CN115905692A

CN115905692A - Resource borrowing evaluation data pushing method and device and computer equipment

Info

Publication number: CN115905692A
Application number: CN202211419136.7A
Authority: CN
Inventors: 易勇强; 张捷; 高尚; 李思隆; 刘一霖; 陈令曦
Original assignee: China Southern Power Grid Internet Service Co ltd
Current assignee: China Southern Power Grid Internet Service Co ltd
Priority date: 2022-11-14
Filing date: 2022-11-14
Publication date: 2023-04-04

Abstract

The application relates to a resource borrowing assessment data pushing method and device, computer equipment, storage medium and computer program products. The method comprises the following steps: acquiring target electricity utilization data corresponding to a plurality of target users; analyzing resource borrowing parameters according to the target electricity utilization data to obtain a qualification evaluation result and a resource borrowing threshold value corresponding to each target user; grading the target electricity utilization data to obtain grading data corresponding to target users; and responding to the resource borrowing request of the target user, and pushing a qualification evaluation result, a resource borrowing threshold value and grading data corresponding to the target user to a target mechanism for processing the resource borrowing request. By adopting the method, the resource borrowing evaluation efficiency can be improved.

Description

Resource borrowing assessment data pushing method and device and computer equipment

Technical Field

The present application relates to the field of computer technologies, and in particular, to a method and an apparatus for pushing resource borrowing assessment data, a computer device, a storage medium, and a computer program product.

Background

With the development of the technical field of computers, a resource borrowing evaluation technology appears, and after a user initiates a resource borrowing request, a mechanism for processing the resource borrowing request generally evaluates resource borrowing evaluation data of the user by using the resource borrowing evaluation technology to determine whether to approve the resource borrowing request of the user.

In the conventional technology, an organization processing the resource borrowing request generally acquires the user credit data through a unified platform so as to evaluate the resource borrowing evaluation data of the user in the following.

However, in the conventional technology, real-time and comprehensive resource borrowing evaluation data cannot be rapidly acquired, and the resource borrowing evaluation efficiency of the institution is affected.

Disclosure of Invention

In view of the above, it is necessary to provide a resource borrowing evaluation data pushing method, apparatus, computer device, computer readable storage medium, and computer program product capable of improving resource borrowing evaluation efficiency in view of the above technical problems.

In a first aspect, the application provides a method for pushing resource borrowing evaluation data. The method comprises the following steps:

acquiring target electricity utilization data corresponding to a plurality of target users;

analyzing resource borrowing parameters according to the target electricity utilization data to obtain a qualification evaluation result and a resource borrowing threshold value which correspond to each target user;

grading the target electricity utilization data to obtain grading data corresponding to target users;

and responding to the resource borrowing request of the target user, and pushing the qualification evaluation result, the resource borrowing threshold value and the grading data corresponding to the target user to a target mechanism for processing the resource borrowing request.

In one embodiment, before obtaining target electricity consumption data corresponding to each of a plurality of target users, the method includes:

acquiring original power consumption data corresponding to a plurality of users, wherein the original power consumption data at least comprises user data and settlement data of each user;

screening user data and settlement data of each user, and determining a plurality of target users meeting the identification conditions and the settlement conditions;

and screening the original power consumption data corresponding to the target users respectively to obtain the target power consumption data corresponding to the target users respectively.

In one embodiment, the screening of the original power consumption data corresponding to each target user, and the obtaining of the target power consumption data corresponding to each target user includes:

determining a data dimension screening condition for screening target electricity utilization data;

and screening the original power consumption data corresponding to the target users according to the data dimension screening conditions to obtain the target power consumption data which meet the data dimension screening conditions and correspond to the target users.

In one embodiment, the resource borrowing parameter analysis according to the target electricity consumption data, and before obtaining the qualification evaluation result and the resource borrowing threshold value corresponding to each target user, the resource borrowing parameter analysis comprises the following steps:

determining an evaluation mode of a resource borrowing threshold, and configuring an evaluation parameter corresponding to each data dimension based on a plurality of data dimensions corresponding to target electricity utilization data, wherein the number of the evaluation parameters corresponding to each data dimension is at least two;

configuring a data model based on an evaluation parameter corresponding to each data dimension and an evaluation mode of a resource borrowing threshold;

analyzing resource borrowing parameters according to the target electricity utilization data to obtain a qualification evaluation result and a resource borrowing threshold value corresponding to each target user, wherein the resource borrowing parameter analysis comprises the following steps:

and inputting the target electricity utilization data into a data model for resource borrowing parameter analysis, and obtaining a qualification evaluation result and a resource borrowing threshold value which correspond to each target user.

In one embodiment, the step of inputting the target electricity consumption data into the data model for resource borrowing parameter analysis to obtain the qualification evaluation result corresponding to each target user comprises the following steps:

obtaining evaluation parameters of a plurality of data dimensions corresponding to a target user;

and when the evaluation parameters corresponding to the target user all meet the evaluation conditions, the qualification evaluation result corresponding to the target user represents that the target user meets the resource borrowing conditions.

In one embodiment, in response to a resource borrowing request of a target user, pushing a qualification evaluation result, a resource borrowing threshold value and grading data corresponding to the target user to a target institution processing the resource borrowing request further includes:

and receiving a resource borrowing evaluation result returned by the target mechanism, and pushing the resource borrowing evaluation result to the target user.

