Resource quota processing method and device

Abstract

The embodiment of the invention provides a resource quota processing method and device, and the method comprises the steps: obtaining the user data of a risk user pushed by a third-party platform, querying a resource quota rule related to the risk user according to the user data, generating a rule editing page of the risk user based on the resource quota rule, issuing the rule editing page to the institution member, obtaining a target quota rule obtained after the institution member edits the resource quota rule based on the rule editing page, and calling a rule engine to update the quota rule of the risk user and determine the resource quota according to the target quota rule. And obtaining the resource quota of the risk user.

Description

Technical Field

[0001] This document relates to the field of data processing technology, and in particular to a resource quota processing method and device. Background Art

[0002] With the continuous development of Internet technology and the continuous improvement of users' living standards, more and more users have begun to transfer resources through the resource quotas provided by institutions. Institutions can provide resource quotas to users so that users can use the resources corresponding to the quotas. However, as more and more users use resource quotas to transfer resources, some risk issues have also arisen. How to better provide resource quotas to users while reducing institutional risks has become a key issue of concern to all parties. Summary of the invention

[0003] One or more embodiments of this specification provide a resource quota processing method, including: obtaining user data of a risk user pushed by a third-party platform, and querying the resource quota rules associated with the risk user based on the user data. Generate a rule editing page for the risk user based on the resource quota rules and send it to the institutional members, and obtain the target quota rules obtained after the institutional members edit the resource quota rules based on the rule editing page. Call the rule engine to update the quota rules and determine the resource quota of the risk user according to the target quota rules, and obtain the resource quota of the risk user.

[0004] One or more embodiments of the present specification provide a resource quota processing device, including: a resource quota rule query module, configured to obtain user data of risk users pushed by a third-party platform, and query the resource quota rules associated with the risk users based on the user data. A target quota rule acquisition module, configured to generate a rule editing page for the risk user based on the resource quota rules and send it to institutional members, and obtain the target quota rules obtained after the institutional members edit the resource quota rules based on the rule editing page. A resource quota determination module, configured to call a rule engine to update the quota rules and determine the resource quota of the risk user according to the target quota rules, and obtain the resource quota of the risk user.

[0005] One or more embodiments of the present specification provide a resource quota processing device, including: a processor; and a memory configured to store computer-executable instructions, wherein the processor executes the computer-executable instructions to implement the following process: obtaining user data of risk users pushed by a third-party platform, and querying the resource quota rules associated with the risk users based on the user data. Generate a rule editing page for the risk user based on the resource quota rules and send it to the institutional members, and obtain the target quota rules obtained after the institutional members edit the resource quota rules based on the rule editing page. Call the rule engine to update the quota rules and determine the resource quota of the risk user according to the target quota rules, and obtain the resource quota of the risk user.

[0006] One or more embodiments of the present specification provide a computer-readable storage medium for storing computer-executable instructions, which implement the following process when executed: obtaining user data of risk users pushed by a third-party platform, and querying the resource quota rules associated with the risk users based on the user data. Generate a rule editing page for the risk user based on the resource quota rules and send it to the institutional members, and obtain the target quota rules obtained after the institutional members edit the resource quota rules based on the rule editing page. Call the rule engine to update the quota rules and determine the resource quota of the risk user according to the target quota rules, and obtain the resource quota of the risk user. BRIEF DESCRIPTION OF THE DRAWINGS

[0007] In order to more clearly illustrate one or more embodiments of the present specification or the technical solutions in the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present specification. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative labor. Figure 1 A schematic diagram of an implementation environment of a resource quota processing method provided in one or more embodiments of this specification; Figure 2 A processing flow chart of a resource quota processing method provided for one or more embodiments of this specification; Figure 3 A processing flow chart of a resource quota processing method applied to a quota rule update scenario provided by one or more embodiments of this specification; Figure 4 A schematic diagram of an embodiment of a resource quota processing device provided in one or more embodiments of this specification; Figure 5A schematic diagram of the structure of a resource quota processing device provided in one or more embodiments of this specification. DETAILED DESCRIPTION

[0008] In order to enable those skilled in the art to better understand the technical solutions in one or more embodiments of this specification, the technical solutions in one or more embodiments of this specification will be clearly and completely described below in conjunction with the drawings in one or more embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this specification, not all of them. Based on one or more embodiments of this specification, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this document.

[0009] The resource quota processing method provided in one or more embodiments of this embodiment can be applied to the implementation scenario of resource quota processing. Figure 1 The implementation environment at least includes: a server 101, which can be one or more servers, a server cluster composed of several servers, or a cloud server of a cloud computing platform. The server 101 is used to receive user data of risky users sent by a third-party platform 102, receive target quota rules submitted by a member terminal 103, and call a rule engine 101-1 to update quota rules and determine resource quotas.

[0010] The implementation environment also includes at least a rule engine 101-1. The rule engine 101-1 can be deployed inside the server 101 or independently deployed, and the rule engine 101-1 is used to update the quota rules and determine the resource quota.

[0011] The implementation environment also includes at least a third-party platform 102, which can be one or more servers, a server cluster consisting of several servers, or a cloud server of a cloud computing platform. The third-party platform 102 can be used to screen risky users and send user data of risky users to the server 101.

