Replacement resource application method and device, equipment, storage medium and program product

Abstract

The invention discloses a replacement resource application method and device, equipment, a storage medium and a program product, and is applied to the field of big data processing.The method comprises the steps that an application request of replacement resources is obtained, and target information of a user associated with the application request is obtained; determining an initial feature according to each piece of sub-data of the target information, and constructing a plurality of derivative features according to each initial feature; according to the evaluation model, each initial feature and each derivative feature, determining a repayment risk level corresponding to the user; determining a first quota of replacement resources applied by the user according to the application request, and determining a second quota matched with the repayment risk level; and in response to the fact that the first quota is smaller than or equal to the second quota, configuring an account corresponding to the replacement resource for the user, adjusting the use quota of the account to the first quota, and outputting login information of the account. In the application, the auditing precision of the quota application of the replacement resource is improved.

Description

Technical Field

[0001] The present application belongs to the field of big data processing technology, and in particular, relates to a replacement resource application method, device, equipment, storage medium and program product. Background Art

[0002] As people's consumption concepts change, more and more users are exchanging resources with financial institutions and using the exchanged resources for consumption.

[0003] Currently, when a user applies for resource replacement, the user's application will be approved, and the user will not be configured with the required amount of replacement resources.

[0004] However, when the amount of replacement resources applied by the user is too large, it becomes difficult for the user to repay, resulting in the user defaulting on repayment. Therefore, it can be seen that the existing method of applying for the amount of replacement resources has the problem of low accuracy of the audit method. Summary of the invention

[0005] The embodiments of the present application provide a replacement resource application method, apparatus, device, storage medium and program product, which are used to solve the problem of low audit accuracy in the existing replacement resource quota application method.

[0006] In a first aspect, an embodiment of the present application provides a replacement resource application method, including:

[0007] Obtaining an application request for replacing resources, and obtaining first target information of a first user associated with the application request, wherein the first target information includes asset information, repayment information, and borrowing information of the first user;

[0008] Determining a first initial feature according to each sub-data of the first target information, and constructing a plurality of first derived features according to each of the first initial features, wherein each sub-data of the first target information includes asset information, repayment information, and borrowing information of the first user;

[0009] Determining a repayment risk level corresponding to the first user according to the evaluation model, each of the first initial features, and each of the first derived features;

[0010] Determining a first amount of replacement resources applied for by the first user according to the application request, and determining a second amount matching the repayment risk level;

[0011] In response to the first quota being less than or equal to the second quota, a first account corresponding to the replacement resource is configured for the first user, the usage quota of the first account is adjusted to the first quota, and login information of the first account is output.

[0012] In some possible implementations, after the step of determining the second amount matching the repayment risk level, the step further includes:

[0013] In response to the first amount being greater than the second amount, determining a target amount according to the second amount, the target amount being less than or equal to the second amount;

[0014] Outputting a quota adjustment message for replacing resources to a terminal device associated with the first user according to the target quota;

[0015] In response to receiving consent information fed back by the terminal device based on the quota adjustment message, configuring a second account corresponding to the replacement resource for the first user, and adjusting the usage quota of the second account to the target quota;

[0016] The login information of the second account is output.

[0017] In some possible implementations, before the step of determining the repayment risk level corresponding to the first user according to the evaluation model, each of the first initial features, and each of the first derived features, the step further includes:

[0018] Acquire multiple training samples, the training samples including second target information and a label of the second user, the label is used to indicate the repayment risk level of the second user for resource replacement, the second target information including asset information, repayment information, and borrowing information of the second user;

[0019] The preset model is trained according to each of the training samples to obtain the evaluation model.

[0020] In some possible implementations, the step of obtaining a plurality of training samples includes:

[0021] Acquire second target information of the second user;

[0022] Determining a label corresponding to the second target information;

[0023] The training sample is constructed according to the second target information and the label.

[0024] In some possible implementations, the step of constructing the training sample according to the second target information and the label includes:

[0025] determining a second initial feature according to each sub-data of the second target information, wherein each sub-data of the second target information includes asset information, repayment information, and borrowing information of the second user;

[0026] constructing a plurality of second derived features according to each of the second initial features;

[0027] The training samples are constructed according to each of the second initial features, each of the second derived features, and the label.

[0028] In some possible implementations, the preset model is a random forest model.

[0029] In some possible implementations, the step of obtaining the first target information of the first user associated with the application request includes:

[0030] Output the application interface for replacement resources;

[0031] The first target information input by the first user is obtained based on the application interface.

