A merchant associated transaction query method, device, system and storage medium

Abstract

This invention provides a method, apparatus, system, and storage medium for querying merchant related-party transactions, relating to the field of financial technology. The method includes: acquiring a related-party transaction table from the system, importing it into a database on the query platform, and saving it; querying the basic information of the target merchant; matching the enterprise information and legal representative information with the data in the related-party transaction table, and outputting the merchant related-party transaction query results. This invention automatically extracts related-party transaction information from the system on the platform side for matching related-party transaction data, adds labeling processing for whether a transaction belongs to a related-party field, and provides prompts for back-end reviewers, process platform reviewers, and merchant details during the query process. It intercepts potential related-party transaction compliance risks in open banking from the source, saves time on manual comparison of related-party transactions during merchant onboarding and approval processes, and greatly improves merchant operational efficiency.

Description

Technical Field

[0001] This invention relates to the field of financial technology, and more specifically, to a method, apparatus, system, and storage medium for querying merchant-related transactions. Background Technology

[0002] With the rapid development of open banking, merchant cooperation verification has become a crucial aspect of banking operations, but this process is currently not adequately supported or optimized. During merchant cooperation, careful vetting of merchants is necessary to ensure transaction security, verifying whether the merchant's business is in competition with or related to any legal entity, enterprise, or group, thereby eliminating security and compliance risks.

[0003] Currently, the main method for querying related-party transactions is through manual inquiries by business personnel. They use big data systems to compare and verify information such as the merchant's social credit code, corporate legal representative's name, and legal representative's ID number to confirm whether the party is a related party in the transaction.

[0004] First, manually querying the information of each partner merchant requires the responsible business personnel to manually search and compare from beginning to end, which is extremely inefficient and becomes a bottleneck when a large number of merchants are connected. It is also time-consuming and labor-intensive. Second, social credit codes and corporate legal person ID numbers are sensitive information. Currently, there is no system that can automatically verify them. These sensitive information needs to be processed manually, which poses a challenge to the protection of sensitive information in financial institutions and has the security risk of information leakage. System traceability and system automation are urgently needed. Third, all companies or legal persons involved in related transactions are currently stored in a big data table. Due to encrypted storage and sensitive content, frequent queries and requests for access by business personnel are difficult and inconvenient.

[0005] In summary, existing methods for querying related-party transactions suffer from drawbacks such as high labor costs, low accuracy, and information security issues related to manual comparison of sensitive information, causing significant inconvenience to financial institutions' risk assessment efforts. Summary of the Invention

[0006] In view of this, and to address the aforementioned technical problems, the present invention provides a method for querying merchant-related transactions in the field of fintech or fintech-related fields, comprising:

[0007] Retrieve the related transaction table from the big data warehouse on the system side, import it into the database on the query platform side, and save it;

[0008] The query platform retrieves the basic information of the target merchant to be queried; wherein, the basic information of the target merchant includes enterprise information and legal person information;

[0009] According to the query review instruction, the query platform matches the enterprise information and legal person information in the basic information of the target merchant with the data in the related transaction table, and outputs the merchant related transaction query results.

[0010] Preferably, the step of obtaining the related transaction table from the big data warehouse on the system side, importing it into the database on the query platform side, and saving it includes:

[0011] The query platform sends an application to the system for access and decryption permissions for the related transaction table; wherein, the related transaction table is synchronized with all related transaction party information on a T+1 basis;

[0012] After obtaining the docking and decryption permissions based on the application information, the query platform decrypts the related transaction table through the ESA interface, and then saves the related transaction table to the database of the query platform through the DSP job method of Hive to db.

[0013] Preferably, the query platform, based on the query review instruction, matches the enterprise information and legal representative information in the target merchant's basic information with the data in the related transaction table, and outputs the merchant related transaction query results, including:

[0014] The enterprise information in the basic information of the target merchant is matched with the data in the related transaction table, and the related transaction enterprise field value is output; and the legal person information is matched with the data in the related transaction table, and the related transaction legal person field value is output.

[0015] If either the related party transaction enterprise field value or the related party transaction legal person field value is 1, then a related party transaction is determined to exist.

[0016] Update the target related transaction field value to 1, and use the target related transaction field value, the related transaction enterprise field value, and the related transaction legal person field value as the merchant related transaction query result.

[0017] Preferably, after matching the enterprise information in the target merchant's basic information with the data in the related transaction table and outputting the related transaction enterprise field value; and after matching the legal person information with the data in the related transaction table and outputting the related transaction legal person field value, the method further includes:

[0018] If both the related party transaction enterprise field value and the related party transaction legal person field value are 0, then it is determined that there is no related party transaction;

[0019] Update the target related transaction field value to 0, and use the target related transaction field value, the related transaction enterprise field value, and the related transaction legal person field value as the merchant related transaction query result.