[0012] The implementation environment may also include a member terminal 103 of an institutional member, which may specifically be a mobile phone, a personal computer, a tablet computer, an e-book reader, a device for information interaction based on AR (Augmented Reality) / VR (Virtual Reality), a vehicle terminal, an IoT device, a wearable smart device, a laptop computer, a desktop computer, etc. The member terminal 103 may receive and display the rule editing page sent by the server 101, and may also interact with the institutional member to edit, save, and submit the target limit rule to the server 101.

[0013] In this implementation environment, the third-party platform 102 screens risky users and pushes user data of risky users to the server 101. The server 101 queries the resource quota rules associated with the risky users based on the user data and generates a rule editing page for the risky users based on the resource quota rules, and sends it to the member terminal 103 of the institution member. The member terminal 103 interacts with the institution member to edit the resource quota rules, obtains the target quota rules, and submits them to the server 101. The server 101 calls the rule engine 101-1 to update the quota rules and determine the resource quota of the risky user according to the target quota rules, and obtains the resource quota of the risky user. By providing the rule editing page to the institution members, the institution members can directly and conveniently edit the resource quota rules, thereby improving the processing efficiency of the resource quota.

[0014] It should be pointed out that, considering that user data belongs to the user's privacy to a certain extent, if you want to obtain user data, you can obtain user authorization before obtaining the user data, so that the relevant processing of user data complies with relevant laws and regulations and user wishes. The authorization method can be to send a user data acquisition reminder to the user during the current rule query process, and the user can obtain authorization to obtain user data after confirming the reminder through the instruction. In addition, user authorization can also be obtained through other methods, such as obtaining authorization to obtain user data through signing an agreement when the user withdraws resources and / or before withdrawing resources.

[0015] One or more embodiments of a resource quota processing method provided in this embodiment are as follows: Reference Figure 2 The resource quota processing method provided in this embodiment specifically includes steps S202 to S206.

[0016] Step S202: acquiring user data of the risky user pushed by the third-party platform, and querying the resource quota rules associated with the risky user according to the user data.

[0017] In this embodiment, the resource quota rule is a rule for calculating the resource quota of the user, and the resource quota rule can be stored in the form of rule text and / or resource quota policy. Specifically, during the application process, the resource quota rule can be used in the form of resource quota policy, and the resource quota policy can be a rule expression to calculate the resource quota and / or credit rating of the user; during the display process to the members of the organization, the resource quota rule can be displayed to the members of the organization in the form of text in natural language, that is, rule text, so that the members of the organization can view or edit the rule text through natural language.

[0018] Furthermore, in order to facilitate the management of user resource quotas, the rules for calculating the user credit level and / or the level quota comparison table can also be configured as resource quota rules, that is, the resource quota rules can include credit rating rules and / or quota tables, wherein the credit rating rules can also be stored and applied in the form of credit rating strategies and / or rule texts, and the quota table can be stored and applied in the form of data tables. In the specific implementation process, the resource quota rules can be associated with the user to efficiently determine the user's resource quota according to the resource quota rules. Optionally, multiple users can share the same resource quota rule.

[0019] In this embodiment, the third-party platform is a platform and / or system for screening and identifying risky users in a user pool. Specifically, the user pool may be a user pool configured for a single organization, that is, the user pool may include members of a single organization, such as building a user pool based on working members in organization A. The user pool may also be a user pool configured for multiple organizations of the same type, that is, the user pool may include members of multiple organizations of the same type. The user pool may also be a user pool configured for multiple organizations of different types. In addition, the user pool may also be formed based on selected users, which is not limited in this embodiment. During the specific execution process, the third-party platform may screen risky users in the user pool based on the data of each user, and push the screened risky users to the server, so that the server sends the rule editing page of the resource quota rules for risky users to the organization members, so that the organization members can edit the resource quota rules through the rule editing page.

[0020] In actual applications, different institutions can provide resource quotas to users at the same time, such as financial institutions and / or resource institutions. Different institutions can configure different user pools and resource quota rules. In this regard, the third-party platform can provide resource quota institutions as the granularity, and screen risky users from the user pool configured by the institution according to the screening rules of the institution. Accordingly, the resource quota of the risky user can be determined according to the resource quota rules associated with the risky user configured by the institution. Optionally, the resource quota includes the user's credit limit and / or funding limit.

[0021] In specific implementation, the third-party platform can screen risky users and query the user data of risky users for push, obtain the user data pushed by the third-party platform, and query the resource quota rules associated with the risky users according to the user information in the user data. Specifically, the resource quota rules set for users by various financial institutions and / or resource institutions can be stored in the resource quota processing system, or the resource quota processing system can also set resource quota rules for users by themselves. In this regard, the resource quota rules of the resource institution associated with the risky user can be queried according to the user identifier in the user data and the associated resource institution identifier, or the associated resource quota rules can be queried according to the user identifier in the user data.

[0022] During the specific implementation process, different institutions can configure different user screening conditions to screen risky users from the user pool and improve the processing efficiency of resource quotas. In this regard, user screening can be performed from the perspective of user resource flow data to improve the accuracy of screening. In an optional implementation provided by this embodiment, the third-party platform screens risky users in the following manner: Obtain resource flow data of candidate users in the user pool, and detect whether target flow data in the resource flow data meets the screening condition; If so, the target user to which the target flow data belongs is regarded as the risk user; If not, no action is required.