In one embodiment, after receiving the resource borrowing evaluation result returned by the target organization and pushing the resource borrowing evaluation result to the target user, the method further comprises the following steps:

under the condition that the resource borrowing evaluation result represents the resource borrowing request of the target user granted by the target organization, regularly acquiring the latest target power utilization data of the target user, and updating the qualification evaluation result, the resource borrowing threshold value and the classification data of the target user;

and pushing the qualification evaluation result, the resource borrowing threshold value and the grading data updated by the target user to the target organization.

In a second aspect, the application further provides a device for pushing resource borrowing evaluation data. The device comprises:

the power consumption data acquisition module is used for acquiring target power consumption data corresponding to a plurality of target users;

the first processing module is used for carrying out resource borrowing parameter analysis according to the target electricity utilization data to obtain a qualification evaluation result and a resource borrowing threshold value which correspond to each target user;

the second processing module is used for carrying out grading processing on the target electricity utilization data to obtain grading data corresponding to each target user;

and the third processing module is used for responding to the resource borrowing request of the target user and pushing the qualification evaluation result, the resource borrowing threshold value and the grading data corresponding to the target user to a target mechanism for processing the resource borrowing request.

In a third aspect, the application also provides a computer device. The computer device comprises a memory storing a computer program and a processor implementing the following steps when executing the computer program:

analyzing resource borrowing parameters according to the target electricity utilization data to obtain a qualification evaluation result and a resource borrowing threshold value corresponding to each target user;

and responding to the resource borrowing request of the target user, and pushing a qualification evaluation result, a resource borrowing threshold value and grading data corresponding to the target user to a target mechanism for processing the resource borrowing request.

In a fourth aspect, the present application further provides a computer-readable storage medium. The computer-readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of:

In a fifth aspect, the present application further provides a computer program product. The computer program product comprising a computer program which when executed by a processor performs the steps of:

According to the method, the device, the computer equipment, the storage medium and the computer program product for pushing the resource borrowing evaluation data, the target power utilization data corresponding to a plurality of target users are obtained, then resource borrowing parameter analysis is carried out according to the target power utilization data, the qualification evaluation result and the resource borrowing threshold value corresponding to each target user are obtained, so that a target organization can refer to the resource borrowing request of the target user when processing the resource borrowing request of the target user, then the target power utilization data are processed in a grading mode, the grading data corresponding to the target users are obtained, the target data corresponding to each target user are enabled to be more visual and clear, and finally the qualification evaluation result, the resource borrowing threshold value and the grading data corresponding to the target user are pushed to the target organization processing the resource borrowing request in response to the resource borrowing request of the target user. In the whole process, after the qualification evaluation result, the resource borrowing threshold value and the grading data corresponding to the target user are pushed to the target institution, the target institution can quickly judge whether the target user meets the resource borrowing condition or not based on the received resource borrowing evaluation data, quickly determine the resource borrowing threshold value of the target user, and can improve the resource borrowing evaluation efficiency of the target institution.

Drawings

FIG. 1 is a diagram of an application environment of a method for pushing resource borrowing evaluation data according to one embodiment;

FIG. 2 is a flowchart illustrating a method for pushing resource borrowing evaluation data according to an embodiment;

FIG. 3 is a diagram illustrating a data processing procedure for resource borrowing evaluation data according to one embodiment;

FIG. 4 is a flowchart illustrating a method for pushing resource borrowing evaluation data according to another embodiment;

FIG. 5 is a block diagram of a pushing device for resource borrowing evaluation data according to one embodiment;

FIG. 6 is a diagram of the internal structure of a computer device in one embodiment.

Detailed Description

In order to make the objects, technical solutions and advantages of the present application more clearly understood, the present application is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of and not restrictive on the broad application.

The resource borrowing assessment data pushing method provided by the embodiment of the application can be applied to the application environment shown in fig. 1. Wherein a plurality of target users 102 communicate with a server 104 over a network. The data storage system may store data that the server 104 needs to process. The data storage system may be integrated on the server 104, or may be located on the cloud or other network server. The server 104 may obtain target electricity consumption data corresponding to each of the plurality of target users 102, perform resource borrowing parameter analysis according to the target electricity consumption data, obtain a qualification evaluation result and a resource borrowing threshold value corresponding to each of the target users 102, perform classification processing on the target electricity consumption data, obtain classification data corresponding to each of the target users 102, and then, in response to a resource borrowing request of the target user 102, push the qualification evaluation result, the resource borrowing threshold value, and the classification data corresponding to the target user 102 to a target organization that processes the resource borrowing request. The plurality of target users 102 may be, but not limited to, various enterprises in normal business status, and the like. The server 104 may be implemented as a stand-alone server or as a server cluster comprised of multiple servers.

In one embodiment, as shown in fig. 2, a method for pushing resource borrowing evaluation data is provided, which is described by taking the method as an example applied to the server 104 in fig. 1, and includes the following steps:

step 202, obtaining target electricity consumption data corresponding to a plurality of target users.

The target electricity utilization data are stored in a data center, the data center can be specifically an electric power data management center with collected electricity utilization data of each user in each region, and the server can be connected with the data center through a network. The target user may specifically be an enterprise in which the target electricity consumption data is stored in the data center.

Specifically, the server may set a sub-server in the data center, and filter the power data of the data center through the sub-server set in the data center, to screen out target power consumption data corresponding to each target user, so as to obtain the target power consumption data corresponding to each of the plurality of target users.

In a specific application, after the target electricity utilization data is screened out based on the sub-server set up in the data center, the server can store the target electricity utilization data in the data center in a table form.

And 204, analyzing the resource borrowing parameters according to the target electricity utilization data to obtain a qualification evaluation result and a resource borrowing threshold value which correspond to each target user.