[0032] In a second aspect, an embodiment of the present application provides a replacement resource application device, including:

[0033] An acquisition module, used to acquire an application request for replacing resources, and acquire first target information of a first user associated with the application request, wherein the first target information includes asset information, repayment information, and borrowing information of the first user;

[0034] a first determination module, configured to determine a first initial feature according to each sub-data of the first target information, and construct a plurality of first derived features according to each of the first initial features, wherein each sub-data of the first target information includes asset information, repayment information, and borrowing information of the first user;

[0035] A second determination module, configured to determine a repayment risk level corresponding to the first user according to an evaluation model, each of the first initial features, and each of the first derived features;

[0036] A third determination module is used to determine a first amount of replacement resources applied for by the first user according to the application request, and determine a second amount matching the repayment risk level;

[0037] A configuration module is used to configure a first account corresponding to the replacement resource for the first user in response to the first quota being less than or equal to the second quota, adjust the usage quota of the first account to the first quota, and output login information of the first account.

[0038] In a third aspect, an embodiment of the present application provides a replacement resource application device, the device comprising: a processor and a memory storing computer program instructions; when the processor executes the computer program instructions, the replacement resource application method as described above is implemented.

[0039] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, characterized in that computer program instructions are stored on the computer-readable storage medium, and when the computer program instructions are executed by a processor, the above-mentioned replacement resource application method is implemented.

[0040] In a fifth aspect, an embodiment of the present application provides a computer program product. When instructions in the computer program product are executed by a processor of an electronic device, the electronic device is enabled to execute the resource replacement application method as described above.

[0041] The replacement resource application method, device, equipment, storage medium and program product of the embodiment of the present application obtain the application request for replacement resources and the target information of the user associated with the application request, obtain multiple initial features through the target information, and construct derived features based on the initial features, and determine the repayment risk level of the user based on the initial features, the derived features and the evaluation model, determine the first amount of the user's application for replacement resources based on the application request, and determine the second amount matching the repayment risk level, when the first amount is less than or equal to the second amount, configure the account of the replacement resource for the user, adjust the usage amount of the account to the first amount, and then output the login information of the account. In the present application, the repayment risk level of the user's replacement resources is determined by the user's asset information, loan information and repayment information, so that the usage amount of the replacement resources that the user can use is configured to be lower than the amount under the repayment risk level, so as to avoid the user defaulting on repayment due to configuring too large an amount for the user, thereby improving the audit accuracy of the quota application for replacement resources. In addition, the construction of derived features through the initial features obtained from the target information can improve the accuracy of determining the repayment risk level. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the technical solution of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0043] Figure 1 It is a schematic diagram of the scenario involved in the resource replacement application method of this application;

[0044] Figure 2 It is a flowchart of the first embodiment of the resource replacement application method of the present application;

[0045] Figure 3 It is a flowchart of the second embodiment of the resource replacement application method of the present application;

[0046] Figure 4 It is a flowchart of the third embodiment of the resource replacement application method of the present application;

[0047] Figure 5 is a flowchart of a fourth embodiment of the resource replacement application method of the present application;

[0048] Figure 6 It is a functional module diagram of the resource replacement application device of the present application;

[0049] Figure 7 It is a structural diagram of the resource replacement application device of this application. DETAILED DESCRIPTION

[0050] The features and exemplary embodiments of various aspects of the present application will be described in detail below. In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain the present application, rather than to limit the present application. For those skilled in the art, the present application can be implemented without the need for some of these specific details. The following description of the embodiments is only to provide a better understanding of the present application by illustrating the examples of the present application.

[0051] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article 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, article or device. In the absence of further restrictions, the elements defined by the statement "include..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0052] It should be noted that the acquisition, storage, use and processing of data in the embodiments of the present application are in compliance with the relevant provisions of national laws and regulations.

[0053] It should be noted that in the embodiments of the present application, certain software, components, models and other existing solutions in the industry may be mentioned, and they should be regarded as exemplary. Their purpose is only to illustrate the feasibility of implementing the technical solution of the present application, but it does not mean that the applicant has or will necessarily use the solution.

[0054] As people's consumption concepts change, more and more users are exchanging resources with financial institutions and using the exchanged resources for consumption.

[0055] Currently, when a user applies for resource replacement, the user's application will be approved, and the user will not be configured with the required amount of replacement resources.

[0056] The inventor of the present application found that when the amount of replacement resources applied by the user is too large, it is difficult for the user to repay the loan, resulting in the user defaulting on the repayment. Therefore, it can be seen that the existing method of applying for the amount of replacement resources has the problem of low accuracy of the review method.

