User data processing method and device, electronic equipment and storage medium

Abstract

The invention provides a user data processing method and device, electronic equipment and a storage medium, and relates to the technical field of data processing. In the application, after the data adjustment instructions of the plurality of data managers for the target user are received, the data adjustment information corresponding to the plurality of data adjustment instructions can be determined based on the indication types corresponding to the plurality of data adjustment instructions, so that the target user can be adjusted according to the preset data adjustment instruction description mode. And converting the plurality of data adjustment indications into target data indications represented by the same data adjustment information indication mode. By adopting the mode, the data adjustment indication indicated by different data adjustment information indication modes is converted into the target data indication indicated by the same data adjustment information indication mode, so that the recognition efficiency and the recognition accuracy of the adjustment information of the user data (namely the lending condition of the target user) subsequently are improved.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a user data processing method, device, electronic device and storage medium. Background Art

[0002] At present, for the three stages of the user's (i.e., object) lending process (i.e., pre-loan, mid-loan, and post-loan), managers at different stages can flexibly adjust the user's lending situation based on information such as the user's credit and / or repayment ability, and indicate corresponding adjustment information according to the adjustment information indication methods set for the aforementioned three stages.

[0003] After receiving the adjustment information instruction from the administrator, the credit system can identify the adjustment information in combination with the adjustment information instruction method set at the corresponding stage, and save the adjustment information to the database set for the user for subsequent related business processing. For example, query the user's current loan status.

[0004] However, with the above method, since it is necessary to combine the adjustment information indication methods set at different stages in order to accurately identify the corresponding adjustment information, the efficiency of the credit system in identifying the adjustment information is low.

[0005] In addition, if the same adjustment information indication refers to different adjustment information in different adjustment information indication methods, it may cause the credit system to be unable to accurately identify the adjustment information.

[0006] For example, the adjustment information indication A in the pre-loan stage is used to indicate the adjustment of the user's fixed credit limit, and there is also an adjustment information indication A in the loan stage, and A is used to indicate the adjustment of the user's temporary credit limit. Then, if the credit system determines that the received adjustment information indication is A, the problem of inaccurate recognition result of the adjustment information may occur. Summary of the invention

[0007] Embodiments of the present application provide a user data processing method, device, electronic device, and storage medium to improve the recognition efficiency and recognition accuracy of adjustment information of user data.

[0008] In a first aspect, an embodiment of the present application provides a method for processing user data, the method comprising:

[0009] receiving data adjustment instructions for target users respectively from multiple data managers; wherein the multiple data adjustment instructions correspond to at least two data adjustment information indication modes, and each data adjustment instruction is used to indicate data adjustment information of the corresponding data manager for user data of the target user, and the user data represents the borrowing and lending situation of the target user;

[0010] Determining data adjustment information corresponding to the multiple data adjustment indications respectively based on indication types corresponding to the multiple data adjustment indications respectively;

[0011] Based on the multiple data adjustment information and the preset data adjustment indication description mode, the multiple data adjustment indications are converted into multiple target data indications.

[0012] In an optional embodiment, determining data adjustment information corresponding to the multiple data adjustment indications respectively based on indication types corresponding to the multiple data adjustment indications respectively includes:

[0013] For multiple data adjustment instructions, perform the following operations respectively:

[0014] Determining an indication type of a data adjustment indication based on a borrowing and lending time identifier associated with a data adjustment indication;

[0015] Based on the data adjustment information indication mode associated with the indication type, data adjustment information corresponding to a data adjustment indication is determined.

[0016] In an optional embodiment, the data adjustment indication description method is used to describe at least one inherent adjustment type and / or at least one newly added adjustment type for user data of the target user.

[0017] In an optional embodiment, after converting the multiple data adjustment indications into multiple target data indications, the method further includes:

[0018] Responding to an adjustment information query request for a first target data indication, and determining an adjustment type to be queried based on the adjustment information query request; wherein the first target data indication is any one of a plurality of target data indications;

[0019] Based on the first target data indication and the query condition set for the adjustment type to be queried, a data adjustment result corresponding to the adjustment type to be queried is determined.

[0020] In an optional embodiment, determining the data adjustment result corresponding to the adjustment type to be queried based on the first target data indication and the query condition set for the adjustment type to be queried includes:

[0021] Determine the position information of the indication value corresponding to the adjustment type to be queried in the first target data indication;

[0022] Based on the location information, the first target data indication and the query condition, obtaining a first sub-target data indication and a sub-query condition;

[0023] Based on the first sub-target data indication and the sub-query condition, a data adjustment result corresponding to the adjustment type to be queried is determined.

[0024] In an optional embodiment, the query condition is obtained in the following manner:

[0025] A first query value is set for the adjustment type to be queried, and a second query value is set for the unqueried adjustment type in the first target data indication; wherein the first query value is used to retain the indication value corresponding to the adjustment type to be queried, and the second query value is used to clear the indication value corresponding to the unqueried adjustment type;

[0026] A query condition is obtained based on the first query value and the second query value.

[0027] In a second aspect, an embodiment of the present application further provides a user data processing device, the device comprising:

[0028] A data receiving module, used to receive data adjustment instructions from multiple data managers for target users respectively; wherein the multiple data adjustment instructions correspond to at least two data adjustment information indication modes, and each data adjustment instruction is used to indicate data adjustment information of the corresponding data manager for user data of the target user, and the user data represents the borrowing and lending situation of the target user;

[0029] An information determination module, configured to determine data adjustment information corresponding to the plurality of data adjustment indications respectively based on indication types corresponding to the plurality of data adjustment indications respectively;

[0030] The data conversion module is used to convert the multiple data adjustment indications into multiple target data indications based on the multiple data adjustment information and the preset data adjustment indication description method.

[0031] In an optional embodiment, when determining the data adjustment information respectively corresponding to the multiple data adjustment indications based on the indication types respectively corresponding to the multiple data adjustment indications, the information determination module is specifically used to:

[0032] For multiple data adjustment instructions, perform the following operations respectively:

[0033] Determining an indication type of a data adjustment indication based on a borrowing and lending time identifier associated with a data adjustment indication;

[0034] Based on the data adjustment information indication mode associated with the indication type, data adjustment information corresponding to a data adjustment indication is determined.