[0023] Optionally, the screening condition includes: the number of resource transfers is greater than a first threshold and / or the resource transfer period is greater than a second threshold.

[0024] Specifically, for a single resource institution and / or financial institution, the resource flow data of the candidate users in the user pool of the institution is obtained, and the resource flow data is checked to see whether it meets the screening conditions of the institution. If so, the target users who meet the screening conditions are regarded as risky users. Optionally, the resource flow data includes the number of resource flows and / or the resource flow period of the candidate users in a single resource institution and / or financial institution.

[0025] For example, the number of overdue times and overdue time of each candidate user is obtained, and it is detected whether the number of overdue times is greater than a first threshold and whether the overdue time is greater than a second threshold, and the target users whose number of overdue times is greater than the first threshold and whose overdue time is greater than the second threshold are regarded as risky users.

[0026] In addition, the screening conditions can also be configured for multiple resource agencies and / or financial institutions associated with the user, that is: the screening conditions are configured by the resource quota processing system, and the resource flow data may include the number of resource transfers and / or resource transfer periods of the candidate user in the associated multiple resource agencies and / or financial institutions; in this regard, it can be detected whether the total number of resource transfers of the candidate user in multiple resource agencies and / or financial institutions is greater than the number threshold, and / or it can be detected whether the total number of resource transfers of the candidate user in multiple resource agencies and / or financial institutions is greater than the period threshold, and the candidate users who meet the conditions are regarded as risky users.

[0027] For example, the total number of overdue payments and the total overdue duration of each candidate user in each institution are obtained, and it is detected whether the total number of overdue payments is greater than the number threshold and whether the total overdue duration is greater than the duration threshold. Target users whose total number of overdue payments is greater than the number threshold and whose total overdue duration is greater than the duration threshold are identified as risky users.

[0028] It should be noted that in this embodiment, the risky users may be multiple users. Resource quota rules are set for multiple risky users and associated operations are performed for each risky user. That is, the resource quota rules can be shared by multiple risky users. In addition, the risky users can also filter out single users. The specific resource quota rules are handled in a similar way to the above-mentioned multiple risky users, and can be executed with reference to the above-mentioned operations. This embodiment will not be repeated here.

[0029] Step S204: Generate a rule editing page for the risky user based on the resource quota rule and send it to the institution member, and obtain a target quota rule obtained after the institution member edits the resource quota rule based on the rule editing page.

[0030] In specific implementation, based on the rule text of the resource quota rule of the risk user queried, a rule editing page for the risk user is generated and sent to the organization members, so that the organization members can view the resource quota rule of the risk user through the terminal device and send it back after editing, and obtain the target quota rule after the organization members edit the resource quota rule. Specifically, the rule text of the resource quota rule can be configured in the corresponding area of ​​the page to be configured, and the control configuration can be selected to generate the rule editing page on the page to be configured.

[0031] In this embodiment, the rule editing page is a page used to display the user's current resource quota rules to the organization members and provide the organization members with the function of editing the resource quota rules. Specifically, the rule editing page can be configured with the rule text of the resource quota rules currently used by the user so that the organization members can view them. Multiple controls can also be configured in the rule editing page to implement functions such as adding, modifying, and saving resource quota rules. It should be noted that the content displayed in the rule editing page can be determined by the login information of the organization members. For the controls configured in the rule editing page, controls that match the operation permissions in the login information can be filtered; for example: some organization members only have the permission to view the rules, then the rule editing page of these organization members is not configured with rule modification controls and rule addition controls, or the status of the rule modification controls and rule addition controls in the rule editing page is configured as a non-triggerable state.

[0032] During the specific execution process, the operation authority of the organization member can be determined according to the member identifier contained in the login request of the organization member, and the target control can be screened according to the operation authority, thereby improving the security and traceability of the resource quota editing process; in an optional implementation manner provided by this embodiment, before generating the rule editing page, it also includes: Obtaining a login request of the organization member, and determining the operation authority of the organization member based on the member identifier included in the login request; Accordingly, the rule editing page is generated, including: Query the rule text corresponding to the resource quota rule in the text library, and select the target control that matches the operation permission in the control library; The rule text is configured in the display area of ​​the page to be configured, and the target control is configured in the interactive area of ​​the page to be configured to obtain the rule editing page.

[0033] Specifically, you can first obtain an empty page to be configured, query the rule text corresponding to the current resource quota rule of the risk user in the rule text library, and configure the rule text in the rule display area of ​​the page to be configured, filter out the target control that matches the operation authority in the control library, and configure the target control in the interactive area of ​​the page to be configured to obtain a rule editing page configured with the rule text and the target control.

[0034] During the specific rule editing process, organization members can modify the rules by selecting the edited rules in the rule editing page, that is: selecting the pre-edited rules to modify the rules, or organization members can add new rules by adding rules, that is: entering new rule text to add rules. The following is a specific explanation of the two rule editing methods.