[0057] The inventor of the present application therefore came up with the idea of ​​determining the repayment risk level of a user's replacement resources through the user's asset information, loan information, repayment information and other information, thereby configuring the usage limit of the replacement resources available to the user to be lower than the limit under the repayment risk level, thereby avoiding configuring an excessively large limit for the user, which may cause the user to default on repayment, and improving the review accuracy of the application for the limit of replacement resources.

[0058] Reference Figure 1 , Figure 1 This is a schematic diagram of the scenario of the resource application method for this application. Figure 1 , the user 100 can send an application request for replacement resources to the replacement resource application device 300 through the terminal device 200, so that the replacement resource application device 300 obtains the application request for replacement resources. The replacement resource application device 300 obtains target information including the asset information, repayment information and borrowing information of the user 100. An evaluation model (not shown) is provided in the replacement resource application device 300, and the replacement resource application device 300 inputs the target information into the evaluation model, and the evaluation model outputs the repayment risk level. The replacement resource application device 300 determines the first amount of replacement resources applied for by the user 100 based on the application request, and determines the second amount that matches the repayment risk level. If the first amount is less than or equal to the second amount, a replacement resource account is configured for the user 100, and the usage amount of the account is adjusted to the first amount, and the login information of the account is sent to the terminal device 200.

[0059] The following combination Figure 1 , the resource replacement application method of this application is described in detail.

[0060] Reference Figure 2 , Figure 2 FIG. 2 is a flow chart of a first embodiment of a resource replacement application method of the present invention. The resource replacement application method includes:

[0061] Step S201, obtaining an application request for replacing resources, and obtaining first target information of a first user associated with the application request, wherein the first target information includes asset information, repayment information, and borrowing information of the first user.

[0062] In this embodiment, the execution subject is a replacement resource application device. For the sake of convenience, the device is used below to refer to the replacement resource application device. The device can be a server or any terminal device with the replacement resource application function. The replacement resource refers to the resource that the user replaces with his own assets. The assets include invisible assets and physical assets. Invisible assets are, for example, the user's credit, physical assets are, for example, the user's house, and resources are, for example, digital currency.

[0063] When a user needs to apply for a replacement resource, he can send an application request to the device. The application request carries the type and amount of the replacement resource that the user needs to apply for, and the amount is defined as the first amount. There are many types of replacement resources, for example, commercial replacement resources that use credit as an asset for resource replacement, and civil replacement resources that use housing savings for resource replacement.

[0064] After obtaining the application request, the device parses the application request to obtain the user identifier corresponding to the user, and the user is defined as the first user. The device stores the associated information of the user identifier, and the associated information includes but is not limited to the user's asset information, repayment information, and loan information. The associated information is defined as the first target information.

[0065] Step S202, determining a first initial feature according to each sub-data of the first target information, and constructing a plurality of first derived features according to each first initial feature, wherein each sub-data of the first target information includes asset information, repayment information and loan information of the first user.

[0066] The device extracts each sub-data in the first target information, and each sub-data includes the asset information, repayment information and loan information of the first user. Each sub-data is characterized to obtain the first initial feature. After obtaining each first initial feature, the device constructs multiple first derivative features based on each first initial feature, and then constructs a training sample based on each first initial feature, each first derivative feature and a label, that is, a feature vector is generated based on the first initial feature and the first derivative feature, and the feature vector and the label constitute a training sample. Exemplarily, if the sub-data is repayment information, then the first initial feature is the feature corresponding to the repayment information, and the credit feature can be derived based on the first initial feature. The credit feature is the first derivative feature. For example, the number of overdue times is extracted from the repayment information as the first initial feature, and the credit score is determined by the number of overdue times. The more overdue times, the smaller the credit score, and the credit score is used as the first derivative feature.

[0067] Step S203: determining the repayment risk level corresponding to the first user according to the evaluation model, each first initial feature and each first derived feature.

[0068] An evaluation model is provided in the device, and the device determines the repayment risk level of the first user through the evaluation model, each first initial feature, and each first derived feature. Specifically, the device constructs each first initial feature and each first derived feature into a feature vector, and then inputs the feature vector into the evaluation model to obtain the repayment risk level of the first user after replacing resources output by the evaluation model, and the repayment risk level is equivalent to the probability value of overdue repayment after the first user replaces resources.

[0069] Step S204: determining a first amount of replacement resources applied for by the first user according to the application request, and determining a second amount that matches the repayment risk level.