[0020] Preferably, the step of matching the enterprise information in the target merchant's basic information with the data in the related transaction table includes:

[0021] Using the enterprise social credit code type as the account type field, and using the enterprise social credit code number in the target merchant's basic information as the document number field, perform a select count query on the data in the related transaction table;

[0022] If the count result is greater than 1, then update the value of the related transaction enterprise field to 1;

[0023] If the count result is not greater than 1, then update the value of the related transaction enterprise field to 0.

[0024] Preferably, the step of matching the legal entity information with the data in the related transaction table and outputting the related transaction legal entity field value includes:

[0025] Using the ID card number type as the account type field, and using the corporate legal person's ID card number in the target merchant's basic information as the document number field, perform a select count query on the data in the related transaction table;

[0026] If the count result is greater than 1, then update the value of the related transaction legal person field to 1;

[0027] If the count result is not greater than 1, then update the value of the related transaction legal person field to 0.

[0028] Preferably, after updating the target related transaction field value to 1 and using the target related transaction field value, the related transaction enterprise field value, and the related transaction legal person field value as the merchant related transaction query result, the method further includes:

[0029] The query platform determines whether there are any non-zero field values ​​among the target related transaction field value, the related transaction enterprise field value, and the related transaction legal person field value;

[0030] If there is a field value that is not zero, the query platform will use the non-zero field value as an input parameter and call the submitProcessData method to output the non-zero field value to the process platform so that it can be reviewed by the process platform.

[0031] The query platform saves the merchant information corresponding to the non-zero field values ​​to the database of the system through the ESA interface of the system.

[0032] In addition, to solve the above problems, the present invention also provides a merchant-related transaction query device, comprising:

[0033] The synchronization module is used to retrieve the related transaction tables from the big data warehouse on the system side, import them into the database on the query platform side, and save them.

[0034] The input module is used to query the basic information of the target merchant to be queried from the platform; wherein, the basic information of the target merchant includes enterprise information and legal person information;

[0035] The query module is used by the query platform to match the enterprise information and legal person information in the basic information of the target merchant with the data in the related transaction table according to the query review instruction, and output the merchant related transaction query results.

[0036] In addition, to solve the above problems, the present invention also provides a merchant-related transaction query system, including a memory and a processor. The memory stores a merchant-related transaction query program, and the processor runs the merchant-related transaction query program to enable the merchant-related transaction query system to perform the merchant-related transaction query method as described above.

[0037] In addition, to solve the above problems, the present invention also provides a computer-readable storage medium storing a merchant-related transaction query program, which, when executed by a processor, implements the merchant-related transaction query method as described above.

[0038] This invention provides a method, apparatus, system, and storage medium for querying merchant related-party transactions. The method includes: acquiring a related-party transaction table from a big data warehouse on the system side, importing it into a database on the query platform side, and saving it; the query platform side acquiring basic information of the target merchant to be queried; wherein the basic information of the target merchant includes enterprise information and legal representative information; the query platform side, according to a query review instruction, matching the enterprise information and legal representative information in the basic information of the target merchant with the data in the related-party transaction table, and outputting the merchant related-party transaction query results. The merchant related-party transaction query method provided by this invention automatically extracts related-party transaction information from the system-side big data warehouse on the platform side, matches relevant related-party transaction data, and adds labeling processing for whether a transaction belongs to a related-party transaction field. This provides prompts for back-end reviewers, process platform reviewers, and merchant details during the query process, intercepting potential related-party transaction compliance risks in open banking from the source, saving time on manual comparison of related-party transactions in merchant onboarding and approval processes, greatly improving merchant operational efficiency, and facilitating risk mitigation for financial institutions. Attached Figure Description

[0039] Figure 1 This is a schematic diagram of the hardware operating environment involved in an embodiment of the merchant-related transaction query method of the present invention;

[0040] Figure 2 This is a flowchart illustrating the first embodiment of the merchant-related transaction query method of the present invention;

[0041] Figure 3 This is a detailed flowchart of step S100 in the second embodiment of the merchant-related transaction query method of the present invention;

[0042] Figure 4 This is a detailed flowchart of step S300 in the third embodiment of the merchant-related transaction query method of the present invention;

[0043] Figure 5 This is a flowchart illustrating the detailed steps (steps S311-S313) of step S310 in the third embodiment of the merchant-related transaction query method of the present invention.

[0044] Figure 6 This is a flowchart illustrating the detailed steps (steps S314-S316) of step S310 in the third embodiment of the merchant-related transaction query method of the present invention.

[0045] Figure 7 This is a flowchart illustrating the supplementary technical solution (steps S360-S380) following step S330 in the third embodiment of the merchant-related transaction query method of the present invention.

[0046] Figure 8 This is a schematic diagram of the module connections for the merchant-related transaction query device of the present invention.