[0035] In an optional embodiment, after converting the multiple data adjustment indications into multiple target data indications, the apparatus further includes an information query module, the information query module being configured to:

[0036] Responding to an adjustment information query request for a first target data indication, and determining an adjustment type to be queried based on the adjustment information query request; wherein the first target data indication is any one of a plurality of target data indications;

[0037] Based on the first target data indication and the query condition set for the adjustment type to be queried, a data adjustment result corresponding to the adjustment type to be queried is determined.

[0038] In an optional embodiment, when determining the data adjustment result corresponding to the adjustment type to be queried based on the first target data indication and the query condition set for the adjustment type to be queried, the information query module is specifically used to:

[0039] Determine the position information of the indication value corresponding to the adjustment type to be queried in the first target data indication;

[0040] Based on the location information, the first target data indication and the query condition, obtaining a first sub-target data indication and a sub-query condition;

[0041] Based on the first sub-target data indication and the sub-query condition, a data adjustment result corresponding to the adjustment type to be queried is determined.

[0042] In an optional embodiment, the query condition is obtained by the information query module in the following manner:

[0043] A first query value is set for the adjustment type to be queried, and a second query value is set for the unqueried adjustment type in the first target data indication; wherein the first query value is used to retain the indication value corresponding to the adjustment type to be queried, and the second query value is used to clear the indication value corresponding to the unqueried adjustment type;

[0044] A query condition is obtained based on the first query value and the second query value.

[0045] In a third aspect, an embodiment of the present application further provides an electronic device, including:

[0046] Processor; and

[0047] Memory for storing programs,

[0048] The program includes instructions, and when the instructions are executed by the processor, the processor executes the user data processing method as described in the first aspect.

[0049] In a fourth aspect, an embodiment of the present application further provides a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to enable a computer to execute the user data processing method as described in the first aspect.

[0050] In a fifth aspect, the present application provides a computer program product, which, when called by a computer, enables the computer to execute the steps of the user data processing method as described in the first aspect.

[0051] The beneficial effects of this application are as follows:

[0052] In the user data processing method provided in the embodiment of the present application, after receiving data adjustment indications from multiple data managers respectively for target users, the data adjustment information corresponding to the multiple data adjustment indications respectively can be determined based on the indication types respectively corresponding to the multiple data adjustment indications, thereby converting the aforementioned multiple data adjustment indications into target data indications represented by the same data adjustment information indication method according to a preset data adjustment indication description method.

[0053] In this way, by converting data adjustment indications indicated by different data adjustment information indication modes into target data indications indicated by the same data adjustment information indication mode, the subsequent recognition efficiency and accuracy of adjustment information of user data (i.e., the borrowing and lending situation of the target user) are improved.

[0054] In addition, other features and advantages of the present application will be described in the subsequent description, and partly become apparent from the description, or be understood by practicing the present application. The purpose and other advantages of the present application can be realized and obtained by the structures particularly pointed out in the written description, claims, and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described here are used to provide a further understanding of the present application, constitute a part of the present application, and do not constitute an improper limitation on the present application. In the drawings:

[0056] Figure 1 A schematic diagram of an optional system architecture applicable to the embodiments of the present application;

[0057] Figure 2 A schematic diagram of an implementation flow of a user data processing method provided in an embodiment of the present application;

[0058] Figure 3 A logical schematic diagram for determining data adjustment information provided in an embodiment of the present application;

[0059] Figure 4 A logical schematic diagram of determining a data adjustment result of a to-be-queried adjustment type provided in an embodiment of the present application;

[0060] Figure 5 A schematic diagram of an implementation flow of a method for obtaining query conditions provided in an embodiment of the present application;

[0061] Figure 6 A logical schematic diagram of another method for determining a data adjustment result of a to-be-queried adjustment type provided in an embodiment of the present application;

[0062] Figure 7 A method based on the embodiment of the present application is provided Figure 2 Schematic diagram of application scenarios;

[0063] Figure 8 A schematic diagram of the structure of a user data processing device provided in an embodiment of the present application;

[0064] Fig. 9 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0065] The embodiments of the present application will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present application are shown in the accompanying drawings, it should be understood that the present application can be implemented in various forms and should not be construed as being limited to the embodiments described herein. Instead, these embodiments are provided to provide a more thorough and complete understanding of the present application. It should be understood that the drawings and embodiments of the present application are only for exemplary purposes and are not intended to limit the scope of protection of the present application.

[0066] It should be understood that the various steps described in the method implementation of the present application can be performed in different orders and / or performed in parallel. In addition, the method implementation may include additional steps and / or omit the steps shown. The scope of the present application is not limited in this respect.

[0067] The term "including" and its variations used in this document are open inclusions, that is, "including but not limited to". The term "based on" means "based at least in part on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one other embodiment"; the term "some embodiments" means "at least some embodiments". Relevant definitions of other terms will be given in the description below. It should be noted that the concepts of "first", "second", etc. mentioned in this application are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0068] It should be noted that the modifications of "one" and "plurality" mentioned in the present application are illustrative rather than restrictive, and those skilled in the art should understand that unless otherwise clearly indicated in the context, it should be understood as "one or more".

[0069] The names of the messages or information exchanged between multiple devices in the embodiments of the present application are only used for illustrative purposes and are not used to limit the scope of these messages or information.

[0070] First, the design concept of the embodiment of the present application is briefly introduced below:

[0071] In the current credit system, for the three stages of the user's loan process (i.e., before loan, during loan, and after loan), loan decisions can usually be divided into three categories: user pre-loan decision (i.e., pre-loan decision), user mid-loan decision (i.e., mid-loan decision), and user post-loan decision (i.e., post-loan decision). In these three stages, the loan decision-maker (i.e., manager) can flexibly adjust the user's loan situation (e.g., loan amount and loan method) based on information such as the user's credit and / or repayment ability, and indicate the corresponding adjustment information according to the adjustment information indication methods set for the above three stages.