[0070] The device can obtain the first amount of the replacement resource applied by the first user based on the application request, and determine the amount that matches the repayment risk level, and the amount that matches the repayment risk level is defined as the second amount. Exemplarily, the higher the repayment risk level, the greater the probability value of the first user's overdue repayment, so the higher the repayment risk level, the smaller the maximum amount that the first user can apply for. The device determines the maximum amount mapped by the repayment risk level based on the mapping relationship between the repayment risk level and the amount, and determines the second amount based on the maximum amount. In one example, the maximum amount can be determined as the second amount. In another example, the device determines the amount of money required to be repaid each overdue based on the repayment information of the first user, thereby determining the number of overdue times for the same amount of money, and the device selects the amount of money close to the maximum amount as the target amount of money. If the ratio of the number of overdue times of the target amount of money to the preset number of times is greater than the threshold, the maximum amount is reduced to obtain the second amount of money, and the amount of money close to the maximum amount refers to: the amount of money whose difference with the maximum amount is less than the preset difference.

[0071] Step S205, in response to the first quota being less than or equal to the second quota, configuring a first account corresponding to the replacement resource for the first user, adjusting the usage quota of the first account to the first quota, and outputting login information of the first account.

[0072] After determining the first amount and the second amount, the device determines whether the first amount is less than or equal to the second amount. If the first amount is less than or equal to the second amount, it can be determined that the default repayment risk faced by the amount of replacement resources applied by the first user is acceptable, so the device configures a first account for the first user, adjusts the usage amount of replacement resources of the first account to the first amount, and outputs the login information of the first account, so that the first user logs in to the first account based on the login information to use the replacement resources.

[0073] In this embodiment, the application request for replacement resources and the target information of the user associated with the application request are obtained, multiple initial features are obtained through the target information, and derived features are constructed based on the initial features, and the repayment risk level of the user is determined based on the initial features, the derived features and the evaluation model, the first amount of the user's application for replacement resources is determined based on the application request, and the second amount matching the repayment risk level is determined. When the first amount is less than or equal to the second amount, the account of the replacement resource is configured for the user, the usage amount of the account is adjusted to the first amount, and then the login information of the account is output. In this embodiment, the repayment risk level of the user's replacement resources is determined by the user's asset information, loan information, repayment information and other information, so that the usage amount of the replacement resources that the user can use is configured to be lower than the amount under the repayment risk level, so as to avoid the user defaulting on repayment due to the configuration of too large an amount for the user, thereby improving the audit accuracy of the quota application for replacement resources. In addition, the construction of derived features through the initial features obtained from the target information can improve the accuracy of determining the repayment risk level.

[0074] Reference Figure 3 , Figure 3 This is a flow chart of a second embodiment of the resource replacement application method of the present application. Based on the first embodiment, step S204 includes step S2041, and step S2041 includes:

[0075] Step S2041, determining the first amount of the replacement resource applied for by the first user according to the application request, and determining the second amount matching the repayment risk level, and determining whether the first amount is less than or equal to the second amount. After step S2041, it also includes:

[0076] Step S301: In response to a first credit limit being greater than a second credit limit, a target credit limit is determined according to the second credit limit, and the target credit limit is less than or equal to the second credit limit.

[0077] In this embodiment, when the first credit limit is greater than the second credit limit, the device needs to adjust the credit limit applied by the first user. To this end, the device determines a target credit limit based on the second credit limit, and the target credit limit is less than or equal to the second credit limit, that is, a credit limit less than the second credit limit is set as the target credit limit.

[0078] Step S302: Outputting a quota adjustment message for replacing resources to a terminal device associated with the first user according to the target quota.

[0079] Step S303: in response to the consent information fed back by the receiving terminal device based on the quota adjustment message, a second account corresponding to the replacement resource is configured for the first user, and the usage quota of the second account is adjusted to the target quota.

[0080] Step S304: output the login information of the second account.

[0081] After determining the target credit limit, the device generates a credit limit adjustment message based on the target credit limit. The credit limit adjustment message is, for example, "The current applied credit limit is too large, and it is recommended to adjust the credit limit to the target credit limit."

[0082] After generating a credit limit adjustment message, the device sends the credit limit adjustment message to the terminal device. After receiving the credit limit adjustment message, the terminal device displays the credit limit adjustment message. If the terminal device detects that the user has made an operation to agree to the credit limit adjustment, the terminal device sends a consent message to the device, that is, the device receives the consent information fed back by the terminal device based on the credit limit adjustment message. When the device receives the consent information, it configures a second account corresponding to the replacement resource for the first user, and adjusts the usage limit of the second account to the target limit. The device then outputs the login information of the second account, so that the user can log in to the second account based on the login information to use the replacement resource.