[0035] (1) Rule changes With respect to the rule modification method, multiple rule texts may be provided to the institution members for selection. For example, the institution members may choose to reduce the resource quota and / or credit level after 3 / 4 / 5 overdue times, so as to improve the editing efficiency of the resource quota rule. In an optional implementation manner provided in this embodiment, the target quota rule is obtained in the following manner: After detecting a trigger instruction of the organization member for a rule modification control in the rule editing page, verifying the operation authority of the organization member; If the verification is passed, the target rule text configured for the target area is read according to the trigger instruction of the organization member for the target area and updated to the rule editing page to display the target rule text to the organization member; When the confirmation event of the rule editing page is triggered, the target quota rule is constructed according to the rule information of the rule editing page.

[0036] Specifically, the institution member triggers the rule modification control on the rule editing page displayed on the terminal device to modify the rule. After detecting the trigger instruction, the server verifies the operation authority of the institution member. If the institution member has the editing authority, the verification is passed. The institution member triggers the target area in the rule display area to select the rule. The server updates the target rule text configured in the target area to the rule editing page for display to the institution member. The above operation can be repeated until the institution member clicks Save. After confirming that the event is triggered, the server constructs the target limit rule according to the rule information on the rule editing page.

[0037] For example, after an institution member triggers the modification button, he clicks the extension button corresponding to the overdue management rule, and multiple preset rule texts are displayed on the rule editing page. When it is detected that the institution member triggers the corresponding area of ​​"credit level will be lowered if overdue three times", the overdue management rule will be modified to "credit level will be lowered if overdue three times".

[0038] (2) New rules For the rule adding method, the rule adding control can be configured in the rule editing page according to the operation authority of the organization members, so that the organization members with the new rules can add rules, thereby improving the security of the resource quota rules; in an optional implementation method provided in this embodiment, the target quota rule is obtained in the following way: After detecting the trigger instruction of the organization member for adding a rule control in the rule editing page, reading the newly added rule text input by the organization member; After detecting that the confirmation control is triggered, the target limit rule is generated based on the newly added rule text.

[0039] Optionally, the target control includes the rule adding control that matches the first operation permission.

[0040] Specifically, when the authority of the institution member is the first operation authority, a rule editing page containing a triggerable rule adding control is sent to the institution member. After detecting that the institution member triggers the rule adding control, the new rule text entered by the institution member is read. The above operation can be repeated until the institution member triggers the confirmation control. After detecting that the confirmation control is triggered, the server generates a target limit rule based on the new rule text.

[0041] In practical applications, in order to improve the efficiency of quota processing and the accuracy of resource quota, the resource quota of risky users can also be determined by a pre-trained prediction model, and institutional members can edit the resource quota rules of risky users according to the quota recommendation information output by the prediction model, thereby improving the reliability of resource quota rules; in an optional implementation manner provided by this embodiment, before issuing a rule editing page to institutional members, it also includes: Inputting the user data into a prediction model to perform credit limit prediction and text generation, and obtaining credit limit recommendation information for the risky user; The quota recommendation information is written into the rule editing page so that the institution members can determine the target quota rule according to the quota recommendation information.

[0042] Furthermore, the prediction model may be a large language model, which can call different components and algorithms within the model to perform corresponding processing through prompt information, thereby improving the efficiency of credit limit processing; in an optional implementation provided by this embodiment, credit limit prediction and text generation are performed, including: Inputting resource flow data and user characteristic data in the user data into a quota prediction algorithm to perform quota prediction according to the first prompt information, and obtaining a user predicted quota; According to the second prompt information, the resource flow data and the user predicted quota are input into a text generation component to obtain the quota recommendation information.

[0043] Specifically, firstly, a quota prediction process is performed according to the first prompt information, resource flow data and user feature data in the user data are extracted and input into the quota prediction algorithm to perform quota prediction to obtain the user predicted quota, and the user predicted quota and resource flow data are used as input data for the next layer, and according to the second prompt information, the user predicted quota and resource flow data are input into the text generation component to obtain quota recommendation information.

[0044] It should be pointed out that, considering that user characteristic data belongs to the user's privacy to a certain extent, if you want to obtain user characteristic data, you can obtain authorization from the applicant user before obtaining the user characteristic data. The authorization method can be to send a user characteristic data acquisition reminder to the risky user during the current credit limit prediction process. The risky user can obtain authorization to obtain the user characteristic data after confirming the reminder through the instruction. In addition, user authorization can also be obtained through other methods, such as obtaining authorization to obtain user characteristic data through signing an agreement when the user withdraws resources and / or before withdrawing resources.

[0045] It should be noted that user data may be the data of multiple risk users, that is, the prediction model may generate quota recommendation information shared by multiple risk users based on the data of multiple risk users, so that institutional members may edit the resource quota rules for the multiple risk users according to the quota recommendation information.

[0046] It should also be noted that based on the prediction model provided above, the credit limit rule that matches the user data of the risky user in the rule library can be directly selected through the prediction model, and the server can obtain the credit limit rule and call the rule engine for configuration, that is: step S204 can be replaced by: using the user data as input data to call the prediction model for credit limit prediction and rule matching, and obtain the target credit limit rule that matches the risky user.

[0047] Step S206: Call the rule engine to update the quota rule and determine the resource quota of the risk user according to the target quota rule, and obtain the resource quota of the risk user.

