User data processing method and device, electronic equipment and computer program product

Abstract

The invention discloses a user data processing method and device, electronic equipment and a computer program product. Relates to the field of financial science and technology, and comprises the following steps: under the condition of authorization of M users, obtaining user information of the M users to obtain M groups of user information, M being a positive integer; a number generation model is obtained, the M groups of user information and the number generation model are utilized to determine financial groups associated with the M users and grouping numbers, and the number generation model is obtained by training historical users in a historical time period and grouping numbers of historical financial groups of the historical users; and storing the financial group to a user database according to the grouping number. Through application of the method and the device, the technical problems that the processing efficiency is low when the grouping numbers of the users are determined in related technologies, and the management efficiency is low when the users of the same group are managed are solved.

Description

Technical Field

[0001] This application relates to the field of financial technology, and more specifically, to a method, apparatus, electronic device, and computer program product for processing user data. Background Technology

[0002] In financial institutions' business systems, customer account grouping is a crucial function for effectively managing and tracking the financial information of a large number of customers. Grouping can be based on various criteria, such as region, account type, and customer name, to enable more granular data analysis and business processing. Each group requires a unique group number to ensure that the system can accurately identify and associate accounts belonging to the same group.

[0003] In the existing system architecture, group number generation relies on database sequences. When a group needs to be created for a new customer account, the system requests the next available sequence number from the database sequence, which is then used as the new group number. This method, based on the incremental nature of sequences, ensures that each generated group number is unique, avoiding data conflicts and duplication. However, in the above-mentioned database sequence-based group number generation mechanism, because database sequence updates require locking at the database level to ensure atomicity and uniqueness, the system must operate serially when processing new customer account registrations, meaning only one customer account can be processed at a time. This serial processing method significantly limits the system's processing capacity and efficiency, severely impacts user experience, and can easily lead to excessive consumption of system resources, increasing operational costs.

[0004] There is currently no effective solution to the technical problem of low processing efficiency in determining user group numbers and consequently low management efficiency when managing users in the same group. Summary of the Invention

[0005] The main objective of this application is to provide a user data processing method, apparatus, electronic device, and computer program product to solve the technical problems of low processing efficiency when determining user group numbers and low management efficiency when managing users in the same group in related technologies.

[0006] To achieve the above objectives, according to one aspect of this application, a method for processing user data is provided. The method includes: obtaining user information from M users under authorization, resulting in M ​​sets of user information, where M is a positive integer; obtaining a number generation model, and using the M sets of user information and the number generation model to determine the financial groups associated with the M users and their group numbers, wherein the number generation model is trained from the group numbers of historical users and their historical financial groups within a historical time period; and storing the financial groups in a user database based on the group numbers.

[0007] Furthermore, determining the associated financial groups and group numbers of the M users using the M user information and the number generation model includes: inputting the user information of each user into the number generation model, processing it to obtain the user group numbers of the M users, and obtaining the M user group numbers; selecting user group numbers from the M user group numbers that match the group numbers of the target financial groups in the user database, and obtaining the P target user group numbers, where P is a positive integer; and assigning the users with the P target user group numbers to the target financial groups.

[0008] Furthermore, determining the financial group and group number associated with M users using M sets of user information and a number generation model includes: obtaining a first grouping element; selecting users whose user information matches the first grouping element from the M users to obtain N users, where the first grouping element includes multiple elements, which are elements that all user information of users in the same financial group matches; N users refer to users who are allowed to be divided into one financial group, where N is less than or equal to M and N is a positive integer; inputting the N sets of user information of the N users into the number generation model, processing to obtain a group number; and constructing a financial group based on a group number, N users, and the N sets of user information of the N users.

[0009] Further, inputting N sets of user information from N users into the number generation model and processing them to obtain a group number includes: preprocessing each set of user information from N users to obtain N sets of user data, and concatenating the fields within each set of user data to obtain N combined strings; inputting each combined string into the number generation model to obtain N hash values; if the N hash values ​​are inconsistent, performing the step of filtering from the M users based on the M sets of user information to obtain N users; if the N hash values ​​are consistent, extracting the character data at a preset position in any hash value, and converting the format of the character data at the preset position to obtain the group number.

[0010] Furthermore, constructing a financial group based on a group number, N users, and N groups of user information for those N users includes: obtaining K second grouping elements; dividing the N users into different financial subsets based on the second grouping elements to obtain K financial subsets, wherein each financial group includes at least one financial subset, and each second grouping element is a grouping element that matches the user information of users in the same financial subset, where K is a positive integer; determining the subset number of each financial subset using a number generation model; and constructing a financial group from the K subset numbers, the users associated with the K financial subsets, and the user information of the users associated with the K financial subsets.

[0011] Furthermore, after obtaining user information for M users and obtaining M groups of user information, the method further includes: obtaining Y historical groups within a historical time period, and obtaining the grouping conditions associated with each historical group to obtain Y grouping conditions, where Y is a positive integer; for a user, if the user's user information matches the target grouping condition among the Y grouping conditions, obtaining the historical group associated with the target grouping condition, and assigning the user to the historical group associated with the target grouping condition.