[0072] Since the adjustment information indication methods corresponding to the above three stages are usually not unified or the same, after receiving the adjustment information indication from the loan decision-maker, the credit system needs to combine the adjustment indication information methods set at different stages to accurately identify the corresponding adjustment information, that is, it is impossible to identify the adjustment information intuitively and quickly.

[0073] In addition, if there is inconsistency in the adjustment information indication logic among the adjustment information indication methods of multiple loan decision-makers, for example, the same adjustment information indication in different adjustment information indication methods refers to different adjustment information. This will cause certain difficulties for the credit system in processing the adjustment information indications of different loan decision-makers, and the problem of inaccurate (or unreliable) identification results of the adjustment information may occur.

[0074] In view of this, in order to solve the above problems, the embodiment of the present application proposes a user data processing method, which specifically includes: receiving data adjustment instructions for target users respectively from multiple data managers (i.e., loan decision-makers); wherein the multiple data adjustment instructions correspond to at least two data adjustment information indication modes, and each data adjustment instruction is used to indicate the data adjustment information of the corresponding data manager for the user data of the target user, and the user data represents the loan situation of the target user; then, based on the indication types respectively corresponding to the multiple data adjustment instructions, the data adjustment information respectively corresponding to the multiple data adjustment instructions is determined; finally, based on the multiple data adjustment information and the preset data adjustment instruction description mode, the multiple data adjustment instructions are converted into multiple target data instructions. In this way, through the preset data adjustment instruction description mode, the data adjustment instructions indicated according to different data adjustment information indication modes are converted into target data instructions indicated by the same data adjustment information indication mode, thereby improving the subsequent recognition efficiency and recognition accuracy of the adjustment information of the user data.

[0075] In particular, the preferred embodiments of the present application are described below in conjunction with the drawings in the specification. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present application, and are not used to limit the present application, and the embodiments of the present application and the features in the embodiments may be combined with each other if there is no conflict.

[0076] See also Figure 1 As shown, it is a schematic diagram of a system architecture applicable to an embodiment of the present application, and the system architecture may include: terminal devices (101a, 101b, 101c) and a server 102. The terminal devices (101a, 101b, 101c) and the server 102 may exchange information through a communication network, wherein the communication mode adopted by the communication network may include: a wireless communication mode and a wired communication mode.

[0077] Exemplarily, the terminal devices (101a, 101b, 101c) can access the network through cellular mobile communication technology and communicate with the server 102. The cellular mobile communication technology, for example, includes the fifth generation mobile communication (5th generation mobile networks, 5G) technology or the next generation mobile communication technology. Optionally, the terminal devices (101a, 101b, 101c) can access the network through short-range wireless communication mode and communicate with the server 102. The short-range wireless communication mode, for example, includes wireless fidelity (wireless fidelity, Wi-Fi) technology.

[0078] The embodiment of the present application does not impose any restriction on the number of communication devices involved in the above system architecture. For example, the above system architecture may include more terminal devices, or fewer terminal devices, or other network devices. Figure 1 As shown, only the terminal devices (101a, 101b, 101c) and the server 102 are described as examples, and the above communication devices and their respective functions are briefly introduced below.

[0079] The terminal device (101a, 101b, 101c) is a device that can provide voice and / or data connectivity to users, and can be a device that supports wired and / or wireless connection.

[0080] Exemplarily, the terminal devices (101a, 101b, 101c) may include, but are not limited to: mobile phones, tablet computers, laptop computers, PDAs, mobile internet devices (MID), wearable devices, virtual reality (VR) devices, augmented reality (AR) devices, wireless terminal devices in industrial control, wireless terminal devices in unmanned driving, wireless terminal devices in smart grids, wireless terminal devices in transportation safety, wireless terminal devices in smart cities, or wireless terminal devices in smart homes, etc.

[0081] In addition, a related client may be installed on the terminal device (101a, 101b, 101c), and the client may be software, for example, an application (APP), a browser, a short video software, etc., or a web page, a mini-program, etc.; it should be noted that in the embodiment of the present application, the terminal device (101a, 101b, 101c) may enable the above-mentioned client related to user data processing to send the corresponding data manager's data adjustment instructions for the target user to the server 102, so as to perform subsequent user data processing and other method steps.

[0082] Optionally, the terminal device (101a, 101b, 101c) may enable the above-mentioned client related to user data processing to send an adjustment information query request for the first target data indication to the server 102 to obtain a corresponding data adjustment result.

[0083] Server 102 can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers. It can also be a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (CDNs), and big data and artificial intelligence platforms.

[0084] It should be noted that in the embodiment of the present application, an improved credit system (or user data processing system) is deployed on the server 102, which can timely and accurately identify the data adjustment information of the data manager on the user data of the target user, thereby improving the overall efficiency and accuracy of the credit system and enhancing the user experience.

[0085] It is worth mentioning that in an embodiment of the present application, the server 102 can be used to receive data adjustment instructions from multiple data managers for target users; wherein the multiple data adjustment instructions correspond to at least two data adjustment information indication methods, and each data adjustment indication is used to indicate the data adjustment information of the corresponding data manager for the user data of the target user, and the user data represents the borrowing and lending situation of the target user; then, based on the indication types corresponding to the multiple data adjustment indications, the data adjustment information corresponding to the multiple data adjustment indications is determined; finally, based on the multiple data adjustment information and the preset data adjustment indication description method, the multiple data adjustment indications are converted into multiple target data indications.

[0086] The user data processing method provided by the exemplary embodiment of the present application is described below in combination with the above-mentioned system architecture and with reference to the accompanying drawings. It should be noted that the above-mentioned system architecture is only shown to facilitate understanding of the spirit and principles of the present application, and the implementation of the present application is not limited in this respect.

[0087] See also Figure 2 As shown, it is a schematic diagram of an implementation process of a user data processing method provided in an embodiment of the present application. The execution subject takes a server as an example. The specific implementation process of the method is as follows:

[0088] S201: Receive data adjustment instructions from multiple data managers for target users.