The target electricity consumption data corresponding to each target user includes identification information of the target user, and the identification information of the target user may specifically be an industry code of the target user, for example, an industry code of an enterprise. The resource borrowing parameter corresponding to each target user may specifically be a qualification evaluation result and a resource borrowing threshold corresponding to each target user.

Specifically, the server may perform resource borrowing parameter analysis on each target user according to the target power consumption data corresponding to each target user, so as to obtain a qualification evaluation result and a resource borrowing threshold value corresponding to each target user. The qualification evaluation result may be used to preliminarily evaluate whether the target user meets the resource borrowing condition, and the resource borrowing threshold may be used to preliminarily evaluate a threshold at which the target user can borrow the resource.

In a specific application, the server may store the identification information, the qualification evaluation result, and the resource borrowing threshold corresponding to each target user in the data center in a form of a table, so that the qualification evaluation result and the resource borrowing threshold corresponding to the identification information of the target user may be obtained from the data center subsequently based on the identification information of the target user.

And step 206, carrying out grading processing on the target electricity utilization data to obtain grading data corresponding to each target user.

Specifically, the server may perform hierarchical processing on the target electricity consumption data of each data dimension based on a plurality of data dimensions corresponding to the target electricity consumption data to obtain hierarchical data corresponding to each target user, where the data dimensions corresponding to the target electricity consumption data may be specifically divided into four dimensions, namely, enterprise electricity consumption basic information, enterprise electricity quantity information, enterprise electricity charge information, and enterprise default information.

In a specific application, for target electricity consumption data of an enterprise electricity charge information dimension, multiple kinds of electricity consumption data of different types, for example, real charge electricity charge data, are configured in the target electricity consumption data corresponding to the dimension. Further, the server may divide the target electricity consumption data corresponding to the dimension into different types, and take the real electricity charge data in the target electricity consumption data corresponding to the dimension as an example for explanation, the server may divide the real electricity charge data into a type, and divide the real electricity charge data into a plurality of levels (A1, A2, A3 \8230;), and each level is configured with a respective real electricity charge range. For example, the target users with high real electricity charge may be classified into a high class A1 of the class a data, and the target users with low real electricity charge may be classified into a class A3 of the class a data. The specific grading mode can be configured according to the actual application scenario, and the grading mode is not limited herein.

In the process, the server can represent the target power consumption data corresponding to the target user by using the corresponding grade without displaying the specific data of the target user by carrying out grading processing on the target power consumption data, so that the aim of protecting the data privacy of the target user is achieved, and meanwhile, the target power consumption data corresponding to the target user can be more visual and clear, so that a subsequent target mechanism can evaluate the target user based on the grade corresponding to each data dimension of the target user.

In a specific application, the server may store the identification information and the hierarchical data corresponding to each target user in the data center in a table form, so that the hierarchical data corresponding to the identification information of the target user may be subsequently acquired from the data center based on the identification information of the target user.

And step 208, responding to the resource borrowing request of the target user, and pushing the qualification evaluation result, the resource borrowing threshold value and the grading data corresponding to the target user to a target mechanism for processing the resource borrowing request.

Specifically, the server may respond to the resource borrowing request of the target user, obtain the qualification evaluation result, the resource borrowing threshold value and the classification data corresponding to the target user from the data center based on the identification information of the target user, and push the qualification evaluation result, the resource borrowing threshold value and the classification data corresponding to the target user to the target organization processing the corresponding resource borrowing request.

In a specific application, under the condition that a target user initiates a resource borrowing request, a server can obtain identification information of the target user and data access permission granted by the target user, then obtain a qualification evaluation result, a resource borrowing threshold value and classification data corresponding to the target user from a data center based on the data access permission granted by the target user, and push the qualification evaluation result, the resource borrowing threshold value and the classification data corresponding to the target user to a target mechanism capable of processing the corresponding resource borrowing request.

According to the method for pushing the resource borrowing evaluation data, the target power utilization data corresponding to the target users are obtained, then resource borrowing parameter analysis is carried out according to the target power utilization data, the qualification evaluation result and the resource borrowing threshold value corresponding to each target user are obtained, so that a target organization can refer to the target users when processing resource borrowing requests of the target users, then grading processing is carried out on the target power utilization data, the grading data corresponding to the target users are obtained, the target data corresponding to each target user are visual and clear, and finally the qualification evaluation result, the resource borrowing threshold value and the grading data corresponding to the target users are pushed to the target organization processing the resource borrowing requests in response to the resource borrowing requests of the target users. In the whole process, after the qualification evaluation result, the resource borrowing threshold value and the grading data corresponding to the target user are pushed to the target institution, the target institution can quickly judge whether the target user meets the resource borrowing condition or not based on the received resource borrowing evaluation data, quickly determine the resource borrowing threshold value of the target user, and can improve the resource borrowing evaluation efficiency of the target institution.

screening user data and settlement data of each user, and determining a plurality of target users meeting identification conditions and settlement conditions;

and screening the original power utilization data corresponding to the target users respectively to obtain the target power utilization data corresponding to the target users respectively.

The original electricity consumption data of each user are stored in a data center. When the user data corresponding to the user comprises the identification information, the user is represented to meet the identification condition. And when the settlement data corresponding to the user is not zero, representing that the user meets the settlement condition.

Specifically, the server may obtain original power consumption data corresponding to each of the plurality of users based on a sub-server installed in the data center, where the original power consumption data at least includes user data and settlement data of each user. In the data center, the server can control the sub-servers arranged in the data center, screen the original data of each user and determine a plurality of target users meeting the identification condition and the settlement condition. And then, screening the original power utilization data corresponding to the target users respectively to obtain the target power utilization data corresponding to the target users respectively.