[0012] Furthermore, after storing the financial groups in the user database according to the group number, the method further includes: receiving a user management instruction; extracting a target group number from the user management instruction, wherein the user management instruction is used to modify the user information of the financial groups associated with the target group number; extracting Y users of the financial groups associated with the target group number from the user database according to the target group number, wherein Y is a positive integer; and adjusting the user information of the Y users according to the user management instruction.

[0013] To achieve the above objectives, according to another aspect of this application, a user data processing apparatus is provided. The apparatus includes: a first acquisition unit, configured to acquire user information of M users, given authorization from M users, to obtain M sets of user information, where M is a positive integer; a second acquisition unit, configured to acquire a number generation model, and use the M sets of user information and the number generation model to determine the financial groups associated with the M users and their group numbers, wherein the number generation model is trained from historical users within a historical time period and the group numbers of historical financial groups of historical users; and a storage unit, configured to store the financial groups in a user database according to the group numbers.

[0014] According to another aspect of the present invention, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored executable program, wherein, when the executable program is running, it controls the device where the computer-readable storage medium is located to perform any of the above-described user data processing methods.

[0015] According to another aspect of the present invention, an electronic device is also provided, including one or more processors and a memory, the memory storing an executable program, and the processor for running the program, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement any of the above-described user data processing methods.

[0016] According to another aspect of the present invention, a computer program product is also provided, the computer program product including a computer program, wherein the computer program, when executed by a processor, implements any of the above-described user data processing methods.

[0017] In this embodiment, user data processing is employed. With authorization from M users, user information for M users is obtained, resulting in M ​​sets of user information, where M is a positive integer. A number generation model is acquired, and the financial groups and group numbers associated with the M users are determined using the M sets of user information and the number generation model. The number generation model is trained using the group numbers of historical users and their historical financial groups within a historical time period. The financial groups are then stored in the user database based on the group numbers. This addresses the technical problems of low processing efficiency in determining user group numbers and consequently low management efficiency when managing users within the same group in related technologies. By utilizing user information and the number generation model to determine the financial groups and group numbers associated with each user, the efficiency of determining user group numbers and, consequently, the efficiency of managing users and their corresponding user information is improved. Attached Figure Description

[0018] The accompanying drawings, which form part of this application, are used to provide a further understanding of this application. The illustrative embodiments and descriptions of this application are used to explain this application and do not constitute an undue limitation of this application. In the drawings:

[0019] Figure 1 It is a hardware structure block diagram of a computer terminal (or mobile device) used to implement a method for processing user data;

[0020] Figure 2 This is a flowchart of a user data processing method provided according to an embodiment of this application;

[0021] Figure 3 This is a schematic diagram of a financial group provided according to an embodiment of this application;

[0022] Figure 4 This is a schematic diagram of a user data processing apparatus provided according to an embodiment of this application;

[0023] Figure 5 This is a structural block diagram of an electronic device according to an embodiment of this application. Detailed Implementation

[0024] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0025] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0026] It should be noted that all information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for display, data used for analysis, etc.) involved in this application are information and data authorized by the user or fully authorized by all parties. For example, this system has interfaces with relevant users or organizations to provide users with corresponding operation data for them to choose to agree to or refuse automated decision-making results. Before obtaining relevant information, a request for obtaining the information needs to be sent to the aforementioned user or organization through the interface, and the relevant information is obtained after receiving consent from the aforementioned user or organization; if the user chooses to refuse, the expert decision-making process is initiated. Users can view the purpose of data use in real time through authorization decoding and have the right to withdraw authorization or delete data at any time. After the authorization is withdrawn, the system will terminate the relevant data processing within 24 hours.

[0027] It should be noted that the information collected in this application is information and data authorized by the user or fully authorized by all parties, and the collection, storage, use, processing, transmission, provision, disclosure and application of the relevant data all comply with the relevant laws, regulations and standards of the relevant regions, take necessary confidentiality measures, do not violate public order and good morals, and provide corresponding operation access points for users to choose to authorize use or refuse use.

[0028] Example 1

[0029] According to an embodiment of this application, a method embodiment for processing user data is also provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0030] The method embodiment provided in Embodiment 1 of this application can be executed on a mobile terminal, computer terminal, or similar computing device. Figure 1 This is a hardware structure block diagram of a computer terminal (or mobile device) used to implement a method for processing user data, such as... Figure 1 As shown, computer terminal 10 (or mobile device) may include one or more ( Figure 1 The processor 102 (which may include, but is not limited to, a microprocessor MCU (Microcontroller Unit) or a programmable gate array (FPGA)) is shown as 102a, 102b, ..., 102n. It also includes a memory 104 for storing data and a transmission device 106 for communication functions. In addition, it may include: a display, an input / output interface, a Universal Serial Bus (USB) port (which may be included as one of the ports of a BUS bus), a network interface, a keyboard, a cursor control device, a power supply, and / or a camera. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the aforementioned electronic device. For example, computer terminal 10 may also include... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.