[0048] The resource quota processing method provided in this embodiment manages and applies the user's resource quota rules by setting up a rule engine. After the institution member edits the resource quota rules, the rule engine is called to update the quota rules of the risky user and determine the resource quota based on the updated rules to obtain the resource quota of the risky user. Through the combination of the rule engine and the graphical interface, the resource quota is processed conveniently and efficiently, thereby improving the reliability and accuracy of the resource quota.

[0049] In specific implementation, the target quota rule and user data are used as input to call the rule engine, so that the rule engine updates the quota rule of the risk user according to the target quota rule, and determines the resource quota of the risk user according to the target quota rule to obtain the resource quota of the risk user. Specifically, the rule engine can cancel the available mark of the resource quota rule currently applied by the risk user and mark the target quota rule as available, determine the credit level of the risk user according to the target quota rule, and select the target quota corresponding to the credit level as the resource quota.

[0050] During the specific execution process, the rule engine may process the target rating rule and the target quota table included in the target quota rule respectively, first determining the credit level of the risk user and determining the resource quota corresponding to the credit level to improve the accuracy and reliability of the resource quota; in an optional implementation provided by this embodiment, the quota rule of the risk user is updated and the resource quota is determined according to the target quota rule, including: Extracting the target rating rule and the target quota table included in the target quota rule, updating the resource quota rule associated with the risk user to the target rating rule and the target quota table, and configuring the target rating rule and the target quota table; A credit rating is performed according to the user data and the target rating rule to obtain the credit level of the risk user, and a target quota matching the credit level is searched in the target quota table as the resource quota.

[0051] Specifically, the rule engine can extract the target rating rules for credit rating and the target quota table for matching the quota corresponding to the credit level contained in the target quota rules, update the resource quota rules associated with the risk user into the target rating rules and the target quota table, and write the target rating rules and the target quota table into the configuration file to update the quota rules, then perform credit rating according to the target rating rules based on the user data to obtain the credit level of the risk user, and query the target quota matching the credit level in the target quota table as the resource quota of the risk user.

[0052] In the specific rule update process, in order to improve the traceability of the resource quota rules, a version identifier may be set for each resource quota rule and a historical rule library of each historical resource quota rule may be constructed; in an optional implementation manner provided in this embodiment, the quota rule update includes: canceling the available status mark of the version identifier of the resource quota rule, and writing the resource quota rule into the historical rule library; A version identifier of the target credit limit rule is generated, and the version identifier of the target credit limit rule is marked as an available state.

[0053] Furthermore, version identifiers of the target rating rules and the target quota table can be generated and status markings can be performed, for example: canceling the available status mark of the version identifier of the resource quota rule, and writing the resource quota rule into the historical rule base; generating version identifiers of the target rating rules and the target quota table, and marking the version identifiers of the target rating rules and the target quota table as available status.

[0054] During the specific rule update process, the rule base may store the rule text of the resource quota rule and / or the resource quota policy of the resource quota rule, and convert the target quota rule into the target quota policy so that the rule engine applies the target quota policy to determine the resource quota. During the resource quota determination process, the resource quota may be determined according to the target quota policy. For example: convert the target quota rule into the target quota policy and configure the target quota policy; determine the resource quota of the risky user according to the target quota policy based on the user data. The specific configuration policy process may refer to the configuration process of the above-mentioned target quota rule, and this embodiment will not be repeated here.

[0055] In actual applications, the user data of each risk user is different, and different resource quotas may be calculated when sharing the same target quota rule; in view of this, after determining the resource quota of each risk user, the rule engine can also configure the resource quota to apply the resource quota to the risk user one by one, thereby improving the timeliness of resource quota processing; in an optional implementation manner provided by this embodiment, after the step of obtaining the resource quota of the risk user is executed, it also includes: The historical resource quota of each risk user is queried, and the historical resource quota is updated based on the resource quota corresponding to each risk user.

[0056] It should be noted that the updated resource quota may be the risk user's quota at a single resource institution and / or financial institution.

[0057] In practical applications, the user's resource quota can also be recorded through the blockchain to record the resource quota through the immutability of the blockchain and improve the transparency of the resource quota; in an optional implementation provided by this embodiment, after the step of obtaining the resource quota of the risk user is executed, it also includes: The resource quota of the risky user is sent to the blockchain node so that the blockchain node updates the quota information of the risky user on the blockchain.

[0058] It should be noted that the updating process of the resource quota of each risk user can refer to the above quota updating process, which will not be described in detail in this embodiment.

[0059] In summary, the one or more resource quota processing methods provided in this embodiment obtain user data of risk users pushed by a third-party platform, and query the resource quota rules of risk users based on the user data, perform resource quota processing on risk users in a targeted manner, generate a rule editing page for risk users based on the resource quota rules and issue it to institutional members, and provide institutional members with a graphical interface so that institutional members can conveniently edit rules. After editing the resource quota rules based on the rule editing page, institutional members obtain target quota rules and transmit them back. After obtaining the target quota rules, the rule engine is called to update the quota rules of the risk users and determine the resource quota according to the target quota rules, and the resource quota of the risk users is obtained. The resource quota of the risk users is managed and applied by the rule engine, thereby improving the resource quota processing efficiency and improving the reliability and accuracy of the resource quota. Furthermore, by configuring the prediction model and / or the large language model to generate quota recommendation information for risky users based on user data, the high computing power of the model is used to assist institutional members in making decisions and editing and modifying resource quota rules, thereby improving the reliability of resource quota rules.