[0047] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0048] The embodiments of the present invention are described in detail below, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout.

[0049] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0050] In this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," "linking," and "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0051] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0052] like Figure 1 The diagram shown is a structural schematic of the hardware operating environment of the terminal involved in an embodiment of the present invention.

[0053] The merchant-related transaction query system of this invention can be a PC, or a mobile terminal device such as a smartphone, tablet, or laptop. The system may include: a processor 1001 (e.g., a CPU), a network interface 1004, a user interface 1003, a memory 1005, and a communication bus 1002. The communication bus 1002 is used to establish communication between these components. The user interface 1003 may include a display screen, an input unit such as a keyboard, or a remote control; optionally, the user interface 1003 may also include a standard wired interface or a wireless interface. The network interface 1004 may optionally include a standard wired interface or a wireless interface (e.g., a Wi-Fi interface). The memory 1005 may be a high-speed RAM or a stable memory, such as a disk drive. Optionally, the memory 1005 may also be a storage device independent of the processor 1001. Optionally, the merchant-related transaction query system may also include RF (Radio Frequency) circuitry, audio circuitry, a Wi-Fi module, etc. In addition, the merchant-related transaction query system can also be configured with other sensors such as gyroscopes, barometers, hygrometers, thermometers, and infrared sensors, which will not be elaborated here.

[0054] Those skilled in the art will understand that Figure 1 The merchant-related transaction query system shown is not intended to limit it and may include more or fewer components than illustrated, or combine certain components, or have different component arrangements. Figure 1 As shown, the memory 1005, which is a computer-readable storage medium, may include an operating system, a data interface control program, a network connection program, and a merchant-related transaction query program.

[0055] In summary, the merchant related transaction query method provided by this invention automatically extracts related transaction information from the system's big data warehouse on the platform side, matches relevant related transaction data, and adds labeling processing for whether a transaction belongs to a related party. This method provides prompts for back-end reviewers, process platform reviewers, and merchant details during the query process. It intercepts potential related transaction compliance risks in open banking from the source, saves time on manual comparison of related transactions during merchant onboarding and approval processes, greatly improves merchant operational efficiency, and facilitates risk mitigation for financial institutions.

[0056] Example 1:

[0057] Reference Figure 2 This invention provides a method for querying merchant-related transactions, including:

[0058] Step S100: Obtain the related transaction table from the big data warehouse on the system side, import it into the database on the query platform side and save it;

[0059] The merchant-related transaction query method provided in this embodiment modifies the merchant onboarding process and platform of the open bank, adding a step for the system to automatically retrieve related transaction information from big data. This method can be applied between the query platform and the system. When business personnel perform queries, they input relevant information through the query platform and realize the merchant-related transaction query through data interaction between the query platform and the system.

[0060] As mentioned above, the big data warehouse on the system side contains related transaction tables. The query platform can obtain the related transaction tables in real time or at regular intervals and import them into the database for storage, provided it has certain permissions.

[0061] Step S200: Obtain the basic information of the target merchant to be queried from the query platform; wherein, the basic information of the target merchant includes enterprise information and legal person information;

[0062] As mentioned above, business personnel input the information they need to query through the platform, which is the basic information of the target merchant. This includes two aspects: enterprise information and legal representative information. The enterprise and legal representative information may contain relevant information that demonstrates the uniqueness of the enterprise and its legal representative.

[0063] For example, company information may include, but is not limited to, company name, company type, registered address, registered capital, business scope, legal representative's name, business license number, and tax registration certificate number. Specific company information may also include the company's establishment date, shareholder information, organization code certificate number, and credit rating.

[0064] Legal entity information may include, but is not limited to, the legal representative's name, gender, age, ID number, contact information, and other basic personal information, as well as information such as the company they work for, their position within the company, the company's business scope, and the company's registered address. In some cases, legal entity information may also include sensitive information such as financial information and records of relevant administrative actions.

[0065] In this embodiment, compared to the information retrieved through queries in conventional techniques, the fields "company legal representative's name (merchant_legal_person)" and "company legal representative's ID number (merchant_legal_person_id_number)" are added and stored in the merchant information table database. This facilitates more accurate information querying and matching.

[0066] In step S300, the query platform matches the enterprise information and legal person information in the basic information of the target merchant with the data in the related transaction table according to the query review instruction, and outputs the merchant related transaction query results.

[0067] When a user (i.e., a business person) makes a query on the query platform, after entering the relevant merchant information and saving or submitting for review, a query review instruction will be generated. The query platform will then perform data matching processing, matching the enterprise information and legal person information in the target merchant's basic information with the data in the related transaction table, and outputting the matching results, i.e., the merchant related transaction query results.