[0031] It should be noted that the aforementioned one or more processors 102 and / or other data processing circuits are generally referred to herein as "data processing circuits". These data processing circuits may be embodied, in whole or in part, in software, hardware, firmware, or any other combination thereof. Furthermore, the data processing circuits may be a single, independent processing module, or may be integrated, in whole or in part, into any other element within the computer terminal 10 (or mobile device). As involved in the embodiments of this application, the data processing circuits serve as a processor control mechanism (e.g., selection of a variable resistor termination path connected to an interface).

[0032] The memory 104 can be used to store software programs and modules of application software, such as the program instructions / data storage device corresponding to the user data processing method in this embodiment. The processor 102 executes various functional applications and data processing by running the software programs and modules stored in the memory 104, thereby realizing the aforementioned user data processing method. The memory 104 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory remotely located relative to the processor 102, and these remote memories can be connected to the computer terminal 10 via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0033] The transmission device 106 is used to receive or send data via a network. Specific examples of the network described above may include a wireless network provided by the communication provider of the computer terminal 10. In one example, the transmission device 106 includes a network interface controller (NIC) and a network interface, which can be connected to other network devices via a base station to communicate with the Internet. In another example, the transmission device 106 may be a radio frequency (RF) module, used for wireless communication with the Internet.

[0034] The display can be, for example, a touchscreen liquid crystal display (LCD), which allows the user to interact with the user interface of the computer terminal 10 (or mobile device).

[0035] Under the aforementioned operating environment, this application provides the following: Figure 2 The method for processing user data is shown. Figure 2 This is a flowchart of a user data processing method provided according to an embodiment of this application, such as... Figure 2 As shown, the method includes the following steps:

[0036] Step S201: With authorization from M users, obtain user information from M users to obtain M sets of user information, where M is a positive integer.

[0037] Specifically, in order to identify multiple user financial groups and their corresponding group numbers, it is necessary to obtain the authorization of these users before acquiring their relevant information. After these users authorize the process, user information for each user, including key fields such as customer number, account name, and region code, is obtained, thereby generating multiple sets of user information.

[0038] Step S202: Obtain the number generation model. Use the M sets of user information and the number generation model to determine the financial groups and group numbers associated with the M users. The number generation model is trained from the group numbers of historical users and their historical financial groups within the historical time period.

[0039] It should be noted that a number generation model can be used to determine group numbers. This model calculates group numbers using a hash algorithm. A hash algorithm ensures that for the same data or the same set of data, the result remains unchanged after each hashing process. Even slight differences in the data will alter the hash result. Therefore, after determining each financial group, the group numbers calculated using the hash algorithm will be the same. Furthermore, the model's training data can originate from existing user information and their corresponding financial group numbers within a historical time period. By learning patterns and relationships in historical data, the model can predict the most appropriate group assignment for a given user information, thereby generating the corresponding group number.

[0040] After obtaining multiple sets of user information, these user information can be input into a number to generate a model. The model then determines the corresponding group number and identifies the associated financial group based on the group number, thereby significantly improving the efficiency of account information processing. The financial group refers to a group formed by grouping customer accounts with the same characteristics or associations (such as the same region or the same account name).

[0041] Step S203: Store the financial group to the user database according to the group number.

[0042] Specifically, after obtaining the financial groups and group numbers of all the aforementioned users, the generated group numbers and corresponding financial group information can be stored together in the user database of the financial institution for subsequent querying, management, and data analysis.

[0043] It should be noted that after being stored in the user database, the group number and financial group information can be accessed and utilized by other components or business processes. For example, the group number can be used to quickly locate a specific financial group, accelerating the query speed and improving the efficiency and response speed of business operations. By storing the group number and financial group information in the user database, centralized management is facilitated, data redundancy is reduced, and data consistency and accuracy are improved. The stored group number and financial group information can be used for business analysis and decision-making, such as monitoring account activity under specific regions or account names to identify potential business patterns or risks.

[0044] The user data processing method provided in this application embodiment obtains user information from M users with authorization, resulting in M ​​sets of user information, where M is a positive integer; obtains a number generation model, and uses the M sets of user information and the number generation model to determine the financial groups and group numbers associated with the M users, wherein the number generation model is trained from the group numbers of historical users and their historical financial groups within a historical time period; and stores the financial groups in the user database according to the group numbers. This solves the technical problem in related technologies where the processing efficiency of determining user group numbers is low, and consequently, the management efficiency of managing users in the same group is low. By using user information and the number generation model to determine the financial groups and group numbers associated with each user, the method achieves the technical effect of improving the efficiency of determining user group numbers and thus improving the efficiency of managing users and their corresponding user information.

[0045] Optionally, in the user data processing method provided in this application embodiment, determining the financial groups associated with M users and their group numbers using M sets of user information and a number generation model includes: inputting the user information of each user into the number generation model, processing it to obtain the user group numbers of the M users, and obtaining M user group numbers; selecting user group numbers from the M user group numbers that are consistent with the group numbers of the target financial groups in the user database, and obtaining P target user group numbers, where P is a positive integer; and assigning the users with the P target user group numbers to the target financial groups.