[0089] Among them, multiple data adjustment indications correspond to at least two data adjustment information indication methods, and each data adjustment indication is used to indicate the data adjustment information of the corresponding data manager for the user data of the target user, and the user data represents the loan situation of the target user. Optionally, the aforementioned user data may include the loan amount and / or loan method of the target user, and the aforementioned data adjustment information may include the adjustment information of the loan amount and / or loan method of the target user by the data manager. It should be noted that the embodiments of the present application do not specifically limit the aforementioned user data and data adjustment information.

[0090] For ease of description and understanding, in the following text, the aforementioned fixed loan amount is referred to as a fixed amount, the aforementioned temporary loan amount is referred to as a temporary amount, the aforementioned loan method for the fixed loan amount is referred to as a fixed price, and the aforementioned loan method for the temporary amount is referred to as a temporary price. Of course, the aforementioned four items may also have other names, which are not limited in the embodiments of the present application.

[0091] For example, the loan amount may include a fixed loan amount and a temporary loan amount, and the loan method may include a loan method for a fixed loan amount and a loan method for a temporary loan amount. In addition, the loan method may specifically include one or more of a repayment method (e.g., equal principal and interest method and equal principal), a repayment period (e.g., 120 periods, 240 periods, or 360 periods, one period being one month), and a loan interest rate (e.g., 2.85%).

[0092] Take three data managers (for example, data manager 1, data manager 2, and data manager 3), the user data includes fixed amount, temporary amount, fixed price, and temporary price, and the three data managers correspond to different data adjustment information indication modes (in order: indication mode 1, indication mode 2, and indication mode 3) as an example, wherein the data adjustment information indications corresponding to the three indication modes are shown in Table 1:

[0093] Table 1 Example of the correspondence between data adjustment information indication and data adjustment information

[0094]

[0095] Based on the corresponding relationship between the data adjustment information indication and the data adjustment information recorded in the above table, it can be known that the data manager can indicate the data adjustment information of the user data of the target user according to the corresponding data information adjustment indication method.

[0096] Taking the example of data manager 1 using indication method 2 to indicate the data adjustment information of the target user's user data, assuming that the data adjustment information of the user data by data manager 1 is: "adjusted fixed amount, unadjusted temporary amount, adjusted fixed price and unadjusted temporary price", then data manager 1 can use indication method 2 to indicate the above data adjustment information as A1 b2 C1 d2.

[0097] Therefore, when executing step S201, the server can receive the data adjustment instructions of the three data managers for the target user. For example, data adjustment instruction 1 of data manager 1 is A1 B1 C2 D2, data adjustment instruction 2 of data manager 2 is A1 b2 C1 d2, and data adjustment instruction 3 of data manager 3 is a2 b1 c2 d2.

[0098] S202: Determine data adjustment information corresponding to the multiple data adjustment indications respectively based on indication types corresponding to the multiple data adjustment indications respectively.

[0099] Among them, each indication type can be used to determine the corresponding data adjustment information indication mode. That is, there is a corresponding relationship between the indication type and the data adjustment information indication mode. In other words, the server can determine the data adjustment information indication modes corresponding to the above-mentioned multiple data adjustment indications respectively according to the indication types corresponding to the above-mentioned multiple data adjustment indications respectively, and the corresponding relationship between the preset indication types and the data adjustment indication modes.

[0100] For example, the above three data adjustment information indication modes (ie indication mode 1, indication mode 2 and indication mode 3) are still taken as an example. The indication types corresponding to the above three data adjustment information indication modes are shown in Table 2:

[0101] Table 2 Example of correspondence between data adjustment information indication mode and indication type

[0102]

[0103] It can be seen from the above table that the indication types corresponding to the above indication mode 1, indication mode 2 and indication mode 3 are respectively: Type 1, Type 2 and Type 3. In particular, the specific representation method of the indication type is not limited in the embodiment of the present application.

[0104] Furthermore, the server may determine the data adjustment information corresponding to the plurality of data adjustment instructions respectively according to the data adjustment information indication modes corresponding to the plurality of data adjustment instructions respectively.

[0105] Exemplarily, the data adjustment instructions (i.e., data adjustment instruction 1, data adjustment instruction 2, and data adjustment instruction 3) corresponding to the above three data managers are still taken as an example, that is, data adjustment instruction 1 of data manager 1 is A1 B1 C2 D2, data adjustment instruction 2 of data manager 2 is A1 b2 C1 d2, and data adjustment instruction 3 of data manager 3 is a2 b1 c2 d2. After the server determines that the data adjustment information indication modes corresponding to the above three data managers are: indication mode 1, indication mode 2, and indication mode 3, it can be determined that the data adjustment information corresponding to the above three data adjustment instructions are: "adjustment of fixed amount, adjustment of temporary amount, unadjustment of fixed price, and unadjustment of temporary price", "adjustment of fixed amount, unadjustment of temporary amount, adjustment of fixed price, and unadjustment of temporary price", and "unadjustment of fixed amount, adjustment of temporary amount, unadjustment of fixed price, and unadjustment of temporary price".

[0106] In an optional implementation, in order to quickly and accurately determine the data adjustment information corresponding to the multiple data adjustment instructions based on the indication types corresponding to the multiple data adjustment instructions, when executing step S202, refer to Figure 3 As shown, the server can perform the following operations respectively for the aforementioned multiple data adjustment indications: determine the indication type of a data adjustment indication based on a loan time identifier associated with a data adjustment indication, and thereby determine the data adjustment information corresponding to the aforementioned data adjustment indication based on the data adjustment information indication method associated with the indication type.

[0107] Based on the above method, since the above loan time identifier can usually represent a certain stage of the target user in the loan process, and different data adjustment indication information modes are usually set for different stages. Therefore, the server can quickly determine the indication type of the data adjustment indication according to the loan time identifier associated with the data adjustment indication, and thus can quickly determine the data adjustment information corresponding to the aforementioned data adjustment indication according to the data adjustment information indication mode associated with the indication type.