[0068] The merchant-related transaction query results obtained above contain relevant information about the merchants. When business personnel view merchant information in the backend, they can check whether the relevant merchants belong to related transactions, whether they contain corresponding tags, and can also display sensitive information through masking.

[0069] The merchant related transaction query method provided in this embodiment automatically extracts related transaction information from the system's big data warehouse on the platform side, matches relevant related transaction data, and adds labeling processing for whether a transaction belongs to a related party. During the query, it can provide prompts for back-end reviewers, process platform reviewers, and merchant details display. It intercepts the compliance risks of potential related transaction enterprises in open banking from the source, saves the time of manual comparison of related transactions in the merchant onboarding and approval process, greatly improves the efficiency of merchant operations, and facilitates the risk elimination work of financial institutions.

[0070] Example 2:

[0071] Reference Figure 3 The second embodiment of the present invention provides a method for querying merchant-related transactions. Based on the above embodiment 1, step S100, which involves obtaining the related transaction table from the big data warehouse on the system side, importing it into the database on the query platform side, and saving it, includes:

[0072] In step S110, the query platform sends an application for access permission and decryption permission for the related transaction table to the system; wherein, the related transaction table is synchronized with all related transaction party information on a T+1 basis.

[0073] In financial transactions, "T+1" refers to the next business day after the transaction date (T), where "T" is the date the event occurs. Therefore, "T+1" means the second business day after the event occurs.

[0074] In securities trading, maintaining T+1 synchronization means that the settlement time of a transaction is consistent with T+1, that is, the settlement process begins on the day the transaction is made and ends on T+1, at which point all related matters such as delivery and clearing are completed. This ensures the fairness and transparency of transactions, and also facilitates risk control and supervision.

[0075] Step S120: After obtaining the docking permission and decryption permission according to the application information, the query platform decrypts the related transaction table through the ESA interface, and saves the related transaction table to the database of the query platform through the DSP job mode of hive to db after decryption.

[0076] As described above, step S100 is used to obtain the related transaction table from the big data warehouse on the system side, import it into the database on the query platform side, and save it. This step includes the following two sub-steps:

[0077] In step S110, the query platform sends a request to the system, requesting permission to connect to and decrypt the related transaction table. This related transaction table is synchronized in real-time with all related transaction information. This step enables information exchange between the query platform and the system.

[0078] In step S120, after obtaining access and decryption permissions, the query platform uses the ESA interface to decrypt the related transaction table and saves it to the query platform's database using a Hive to DB DSP job. This step imports and decrypts the related transaction table and saves it to the query platform's database, providing data support for subsequent merchant related transaction queries.

[0079] Specifically, in step S110, "interface access permission" refers to the permission of the query platform to access the related transaction table on the system side, and "decryption permission" refers to the permission of the query platform to decrypt encrypted data. In step S120, "ESA" refers to Enterprise Security Architecture, a software architecture used for data transmission and security control; "hivetodb" refers to the method of using Hive in the Hadoop ecosystem as a data warehouse to interact with traditional relational databases; and "DSP" refers to Distributed Processing Service, a technology for big data processing based on a distributed architecture.

[0080] The above steps primarily involve importing the related transaction tables from the system's big data warehouse into the query platform's database and decrypting sensitive information to facilitate subsequent merchant related transaction queries. This achieves information interaction and data sharing between the query platform and the system; ensures data security through encryption and access control; utilizes distributed processing and other technologies to achieve efficient data processing and storage; and improves the efficiency and accuracy of merchant related transaction queries while reducing labor costs and risks.

[0081] For example, if an open bank needs to query related-party transactions for a company, the query platform requests access to and decryption permissions for the related-party transaction table from the system. After authorization, it decrypts the table via the ESA interface and saves it to the query platform's database using a Hive to database DSP job. This allows the bank to quickly query the company's related-party transactions on the query platform, reducing the time and cost of manual queries and improving query accuracy.

[0082] Example 3:

[0083] Reference Figure 4 The third embodiment of the present invention provides a method for querying merchant-related transactions. Based on the above embodiment 1, in step S300, the query platform matches the enterprise information and legal person information in the basic information of the target merchant with the data in the related transaction table according to the query review instruction, and outputs the merchant-related transaction query results, including:

[0084] Step S310: Match the enterprise information in the target merchant's basic information with the data in the related transaction table, and output the related transaction enterprise field value; and match the legal person information with the data in the related transaction table respectively, and output the related transaction legal person field value.

[0085] In this step, the query platform matches the enterprise information and legal representative information from the target merchant's basic information with the data in the related transaction table, based on the query review instructions. The matching rules may include different information such as enterprise name, unified social credit code, and ID card number. If a match is successful, the related transaction enterprise field value and related transaction legal representative field value are output to further confirm whether a related transaction exists based on the matching results.