[0046] The method for determining a user's financial group and group number is to filter financial groups based on the group number. Specifically, the user information of all users (which may include customer number, area code, and account name) can be input one by one into the number generation model. The model can then calculate the user group number that matches the user's characteristics based on the input user information. This avoids the inefficient operation of serially accessing the database sequence in traditional methods and significantly improves the efficiency of account registration and group number allocation.

[0047] Furthermore, from the user group numbers output above, numbers that match the existing target financial group numbers in the user database are selected. This selection process involves comparing the newly generated user group numbers with the existing target financial group numbers in the database to determine which new users can be added to existing financial groups, avoiding the creation of unnecessary new groups and ensuring group consistency and data integrity. Finally, users with multiple matching user group numbers are selected and assigned to the corresponding financial groups based on their matching target financial group numbers, thereby improving the overall performance and accuracy when processing large-scale user data.

[0048] This embodiment utilizes a number generation model to process large amounts of user information in parallel, quickly generating user group numbers. Then, through database filtering, new users can be accurately categorized into existing financial groups, reducing unnecessary group creation and optimizing the database structure. This not only improves the efficiency of user account grouping and reduces processing latency, but also provides financial institutions with a more intelligent and flexible means of customer data management, significantly enhancing user experience and the data processing capabilities of financial institutions.

[0049] Optionally, in the user data processing method provided in this application embodiment, determining the financial group associated with M users and the group number using M sets of user information and a number generation model includes: obtaining a first grouping element; filtering users whose user information matches the first grouping element from the M users to obtain N users, wherein the first grouping element includes multiple elements, and the multiple elements are elements that all user information of users in the same financial group matches; N users refer to users who are allowed to be divided into one financial group, N is less than or equal to M, and N is a positive integer; inputting the N sets of user information of the N users into the number generation model, processing to obtain a group number, and constructing a financial group based on a group number, N users, and the N sets of user information of the N users.

[0050] Another method for determining a user's financial group and group number is to filter users based on grouping elements. Specifically, the first grouping element can be obtained to determine whether a user is qualified to be classified into the same financial group. For example, the elements in the first grouping element can be the same area code and the same account name, and all user information must be the same at the same time.

[0051] Furthermore, the user information of the above users is filtered, and only those users whose user information completely matches the first grouping element are retained, forming a subset of N users. The filtering process involves comparing the matching degree of each user's user information with multiple elements in the first grouping element. Only when all elements match successfully will the user be included in the list of N users. For example, when the first grouping element is that the area code and the account name in the user information are the same, users with the same area code and the same account name can be grouped together.

[0052] The information of the selected users is then input into the number generation model. The model processes this information and calculates a group number. This group number is calculated using a model algorithm based on the common information of the selected users (i.e., the multiple elements covered by the first group element). This ensures that even with parallel processing of a large amount of user information, a unique and correct group number can be generated. Finally, the newly generated group number, N users, and their information are combined to formally constitute a new financial group. This group information is then stored in the user database. For example, Figure 3 This is a schematic diagram of a financial group provided according to an embodiment of this application, such as... Figure 3 As shown, after obtaining authorization from three users (User A, User B, and User C), user information such as their accounts and area codes can be retrieved from the financial institution's database (User A's account number is 001, User B's account number is 002, and User C's account number is 003). Then, the user information is filtered according to the first grouping element. Finally, User A and User C are divided into a financial group with group number A01, and User B is divided into a financial group with group number A02.

[0053] This embodiment effectively solves the problem of how to efficiently and accurately group customer accounts in a large-scale data processing environment by filtering user information and generating group numbers. It not only improves the speed of data processing, but also makes the division of financial groups conform to business logic, avoids unnecessary group duplication, and reduces management complexity.

[0054] Optionally, in the user data processing method provided in this application embodiment, inputting N sets of user information from N users into a number generation model to obtain a group number includes: preprocessing each set of user information from N users to obtain N sets of user data, and concatenating the fields within each set of user data to obtain N combined strings; inputting each combined string into the number generation model to obtain N hash values; if the N hash values ​​are inconsistent, performing the step of filtering from the M users based on the M sets of user information to obtain N users; if the N hash values ​​are consistent, extracting character data at a preset position in any hash value, and converting the format of the character data at the preset position to obtain a group number.

[0055] Specifically, when using the number generation model to determine the group numbers of the selected users, the user information of the selected users can first be preprocessed. This involves preprocessing the information set, including customer number, area code, and account name, such as cleaning, standardizing, and formatting the original user information to obtain multiple sets of user data. Then, the fields within each set of user data, such as customer number, area code, and account name, are concatenated to form multiple independent combined strings. By generating combined strings through field concatenation, the data format required by the number generation model is created, enabling the model to accurately understand and process the information of each user.

[0056] Further, each combined string is input into the model for number generation. The model processes each input string to generate a corresponding hash value. The hash values ​​are then evaluated. If the hash values ​​are inconsistent after calculation, it indicates that these users do not meet the criteria for being classified into the same financial group. The process must revert to the initial screening step, re-evaluating all users to find the truly eligible user group. When all hash values ​​are consistent, it indicates that these users meet the criteria for being classified into the same financial group. At this point, character data at a preset position is extracted from any hash value, for example, the first 15 characters are extracted. This character data is then formatted to meet the requirements for group numbering (such as format), finally yielding the group number.