[0108] Taking data adjustment indication 4 as a2 B1 c2 D1 as an example, assuming that the loan time identifier associated with data adjustment indication 4 represents that the target user is in the pre-loan stage of the loan process, and the indication types associated with the pre-loan stage, the mid-loan stage and the post-loan node are Type2, Type3 and Type1 in Table 2 above, respectively. Then, after the server determines that the loan time identifier associated with data adjustment indication 4 is the pre-loan stage, it can determine that the indication type of data adjustment indication 4 is Type2, and thus according to the correspondence between the data adjustment information indication mode and the indication type recorded in Table 2 above, it can be determined that the data adjustment information indication mode corresponding to data adjustment indication 4 is indication mode 2. Further, in combination with the correspondence between the data adjustment information indication and the data adjustment information shown in Table 1, the server can determine that the data adjustment information corresponding to data adjustment indication 4 is: "unadjusted fixed amount, adjusted temporary amount, unadjusted fixed price and adjusted temporary price".

[0109] S203: Based on the multiple data adjustment information and the preset data adjustment indication description method, convert the multiple data adjustment indications into multiple target data indications.

[0110] Among them, the above-mentioned data adjustment indication description method can be used to describe at least one inherent adjustment type and / or at least one newly added adjustment type for the user data of the target user. For example, the aforementioned inherent adjustment types may include but are not limited to whether to adjust the fixed amount, whether to adjust the temporary amount, whether to adjust the fixed price, and whether to adjust the temporary price. The aforementioned newly added adjustment types may include positive and negative adjustments. For example, positive and negative adjustments may specifically include positive adjustments, negative adjustments, horizontal adjustments, and no distinction between positive and negative directions. It should be noted that the embodiments of the present application do not limit the specific contents of the aforementioned inherent adjustment types and the aforementioned newly added adjustment types. Exemplarily, the aforementioned inherent adjustment types may also include: revoking the temporary amount and revoking the temporary price.

[0111] In an optional implementation, the data adjustment indication description method can be a binary-based structured data to clearly and accurately represent the data adjustment information of the user data for the target user. Take the above-mentioned structured data (i.e., field) consisting of 10 binary bits as an example, where each adjacent two bits of binary data corresponds to a data adjustment type. For example, the 10-bit binary "XXXXXXXXXX" can represent from high to low: positive and negative adjustment, whether to adjust the fixed amount, whether to adjust the temporary amount, whether to adjust the fixed price, and whether to adjust the temporary price. In the embodiment of the present application, each adjacent two bits of binary data can be standardized by defining an enumeration. Exemplarily, the enumeration value (i.e., binary value) and its corresponding data adjustment information can be shown in Table 3:

[0112] Table 3 Correspondence between different enumeration values ​​and different data adjustment information

[0113]

[0114] For example, assuming that a data adjustment indication is 0101000110, the data adjustment indication can be split into every two digits, and then the data adjustment information (i.e., meaning) corresponding to the data adjustment indication can be determined according to the correspondence between different enumeration values ​​and different data adjustment information recorded in the above Table 3: The data adjustment of the user data this time is a positive adjustment for the user, the fixed amount is adjusted and the temporary amount is not adjusted, the fixed price is adjusted and the temporary price is revoked.

[0115] By adopting the above method, every two bits can be encoded according to predefined rules, and the above data adjustment information (such as adjustment amount operation and price adjustment operation) can be converted into binary code. Moreover, through this encoding method, the adjustment content and positive and negative decisions (i.e. data adjustment information) can be converted into machine-recognizable structured data to achieve standardization and normalization of data adjustment information. In other words, through the design of structured data, the adjustment content and positive and negative decisions can be quickly identified, which greatly improves the processing efficiency of the credit system, while also improving the user experience and the overall reliability of the system.

[0116] In addition, by introducing binary-based structured data, a unified representation of data adjustment information is achieved, solving the problems of incomplete adjustment information verification, mixed information, and inconsistent variables in the existing system, thereby improving the accuracy and efficiency of credit system data processing. From the reserved fields in Table 2, it can be seen that the newly designed binary fields allow flexible expansion and adjustment of adjustment types and enumeration values ​​according to business needs, making the credit system more adaptable and extensible.

[0117] Exemplarily, when executing step S203, still taking the data adjustment information corresponding to the above-mentioned data adjustment indication 1, data adjustment indication 2 and data adjustment indication 3 respectively, and the preset data adjustment indication description method as the above-mentioned 10-bit binary structured data as an example, assuming that the above-mentioned data adjustment indication 1 corresponds to positive adjustment, the above-mentioned data adjustment indication 2 corresponds to horizontal adjustment, and the above-mentioned data adjustment indication 3 corresponds to negative adjustment, then the server can convert the above-mentioned 3 data adjustment indications into 3 target data indications according to the data adjustment information corresponding to the above-mentioned 3 data adjustment indications respectively and the above-mentioned 10-bit binary structured data. Specifically, the target data indication 1 corresponding to the data adjustment indication 1 is "0101010000", the target data indication 2 corresponding to the data adjustment indication 2 is "1101000100", and the target data indication 3 corresponding to the data adjustment indication 3 is "0100010000". For another example, if the aforementioned three data adjustment indications do not have positive or negative adjustment information, it can be assumed that the aforementioned three data adjustment indications do not distinguish between positive and negative adjustments, and the aforementioned target data indication 1 is "0001010000", the aforementioned target data indication 2 is "0001000100" and the aforementioned target data indication 3 is "0000010000".

[0118] In an alternative implementation, see Figure 4 As shown, after converting the above-mentioned multiple data adjustment indications into multiple target data indications, the server can also perform the following operations for any one of the above-mentioned multiple target data indications, namely, the first target data indication: respond to the adjustment information query request for the first target data indication, and determine the adjustment type to be queried based on the adjustment information query request, thereby determining the data adjustment result corresponding to the adjustment type to be queried based on the first target data indication and the query condition set for the adjustment type to be queried. In this way, according to the query condition set for the adjustment type to be queried, the data adjustment result related to the adjustment type to be queried can be quickly and accurately queried, thereby improving the efficiency and accuracy of the credit system in identifying the data adjustment information of the relevant user (such as the target user).