[0086] By automating the processing of merchant basic information and related transaction data, efficiency and accuracy have been improved, while reducing human intervention and errors. Automated matching and output methods lower labor and time costs, while also reducing errors and risks.

[0087] Step S320: If either the related transaction enterprise field value or the related transaction legal person field value is 1, then it is determined that a related transaction exists.

[0088] In this step, the query platform judges the output values ​​of the related transaction enterprise field and the related transaction legal person field. If either field is 1, it is determined that the merchant has a related transaction.

[0089] By automating processing and judgment, the efficiency of screening and judging related transactions of merchants has been improved, reducing labor and time costs, while also improving accuracy and efficiency and reducing errors and risks.

[0090] Step S330: Update the target related transaction field value to 1, and use the target related transaction field value, the related transaction enterprise field value, and the related transaction legal person field value as the merchant related transaction query result.

[0091] In this step, the query platform judges the output values ​​of the related transaction enterprise field and the related transaction legal person field. If either field is 1, it is determined that the merchant has a related transaction.

[0092] The above steps automate the processing and judgment of related-party transactions, enabling the supervision and management of such transactions. Specifically, by matching the target merchant's basic information with data in the related-party transaction table, the values ​​of the related-party transaction enterprise field and the related-party transaction legal person field are output. Then, it is determined that if either the related-party transaction enterprise field or the related-party transaction legal person field has a value of 1, a related-party transaction is identified. Finally, the target related-party transaction field value is updated to 1, and the target related-party transaction field value, the related-party transaction enterprise field value, and the related-party transaction legal person field value are used as the merchant related-party transaction query result. Automated processing and updating improve efficiency and accuracy, reduce manual intervention and errors, lower costs and risks, and facilitate subsequent risk assessment and supervision.

[0093] Further, in step S310, after matching the enterprise information in the target merchant's basic information with the data in the related transaction table and outputting the related transaction enterprise field value; and after matching the legal person information with the data in the related transaction table and outputting the related transaction legal person field value, the method further includes:

[0094] Step S340: If the value of the related transaction enterprise field and the value of the related transaction legal person field are both 0, it is determined that there is no related transaction.

[0095] In this step, the query platform checks the output values ​​of the related transaction enterprise field and the related transaction legal person field. If both are 0, it is determined that the merchant does not have any related transactions.

[0096] This step improves the efficiency of screening and judging merchant-related transactions through automated processing and judgment. By using an automated approach to judgment, labor and time costs are reduced, while accuracy and efficiency are improved, and errors and risks are reduced.

[0097] Step S350: Update the target related transaction field value to 0, and use the target related transaction field value, the related transaction enterprise field value, and the related transaction legal person field value as the merchant related transaction query result.

[0098] In one specific implementation, if the number of queries is greater than or equal to 1, the enterprise or legal person is considered to be involved in a related-party transaction with our bank. When saving to the merchant information table in the open banking core database, the following three fields are updated: 1) whether it is a related-party transaction enterprise, 2) whether it is a related-party transaction legal person, and 3) whether it belongs to a related-party transaction party. At the same time, these three fields are used as input parameters and transmitted to the process platform system via HTTP or ESA interface to display details for reference by process reviewers.

[0099] In this step, the query platform updates the target related transaction field value to 0 based on the judgment result, and uses the target related transaction field value, related transaction enterprise field value, and related transaction legal person field value as the merchant related transaction query result.

[0100] By automating the processing and updating of target related transaction field values, the manual and time costs are reduced, while accuracy and efficiency are improved, facilitating subsequent risk assessment and supervision.

[0101] In summary, the above steps automate the processing and assessment of related-party transactions for merchants. Specifically, by evaluating the output values ​​of the related-party transaction enterprise field and the related-party transaction legal person field, if both are 0, it is determined that there are no related-party transactions for the merchant. Finally, the target related-party transaction field value is updated to 0, and these three values ​​are used as the merchant's related-party transaction query result. Automated processing and updating improve efficiency and accuracy, reduce human intervention and errors, lower costs and risks, and facilitate subsequent risk assessment and supervision.

[0102] Further reference Figure 5 In step S310, matching the enterprise information in the target merchant's basic information with the data in the related transaction table includes:

[0103] Step S311: Using the enterprise social credit code type as the account type field and the enterprise social credit code number in the target merchant's basic information as the document number field, perform a select count query on the data in the related transaction table;

[0104] In this step, the query platform filters out data that meets the criteria from the related transaction table based on the query review instructions. Specifically, the enterprise social credit code type is used as the account type field, and the enterprise social credit code number in the target merchant's basic information is used as the document number field. Then, the select count function is used to count the data that meets the criteria.

[0105] Step S312: If the count result is greater than 1, then update the value of the related transaction enterprise field to 1;

[0106] Step S313: If the count result is not greater than 1, then update the value of the related transaction enterprise field to 0.