[0060] This embodiment provides a rule editing page to the institutional members of the institution that provides resource quotas, so that the institutional members can easily and quickly manage the resource quota rules of risky users. Through a graphical interface, the institutional members can edit the resource quota rules on the rule editing page, thereby improving the resource quota processing efficiency and the convenience of editing resource quota rules.

[0061] The following uses the application of a resource quota processing method provided in this embodiment in a quota rule update scenario as an example, combined with Figure 3The resource quota processing method provided in this embodiment is further described. The resource quota processing method applied to the quota rule update scenario specifically includes the following steps.

[0062] Step S302: Obtain user data of the risky user pushed by the third-party platform, and query the resource quota rules associated with the risky user according to the user data.

[0063] Step S304: input the user data into the prediction model to predict the credit limit of the risky user and generate recommendation information to obtain the credit limit recommendation information of the risky user.

[0064] Step S306, obtaining a login request from an organization member, and determining the operation authority of the organization member according to the member identifier in the login request.

[0065] Step S308: Select a target control that matches the operation permission in the control library.

[0066] Step S310, generating a rule editing page for risky users based on resource quota rules, target controls, and quota recommendation information and sending it to institutional members.

[0067] Step S312, obtaining the target quota rule obtained after the institution member edits the resource quota rule based on the rule editing page.

[0068] Step S314, calling the rule engine to update the quota rules of risky users and determine the resource quota according to the target quota rules, and obtaining the resource quota corresponding to each risky user.

[0069] Step S316, querying the historical resource quota of each risk user, and updating the historical resource quota of each risk user based on the resource quota corresponding to each risk user.

[0070] It should be noted that any one of steps S302 to S316 or any combination of multiple steps can be combined with any one of steps S202 to S206 to form a new implementation method according to the needs of implementation deployment; in addition, according to the needs of actual deployment, any one or multiple technical features can be selected from steps S302 to S316 and combined with any one or multiple technical features provided by steps S202 to S206 to form a new implementation method; or, any one or multiple technical features in steps S302 to S316 can be replaced with any one or multiple technical features provided by steps S202 to S206 to form a new implementation method according to the needs of actual deployment, which will not be elaborated here.

[0071] An embodiment of a resource quota processing device provided in this specification is as follows: In the above-mentioned embodiment, a resource quota processing method is provided, and correspondingly, a resource quota processing device is also provided, which is described below in conjunction with the accompanying drawings.

[0072] Reference Figure 4 , which shows a schematic diagram of an embodiment of a resource quota processing device provided in this embodiment.

[0073] Since the device embodiment corresponds to the method embodiment, the description is relatively simple, and the relevant parts can refer to the corresponding description of the method embodiment provided above. The device embodiment described below is only illustrative.

[0074] This embodiment provides a resource quota processing device, the device comprising: The resource quota rule query module 402 is configured to obtain user data of risky users pushed by a third-party platform, and query resource quota rules associated with the risky users according to the user data; The target quota rule acquisition module 404 is configured to generate a rule editing page for the risk user based on the resource quota rule and send it to the institution member, and acquire the target quota rule obtained after the institution member edits the resource quota rule based on the rule editing page; The resource quota determination module 406 is configured to call the rule engine to update the quota rule and determine the resource quota of the risk user according to the target quota rule, and obtain the resource quota of the risk user.

[0075] An embodiment of a message reminder device provided in this specification is as follows: Corresponding to the resource quota processing method described above, based on the same technical concept, one or more embodiments of this specification further provide a message reminder device, which is used to execute the resource quota processing method provided above. Figure 5 A schematic diagram of the structure of a message reminder device provided in one or more embodiments of this specification.

[0076] A message reminder device provided in this embodiment includes: like Figure 5As shown, the message reminder device may have relatively large differences due to different configurations or performances, and may include one or more processors 501 and memory 502, and the memory 502 may store one or more storage applications or data. Among them, the memory 502 may be a short-term storage or a persistent storage. The application stored in the memory 502 may include one or more modules (not shown in the figure), and each module may include a series of computer executable instructions in the message reminder device. Furthermore, the processor 501 may be configured to communicate with the memory 502 and execute a series of computer executable instructions in the memory 502 on the message reminder device. The message reminder device may also include one or more power supplies 503, one or more wired or wireless network interfaces 504, one or more input / output interfaces 505, and one or more keyboards 506.

[0077] In a specific embodiment, the message reminder device includes a memory and one or more programs, wherein the one or more programs are stored in the memory, and the one or more programs may include one or more modules, and each module may include a series of computer executable instructions in the message reminder device, and the one or more programs are configured to be executed by one or more processors, including computer executable instructions for performing the following: Obtain user data of risky users pushed by a third-party platform, and query resource quota rules associated with the risky users based on the user data; Generate a rule editing page for the risk user based on the resource quota rule and send it to the institution member, and obtain a target quota rule obtained after the institution member edits the resource quota rule based on the rule editing page; The rule engine is called to update the quota rule and determine the resource quota of the risk user according to the target quota rule, and obtain the resource quota of the risk user.