[0119] The above adjustment type to be queried may be any one or combination of at least one inherent adjustment type and / or at least one newly added adjustment type for the user data of the target user described in the above preset data adjustment indication description method. For example, the above adjustment type to be queried may be any one or combination of positive and negative adjustments, whether to adjust a fixed amount, whether to adjust an interim amount, whether to adjust a fixed price, and whether to adjust an interim price. This is not specifically limited in the embodiments of the present application.

[0120] Optionally, the query condition may be one of the following: Figure 5 The method steps shown are obtained:

[0121] S501: Setting a first query value for an adjustment type to be queried, and setting a second query value for an adjustment type not queried in a first target data indication.

[0122] The first query value can be used to retain the indication value corresponding to the adjustment type to be queried, and the second query value can be used to clear the indication value corresponding to the unqueried adjustment type. In this way, the data adjustment result can be fed back only for the adjustment type to be queried in the adjustment information query request, which can reduce the data processing complexity of the credit system.

[0123] For example, taking the above-mentioned first target data indicated as the above-mentioned 10-bit binary structured data as an example, assuming that the adjustment type to be queried is whether to adjust the fixed amount and whether to adjust the fixed price, the server can determine that the first query value corresponding to the above-mentioned adjustment type to be queried is 1111, and the second query value corresponding to the adjustment type not queried in the above-mentioned first target data is 000000.

[0124] S502: Obtain a query condition based on the first query value and the second query value.

[0125] Exemplarily, when executing step S502, after obtaining the first query value and the second query value, the server can determine that the query condition set for the above-mentioned adjustment type to be queried is: 0011001100 based on the format of the above-mentioned 10-bit binary structured data, and the first query value (i.e., 1111) and the second query value (i.e., 000000).

[0126] Since the above-mentioned target data indications and query conditions can both be binary data, and binary operations have a high execution efficiency in the (credit) system, simple logical operations, such as AND operations, can be used to quickly parse and process data adjustment information, thereby improving the processing efficiency and accuracy of the credit system.

[0127] For example, assuming that the first target data indication is represented as format_type, and the adjustment type to be queried in the adjustment information query request is whether to adjust the fixed amount and whether to adjust the fixed price, that is, the query condition set for the adjustment type to be queried is: 0011001100. Then, the calculation formula for the data adjustment result corresponding to the adjustment type to be queried can be specifically expressed as:

[0128] format_type&0011001100; where & is the AND operation.

[0129] Specifically, if the first target data indication is 0101000101, then the server can determine the corresponding data adjustment result as 00 based on the calculation formula of the data adjustment result. 01 00 0100. That is, it can be determined that for the user data corresponding to the first target data indication, this data adjustment operation adjusts the fixed amount and the fixed price.

[0130] In order to reduce the computational complexity of the credit system in determining the data adjustment result corresponding to the adjustment type to be queried, that is, to improve the efficiency of determining the data adjustment result corresponding to the adjustment type to be queried. Figure 6 As shown, the server can determine the position information of the indication value corresponding to the adjustment type to be queried in the first target data indication, and thus obtain the first sub-target data indication and sub-query condition based on the position information, the first target data indication and the query condition, and then determine the data adjustment result corresponding to the adjustment type to be queried based on the first sub-target data indication and the sub-query condition.

[0131] Exemplarily, the first target data indication is still 0101000101, the adjustment type to be queried is whether to adjust the fixed amount and whether to adjust the fixed price, and the query condition is 0011001100. Then, the server can determine that the position information of the indication value corresponding to whether to adjust the fixed amount in the first target data indication is the 7th-8th bit, and the position information of the indication value corresponding to whether to adjust the fixed price in the first target data indication is the 3rd-4th bit. Further, if the number of bits of the binary data corresponding to the sub-query condition is numerically the same as the highest binary bit corresponding to the adjustment type to be queried, then based on the above position information, the first target data indication and the query condition, the server can obtain the first sub-target data indication of 01000101 (i.e., the lower 8 bits of the first target data indication) and the sub-query condition of 11001100 (i.e., the lower 8 bits of the query condition).

[0132] Then, based on the first sub-target data indication and the sub-query condition, the server can determine that the data adjustment result corresponding to the adjustment type to be queried is 01 00 01 00. It can be seen that, compared with the above 10-bit binary calculation, only 8-bit binary calculation is required to determine the data adjustment result, which reduces the calculation complexity of the credit system.

[0133] To further reduce the computational complexity, the server can also determine the number of bits of binary data corresponding to the sub-query condition only according to the number of bits of binary data corresponding to the adjustment type to be queried. For example, if the number of bits of binary data corresponding to whether to adjust the fixed amount and whether to adjust the fixed price is 4, then the number of bits of binary data corresponding to the sub-query condition is also 4. At this time, based on the above position information, the first target data indication and the query condition, the server can obtain the first sub-target data indication as 0101 (i.e., the 7th-8th and 3rd-4th bits of the first target data indication) and the sub-query condition as 1111 (i.e., the 7th-8th and 3rd-4th bits of the query condition).

[0134] Then, based on the first sub-target data indication and the sub-query condition, the server can determine that the data adjustment result corresponding to the adjustment type to be queried is 0101. It can be seen that, compared with the above 10-bit binary calculation and the above 8-bit binary calculation, only 4-bit binary calculation is required when determining the data adjustment result.

[0135] Based on the steps of the user data processing method described in steps S201 to S203, refer to Figure 7 As shown, it is a schematic diagram of an application scenario provided by an embodiment of the present application. The application scenario includes: a decision system and a credit system, and the credit system may include a data preprocessing module, a pre-loan information processing module, a mid-loan information processing module, a post-loan information processing module, a structured data generation module, and a data adjustment information processing module. Among them, the decision system can send multiple data managers to the credit system for data adjustment instructions for target users, and the data preprocessing module can classify and process the received multiple data adjustment instructions, thereby determining the data adjustment information corresponding to the aforementioned multiple data adjustment instructions according to the pre-loan information processing module, the mid-loan information processing module, and the post-loan information processing module, so that through the structured data generation module, based on the obtained multiple data adjustment information and the preset data adjustment instruction description method, the aforementioned multiple data adjustment instructions are converted into multiple target data instructions, so that the data adjustment information processing module can be used to smoothly perform relevant data processing on the aforementioned multiple target data instructions, for example, feedback the data adjustment results according to the query request.