[0057] This embodiment, through preprocessing, hash calculation, and conditional filtering, can detect and process user information that meets the conditions, generate and assign appropriate financial group group numbers, greatly reduce processing time, improve overall operational efficiency, reduce the need for manual intervention, lower the error rate, and enhance user experience and service level.

[0058] Optionally, in the user data processing method provided in this application embodiment, constructing a financial group based on a group number, N users, and N groups of user information of the N users includes: obtaining K second grouping elements; dividing the N users into different financial subsets based on the second grouping elements to obtain K financial subsets, wherein each financial group includes at least one financial subset, and each second grouping element is a grouping element that matches the user information of users in the same financial subset, and K is a positive integer; determining the subset number of each financial subset using a number generation model; and constructing a financial group by the K subset numbers, the users associated with the K financial subsets, and the user information of the users associated with the K financial subsets.

[0059] Specifically, after obtaining the group number, to construct financial groups, the first step is to acquire second grouping elements. These elements can be account type, currency used, etc. Each second grouping element represents a specific rule or condition used to determine whether a user meets the criteria for entering a particular financial subset. For example, second grouping elements could include the same region code and the same currency. Then, using these second grouping elements, the already filtered users are further filtered and divided, grouping users who meet the same grouping element conditions into the same financial subset. In other words, based on the different information from each second grouping element, users are further subdivided into smaller sets of users with common characteristics.

[0060] For each generated financial subset, a numbering model is used to assign it a subset number. Finally, the subset number, along with its associated financial subset and user information within the subset, are integrated to form a complete financial group. This financial group not only includes the original N users but is further refined into multiple financial subsets with specific characteristics. Each subset has its own subset number. The financial group has a multi-level structure, with both macro-level user group classification and micro-level user characteristic segmentation, providing financial institutions with more refined and flexible data management tools.

[0061] This embodiment further segments users, making group division more precise, which greatly improves processing speed and accuracy, provides financial institutions with rich data insight perspectives, and helps to promote business innovation and improve service quality.

[0062] Optionally, in the user data processing method provided in the embodiments of this application, after obtaining user information of M users and obtaining M groups of user information, the method further includes: obtaining Y historical groups within a historical time period, and obtaining the grouping conditions associated with each historical group to obtain Y grouping conditions, where Y is a positive integer; for a user, if the user's user information matches the target grouping condition among the Y grouping conditions, obtaining the historical group associated with the target grouping condition, and assigning the user to the historical group associated with the target grouping condition.

[0063] Specifically, after obtaining user information for all users, the system first retrieves historical groups within a given time period and then identifies grouping criteria associated with each group. These criteria are based on a series of specific attributes, such as the customer's location, account type, and transaction frequency, and are used to define the standards for a financial group. For each user to be processed, their user information is matched against the collected grouping criteria one by one.

[0064] If a user's information fully matches one of the grouping criteria (referred to as the target grouping criterion), then the user is eligible to join the historical group associated with that criterion. Once it is confirmed that a user's information matches a target grouping criterion, the user can be assigned to the historical group associated with that target grouping criterion, achieving seamless integration between new user data and historical data.

[0065] This embodiment analyzes historical groups and grouping conditions to identify and match the groups to which new users belong, significantly improving the efficiency and accuracy of grouping, achieving data continuity and consistency, and enhancing customer experience and satisfaction.

[0066] Optionally, in the user data processing method provided in this application embodiment, after storing the financial group to the user database according to the group number, the method further includes: receiving a user management instruction; extracting a target group number from the user management instruction, wherein the user management instruction is used to modify the user information of the financial group associated with the target group number; extracting Y users of the financial group associated with the target group number from the user database according to the target group number, wherein Y is a positive integer; and adjusting the user information of the Y users according to the user management instruction.

[0067] Specifically, after determining each user's financial group and group number and storing them in the user database, when a user management instruction is received to modify or update user information for a specific financial group, the group number of the financial group to be modified can be extracted first, that is, the target group number can be extracted, thereby avoiding the processing of irrelevant data and improving operational efficiency and accuracy.

[0068] Furthermore, based on the extracted target group number, the user database is accessed to query and extract all users in the financial groups associated with that group number, thus filtering out the target group whose user information needs to be modified. Finally, according to the specific requirements of the user management instructions, the information of the aforementioned users is adjusted accordingly, such as updating account status, modifying account category, and adjusting account association information.

[0069] This embodiment achieves precise positioning of target groups and accurate adjustment of user information by adjusting the user information of relevant users according to user management instructions. It effectively prevents the risks of data misoperation and information leakage, maintains the stability and security of the system, improves the efficiency and flexibility of financial institutions' data management, and provides strong data support for the operation of financial institutions.

[0070] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0071] Example 2

[0072] This application also provides a user data processing apparatus. It should be noted that the user data processing apparatus of this application can be used to execute the user data processing method provided in this application. The user data processing apparatus provided in this application will be described below.