[0078] An embodiment of a computer-readable storage medium provided in this specification is as follows: Corresponding to the resource quota processing method described above, based on the same technical concept, one or more embodiments of this specification also provide a computer-readable storage medium.

[0079] The computer-readable storage medium provided in this embodiment is used to store computer-executable instructions, and the computer-executable instructions implement the following process when executed: Obtain user data of risky users pushed by a third-party platform, and query resource quota rules associated with the risky users based on the user data; Generate a rule editing page for the risk user based on the resource quota rule and send it to the institution member, and obtain a target quota rule obtained after the institution member edits the resource quota rule based on the rule editing page; The rule engine is called to update the quota rule and determine the resource quota of the risk user according to the target quota rule, and obtain the resource quota of the risk user.

[0080] It should be noted that the embodiment of the computer-readable storage medium in this specification and the embodiment of the resource quota processing method in this specification are based on the same inventive concept, so the specific implementation of this embodiment can refer to the implementation of the aforementioned corresponding method, and the repeated parts will not be repeated.

[0081] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referenced to each other. Each embodiment focuses on the differences from other embodiments. For example, the device embodiment, equipment embodiment, and computer-readable storage medium embodiment are similar to the method embodiment, so the description is relatively simple. To read the relevant content in the device embodiment, equipment embodiment, and computer-readable storage medium embodiment, please refer to the partial description of the method embodiment.

[0082] The above is a description of a specific embodiment of the specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0083] In the 1930s, improvements to a technology could be clearly distinguished as hardware improvements (for example, improvements to circuit structures such as diodes, transistors, switches, etc.) or software improvements (improvements to method flows). However, with the development of technology, many of today's method flow improvements can be regarded as direct improvements to hardware circuit structures. Designers almost always obtain the corresponding hardware circuit structure by programming the improved method flow into the hardware circuit. Therefore, it cannot be said that an improvement in a method flow cannot be implemented using hardware entity modules. For example, a programmable logic device (PLD) (such as a field programmable gate array (FPGA)) is such an integrated circuit whose logical function is determined by the user's programming of the device. Designers can "integrate" a digital system on a PLD by programming it themselves, without having to ask chip manufacturers to design and produce dedicated integrated circuit chips. Moreover, nowadays, instead of manually making integrated circuit chips, this kind of programming is mostly implemented by "logic compiler" software, which is similar to the software compiler used when developing and writing programs, and the original code before compilation must also be written in a specific programming language, which is called hardware description language (HDL). There is not only one kind of HDL, but many kinds, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, RHDL (Ruby Hardware Description Language), etc. The most commonly used ones are VHDL (Very-High-Speed ​​Integrated Circuit Hardware Description Language) and Verilog. Those skilled in the art should also know that it is only necessary to program the method flow slightly in the above-mentioned hardware description languages ​​and program it into the integrated circuit, and then it is easy to obtain the hardware circuit that implements the logic method flow.

[0084] The controller may be implemented in any suitable manner, for example, the controller may take the form of a microprocessor or processor and a computer-readable medium storing a computer-readable program code (e.g., software or firmware) executable by the (micro)processor, a logic gate, a switch, an application-specific integrated circuit (ASIC), a programmable logic controller, and an embedded microcontroller, examples of which include but are not limited to the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicone Labs C8051F320, and the memory controller may also be implemented as part of the control logic of the memory. It is also known to those skilled in the art that, in addition to implementing the controller in a purely computer-readable program code manner, the controller may be implemented in the form of a logic gate, a switch, an application-specific integrated circuit, a programmable logic controller, and an embedded microcontroller by logically programming the method steps. Therefore, such a controller may be considered as a hardware component, and the devices for implementing various functions included therein may also be considered as structures within the hardware component. Or even, the devices for implementing various functions may be considered as both software modules for implementing the method and structures within the hardware component.

[0085] The systems, devices, modules or units described in the above embodiments may be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, the computer may be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

[0086] For the convenience of description, the above devices are described in terms of functions and are divided into various units. Of course, when implementing the embodiments of this specification, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0087] It should be understood by those skilled in the art that one or more embodiments of the present specification may be provided as a method, system or computer program product. Therefore, one or more embodiments of the present specification may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present specification may take the form of a computer program product implemented on one or more computer-readable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0088] This specification is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of this specification. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable network live broadcast processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable network live broadcast processing device generate instructions for implementing the processes in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0089] These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable network live broadcast processing device to work in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0090] These computer program instructions may also be loaded onto a computer or other programmable network live processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for executing on the computer or other programmable device to implement the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0091] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0092] Memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.

[0093] Computer-readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer-readable instructions, data structures, program modules or other data. Examples of computer-readable storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory media such as modulated data signals and carrier waves.

[0094] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of further restrictions, the elements defined by the sentence "includes at least one ..." do not exclude the presence of other identical elements in the process, method, commodity or device including the elements.

[0095] One or more embodiments of the present specification may be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. One or more embodiments of the present specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules may be located in local and remote computer storage media, including storage devices.

[0096] The above description is only an embodiment of this document and is not intended to limit this document. For those skilled in the art, this document may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of this document should be included in the scope of the claims of this document.