[0136] In summary, in the user data processing method provided in the embodiment of the present application, after receiving data adjustment instructions for target users respectively from multiple data managers, the data adjustment information corresponding to the multiple data adjustment instructions can be determined based on the indication types corresponding to the multiple data adjustment instructions respectively, so as to convert the aforementioned multiple data adjustment instructions into target data indications represented by the same data adjustment information indication method according to the preset data adjustment indication description method. In this way, it is avoided that the adjustment indication information methods set at different stages need to be combined in the related art to accurately identify the corresponding adjustment information, that is, the adjustment information cannot be identified intuitively and quickly, and the same adjustment information indication refers to different adjustment information in different adjustment information indication methods, resulting in certain difficulties in the credit system when processing the adjustment information indications of different loan decision-makers, which may lead to the problem of inaccurate (or unreliable) identification results of the adjustment information. Therefore, by converting the data adjustment indications indicated by different data adjustment information indication methods into target data indications indicated by the same data adjustment information indication method, the subsequent recognition efficiency and recognition accuracy of the adjustment information of the user data are improved.

[0137] Further, based on the same technical concept, the embodiment of the present application provides a user data processing device, which is used to implement the above method flow of the embodiment of the present application. Figure 8 As shown, the user data processing device 800 includes: a data receiving module 801, an information determining module 802 and a data conversion module 803, wherein:

[0138] The data receiving module 801 is used to receive data adjustment instructions from multiple data managers for target users respectively; wherein the multiple data adjustment instructions correspond to at least two data adjustment information indication modes, and each data adjustment instruction is used to indicate data adjustment information of the corresponding data manager for user data of the target user, and the user data represents the loan situation of the target user;

[0139] An information determination module 802, configured to determine data adjustment information corresponding to the plurality of data adjustment indications respectively based on indication types corresponding to the plurality of data adjustment indications respectively;

[0140] The data conversion module 803 is used to convert the multiple data adjustment indications into multiple target data indications based on the multiple data adjustment information and the preset data adjustment indication description method.

[0141] In an optional embodiment, when determining the data adjustment information respectively corresponding to the multiple data adjustment indications based on the indication types respectively corresponding to the multiple data adjustment indications, the information determination module 802 is specifically configured to:

[0142] For multiple data adjustment instructions, perform the following operations respectively:

[0143] Determining an indication type of a data adjustment indication based on a borrowing and lending time identifier associated with a data adjustment indication;

[0144] Based on the data adjustment information indication mode associated with the indication type, data adjustment information corresponding to a data adjustment indication is determined.

[0145] In an optional embodiment, after converting the multiple data adjustment indications into multiple target data indications, the user data processing device 800 further includes an information query module 804, and the information query module 804 is used to:

[0146] Responding to an adjustment information query request for a first target data indication, and determining an adjustment type to be queried based on the adjustment information query request; wherein the first target data indication is any one of a plurality of target data indications;

[0147] Based on the first target data indication and the query condition set for the adjustment type to be queried, a data adjustment result corresponding to the adjustment type to be queried is determined.

[0148] In an optional embodiment, when determining the data adjustment result corresponding to the adjustment type to be queried based on the first target data indication and the query condition set for the adjustment type to be queried, the information query module 804 is specifically used to:

[0149] Determine the position information of the indication value corresponding to the adjustment type to be queried in the first target data indication;

[0150] Based on the location information, the first target data indication and the query condition, obtaining a first sub-target data indication and a sub-query condition;

[0151] Based on the first sub-target data indication and the sub-query condition, a data adjustment result corresponding to the adjustment type to be queried is determined.

[0152] In an optional embodiment, the query condition is obtained by the information query module 804 in the following manner:

[0153] A first query value is set for the adjustment type to be queried, and a second query value is set for the unqueried adjustment type in the first target data indication; wherein the first query value is used to retain the indication value corresponding to the adjustment type to be queried, and the second query value is used to clear the indication value corresponding to the unqueried adjustment type;

[0154] A query condition is obtained based on the first query value and the second query value.

[0155] Based on the description of the above method embodiment and device embodiment, the exemplary embodiment of the present invention further provides an electronic device, including: at least one processor; and a memory connected to the at least one processor in communication. The memory stores a computer program that can be executed by the at least one processor, and the computer program is used to enable the electronic device to perform the method according to the embodiment of the present invention when executed by the at least one processor.

[0156] An embodiment of the present application also provides a non-transitory computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor of a computer, is used to cause the computer to execute a method according to an embodiment of the present application.

[0157] An embodiment of the present application also provides a computer program product, including a computer program, wherein the computer program, when executed by a processor of a computer, is used to cause the computer to execute a method according to an embodiment of the present application.

[0158] See also Fig. 9As shown, the structured block diagram of the electronic device 900 that can be used as the server or client of the present application will now be described, which is an example of the hardware device that can be applied to various aspects of the present application. The electronic device is intended to represent the computer device of various forms of digital electronics, such as, laptop computers, desktop computers, workbenches, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as, personal digital processing, cellular phones, smart phones, wearable devices and other similar computing devices. The components shown herein, their connections and relationships, and their functions are only used as examples, and are not intended to limit the implementation of the present application described herein and / or required.

[0159] like Fig. 9 As shown, the electronic device 900 includes a computing unit 901, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 902 or a computer program loaded from a storage unit 908 to a random access memory (RAM) 903. In the RAM 903, various programs and data required for the operation of the device 900 can also be stored. The computing unit 901, the ROM 902, and the RAM 903 are connected to each other via a bus 904. An input / output (I / O) interface 905 is also connected to the bus 904.

[0160] A plurality of components in the electronic device 900 are connected to the I / O interface 905, including: an input unit 906, an output unit 907, a storage unit 908, and a communication unit 909. The input unit 906 may be any type of device capable of inputting information to the electronic device 900, and the input unit 906 may receive input digital or character information, and generate key signal inputs related to user settings and / or function control of the electronic device. The output unit 907 may be any type of device capable of presenting information, and may include but is not limited to a display, a speaker, a video / audio output terminal, a vibrator, and / or a printer. The storage unit 908 may include but is not limited to a disk, an optical disk. The communication unit 909 allows the electronic device 900 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks, and may include but is not limited to a modem, a network card, an infrared communication device, a wireless communication transceiver, and / or a chipset, such as a Bluetooth device, a WiFi device, a worldwide interoperability for microwave access (WiMax) device, a cellular communication device, and / or the like.