[0073] According to an embodiment of this application, an apparatus for implementing the above-described user data processing method is also provided. Figure 4This is a schematic diagram of a user data processing apparatus provided according to an embodiment of this application, such as... Figure 4 As shown, the device includes: a first acquisition unit 40, a second acquisition unit 41, and a storage unit 42.

[0074] The first acquisition unit 40 is used to acquire user information of M users under the authorization of M users, and obtain M sets of user information, where M is a positive integer;

[0075] The second acquisition unit 41 is used to acquire the number generation model, and use the M groups of user information and the number generation model to determine the financial groups and group numbers associated with the M users. The number generation model is trained by the group numbers of historical users and historical financial groups of historical users within a historical time period.

[0076] Storage unit 42 is used to store financial groups to the user database according to the group number.

[0077] The user data processing apparatus provided in this application embodiment obtains user information of M users under the authorization of M users through the first acquisition unit 40, resulting in M ​​sets of user information, where M is a positive integer; the second acquisition unit 41 acquires a number generation model, and uses the M sets of user information and the number generation model to determine the financial groups and group numbers associated with the M users, wherein the number generation model is trained by the group numbers of historical users and historical financial groups of historical users within a historical time period; the storage unit 42 stores the financial groups to the user database according to the group numbers. This solves the technical problem in related technologies that there is low processing efficiency when determining the group number of users, and thus low management efficiency when managing users in the same group. By using user information and the number generation model to determine the financial groups and group numbers associated with each user, the technical effect of improving the efficiency of determining the group number of users and thus improving the efficiency of managing users and corresponding user information is achieved.

[0078] Optionally, in the user data processing apparatus provided in this application embodiment, the second acquisition unit 41 includes: a first input module, used to input the user information of each user into a number generation model, process it to obtain user group numbers of M users, and obtain M user group numbers; a filtering module, used to filter user group numbers from the M user group numbers that are consistent with the group numbers of the target financial group in the user database, and obtain P target user group numbers, where P is a positive integer; and an allocation module, used to allocate users with the P target user group numbers to the target financial group.

[0079] Optionally, in the user data processing apparatus provided in this application embodiment, the second acquisition unit 41 includes: a first acquisition module, used to acquire a first grouping element, filter users whose user information matches the first grouping element from M users to obtain N users, wherein the first grouping element includes multiple elements, the multiple elements are elements in which the user information of users in the same financial group matches, and N users refer to users who are allowed to be divided into a financial group, N is less than or equal to M, and N is a positive integer; a second input module, used to input the N groups of user information of N users into a number generation model, process to obtain a grouping number, and form a financial group based on a grouping number, N users and N groups of user information of N users.

[0080] Optionally, in the user data processing apparatus provided in this application embodiment, the second acquisition unit 41 includes: a processing module, used to preprocess a group of user information of N users to obtain N groups of user data, and concatenate the fields within each group of user data to obtain N combined strings; a third input module, used to input each combined string into a number generation model and process it to obtain N hash values; an execution module, used to execute the step of filtering N users from M users based on M groups of user information if the N hash values ​​are inconsistent; and an extraction module, used to extract character data at a preset position in any hash value if the N hash values ​​are consistent, and convert the format of the character data at the preset position to obtain a group number.

[0081] Optionally, in the user data processing apparatus provided in this application embodiment, the second acquisition unit 41 includes: a second acquisition module, configured to acquire K second grouping elements, divide N users into different financial subsets according to the second grouping elements, and obtain K financial subsets, wherein each financial group includes at least one financial subset, and each second grouping element is a grouping element that the user information of the users of the same financial subset is matched, and K is a positive integer; and a determination module, configured to determine the subset number of each financial subset using a number generation model, wherein the financial group is composed of the K subset numbers, the users associated with the K financial subsets, and the user information of the users associated with the K financial subsets.

[0082] Optionally, in the user data processing apparatus provided in the embodiments of this application, the apparatus further includes: a third acquisition unit, configured to, after acquiring user information of M users and obtaining M sets of user information, acquire Y historical groups within a historical time period, and acquire the grouping conditions associated with each historical group to obtain Y grouping conditions, where Y is a positive integer; and a fourth acquisition unit, configured to, for a user, if the user's user information matches the target grouping condition among the Y grouping conditions, acquire the historical group associated with the target grouping condition, and assign the user to the historical group associated with the target grouping condition.

[0083] Optionally, in the user data processing apparatus provided in this application embodiment, the apparatus further includes: a receiving unit, configured to receive a user management instruction after storing the financial group to the user database according to the group number, and extract a target group number from the user management instruction, wherein the user management instruction is used to modify the user information of the financial group associated with the target group number; an extraction unit, configured to extract Y users of the financial group associated with the target group number from the user database according to the target group number, wherein Y is a positive integer; and an adjustment unit, configured to adjust the user information of the Y users according to the user management instruction.

[0084] It should be noted that the first acquisition unit 40, the second acquisition unit 41, and the storage unit 42 mentioned above correspond to steps S201 to S203 in Embodiment 1. The instances and application scenarios implemented by the above units and the corresponding steps are the same, but are not limited to the content disclosed in Embodiment 1. It should be noted that the above modules or units can be hardware or software components stored in memory (e.g., memory 104) and processed by one or more processors (e.g., processors 102a, 102b, ..., 102n). The above units can also be part of a device and can run in the computer terminal 10 provided in Embodiment 1.