In a specific application, taking screening of user data and settlement data of each user as an example for explanation, the server may obtain the user data of each user from the original data of each user based on a sub-server established in the data center, where the user data corresponding to the target user all stores identification information of the target user. Then, the server can screen out the users meeting the identification conditions based on the identification information, and further screen the settlement data corresponding to the users meeting the identification conditions to obtain the target users meeting the identification conditions and the settlement conditions at the same time.

For example, the server may obtain the user information table in the user data, and since the user information table corresponding to the enterprise user stores the industry code of the enterprise, the server may screen out the enterprise user, that is, the user meeting the identification condition, based on the industry code. Then, the server can obtain a settlement account table in settlement data corresponding to the enterprise users, and screen out target enterprise users with actual payment services, namely target users meeting the identification conditions and the settlement conditions, wherein the number of the target users is multiple, and the settlement data is not zero.

In this embodiment, original power consumption data that the target user corresponds in the data center is screened, target power consumption data is obtained, and the target power consumption data that obtain is accurate, and data acquisition is efficient, can avoid in the conventional art, obtains power data through artifical meter reading, leads to the data accuracy to hang down, the not high problem of data acquisition efficiency.

The data dimension screening condition may specifically be: when the electricity utilization data in the original electricity utilization data corresponding to the target user conforms to four dimensions of enterprise electricity utilization basic information, enterprise electricity quantity information, enterprise electricity charge information and enterprise default information, the electricity utilization data is the target electricity utilization data meeting the data dimension screening condition.

Specifically, the server may determine a data dimension screening condition for screening the target electricity consumption data based on data selected by the plurality of target entities and related to the resource borrowing evaluation data, and screen the original electricity consumption data corresponding to each target user according to the data dimension screening condition to obtain the target electricity consumption data meeting the data dimension screening condition corresponding to each target user.

In specific application, it is assumed that a plurality of target institutions select enterprise electricity basic data, enterprise electricity quantity data, enterprise electricity charge data and enterprise default data as data related to resource borrowing evaluation, and a server can respond to selection operations of the plurality of target institutions and screen original electricity data based on four dimensions of enterprise electricity basic information, enterprise electricity quantity information, enterprise electricity charge information and enterprise default information to obtain screened original electricity data. Then, the server can further detect the repeated data in the screened original power consumption data and remove the repeated data, so that the target power consumption data meeting the data dimension screening condition is obtained.

In the embodiment, more comprehensive target electricity utilization data related to resource borrowing evaluation can be screened through the data dimension screening conditions, the application success rate of a target user is improved, the resource borrowing evaluation data are obtained by inputting the target electricity utilization data into the data model, and the technical problems that in the traditional technology, due to manual meter reading, the obtained power data dimension is limited, and the production and management conditions of the target user cannot be comprehensively reflected are solved.

In one embodiment, the resource borrowing parameter analysis is performed according to the target electricity utilization data, and the resource borrowing threshold value and the qualification evaluation result corresponding to each target user are obtained before the resource borrowing parameter analysis comprises the following steps:

determining an evaluation mode of a resource borrowing threshold, and configuring an evaluation parameter corresponding to each data dimension on the basis of a plurality of data dimensions corresponding to target electricity utilization data, wherein the number of the evaluation parameters corresponding to each data dimension is at least two;

performing resource borrowing parameter analysis according to the target electricity utilization data to obtain a qualification evaluation result and a resource borrowing threshold value corresponding to each target user, wherein the resource borrowing parameter analysis comprises the following steps:

Specifically, the server may determine an evaluation mode of the resource borrowing threshold, configure a plurality of evaluation parameters corresponding to each data dimension based on a plurality of data dimensions corresponding to the target electricity consumption data, and configure the data model based on the evaluation parameters corresponding to each data dimension and the evaluation mode of the resource borrowing threshold. In the process of configuring the data model, the server may configure the data model based on the evaluation parameter corresponding to each data dimension and the evaluation mode of the resource borrowing threshold. And then, inputting the target electricity utilization data into a data model for resource borrowing parameter analysis, obtaining a plurality of evaluation parameters and resource borrowing threshold values corresponding to each data dimension, and obtaining the qualification evaluation result corresponding to each target user based on all the evaluation parameters.

In a specific application, taking a plurality of evaluation parameters corresponding to the enterprise electricity utilization basic information dimensions as an example for explanation, the server may obtain the following data in the target electricity utilization data corresponding to each target user at a preconfigured obtaining time: and determining the states of all the power utilization accounts under the name of the target user and the earliest power transmission date of the meter which is not sold under the name of the target user as evaluation parameters corresponding to the power utilization basic information dimensionality of the enterprise.

In a specific application, taking a plurality of evaluation parameters corresponding to the enterprise electricity quantity information dimension as an example for explanation, the server may obtain the following data in the target electricity consumption data corresponding to each target user at a preconfigured obtaining time: and obtaining the reduction amount of the total electricity consumption of the target user in the year near based on the total electricity consumption of the target user in the year near and the total electricity consumption of the target user in the year near. And then, determining the total power consumption of the target user in the period of K months and the reduction of the total power consumption of the target user in the period of one year as evaluation parameters corresponding to the information dimension of the electric quantity of the enterprise. The K may be selected according to actual requirements, and the selection of the K is not limited in this embodiment.

In a specific application, taking a plurality of evaluation parameters corresponding to enterprise electricity fee information dimensions as an example for explanation, the server may obtain the following data in the target electricity consumption data corresponding to each target user at a preconfigured obtaining time: the average electricity consumption amount per month of the target user in the last 12 months and the monthly number of the generated electricity consumption amount of the target user in the last 12 months are determined as the evaluation parameters corresponding to the enterprise electricity charge information dimension.