[0107] As described above, the query platform evaluates the results returned by the `SELECT COUNT` function. If the result is greater than 1, it indicates that the target merchant has related transactions, and the value of the "Related Transaction Enterprise" field needs to be updated to 1.

[0108] Further reference Figure 6 In step S310, the legal entity information is matched with the data in the related transaction table, and the related transaction legal entity field value is output, including:

[0109] Step S314: Using the ID card number type as the account type field and the corporate legal person ID card number in the target merchant's basic information as the document number field, perform a select count query on the data in the related transaction table;

[0110] In this step, the query platform filters out data that meets the criteria from the related transaction table based on the query review instructions. Specifically, the account type field is the ID card number, and the document number field is the corporate legal representative's ID card number from the target merchant's basic information. Then, the select count function is used to count the data that meets the criteria.

[0111] Step S315: If the count result is greater than 1, then update the value of the related transaction legal person field to 1;

[0112] Step S316: If the count result is not greater than 1, then update the value of the related transaction legal person field to 0.

[0113] In this step, the query platform evaluates the result returned by the `SELECT COUNT` function. If the result is greater than 1, it indicates that there are related-party transactions with the target merchant, and the value of the "Legal Representative for Related Transactions" field needs to be updated to 1. In the next step, the query platform evaluates the result returned by the `SELECT COUNT` function. If the result is not greater than 1, it indicates that there are no related-party transactions with the target merchant, and the value of the "Legal Representative for Related Transactions" field needs to be updated to 0.

[0114] The above steps automate the processing and assessment of related-party transactions for merchants. Specifically, by matching and counting the enterprise information in the target merchant's basic information with the data in the related-party transaction table, and the legal representative information with the data in the related-party transaction table respectively, the values ​​of the related-party transaction enterprise field and the related-party transaction legal representative field are output, and the values ​​of the relevant fields are updated. Automated processing and updating improve efficiency and accuracy, reduce human intervention and errors, and also lower costs and risks, facilitating subsequent risk assessment and supervision.

[0115] In one specific implementation, the above steps may include:

[0116] (1) The logic for the first select count() query is as follows:

[0117] a) The related party transaction table is based on the latest data from T-1 day;

[0118] b) The account type field in the big data related transaction table = enterprise social credit code type;

[0119] c) The document number field in related transactions = the enterprise social credit code number entered in the input parameters;

[0120] If the count result is greater than 1, then update the "Whether it belongs to a related transaction enterprise" field to 1;

[0121] If the count result is less than or equal to 1, then update "Whether it belongs to the related transaction enterprise field" to 0;

[0122] (2) The second select count() query logic is as follows:

[0123] a) The related party transaction table is based on the latest data from T-1 day;

[0124] b) The account type field in the big data related transaction table is equal to the ID card number type;

[0125] c) The document number field in related-party transactions = the corporate legal representative's ID number entered in the input parameters;

[0126] If the count result is greater than 1, then update "Whether it belongs to the related transaction legal person field" = 1;

[0127] If the count result is less than or equal to 1, then update "Whether it belongs to the related transaction legal person field" to 0.

[0128] Further reference Figure 7 Step S330, after updating the target related transaction field value to 1 and using the target related transaction field value, the related transaction enterprise field value, and the related transaction legal person field value as the merchant related transaction query result, further includes:

[0129] Step S360: The query platform determines whether there are any non-zero field values ​​among the target related transaction field value, the related transaction enterprise field value, and the related transaction legal person field value;

[0130] The query platform checks the values ​​of the target related transaction field, the related transaction enterprise field, and the related transaction legal person field. If any field value is not zero, it indicates that the merchant has related transactions.

[0131] Step S370: If there is a field value that is not zero, the query platform will use the field value that is not zero as an input parameter and call the submitProcessData method to output the field value that is not zero to the process platform so that it can be reviewed by the process platform.

[0132] In this step, the query platform takes the non-zero field value as the input parameter and calls the submitProcessData method to output the non-zero field value to the process platform so that it can be reviewed by the process platform.

[0133] Step S380: The query platform saves the merchant information corresponding to the non-zero field value to the database of the system through the ESA interface of the system.

[0134] In one specific implementation, the above steps may include:

[0135] (1) After the query platform (e.g., the business opportunity entry system) obtains the three fields related to the transaction by calling the ESA interface, if any field is not 0, the non-zero field is used as the input parameter to call the submitProcessData method, which transmits the information to the process platform system. At the same time, the status of this business opportunity is updated from "created" to "under review". The approval steps can be viewed and performed by opening the process platform.

[0136] (2) Finally, call the ESA add or edit interface of the open banking core system to save the complete information of this merchant to the database.

[0137] The ESA's add or edit interface can be any of the following:

[0138] 1)obp-core-mch.businessOpportunity.update;

[0139] 2)obp-core-mch.businessOpportunity.add.