[0085] Example 3

[0086] Embodiments of this application may provide a computer terminal, which may be any computer terminal device in a group of computer terminals. Optionally, in this embodiment, the aforementioned computer terminal may also be replaced with a mobile terminal or an electronic device, etc.

[0087] Optionally, in this embodiment, the computer terminal may be located in at least one of a plurality of network devices in a computer network.

[0088] In this embodiment, the computer terminal described above can execute the following steps in the user data processing method: Under the authorization of M users, obtain user information of M users to obtain M sets of user information, where M is a positive integer; obtain a number generation model, and use the M sets of user information and the number generation model to determine the financial groups and group numbers associated with the M users, wherein the number generation model is trained from the group numbers of historical users and their historical financial groups within a historical time period; store the financial groups in the user database according to the group numbers.

[0089] Optionally, the aforementioned computer terminal may execute the following steps in the user data processing method: inputting user information of each user into a number generation model, processing to obtain M user group numbers, and obtaining M user group numbers; selecting user group numbers from the M user group numbers that match the group numbers of the target financial group in the user database, and obtaining P target user group numbers, where P is a positive integer; and assigning the users with the P target user group numbers to the target financial group.

[0090] Optionally, the computer terminal described above can execute the program code for the following steps in the user data processing method: obtaining a first grouping element; filtering users whose user information matches the first grouping element from M users to obtain N users, wherein the first grouping element includes multiple elements, and the multiple elements are elements in which the user information of users in the same financial group matches; N users refer to users who are allowed to be divided into one financial group, N is less than or equal to M, and N is a positive integer; inputting the N sets of user information of N users into a number generation model, processing to obtain a grouping number, and constructing a financial group based on a grouping number, N users, and the N sets of user information of N users.

[0091] Optionally, the aforementioned computer terminal can execute the following steps in the user data processing method: preprocessing user information from N users to obtain N sets of user data, and concatenating the fields within each set of user data to obtain N combined strings; inputting each combined string into a number generation model to obtain N hash values; if the N hash values ​​are inconsistent, performing the step of filtering from M users based on M sets of user information to obtain N users; if the N hash values ​​are consistent, extracting character data at a preset position from any hash value, converting the format of the character data at the preset position, and obtaining a group number.

[0092] Optionally, the aforementioned computer terminal may execute the following steps in the user data processing method: obtaining K second grouping elements; dividing N users into different financial subsets based on the second grouping elements to obtain K financial subsets, wherein each financial group includes at least one financial subset, and each second grouping element is a grouping element that matches the user information of users in the same financial subset, where K is a positive integer; determining the subset number of each financial subset using a number generation model, and constituting a financial group by the K subset numbers, the users associated with the K financial subsets, and the user information of the users associated with the K financial subsets.

[0093] Optionally, the computer terminal described above can execute the program code for the following steps in the user data processing method: obtain Y historical groups within a historical time period, and obtain the grouping conditions associated with each historical group to obtain Y grouping conditions, where Y is a positive integer; for a user, if the user's user information matches the target grouping condition among the Y grouping conditions, obtain the historical group associated with the target grouping condition, and assign the user to the historical group associated with the target grouping condition.

[0094] Optionally, the computer terminal described above can execute the program code for the following steps in the user data processing method: receiving a user management instruction; extracting a target group number from the user management instruction, wherein the user management instruction is used to modify the user information of the financial group associated with the target group number; extracting Y users of the financial group associated with the target group number from the user database according to the target group number, wherein Y is a positive integer; and adjusting the user information of the Y users according to the user management instruction.

[0095] Optionally, Figure 5 This is a structural block diagram of an electronic device according to an embodiment of this application. Figure 5 As shown, the electronic device may include: one or more ( Figure 5 (Only one is shown) processor 502, memory 504, memory controller, and peripheral interface, wherein the peripheral interface is connected to the radio frequency module, audio module and display.

[0096] The memory can be used to store software programs and modules, such as the program instructions / modules corresponding to the user data processing method and apparatus in this application embodiment. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory, thereby realizing the aforementioned user data processing method. The memory may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory may further include memory remotely located relative to the processor, and these remote memories can be connected to the terminal via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0097] The processor can access the information and application programs stored in the memory via the transmission device to execute the steps described above in the user data processing method.

[0098] Those skilled in the art will understand that Figure 5The structure shown is for illustrative purposes only. Electronic devices can also be smartphones, tablets, handheld computers, mobile internet devices (MIDs), PADs, and other terminal devices. Figure 5 This does not limit the structure of the aforementioned electronic device. For example, electronic devices may also include components that are more... Figure 5 The more or fewer components shown (such as network interfaces, display devices, etc.), or having the same Figure 5 The different configurations shown.

[0099] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing the hardware related to the terminal device. The program can be stored in a computer-readable storage medium, which may include: flash drive, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc.

[0100] Example 4

[0101] Embodiments of this application also provide a storage medium. Optionally, in this embodiment, the storage medium can be used to store the program code executed by the user data processing method provided in Embodiment 1.