In a specific application, taking a plurality of evaluation parameters corresponding to enterprise default information dimensions as an example for explanation, the server may obtain the following data in the target electricity consumption data corresponding to each target user at a preconfigured obtaining time: and determining the default times of the target user in about 24 months, the default times of the target user in about 12 months and the total real income default fund of the target user in about 24 months, and determining the default times of the target user in about 24 months, the default times of the target user in about 12 months and the total real income default fund of the target user in about 24 months as the evaluation parameters corresponding to the default information dimension of the enterprise.

In a specific application, taking an evaluation manner of the resource borrowing threshold as an example for explanation, the server may obtain the following data in the target electricity consumption data corresponding to each target user at a pre-configured obtaining time: the target users all use the electricity amount in a month in the last year, and the resource borrowing threshold value corresponding to each target user is determined based on the following formula:

resource borrowing threshold

= MIN (T times of monthly average power consumption in the last year, pre-configured initial resource borrowing threshold)

For example, the server may select a minimum value between T times of the monthly average electricity amount of the target user and a preconfigured initial resource borrowing threshold value as the resource borrowing threshold value of the target user. The multiple T and the preconfigured resource borrowing threshold value may be configured according to an actual application scenario, and specifically, different initial resource borrowing threshold values and different multiple T may be preconfigured for different target users applying for resource borrowing, where a specific configuration manner is not limited here.

In a specific application, the server may configure a data model based on an evaluation parameter corresponding to each data dimension and an evaluation mode of the resource borrowing threshold, and the obtained data model may specifically include a power data rule table as shown below:

n1 is a month number threshold of an earliest power transmission date of an un-sold electricity meter under the name of a target user from now, N2 is a month number threshold of electricity generation amount of the target user within nearly 12 months, Y1 is a monthly average electricity amount threshold of the target user, Y2 is a default amount threshold of total actual charge of the target user within nearly 24 months, M is a default number threshold of the target user within nearly 12 months, R% is a percentage threshold of the total electricity consumption of the target user within nearly one year to the total electricity consumption of the target user within nearly one year, N1, N2, Y1, Y2, M, R, and K can be configured according to an actual application scene, and the configuration of N1, N2, Y1, Y2, M, R, and K is not limited in the embodiment. The power data rule table may be specifically configured to evaluate an evaluation parameter and a resource borrowing threshold value of each data dimension corresponding to each target user, the power data rules of items 1 to 9 in the power data rule table may be used as evaluation conditions of the corresponding evaluation parameter, and the power data rule of item 10 in the power data rule table may be used to determine the resource borrowing threshold value of each target user.

In a specific application, the server can input the target electricity utilization data into the data model, perform resource borrowing parameter analysis on the target electricity utilization data based on the evaluation conditions of the power data rule table in the data model, judge whether the evaluation parameters corresponding to the target users meet the evaluation conditions, and further obtain the qualification evaluation result corresponding to each target user.

In this embodiment, by configuring the power data rule table in the data model, the qualification evaluation result and the resource borrowing threshold value corresponding to each target user can be determined, so that reference can be made when a subsequent target organization evaluates the resource borrowing data corresponding to the target user, and the resource borrowing evaluation efficiency is improved.

Specifically, the server may obtain an evaluation parameter of each data dimension corresponding to the target user based on a power data rule table in the data model, and when all the evaluation parameters corresponding to the target user satisfy the evaluation condition, the qualification evaluation result corresponding to the target user represents that the target user satisfies the resource borrowing condition.

In a specific application, the power data rule data table is taken as an example for explanation, after target electricity consumption data corresponding to each target user is input into the data model, evaluation parameters of multiple data dimensions corresponding to the target user can be obtained, and assuming that the target user meets the resource borrowing condition, the evaluation parameters corresponding to the target user will simultaneously meet the following evaluation conditions:

the states of all the electricity utilization accounts under the name of the target user are normal (account cancellation or power failure of not all accounts);

the number of the months of the earliest power transmission date of the meter without selling the household under the name of the target user is not less than N1 month;

the total electricity consumption of the target user in the last T months is more than 0;

the reduction amount of the total electricity consumption of the target user in the last year is lower than R% of the total electricity consumption of the target user in the last year;

the monthly average electricity consumption amount of the target user in the last 12 months is more than Y1 yuan;

the number of months of the electricity consumption generated by the target user in the last 12 months is not less than N2 months;

the default times of the target user in the last 24 months are not more than 3M;

the default times of the target user in the last 12 months are not more than M;

the total real estate default for the target user in the last 24 months is less than Y2-ary.

In this embodiment, the resource borrowing evaluation result of the target user is obtained through the evaluation condition in the power data rule table, and the purpose of preliminarily determining whether the target user meets the resource borrowing condition can be achieved, so that a subsequent target institution can refer to the resource borrowing evaluation data of the target user when evaluating the resource borrowing evaluation data.

The target entity may be, but is not limited to, various entities that may borrow resources from the target user. The resource borrowing evaluation result specifically may include but is not limited to: whether the target institution agrees with the resource borrowing request of the target user, and the final resource borrowing threshold set by the target institution.

Specifically, after the server pushes the resource borrowing evaluation data of the target user to the target mechanism, the server may receive a resource borrowing evaluation result returned by the target mechanism, and push the resource borrowing evaluation result to the target user, so as to remind the target user to check the resource borrowing evaluation result. The manner in which the server pushes the resource borrowing evaluation result to the target user may specifically be: real-time popup, short message, etc. The specific push mode may be configured based on an actual application scenario, and the push mode is not limited in this embodiment.

