a standard column average method;
and carrying out consistency check on the first index weight, judging whether the first index weight is reasonable, and calculating a second index weight of the secondary index based on the first index weight when the first index weight is reasonable.
4. The cross-border e-commerce wind control management method according to claim 3, wherein the primary indicators include enterprise risk, commodity import risk, commodity export risk, import order risk, export order risk, cross-border e-commerce trade order risk, contract risk, import transportation risk, export letter of credit risk, and exchange rate risk.
5. The cross-border e-commerce wind control management method according to claim 1, wherein the wind control judgment result comprises a customer admission wind control judgment result, a commodity admission wind control judgment result, a business risk early warning and a business risk analysis.
6. A cross-border e-commerce wind control management system, comprising:
the system comprises a receiving unit, a processing unit and a processing unit, wherein the receiving unit is used for receiving cross-border service related data, and the cross-border service related data comprises enterprise information, commodity information, e-commerce transaction orders, purchase warehousing orders, sale ex-warehouse orders and customs declaration data;
the calling unit is used for calling a correlation database from a data center according to the cross-border service related data;
and the wind control unit is used for performing wind control judgment on the cross-border service related data and outputting a wind control judgment result of the cross-border service by the associated database and a preset wind control model.
7. The cross-border electricity merchant wind control management system according to claim 6, wherein the invoking unit is specifically configured to:
if the cross-border service related data comprises enterprise information, third-party platform enterprise credit investigation information data, customs enterprise management credit platform data and national credit platform data are called from the data center;
and if the cross-border service related data comprises commodity information, calling a sensitive word bank, a wild animal directory, an endangered item and a wild plant directory from the data center.
8. The cross-border electricity business wind control management system according to claim 7, wherein the preset wind control model is specifically constructed by:
constructing a first-level index and a second-level index, wherein the first-level index corresponds to a plurality of second-level indexes respectively;
constructing a judgment matrix of the first-level index based on an AHP analytic hierarchy process;
calculating the first index weight of the primary index by a standard column average method;
and carrying out consistency check on the first index weight, judging whether the first index weight is reasonable, and calculating a second index weight of the secondary index based on the first index weight when the first index weight is reasonable.
9. The cross-border e-commerce wind management system according to claim 8, wherein the primary indicators include enterprise risk, commodity import risk, commodity export risk, import order risk, export order risk, cross-border e-commerce trade order risk, contract risk, import transportation risk, export letter of credit risk, and exchange rate risk.
10. The cross-border electricity business wind control management system according to claim 6, wherein the wind control judgment result comprises a customer admission wind control judgment result, a commodity admission wind control judgment result, a business risk early warning and a business risk analysis.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011269343.XA CN112365165A (en) | 2020-11-13 | 2020-11-13 | Cross-border e-commerce wind control management method and system |
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| CN113706089A (en) * | 2021-06-02 | 2021-11-26 | 吉林省爱阳光新科技有限公司 | Cross-border e-commerce automatic customs declaration method, device and storage medium |
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| CN115860747A (en) * | 2022-12-13 | 2023-03-28 | 昆山华东信息科技有限公司 | Customs import and export commodity risk management method and system based on big data |
| CN117371890A (en) * | 2023-10-31 | 2024-01-09 | 深圳隆发健康生活有限公司 | Cross-border electronic commerce-based supply chain management method and system |
| CN121073327A (en) * | 2025-08-19 | 2025-12-05 | 广州纽力物联科技有限公司 | Cross-border logistics information visual management method and system based on big data |
| WO2026036748A1 (en) * | 2025-04-03 | 2026-02-19 | 重庆城市职业学院 | Intelligent international trade risk prevention and control method and system based on multi-modal data analysis |
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| CN115860747A (en) * | 2022-12-13 | 2023-03-28 | 昆山华东信息科技有限公司 | Customs import and export commodity risk management method and system based on big data |
| CN117371890A (en) * | 2023-10-31 | 2024-01-09 | 深圳隆发健康生活有限公司 | Cross-border electronic commerce-based supply chain management method and system |
| WO2026036748A1 (en) * | 2025-04-03 | 2026-02-19 | 重庆城市职业学院 | Intelligent international trade risk prevention and control method and system based on multi-modal data analysis |
| CN121073327A (en) * | 2025-08-19 | 2025-12-05 | 广州纽力物联科技有限公司 | Cross-border logistics information visual management method and system based on big data |
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