[0140] (3) When calling interfaces such as details, display the enterprise social credit code and legal person ID number that have been entered in accordance with industry standards using a mask.

[0141] (4) When the merchant information is successfully entered and submitted for review, it is sent to the process platform for review. Each reviewer in the approval process can see the two flags of the merchant and use them as a reference during the review.

[0142] In the above steps, the query platform saves the merchant information corresponding to the non-zero field values ​​to the system's database through the system's ESA interface.

[0143] The above steps automate processing, judgment, and collaborative work. Specifically, by checking whether there are any non-zero values ​​in the target related transaction field, related transaction enterprise field, and related transaction legal person field, the non-zero field values ​​are output to the process platform for review, and the approved merchant information is saved to the system's database. Automated processing and updating improve efficiency and accuracy, reduce manual intervention and errors, lower costs and risks, and facilitate subsequent queries, monitoring, and recording. Collaboration with the process platform better ensures the security and compliance of merchant information.

[0144] In summary, this embodiment modifies the merchant onboarding process and platform of the open banking system, adding a system that automatically retrieves related transaction information from big data and automatically adds tags indicating whether a transaction is related. This system works effectively for back-end reviewers, platform reviewers, and merchant details display, intercepting potential compliance risks of related transactions in open banking at the source. Furthermore, the system's automatic back-end calculations avoid the compliance risks of business personnel frequently viewing sensitive merchant information, and the system also saves time spent manually comparing related transactions during merchant onboarding and approval processes, greatly improving merchant operational efficiency.

[0145] In addition, refer to Figure 8 This embodiment also provides a merchant-related transaction query device, including:

[0146] Synchronization module 10 is used to obtain the related transaction table in the big data warehouse on the system side, import it into the database on the query platform side and save it;

[0147] Input module 20 is used to query the platform to obtain the basic information of the target merchant to be queried; wherein, the basic information of the target merchant includes enterprise information and legal person information;

[0148] The query module 30 is used by the query platform to match the enterprise information and legal person information in the basic information of the target merchant with the data in the related transaction table according to the query review instruction, and output the merchant related transaction query results.

[0149] In addition, this embodiment also provides a merchant-related transaction query system, including a memory and a processor. The memory stores a merchant-related transaction query program, and the processor runs the merchant-related transaction query program to enable the merchant-related transaction query system to perform the merchant-related transaction query method as described above.

[0150] In addition, this embodiment also provides a computer-readable storage medium storing a merchant-related transaction query program, which, when executed by a processor, implements the merchant-related transaction query method as described above.

[0151] In summary, the present invention provides a merchant related transaction query method, device, system, and storage medium. The method automatically extracts related transaction information from the system's big data warehouse on the platform side, matches relevant related transaction data, and adds labeling processing for whether a transaction belongs to a related party. During the query, it can provide prompts for back-end reviewers, process platform reviewers, and merchant details display. It intercepts potential related transaction compliance risks in open banking from the source, saves time in the merchant onboarding and approval process for manual comparison of related transactions, greatly improves merchant operational efficiency, and facilitates risk elimination work for financial institutions.

[0152] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0153] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of the present invention. The above are only preferred embodiments of the present invention and do not limit the patent scope of the present invention. Any equivalent structural or procedural transformations made based on the content of the present invention specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A method for querying merchant-related transactions, characterized in that, include: Retrieve the related transaction table from the big data warehouse on the system side, import it into the database on the query platform side, and save it; The query platform retrieves the basic information of the target merchant to be queried; wherein, the basic information of the target merchant includes enterprise information and legal person information; The query platform, based on the query review instruction, matches the enterprise information and legal representative information in the target merchant's basic information with the data in the related transaction table, and outputs the merchant related transaction query results, specifically including: The enterprise information in the basic information of the target merchant is matched with the data in the related transaction table, and the related transaction enterprise field value is output; and the legal person information is matched with the data in the related transaction table, and the related transaction legal person field value is output. If either the related party transaction enterprise field value or the related party transaction legal person field value is 1, then a related party transaction is determined to exist. Update the target related transaction field value to 1, and use the target related transaction field value, the related transaction enterprise field value, and the related transaction legal person field value as the merchant related transaction query result; After updating the target related transaction field value to 1, and using the target related transaction field value, the related transaction enterprise field value, and the related transaction legal person field value as the merchant related transaction query result, the process further includes: The query platform determines whether there are any non-zero field values ​​among the target related transaction field value, the related transaction enterprise field value, and the related transaction legal person field value; If there is a field value that is not zero, the query platform will use the non-zero field value as an input parameter and call the submitProcessData method to output the non-zero field value to the process platform so that it can be reviewed by the process platform. The query platform saves the merchant information corresponding to the non-zero field values ​​to the database of the system through the ESA interface of the system. When calling interfaces such as details, the enterprise's social credit code and legal representative's ID number that have been entered are displayed with a mask that conforms to industry standards. When merchant information is successfully entered and submitted for review, it is sent to the process platform for review. Each reviewer in the approval process can see the values ​​of the related transaction enterprise field and the related transaction legal person field of the merchant and use them as a reference during the review.