In a specific application, when the resource borrowing evaluation result returned by the target entity indicates that the target entity grants a resource borrowing request of a certain target user, the target user may initiate the target resource borrowing request within a final resource borrowing threshold value based on a final resource borrowing threshold value set by the target entity in the resource borrowing evaluation result, wherein the target resource borrowing request at least includes the number of resources borrowed by the target user. Then, the server can push a target resource borrowing request initiated by the target user to the target mechanism, and the target mechanism borrows a corresponding number of resources to the target user.

In the embodiment, the resource borrowing evaluation result of the target mechanism is pushed to the target user initiating the resource borrowing request in time, so that the target user initiating the resource borrowing request can perform the next operation according to the self requirement.

under the condition that the resource borrowing evaluation result represents the resource borrowing request of the target user granted by the target mechanism, the latest target power utilization data of the target user is regularly acquired, and the qualification evaluation result, the resource borrowing threshold value and the grading data of the target user are updated;

Specifically, under the condition that the resource borrowing evaluation result represents that the target institution grants the resource borrowing request of the target user, the server can periodically acquire the latest target electricity utilization data of the target user, update the qualification evaluation result, the resource borrowing threshold value and the grading data of the target user, and then push the updated qualification evaluation result, the updated resource borrowing threshold value and the updated grading data of the target user to the target institution. For example, the server may update the qualification evaluation result, the resource borrowing threshold value, and the classification data of the target user once every month, and push the updated qualification evaluation result, the updated resource borrowing threshold value, and the updated classification data of the target user to the target organization. In the foregoing process, a specific update period may be configured according to an actual application scenario, and the update period is not limited in this embodiment.

In a specific application, after a target organization permits a resource borrowing request of a certain target user, the server can respond to a data viewing request of the target organization, obtain a real-time qualification evaluation result, a real-time resource borrowing threshold value and real-time grading data of the target user, and push the real-time qualification evaluation result, the real-time resource borrowing threshold value and the real-time grading data of the target user to the target organization.

In this embodiment, after the target entity grants the target user resource borrowing, the latest resource borrowing evaluation data of the target user is periodically pushed to the target entity, so that the target entity can periodically monitor the resource borrowing evaluation data of the target user.

In one embodiment, when a user other than the target user initiates a resource borrowing request, the server will return an error notification because the power consumption data of the user is not stored in the data center.

In one embodiment, as shown in fig. 3, a data processing flow diagram of resource borrowing evaluation data is provided to illustrate the above method for pushing resource borrowing evaluation data.

The method comprises the steps that a service department where a server is located initiates a data use permission application to a data center, a sub-server associated with the server is developed in the data center, the data center opens data permission to the sub-server, the server can clean original power utilization data corresponding to each user in the data center through the sub-server, namely data screening, so that target power utilization data corresponding to target users are screened out, the obtained target power utilization data are input into a data model, qualification evaluation results, resource borrowing threshold values and grading data corresponding to the target users are obtained, and identification information, qualification evaluation results, resource borrowing threshold values and grading data corresponding to the target users are stored in the data center in a form of a table, so that qualification evaluation results, resource borrowing threshold values and grading data corresponding to the identification information can be obtained from the data center according to the identification information of the target users later. Wherein the server can configure the data model based on the data model rules provided by the target organization, e.g., the data dimension requirements provided by the target organization.

Furthermore, the platform where the server is located can respond to a service request of a target user, a data service interface developed by the platform is utilized, based on identification information of the target user, a qualification evaluation result, a resource borrowing threshold value and classification data corresponding to the identification information of the target user are called from the data center, namely the resource borrowing evaluation data of the target user, data processing is carried out on the resource borrowing evaluation data of the target user, the resource borrowing evaluation data of the target user are pushed to a target organization in a form of a table, the resource borrowing evaluation result returned by the target organization is received, and the resource borrowing evaluation result of the target organization is pushed to the target user.

In one embodiment, as shown in FIG. 4, another pushing method of resource borrowing evaluation data is provided. The method comprises the following steps:

step 402, obtaining original power consumption data corresponding to a plurality of users, wherein the original power consumption data at least comprises user data and settlement data of each user, screening the user data of each user, and determining a plurality of target users meeting identification conditions and settlement conditions;

step 404, determining data dimension screening conditions for screening the target electricity consumption data, and screening the original electricity consumption data corresponding to the target users according to the data dimension screening conditions to obtain the target electricity consumption data meeting the data dimension screening conditions corresponding to the target users;

step 406, determining an evaluation mode of the resource borrowing threshold, and configuring an evaluation parameter corresponding to each data dimension based on a plurality of data dimensions corresponding to the target electricity utilization data, wherein the number of the evaluation parameters corresponding to each data dimension is at least two;

step 408, configuring a data model based on the evaluation parameters corresponding to each data dimension and the evaluation mode of the resource borrowing threshold, and inputting the target electricity utilization data into the data model to perform resource borrowing parameter analysis;

step 410, obtaining evaluation parameters of a plurality of data dimensions and resource borrowing thresholds corresponding to target users, and obtaining qualification evaluation results corresponding to each target user according to the evaluation parameters of the plurality of data dimensions corresponding to the target users, wherein when the evaluation parameters corresponding to the target users all meet the evaluation conditions, the qualification evaluation results corresponding to the target users represent that the target users meet the resource borrowing conditions;

step 412, performing grading processing on the target electricity consumption data to obtain grading data corresponding to each target user;

step 414, responding to the resource borrowing request of the target user, and pushing the qualification evaluation result, the resource borrowing threshold value and the grading data corresponding to the target user to a target mechanism for processing the resource borrowing request;

step 416, receiving a resource borrowing evaluation result returned by the target mechanism, and pushing the resource borrowing evaluation result to the target user;

step 418, under the condition that the resource borrowing evaluation result represents the resource borrowing request of the target user granted by the target mechanism, regularly acquiring the latest target electricity utilization data of the target user, and updating the qualification evaluation result, the resource borrowing threshold value and the grading data of the target user;

and step 420, pushing the qualification evaluation result, the resource borrowing threshold value and the grading data updated by the target user to the target organization.