[0102] Optionally, in this embodiment, the storage medium may be located in any computer terminal in a group of computer terminals in a computer network, or in any mobile terminal in a group of mobile terminals.

[0103] Optionally, in this embodiment, the storage medium is configured to store program code for performing the following steps: under the authorization of M users, obtain user information of M users to obtain M sets of user information, where M is a positive integer; obtain a number generation model, and use the M sets of user information and the number generation model to determine the financial groups and group numbers associated with the M users, wherein the number generation model is trained by the group numbers of historical users and historical financial groups of historical users within a historical time period; store the financial groups in the user database according to the group numbers.

[0104] This application also provides a computer program product, which, when executed on a data processing device, is adapted to perform user data processing method steps.

[0105] The sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0106] In the above embodiments of this application, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0107] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection of units or modules may be electrical or other forms.

[0108] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0109] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0110] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard drive, magnetic disk, or optical disk.

[0111] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method for processing user data, characterized in that, include: With authorization from M users, obtain the user information of the M users to obtain M sets of user information, where M is a positive integer; Obtain a number generation model, and use the M groups of user information and the number generation model to determine the financial groups and group numbers associated with the M users, wherein the number generation model is trained from the group numbers of historical users and their historical financial groups within a historical time period. The financial groups are stored in the user database according to the group number.

2. The method according to claim 1, characterized in that, Using the M sets of user information and the number generation model, determining the associated financial groups and group numbers of the M users includes: Input each user's information into the number generation model, process it to obtain the user group numbers of the M users, and obtain the M user group numbers; From the M user group numbers, select user group numbers that match the group numbers of the target financial group in the user database to obtain P target user group numbers, where P is a positive integer; The users with the P target user group numbers are assigned to the target financial group.

3. The method according to claim 1, characterized in that, Using the M sets of user information and the number generation model, determining the associated financial groups and group numbers of the M users includes: Obtain the first grouping element, filter users whose user information matches the first grouping element from the M users to obtain N users, wherein the first grouping element includes multiple elements, the multiple elements are elements in which the user information of users in the same financial group matches, and the N users refer to users who are allowed to be divided into one financial group, N is less than or equal to M, and N is a positive integer; The N sets of user information of the N users are input into the number generation model, processed to obtain a group number, and a financial group is formed based on the group number, the N users, and the N sets of user information of the N users.

4. The method according to claim 3, characterized in that, Inputting N sets of user information from the N users into the number generation model, and processing them to obtain a group number includes: Preprocess the user information of N users into N sets of user data, and concatenate the fields within each set of user data to obtain N combined strings; Each combined string is input into the number generation model, and N hash values ​​are obtained; If the N hash values ​​are inconsistent, the step of filtering N users from the M users based on the M sets of user information is performed. If the N hash values ​​are consistent, extract the character data at a preset position in any hash value, convert the format of the character data at the preset position, and obtain the group number.

5. The method according to claim 3, characterized in that, A financial group is formed based on the aforementioned group number, the N users, and the N sets of user information for the N users, including: Obtain K second grouping elements, and divide the N users into different financial subsets according to the second grouping elements to obtain K financial subsets. The financial group includes at least one financial subset. Each second grouping element is a grouping element that matches the user information of users in the same financial subset. K is a positive integer. The subset number of each financial subset is determined using the numbering generation model. The financial group consists of K subset numbers, the users associated with the K financial subsets, and the user information of the users associated with the K financial subsets.

6. The method according to claim 1, characterized in that, After obtaining the user information of the M users and obtaining M sets of user information, the method further includes: Get Y historical groups within a historical time period, and get the grouping conditions associated with each historical group to obtain Y grouping conditions, where Y is a positive integer; For a user, if the user information matches the target group condition among the Y grouping conditions, the historical group associated with the target group condition is obtained, and the user is assigned to the historical group associated with the target group condition.

7. The method according to claim 1, characterized in that, After storing the financial group in the user database according to the group number, the method further includes: Receive user management instructions, extract target group number from the user management instructions, wherein the user management instructions are used to modify user information of the financial group associated with the target group number; Based on the target group number, extract Y users from the user database belonging to the financial group associated with the target group number, where Y is a positive integer; The user information of the Y users is adjusted according to the user management instructions.

8. A user data processing apparatus, characterized in that, include: The first acquisition unit is used to acquire user information of the M users under the authorization of the M users, and obtain M sets of user information, where M is a positive integer; The second acquisition unit is used to acquire the number generation model, and use the M groups of user information and the number generation model to determine the financial groups and group numbers associated with the M users. The number generation model is trained by the group numbers of historical users and their historical financial groups within a historical time period. A storage unit is used to store the financial groups to the user database according to the group number.

9. An electronic device, characterized in that, include: Memory, which stores executable programs; A processor for running the program, wherein the program, when running, performs the user data processing method according to any one of claims 1 to 7.

10. A computer program product comprising computer instructions, characterized in that, When the computer instructions are executed by the processor, they implement the steps of the user data processing method according to any one of claims 1 to 7.

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