2. The merchant-related transaction query method as described in claim 1, characterized in that, The process of obtaining the related transaction table from the big data warehouse on the system side, importing it into the database on the query platform side, and saving it includes: The query platform sends an application to the system for access and decryption permissions for the related transaction table; wherein, the related transaction table is synchronized with all related transaction party information on a T+1 basis; After obtaining the docking and decryption permissions based on the application information, the query platform decrypts the related transaction table through the ESA interface, and then saves the related transaction table to the database of the query platform through the DSP job method of Hive to db.

3. The merchant-related transaction query method as described in claim 1, characterized in that, The step involves matching the enterprise information in the target merchant's basic information with the data in the related transaction table, and outputting the related transaction enterprise field value. Furthermore, after matching the legal entity information with the data in the related-party transaction table and outputting the related-party transaction legal entity field value, the process also includes: If both the related party transaction enterprise field value and the related party transaction legal person field value are 0, then it is determined that there is no related party transaction; Update the target related transaction field value to 0, and use the target related transaction field value, the related transaction enterprise field value, and the related transaction legal person field value as the merchant related transaction query result.

4. The method of claim 1, wherein the merchant association transaction query is a query of a transaction database of a merchant association. The step of matching the enterprise information in the target merchant's basic information with the data in the related transaction table includes: Using the enterprise social credit code type as the account type field, and using the enterprise social credit code number in the target merchant's basic information as the document number field, perform a select count query on the data in the related transaction table; If the count result is greater than 1, then update the value of the related transaction enterprise field to 1; If the count result is not greater than 1, then update the value of the related transaction enterprise field to 0.

5. The method of claim 1, wherein the merchant association transaction query is a query of a transaction database of a merchant association. The step of matching the legal entity information with the data in the related transaction table and outputting the related transaction legal entity field value includes: Using the ID card number type as the account type field, and using the corporate legal person's ID card number in the target merchant's basic information as the document number field, perform a select count query on the data in the related transaction table; If the count result is greater than 1, then update the value of the related transaction legal person field to 1; If the count result is not greater than 1, then update the value of the related transaction legal person field to 0.

6. A merchant-related transaction query device, characterized in that, include: The synchronization module is used to retrieve the related transaction tables from the big data warehouse on the system side, import them into the database on the query platform side, and save them. The input module is used to query the basic information of the target merchant to be queried from the platform; wherein, the basic information of the target merchant includes enterprise information and legal person information; The query module is used by the query platform to match the enterprise information and legal representative information in the target merchant's basic information with the data in the related transaction table according to the query review instruction, and output the merchant related transaction query results, specifically including: The enterprise information in the basic information of the target merchant is matched with the data in the related transaction table, and the related transaction enterprise field value is output; and the legal person information is matched with the data in the related transaction table, and the related transaction legal person field value is output. If either the related party transaction enterprise field value or the related party transaction legal person field value is 1, then a related party transaction is determined to exist. Update the target related transaction field value to 1, and use the target related transaction field value, the related transaction enterprise field value, and the related transaction legal person field value as the merchant related transaction query result; After updating the target related transaction field value to 1, and using the target related transaction field value, the related transaction enterprise field value, and the related transaction legal person field value as the merchant related transaction query result, the process further includes: The query platform determines whether there are any non-zero field values ​​among the target related transaction field value, the related transaction enterprise field value, and the related transaction legal person field value; If there is a field value that is not zero, the query platform will use the non-zero field value as an input parameter and call the submitProcessData method to output the non-zero field value to the process platform so that it can be reviewed by the process platform. The query platform saves the merchant information corresponding to the non-zero field values ​​to the database of the system through the ESA interface of the system. When calling interfaces such as details, the enterprise's social credit code and legal representative's ID number that have been entered are displayed with a mask that conforms to industry standards. When merchant information is successfully entered and submitted for review, it is sent to the process platform for review. Each reviewer in the approval process can see the values ​​of the related transaction enterprise field and the related transaction legal person field of the merchant and use them as a reference during the review.

7. A merchant association transaction inquiry system, characterized by, The system includes a memory and a processor. The memory stores a merchant-related transaction query program, and the processor runs the merchant-related transaction query program to enable the merchant-related transaction query system to perform the merchant-related transaction query method as described in any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a merchant-related transaction query program, which, when executed by a processor, implements the merchant-related transaction query method as described in any one of claims 1-5.

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