It should be understood that, although the steps in the flowcharts related to the embodiments described above are shown in sequence as indicated by the arrows, the steps are not necessarily performed in sequence as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least a part of the steps in the flowcharts related to the embodiments described above may include multiple steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, and the execution order of the steps or stages is not necessarily sequential, but may be performed alternately or alternately with other steps or at least a part of the steps or stages in other steps.

Based on the same inventive concept, the embodiment of the present application further provides a resource borrowing evaluation data pushing device for implementing the above-mentioned resource borrowing evaluation data pushing method. The implementation scheme for solving the problem provided by the apparatus is similar to the implementation scheme described in the method above, so specific limitations in the following embodiments of one or more resource borrowing evaluation data pushing apparatus may refer to the limitations on the resource borrowing evaluation data pushing method above, and details are not described here again.

In one embodiment, as shown in fig. 5, there is provided a pushing apparatus for resource borrowing evaluation data, including: an electricity data acquisition module 502, a first processing module 504, a second processing module 506, and a third processing module 508, wherein:

the power consumption data acquisition module 502 is configured to acquire target power consumption data corresponding to each of a plurality of target users;

a first processing module 504, configured to perform resource borrowing parameter analysis according to the target electricity consumption data, and obtain a qualification evaluation result and a resource borrowing threshold value that each target user corresponds to;

the second processing module 506 is configured to perform hierarchical processing on the target electricity consumption data to obtain hierarchical data corresponding to each target user;

the third processing module 508 is configured to, in response to the resource borrowing request of the target user, push the qualification evaluation result, the resource borrowing threshold value, and the classification data corresponding to the target user to a target organization that processes the resource borrowing request.

In the pushing device for the resource borrowing evaluation data, the target power consumption data corresponding to a plurality of target users are obtained, then resource borrowing parameter analysis is carried out according to the target power consumption data, the qualification evaluation result and the resource borrowing threshold value corresponding to each target user are obtained, so that a target organization can refer to the resource borrowing request of the target user when processing the resource borrowing request of the target user, then the target power consumption data are processed in a grading mode, the grading data corresponding to the target users are obtained, the target data corresponding to each target user are visual and clear, and finally the qualification evaluation result, the resource borrowing threshold value and the grading data corresponding to the target users are pushed to the target organization processing the resource borrowing request in response to the resource borrowing request of the target users. In the whole process, after the qualification evaluation result, the resource borrowing threshold value and the grading data corresponding to the target user are pushed to the target institution, the target institution can quickly judge whether the target user meets the resource borrowing condition or not based on the received resource borrowing evaluation data, quickly determine the resource borrowing threshold value of the target user, and can improve the resource borrowing evaluation efficiency of the target institution.

In one embodiment, the resource borrowing evaluation data pushing device further includes a fourth processing module, where the fourth processing module is configured to obtain original power consumption data corresponding to each of the multiple users, where the original power consumption data at least includes user data and settlement data of each user, and filter the user data of each user to determine a target user that meets the identification condition and the settlement condition, and then filter the original power consumption data corresponding to each of the target users to obtain target power consumption data corresponding to each of the target users, where the number of the target users is multiple.

In one embodiment, the resource borrowing evaluation data pushing device further includes a fifth processing module, where the fifth processing module is configured to determine a data dimension screening condition for screening target electricity consumption data, and screen, according to the data dimension screening condition, original electricity consumption data corresponding to each target user to obtain target electricity consumption data meeting the data dimension screening condition and corresponding to each target user.

In one embodiment, the resource borrowing assessment data pushing device further includes a sixth processing module, where the sixth processing module is configured to determine an assessment manner of a resource borrowing threshold, configure, based on multiple data dimensions corresponding to target power consumption data, assessment parameters corresponding to each data dimension, where the assessment parameters corresponding to each data dimension are at least two, then configure a data model based on the assessment parameters corresponding to each data dimension and the assessment manner of the resource borrowing threshold, and input the target power consumption data into the data model to perform resource borrowing parameter analysis, so as to obtain a qualification assessment result and a resource borrowing threshold corresponding to each target user.

In one embodiment, the resource borrowing evaluation data pushing device further includes a seventh processing module, where the seventh processing module is configured to obtain evaluation parameters of multiple data dimensions corresponding to the target user, and when all the evaluation parameters corresponding to the target user meet the evaluation conditions, a qualification evaluation result corresponding to the target user represents that the target user meets the resource borrowing conditions.

In one embodiment, the resource borrowing evaluation data pushing apparatus further includes an eighth processing module, where the eighth processing module is configured to receive a resource borrowing evaluation result returned by the target entity, and push the resource borrowing evaluation result to the target user.