[0083] In this embodiment, when the first credit limit is greater than the second credit limit, credit limit adjustment information is fed back to the user so that the user can reduce the credit limit applied for, ensuring that the user can successfully apply for resource replacement and that the risk of default repayment after the user replaces resources is not too high.

[0084] Reference Figure 4 , Figure 4 This is a flowchart of a third embodiment of the resource replacement application method of the present application, based on the first or second embodiment, before step S201, further comprising:

[0085] Step S401, obtaining multiple training samples, the training samples include second target information and a label of the second user, the label is used to indicate the repayment risk level of the second user for resource replacement, and the second target information includes the asset information, repayment information and borrowing information of the second user.

[0086] In this embodiment, the device obtains multiple training samples, each training sample includes a second user's second target information and a label, the label refers to the repayment risk level of the second user for resource replacement, and the second target information includes the second user's asset information, repayment information and loan information.

[0087] Step S402: training the preset model according to each training sample to obtain an evaluation model.

[0088] After obtaining each training sample, the device trains the preset model based on the training sample to obtain an evaluation model.

[0089] It should be noted that the preset model is a random forest model, which is also the evaluation model business random forest model. The reasons for using the random forest model are as follows:

[0090] The generalization ability of the random dark green model is higher: the random forest is set with multiple decision trees. It improves the generalization ability of the model by constructing multiple decision trees and combining their prediction results. This integrated learning strategy can usually reduce overfitting and improve prediction accuracy.

[0091] Importance of feature selection: Random forest algorithm can evaluate the importance of each feature in prediction, which is very helpful for selecting relevant features, understanding data, and optimizing models. In the prediction of replacement resource related data, selecting appropriate features is the key to improving prediction accuracy.

[0092] Ability to handle nonlinear relationships: The random forest model can handle nonlinear relationships in the data, which enables it to cope with complex prediction problems. The data related to resource replacement may be affected by multiple factors, and the relationship between these factors may not be linear, so it is suitable for predicting such complex problems.

[0093] High robustness: The random forest model is robust to noise and outliers, which helps reduce the impact of data quality issues on prediction results.

[0094] Easy to parallelize: The decision trees used to build the random forest are independent of each other, which makes the model easy to parallelize and can effectively utilize multi-core processors to increase training speed.

[0095] Comparison of the advantages of random forest model with other models:

[0096] Compared with traditional linear regression: Traditional linear regression models assume that there is a linear relationship between independent variables and dependent variables, which may be limited when dealing with complex nonlinear relationships. The random forest model does not have such limitations and can handle a wider range of data types and relationships.

[0097] Compared with decision trees: a single decision tree may be susceptible to overfitting, while random forests can reduce the risk of overfitting by integrating the results of multiple decision trees. In addition, random forests can also evaluate the importance of features and provide more information to help understand the data.

[0098] Automated feature selection: Compared with some traditional methods that require manual feature selection, random forests can automatically evaluate the importance of each feature, reducing the need for human intervention and making the model more objective and accurate.

[0099] In summary, the use of random forest models to predict replacement resource-related data has higher prediction accuracy, stronger ability to handle complex relationships, and more advantages than traditional data analysis methods, which makes the random forest model a powerful tool for predicting replacement resource-related data.

[0100] In this embodiment, the evaluation model constructed by the random forest model can help predict the repayment default risk after replacing resources. The repayment default risk can be used to screen out better users, which helps to reduce the repayment default rate and reduce the loss of replacement resources.

[0101] Reference Figure 5 , Figure 5 This is a flow chart of a fourth embodiment of the resource replacement application method of the present application. Based on the third embodiment, step S401 includes:

[0102] Step S501, obtaining second target information of a second user.

[0103] Step S502: determine the tag corresponding to the second target information.

[0104] Step S503: construct training samples according to the second target information and the label.

[0105] In this embodiment, the device obtains the second target information of the second user. The second user is a user who has completed the application for replacement resources, and the second user has stored asset information, repayment information and loan information in the device. Asset information includes but is not limited to the user's real estate, cash amount, virtual assets, etc., loan information includes but is not limited to the replacement resources that the user has completed the application for, the amount and type of the replacement resources that have been applied for, etc., and repayment information includes but is not limited to the repayment amount and repayment date of the used amount of the replacement resources. In addition, the second target information may also include the personal information of the second user, such as the user's age, occupation, income, etc. Of course, the first target information may also include the personal information of the first user.

[0106] After obtaining the second target information, the device determines a label corresponding to the second target information. The label is configured based on the second user's current repayment information. For example, the number of overdue repayments of the second user is determined based on the repayment information. The more overdue repayments, the higher the repayment risk level indicated by the label.