[0161] The computing unit 901 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 901 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors (DSP), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 901 performs the various methods and processes described above. For example, in some embodiments, the above-mentioned user data processing method may be implemented as a computer software program, which is tangibly included in a machine-readable medium, such as a storage unit 908. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 900 via the ROM 902 and / or the communication unit 909. In some embodiments, the computing unit 901 may be configured to perform the above-mentioned user data processing method by any other appropriate means (e.g., by means of firmware).

[0162] The program code for implementing the method of the present application can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that the program code, when executed by the processor or controller, implements the functions / operations specified in the flow chart and / or block diagram. The program code can be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0163] In the context of the present application, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a RAM, a ROM, an erasable programmable read-only memory (EPROM) or a flash memory, an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0164] As used herein, the terms "machine-readable medium" and "computer-readable medium" refer to any computer program product, apparatus, and / or device (e.g., disk, optical disk, memory, programmable logic device (PLD)) for providing machine instructions and / or data to a programmable processor, including a machine-readable medium that receives machine instructions as a machine-readable signal. The term "machine-readable signal" refers to any signal for providing machine instructions and / or data to a programmable processor.

[0165] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a cathode ray tub (CRT) or a liquid crystal display (LCD) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0166] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), and the Internet.

[0167] A computer system may include clients and servers. Clients and servers are generally remote from each other and usually interact through a communication network. The relationship of client and server is generated by computer programs running on respective computers and having a client-server relationship to each other.

[0168] Furthermore, it should be understood that what is disclosed above is only a preferred embodiment of the present application, and certainly cannot be used to limit the scope of rights of the present invention. Therefore, equivalent changes made according to the claims of the present invention are still within the scope covered by the present application.

Claims

1. A method for processing user data, It is characterized in that include: receiving data adjustment instructions for target users respectively from multiple data managers; wherein the multiple data adjustment instructions correspond to at least two data adjustment information indication modes, and each data adjustment instruction is used to indicate data adjustment information of the corresponding data manager for user data of the target user, wherein the user data represents the borrowing and lending situation of the target user; Determining data adjustment information corresponding to each of the multiple data adjustment indications based on indication types corresponding to each of the multiple data adjustment indications; Based on the multiple data adjustment information and the preset data adjustment indication description method, the multiple data adjustment indications are converted into multiple target data indications.

2. The method according to claim 1, It is characterized in that The determining, based on the indication types respectively corresponding to the multiple data adjustment indications, the data adjustment information respectively corresponding to the multiple data adjustment indications comprises: For the multiple data adjustment instructions, the following operations are performed respectively: Determining an indication type of a data adjustment indication based on a borrowing and lending time identifier associated with the data adjustment indication; Based on the data adjustment information indication mode associated with the indication type, the data adjustment information corresponding to the one data adjustment indication is determined.

3. The method according to claim 1, It is characterized in that The data adjustment indication description method is used to describe at least one inherent adjustment type and / or at least one newly added adjustment type for the user data of the target user.

4. The method according to claim 1, 2 or 3, It is characterized in that After converting the multiple data adjustment indications into multiple target data indications, the method further includes: Responding to an adjustment information query request for a first target data indication, and determining an adjustment type to be queried based on the adjustment information query request; wherein the first target data indication is any one of the multiple target data indications; Based on the first target data indication and a query condition set for the adjustment type to be queried, a data adjustment result corresponding to the adjustment type to be queried is determined.

5. The method according to claim 4, It is characterized in that The determining, based on the first target data indication and the query condition set for the adjustment type to be queried, the data adjustment result corresponding to the adjustment type to be queried includes: Determine the position information of the indication value corresponding to the adjustment type to be queried in the first target data indication; Based on the location information, the first target data indication and the query condition, obtaining a first sub-target data indication and a sub-query condition; Based on the first sub-target data indication and the sub-query condition, the data adjustment result corresponding to the adjustment type to be queried is determined.

6. The method according to claim 4, It is characterized in that The query condition is obtained in the following manner: A first query value is set for the adjustment type to be queried, and a second query value is set for the unqueried adjustment type in the first target data indication; wherein the first query value is used to retain the indication value corresponding to the adjustment type to be queried, and the second query value is used to clear the indication value corresponding to the unqueried adjustment type; The query condition is obtained based on the first query value and the second query value.

7. A user data processing device, It is characterized in that include: A data receiving module, used to receive data adjustment instructions from multiple data managers for target users respectively; wherein the multiple data adjustment instructions correspond to at least two data adjustment information indication modes, and each data adjustment instruction is used to indicate data adjustment information of the corresponding data manager for user data of the target user, and the user data represents the borrowing and lending situation of the target user; An information determination module, configured to determine data adjustment information corresponding to the multiple data adjustment indications respectively based on indication types corresponding to the multiple data adjustment indications respectively; The data conversion module is used to convert the multiple data adjustment indications into multiple target data indications based on the multiple data adjustment information and the preset data adjustment indication description method.

8. The device according to claim 7, It is characterized in that After converting the multiple data adjustment indications into multiple target data indications, the device further includes an information query module, wherein the information query module is used to: Responding to an adjustment information query request for a first target data indication, and determining an adjustment type to be queried based on the adjustment information query request; wherein the first target data indication is any one of the multiple target data indications; Based on the first target data indication and a query condition set for the adjustment type to be queried, a data adjustment result corresponding to the adjustment type to be queried is determined.

9. An electronic device, include: processor; as well as Memory for storing programs, The program includes instructions, which, when executed by the processor, cause the processor to perform the method according to any one of claims 1 to 6.

10. A non-transitory computer-readable storage medium storing computer instructions, in, The computer instructions are used to cause the computer to execute the method according to any one of claims 1 to 6.

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