In one embodiment, the resource borrowing evaluation data pushing device further includes a ninth processing module, where the ninth processing module is configured to, in a case that the resource borrowing evaluation result represents that the target institution grants a resource borrowing request of the target user, periodically obtain latest target electricity consumption data of the target user, update the qualification evaluation result, the resource borrowing threshold value, and the classification data of the target user, and then push the updated qualification evaluation result, the updated resource borrowing threshold value, and the classification data of the target user to the target institution.

The modules in the pushing device for resource borrowing assessment data can be wholly or partially implemented by software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.

In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as shown in fig. 6. The computer device includes a processor, a memory, an Input/Output interface (I/O for short), and a communication interface. The processor, the memory and the input/output interface are connected through a system bus, and the communication interface is connected to the system bus through the input/output interface. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operating system and the computer program to run on the non-volatile storage medium. The database of the computer device is for storing push data of the resource borrowing evaluation data. The input/output interface of the computer device is used for exchanging information between the processor and an external device. The communication interface of the computer device is used for connecting and communicating with an external terminal through a network. The computer program is executed by a processor to implement a method for pushing resource borrowing evaluation data.

Those skilled in the art will appreciate that the architecture shown in fig. 6 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.

In one embodiment, a computer device is provided, comprising a memory and a processor, the memory having stored therein a computer program, the processor implementing the steps of the above-described method embodiments when executing the computer program.

In an embodiment, a computer-readable storage medium is provided, on which a computer program is stored, which computer program, when being executed by a processor, carries out the steps of the above-mentioned method embodiments.

In an embodiment, a computer program product is provided, comprising a computer program which, when being executed by a processor, carries out the steps of the above-mentioned method embodiments.

It should be noted that, the user information (including but not limited to user equipment information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) referred to in the present application are information and data authorized by the user or sufficiently authorized by each party, and the collection, use and processing of the related data need to comply with the relevant laws and regulations and standards of the relevant country and region.

It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, database, or other medium used in the embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high-density embedded nonvolatile Memory, resistive Random Access Memory (ReRAM), magnetic Random Access Memory (MRAM), ferroelectric Random Access Memory (FRAM), phase Change Memory (PCM), graphene Memory, and the like. Volatile Memory can include Random Access Memory (RAM), external cache Memory, and the like. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM), for example. The databases referred to in various embodiments provided herein may include at least one of relational and non-relational databases. The non-relational database may include, but is not limited to, a block chain based distributed database, and the like. The processors referred to in the various embodiments provided herein may be, without limitation, general purpose processors, central processing units, graphics processors, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, or the like.

The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.

The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is specific and detailed, but not construed as limiting the scope of the present application. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present application should be subject to the appended claims.

Claims

1. A method for pushing resource borrowing evaluation data, the method comprising:

performing resource borrowing parameter analysis according to the target electricity utilization data to obtain a qualification evaluation result and a resource borrowing threshold value corresponding to each target user;

carrying out grading processing on the target electricity utilization data to obtain grading data corresponding to the target users respectively;

responding to the resource borrowing request of the target user, and pushing the qualification evaluation result, the resource borrowing threshold value and the grading data corresponding to the target user to a target mechanism for processing the resource borrowing request.

2. The method of claim 1, wherein obtaining target electricity consumption data corresponding to each of a plurality of target users comprises:

screening the user data and settlement data of each user, and determining a plurality of target users meeting the identification condition and the settlement condition;

3. The method according to claim 2, wherein the screening of the original power consumption data corresponding to each of the target users to obtain the target power consumption data corresponding to each of the target users comprises:

4. The method according to claim 1, wherein the performing resource borrowing parameter analysis according to the target electricity consumption data to obtain a qualification evaluation result and a resource borrowing threshold value corresponding to each target user comprises:

determining an evaluation mode of the resource borrowing threshold, and configuring an evaluation parameter corresponding to each data dimension based on a plurality of data dimensions corresponding to the target electricity utilization data, wherein the number of the evaluation parameters corresponding to each data dimension is at least two;

configuring a data model based on the evaluation parameters corresponding to each data dimension and the evaluation mode of the resource borrowing threshold;

the analyzing resource borrowing parameters according to the target electricity utilization data to obtain the qualification evaluation result and the resource borrowing threshold value corresponding to each target user comprises the following steps:

and inputting the target electricity utilization data into the data model to perform resource borrowing parameter analysis, and obtaining a qualification evaluation result and a resource borrowing threshold value which are respectively corresponding to each target user.

5. The method according to claim 4, wherein the inputting the target electricity consumption data into the data model for resource borrowing parameter analysis, and the obtaining of the qualification evaluation result corresponding to each target user comprises:

obtaining evaluation parameters of a plurality of data dimensions corresponding to the target user;

6. The method according to claim 1, wherein the pushing the qualification evaluation result, the resource borrowing threshold value and the ranking data corresponding to the target user to the target organization processing the resource borrowing request in response to the resource borrowing request of the target user further comprises:

7. The method according to claim 6, wherein after receiving the resource borrowing assessment result returned by the target organization and pushing the resource borrowing assessment result to the target user, further comprising:

under the condition that the resource borrowing evaluation result represents that the target mechanism permits the resource borrowing request of the target user, regularly acquiring the latest target electricity utilization data of the target user, and updating the qualification evaluation result, the resource borrowing threshold and the grading data of the target user;

8. A pushing apparatus of resource borrowing evaluation data, the apparatus comprising:

the second processing module is used for carrying out grading processing on the target electricity utilization data to obtain grading data corresponding to the target users;

and the third processing module is used for responding to the resource borrowing request of the target user, and pushing the qualification evaluation result, the resource borrowing threshold value and the grading data corresponding to the target user to a target mechanism for processing the resource borrowing request.

9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of the method of any of claims 1 to 7.

10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 7.