[0107] After determining the label, the device can construct a training sample based on the second target information and the label.

[0108] In one example, the device extracts each sub-data in the second target information, each sub-data including the asset information, repayment information and loan information of the second user. Each sub-data is characterized to obtain a second initial feature, thereby constructing a feature vector based on each second initial feature, and the feature vector and the label can constitute a training sample.

[0109] In another example, after obtaining each second initial feature, the device constructs multiple second derived features based on each second initial feature, and then constructs a training sample based on each second initial feature, each second derived feature and a label, that is, a feature vector is generated based on the second initial feature and the second derived feature, and the feature vector and the label constitute a training sample. Exemplarily, if the sub-data is repayment information, then the second initial feature is the feature corresponding to the repayment information, and the credit feature can be derived based on the second initial feature, and the credit feature is the second derived feature. For example, the number of overdue times is extracted from the repayment information as the second initial feature, and the credit score is determined by the number of overdue times, and the more overdue times, the smaller the credit score, and the credit score is used as the second derived feature.

[0110] It should be noted that after obtaining each training sample, each training sample is divided into a training set and a test set. The training samples in the training set are used to train the preset model, and the training samples in the test set are used to test the trained model. If the performance of the model is higher than the threshold, the model is used as an evaluation model. The performance of the model that needs to be tested includes at least one of accuracy, recall, mean square error and F1 value. Accuracy refers to the proportion of correct predictions made by the model; recall refers to the proportion of positive examples that are actually positive and predicted as positive by the model; F1 value: an indicator that comprehensively considers accuracy and recall; mean square error: the average error between the predicted value and the actual value, used to evaluate the accuracy of the prediction.

[0111] In this embodiment, the device obtains the second target information of the second user, and then determines the label corresponding to the second target information, thereby constructing a training sample based on the label and the second target information.

[0112] In one embodiment, the device may set a visual page interaction. Specifically, the device outputs an application interface for replacing resources, and the first user may input his / her first target information on the application interface, and the device will check the first target information. If the first target information is checked correctly, the device will obtain the first target information input by the first user from the application interface.

[0113] Furthermore, a plurality of types of evaluation models are provided in the device. The type of evaluation model selected by the first user will cause the type of replacement resource applied for by the first user to be consistent with the type of evaluation model. For example, if the first user selects a civilian type evaluation model in the model selection interface of the device, it can be determined that the type of replacement resource applied for by the user is also civilian type. After the device acquires the first target information, the device outputs a model selection interface. If a model selection operation based on the model selection interface is detected, the first target information is input into the evaluation model selected by the model selection operation. In this way, the type of replacement resource is unified with the model of the model, thereby preventing the user from selecting the wrong evaluation model to apply for the wrong type of replacement resource.

[0114] See also Figure 6 The replacement resource application device 600 provided in the embodiment of the present application includes:

[0115] The acquisition module 610 is used to acquire an application request for replacing resources, and acquire first target information of a first user associated with the application request, wherein the first target information includes asset information, repayment information, and loan information of the first user;

[0116] A first determination module 620 is used to determine a first initial feature according to each sub-data of the first target information, and to construct a plurality of first derived features according to each first initial feature, wherein each sub-data of the first target information includes asset information, repayment information, and loan information of the first user;

[0117] A second determination module 630, configured to determine a repayment risk level corresponding to the first user according to the evaluation model, each first initial feature, and each first derived feature;

[0118] The third determination module 640 is used to determine the first amount of replacement resources applied for by the first user according to the application request, and determine the second amount matching the repayment risk level;

[0119] The configuration module 650 is used to configure a first account corresponding to the replacement resource for the first user in response to the first quota being less than or equal to the second quota, adjust the usage quota of the first account to the first quota, and output login information of the first account.

[0120] In one embodiment, the replacement resource application device 600 is specifically used for:

[0121] In response to the first amount being greater than the second amount, determining a target amount according to the second amount, the target amount being less than or equal to the second amount;

[0122] Outputting a quota adjustment message for replacing resources to a terminal device associated with the first user according to the target quota;

[0123] In response to the consent information fed back by the receiving terminal device based on the quota adjustment message, configuring a second account corresponding to the replacement resource for the first user, and adjusting the usage quota of the second account to the target quota;

[0124] Output the login information of the second account.

[0125] In one embodiment, the replacement resource application device 600 is specifically used for:

[0126] Acquire multiple training samples, the training samples include second target information of the second user and a label, the label is used to indicate the repayment risk level of the second user for resource replacement, and the second target information includes asset information, repayment information, and borrowing information of the second user;

[0127] The preset model is trained according to each training sample to obtain an evaluation model.