Claims

1. A resource quota processing method, comprising: Obtain user data of risky users pushed by a third-party platform, and query resource quota rules associated with the risky users based on the user data; Generate a rule editing page for the risk user based on the resource quota rule and send it to the institution member, and obtain a target quota rule obtained after the institution member edits the resource quota rule based on the rule editing page; The rule engine is called to update the quota rule and determine the resource quota of the risk user according to the target quota rule, and obtain the resource quota of the risk user.

2. The resource quota processing method according to claim 1, after the operation of generating the rule editing page of the risk user based on the resource quota rule is executed, and before the operation of issuing the rule to the institution members is executed, it also includes: Inputting the user data into a prediction model to perform credit limit prediction and text generation, and obtaining credit limit recommendation information for the risky user; The quota recommendation information is written into the rule editing page so that the institution members can determine the target quota rule according to the quota recommendation information.

3. The resource quota processing method according to claim 2, wherein the quota prediction and text generation comprises: Inputting resource flow data and user characteristic data in the user data into a quota prediction algorithm to perform quota prediction according to the first prompt information, and obtaining a user predicted quota; According to the second prompt information, the resource flow data and the user predicted amount are input into a text generation component to generate recommendation information to obtain the amount recommendation information.

4. The resource quota processing method according to claim 1, before generating the rule editing page of the risk user based on the resource quota rule and sending it to the organization member for execution, further comprising: Obtaining a login request of the organization member, and determining the operation authority of the organization member based on the member identifier included in the login request; Correspondingly, the rule editing page for generating the risk user based on the resource quota rule includes: Query the rule text corresponding to the resource quota rule in the text library, and select the target control that matches the operation permission in the control library; The rule text is configured in the display area of ​​the page to be configured, and the target control is configured in the interactive area of ​​the page to be configured to obtain the rule editing page.

5. According to the resource quota processing method of claim 4, the target quota rule is obtained in the following manner: After detecting a trigger instruction of the organization member for a rule modification control in the rule editing page, verifying the operation authority of the organization member; If the verification is passed, the target rule text configured for the target area is read according to the editing operation of the institution member on the target area and updated to the rule editing page to display the target rule text to the institution member; When the confirmation event of the rule editing page is triggered, the target quota rule is constructed according to the rule information of the rule editing page.

6. According to the resource quota processing method of claim 4, the target quota rule is obtained in the following manner: After detecting the trigger instruction of the organization member for the rule adding control in the rule editing page, reading the newly added rule text input by the organization member; the target control includes the rule adding control matching the first operation authority; After detecting that the confirmation control is triggered, the target limit rule is generated based on the newly added rule text.

7. The resource quota processing method according to claim 1, wherein updating the quota rule of the risky user and determining the resource quota according to the target quota rule comprises: Extracting the target rating rule and the target quota table included in the target quota rule, updating the resource quota rule associated with the risk user to the target rating rule and the target quota table, and configuring the target rating rule and the target quota table; A credit rating is performed according to the user data and the target rating rule to obtain the credit level of the risk user, and a target quota matching the credit level is searched in the target quota table as the resource quota.

8. The resource quota processing method according to claim 7, wherein the configuring the target rating rule and the target quota table comprises: canceling the available status mark of the version identifier of the resource quota rule, and writing the resource quota rule into the historical rule library; The version identifiers of the target rating rule and the target quota table are generated, and the version identifiers of the target rating rule and the target quota table are marked as being in an available state.

9. According to the resource quota processing method of claim 1, the risky users are screened and obtained by the third-party platform in the following manner: Obtain resource flow data of candidate users in the user pool, and detect whether target flow data in the resource flow data meets the screening condition; If so, the target user to which the target flow data belongs is regarded as the risk user; in, The screening conditions include: the number of resource transfers is greater than a first threshold and / or the resource transfer period is greater than a second threshold.

10. The resource quota processing method according to claim 1, wherein the calling rule engine updates the quota rule of the risk user and determines the resource quota according to the target quota rule, and after the step of obtaining the resource quota of the risk user is executed, the method further comprises: The historical resource quota of each risk user is queried, and the historical resource quota is updated based on the resource quota corresponding to each risk user.

11. A resource quota processing device, comprising: A resource quota rule query module is configured to obtain user data of risky users pushed by a third-party platform, and query resource quota rules associated with the risky users according to the user data; A target quota rule acquisition module is configured to generate a rule editing page for the risk user based on the resource quota rule and send it to the institution member, and acquire a target quota rule obtained after the institution member edits the resource quota rule based on the rule editing page; The resource quota determination module is configured to call the rule engine to update the quota rule and determine the resource quota of the risk user according to the target quota rule, and obtain the resource quota of the risk user.

12. A resource quota processing device, comprising: processor; and a memory configured to store computer executable instructions, wherein the processor executes the computer executable instructions to implement the following process: Obtain user data of risky users pushed by a third-party platform, and query resource quota rules associated with the risky users based on the user data; Generate a rule editing page for the risk user based on the resource quota rule and send it to the institution member, and obtain a target quota rule obtained after the institution member edits the resource quota rule based on the rule editing page; The rule engine is called to update the quota rule and determine the resource quota of the risk user according to the target quota rule, and obtain the resource quota of the risk user.

13. A computer-readable storage medium for storing computer-executable instructions, wherein the computer-executable instructions implement the steps of the method of claim 1 when executed.

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