[0128] In one embodiment, the replacement resource application device 600 is specifically used for:

[0129] Acquire second target information of a second user;

[0130] Determine a label corresponding to the second target information;

[0131] Construct training samples based on the second target information and labels.

[0132] In one embodiment, the replacement resource application device 600 is specifically used for:

[0133] Determine the second initial feature according to each sub-data of the second target information, wherein each sub-data of the second target information includes asset information, repayment information, and borrowing information of the second user;

[0134] constructing a plurality of second derived features according to each second initial feature;

[0135] A training sample is constructed according to each second initial feature, each second derived feature and a label.

[0136] In one embodiment, the preset model is a random forest model.

[0137] In one embodiment, the replacement resource application device 600 is specifically used for:

[0138] Output the application interface for replacement resources;

[0139] The first target information input by the first user is obtained based on the application interface.

[0140] Each module of the replacement resource application device provided in the embodiment of the present application can realize Figures 2 to 5Any of the embodiments provides the functions of each step of the resource replacement application method and can achieve its corresponding technical effects. For the sake of concise description, they will not be repeated here.

[0141] Figure 7 A schematic diagram of the hardware structure of a replacement resource application device provided in an embodiment of the present application is shown.

[0142] The replacement resource application device may include a processor 701 and a memory 702 storing computer program instructions.

[0143] Specifically, the processor 701 may include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiments of the present application.

[0144] The memory 702 may include a large capacity memory for data or instructions. By way of example and not limitation, the memory 702 may include a hard disk drive (HDD), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (USB) drive or a combination of two or more of these. In appropriate cases, the memory 702 may include a removable or non-removable (or fixed) medium. In appropriate cases, the memory 702 may be inside or outside the integrated gateway disaster recovery device. In a specific embodiment, the memory 702 is a non-volatile solid-state memory.

[0145] In certain embodiments, the memory 702 may include a read-only memory (ROM), a random access memory (RAM), a magnetic disk storage media device, an optical storage media device, a flash memory device, an electrical, optical or other physical / tangible memory storage device. Thus, in general, the memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., a memory device) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the method according to an aspect of the present disclosure.

[0146] The processor 701 implements any one of the authentication methods in the above embodiments by reading and executing computer program instructions stored in the memory 702 .

[0147] In one example, the replacement resource application device may further include a communication interface 703 and a bus 710. Figure 7 As shown, the processor 701, the memory 702, and the communication interface 703 are connected via a bus 710 and communicate with each other.

[0148] The communication interface 703 is mainly used to implement communication between various modules, devices, units and / or equipment in the embodiments of the present application.

[0149] Bus 710 includes hardware, software or both, and the parts of online data flow billing equipment are coupled to each other. For example, but not limitation, bus may include accelerated graphics port (AGP) or other graphics bus, enhanced industrial standard architecture (EISA) bus, front-end bus (FSB), hypertransport (HT) interconnection, industrial standard architecture (ISA) bus, infinite bandwidth interconnection, low pin count (LPC) bus, memory bus, micro channel architecture (MCA) bus, peripheral component interconnection (PCI) bus, PCI-Express (PCI-X) bus, serial advanced technology attachment (SATA) bus, video electronics standard association local (VLB) bus or other suitable bus or two or more of these combinations. In appropriate cases, bus 710 may include one or more buses. Although the present application embodiment describes and shows a specific bus, the present application considers any suitable bus or interconnection.

[0150] The data transmission method in the above embodiment can be implemented by providing a computer storage medium in the present application embodiment. The computer storage medium stores computer program instructions; when the computer program instructions are executed by a processor, any one of the data transmission methods in the above embodiment is implemented.

[0151] An embodiment of the present application further provides a computer program product, including a computer program, which implements any one of the data transmission methods in the above embodiments when the computer program is processed and executed.

[0152] It should also be noted that the exemplary embodiments mentioned in this application describe some methods or systems based on a series of steps or devices. However, this application is not limited to the order of the above steps, that is, the steps can be performed in the order mentioned in the embodiment, or in a different order from the embodiment, or several steps can be performed simultaneously.

[0153] The above reference is to the flowchart and / or block diagram of the method, device (system) and computer program product according to the embodiment of the present disclosure. It should be understood that each box in the flowchart and / or block diagram and the combination of each box 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, or other programmable permutation resource application device to produce a machine so that these instructions executed by the processor of the computer or other programmable permutation resource application device enable the implementation of the function / action specified in one or more boxes of the flowchart and / or block diagram. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field programmable logic circuit. It can also be understood that each box in the block diagram and / or flowchart and the combination of boxes in the block diagram and / or flowchart can also be implemented by dedicated hardware that performs a specified function or action, or can be implemented by a combination of dedicated hardware and computer instructions.

[0154] The above are only specific implementation methods of the present application. Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working processes of the systems, modules and units described above can refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here. It should be understood that the protection scope of the present application is not limited to this. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed in this application, and these modifications or replacements should be included in the protection scope of this application.

Claims

1. A method for applying for replacement resources, characterized in that: include: Obtaining an application request for replacing resources, and obtaining first target information of a first user associated with the application request, wherein the first target information includes asset information, repayment information, and borrowing information of the first user; Determining a first initial feature according to each sub-data of the first target information, and constructing a plurality of first derived features according to each of the first initial features, wherein each sub-data of the first target information includes asset information, repayment information, and borrowing information of the first user; Determining a repayment risk level corresponding to the first user according to the evaluation model, each of the first initial features, and each of the first derived features; Determining a first amount of replacement resources applied for by the first user according to the application request, and determining a second amount matching the repayment risk level; In response to the first quota being less than or equal to the second quota, a first account corresponding to the replacement resource is configured for the first user, the usage quota of the first account is adjusted to the first quota, and login information of the first account is output.

2. The method for applying for replacement resources according to claim 1, characterized in that: After the step of determining the second amount matching the repayment risk level, the method further includes: In response to the first amount being greater than the second amount, determining a target amount according to the second amount, the target amount being less than or equal to the second amount; Outputting a quota adjustment message for replacing resources to a terminal device associated with the first user according to the target quota; In response to receiving consent information fed back by the terminal device based on the quota adjustment message, configuring a second account corresponding to the replacement resource for the first user, and adjusting the usage quota of the second account to the target quota; The login information of the second account is output.

3. The method for applying for replacement resources according to claim 1, characterized in that: Before the step of determining the repayment risk level corresponding to the first user according to the evaluation model, each of the first initial features and each of the first derived features, the step further includes: Acquire multiple training samples, the training samples including second target information and a label of the second user, the label is used to indicate the repayment risk level of the second user for resource replacement, the second target information including asset information, repayment information, and borrowing information of the second user; The preset model is trained according to each of the training samples to obtain the evaluation model.

4. The resource replacement application method according to claim 3, characterized in that: The step of obtaining a plurality of training samples comprises: Acquire second target information of the second user; Determining a label corresponding to the second target information; The training sample is constructed according to the second target information and the label.

5. The method for applying for replacement resources according to claim 4, characterized in that: The step of constructing the training sample according to the second target information and the label includes: determining a second initial feature according to each sub-data of the second target information, wherein each sub-data of the second target information includes asset information, repayment information, and borrowing information of the second user; constructing a plurality of second derived features according to each of the second initial features; The training samples are constructed according to each of the second initial features, each of the second derived features, and the label.

6. The method for applying for replacement resources according to claim 3, characterized in that: The preset model is a random forest model.

7. The method for applying for replacement resources according to any one of claims 1 to 6, characterized in that: The step of obtaining the first target information of the first user associated with the application request includes: Output the application interface for replacement resources; The first target information input by the first user is obtained based on the application interface.

8. A replacement resource application device, characterized in that: include: An acquisition module, used to acquire an application request for replacing resources, and acquire first target information of a first user associated with the application request, wherein the first target information includes asset information, repayment information, and borrowing information of the first user; a first determination module, configured to determine a first initial feature according to each sub-data of the first target information, and construct a plurality of first derived features according to each of the first initial features, wherein each sub-data of the first target information includes asset information, repayment information, and borrowing information of the first user; A second determination module, configured to determine a repayment risk level corresponding to the first user according to an evaluation model, each of the first initial features, and each of the first derived features; A third determination module is used to determine a first amount of replacement resources applied for by the first user according to the application request, and determine a second amount matching the repayment risk level; A configuration module is used to configure a first account corresponding to the replacement resource for the first user in response to the first quota being less than or equal to the second quota, adjust the usage quota of the first account to the first quota, and output login information of the first account.

9. A replacement resource application device, characterized in that: The device comprises: a processor and a memory storing computer program instructions; when the processor executes the computer program instructions, the replacement resource application method as claimed in any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer program instructions, and when the computer program instructions are executed by a processor, the method for applying for replacement resources according to any one of claims 1 to 7 is implemented.

11. A computer program product, characterized in that When the instructions in the computer program product are executed by a processor of an electronic device, the electronic device is enabled to execute the resource replacement application method as described in any one of claims 1 to 7.

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