Dynamic configuration-based trust matching method, device, equipment and medium

Abstract

The application discloses a dynamic configuration-based credit matching method, device, equipment and medium, and the method comprises the following steps: updating a preset credit matching database according to credit update information from a credit terminal, obtaining credit basic information corresponding to a credit request from a client from a management information database, and further performing credit scoring to obtain a credit score value, obtaining candidate credit matching information corresponding to the credit request and the credit score value from the credit matching database, and screening the target credit channel from the candidate credit matching information according to the life insurance basic information and sending the target credit channel to the client. The application belongs to the technical field of artificial intelligence, dynamically configures the credit matching rules contained in the credit matching database based on the credit update information, intelligently matches based on the credit matching rules to screen the target credit channel, dynamically configures and timely updates the credit matching rules, and improves the flexibility of rule configuration and the accuracy of credit matching.

Description

Technical Field

[0001] This invention relates to the field of artificial intelligence technology, and belongs to the application scenario of credit matching for customers based on dynamic configuration in smart finance. In particular, it relates to a credit matching method, device, equipment and medium based on dynamic configuration. Background Technology

[0002] In corporate finance, credit transactions can be processed through multiple channels. When handling specific credit transactions, different funding sources need to be recommended based on the customer's qualifications. However, due to the varying qualifications of customers and the differences in funding limits and credit conditions among different channels, companies typically rely on sales staff to match and analyze customer qualifications with the standards of the credit channels before recommending the appropriate channel. This method is time-consuming, labor-intensive, and lacks flexibility. It cannot dynamically adjust the matching analysis process based on market conditions or changes in credit channels. This inability to adjust the matching analysis process in real time makes it difficult to accurately match customers with credit channels, thus impacting the efficiency of credit transactions. Therefore, existing methods for credit matching suffer from insufficient accuracy due to their lack of flexibility. Summary of the Invention

[0003] This invention provides a method, apparatus, device, and medium for credit matching based on dynamic configuration, aiming to solve the problem of insufficient accuracy in credit matching and docking in the prior art.

[0004] In a first aspect, embodiments of the present invention provide a credit matching method based on dynamic configuration. This method is applied in a management server, wherein a network connection is established between the management server, the client, and the credit terminal to achieve data transmission. The method includes:

[0005] If a credit update message is received from the credit terminal, the preset credit matching database is updated according to the credit update message;

[0006] If a credit granting request is received from a client, the system retrieves the basic credit granting information corresponding to the credit granting request from a pre-set management information database.

[0007] The credit scoring is performed on the basic credit information according to the preset credit scoring model to obtain the credit score value corresponding to the basic credit information;

[0008] Obtain alternative credit matching information that matches the credit score and the credit request from the credit matching database;

[0009] Based on the basic credit information, target credit channels that match the basic credit information are selected from the candidate credit matching information;

[0010] Send the target credit channel to the client.

[0011] Secondly, embodiments of the present invention provide a credit matching device based on dynamic configuration, comprising:

[0012] The authorization matching database update unit is used to update the preset authorization matching database according to the authorization update information received from the authorization terminal if authorization update information is received.

[0013] The credit granting basic information acquisition unit is used to obtain the credit granting basic information corresponding to the credit granting request from a preset management information database if a credit granting request is received from the client.

[0014] The credit score acquisition unit is used to perform credit scoring on the basic credit information according to a preset credit scoring model, so as to obtain a credit score value corresponding to the basic credit information.

[0015] The alternative credit matching information acquisition unit is used to acquire alternative credit matching information that matches the credit score and the credit request from the credit matching database.

[0016] The target credit channel acquisition unit is used to filter out the target credit channel that matches the credit basic information from the candidate credit matching information based on the credit basic information.

[0017] The target credit channel sending unit is used to send the target credit channel to the client.

[0018] Thirdly, embodiments of the present invention provide a computer device including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the dynamic configuration-based trust matching method described in the first aspect.

[0019] Fourthly, embodiments of the present invention also provide a computer-readable storage medium storing a computer program that, when executed by a processor, causes the processor to perform the dynamically configured trust matching method described in the first aspect.

[0020] This invention provides a dynamically configured credit matching method, apparatus, device, and medium. The method updates a pre-set credit matching database based on credit update information from a credit terminal. It retrieves basic credit information corresponding to a credit request from a client from a management information database, and further performs credit scoring to obtain a credit score value. It then retrieves candidate credit matching information corresponding to the credit request and credit score value from the credit matching database, and filters the target credit channel from the candidate credit matching information based on basic life insurance information, sending it to the client. This method allows for dynamic configuration of credit matching rules in the credit matching database based on credit update information, and intelligent matching of credit requests and credit score values ​​based on these dynamically configured rules to filter target credit channels. By dynamically configuring and updating credit matching rules in a timely manner, the flexibility of obtaining credit channels during credit matching is significantly improved, as well as the efficiency and accuracy of credit matching. Attached Figure Description

[0021] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 This is a flowchart illustrating the credit matching method based on dynamic configuration provided in an embodiment of the present invention.

[0023] Figure 2 This is a schematic diagram illustrating an application scenario of the credit matching method based on dynamic configuration provided in an embodiment of the present invention.

[0024] Figure 3 This is a schematic diagram of a sub-process of the credit matching method based on dynamic configuration provided in an embodiment of the present invention;

[0025] Figure 4 This is a schematic diagram of another sub-process of the credit matching method based on dynamic configuration provided in an embodiment of the present invention;

[0026] Figure 5 This is a schematic diagram of another sub-process of the credit matching method based on dynamic configuration provided in an embodiment of the present invention;

[0027] Figure 6 This is a schematic diagram of another sub-process of the credit matching method based on dynamic configuration provided in an embodiment of the present invention;

[0028] Figure 7 This is a schematic diagram of another sub-process of the credit matching method based on dynamic configuration provided in an embodiment of the present invention;

[0029] Figure 8 This is another flowchart illustrating the credit matching method based on dynamic configuration provided in an embodiment of the present invention.

[0030] Figure 9 A schematic block diagram of a credit matching device based on dynamic configuration provided in an embodiment of the present invention;

[0031] Figure 10 A schematic block diagram of a computer device provided for an embodiment of the present invention. Detailed Implementation

[0032] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0033] It should be understood that, when used in this specification and the appended claims, the terms "comprising" and "including" indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0034] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0035] It should also be further understood that the term "and / or" as used in this specification and the appended claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0036] Please see Figure 1 and Figure 2 , Figure 1 This is a flowchart illustrating the credit matching method based on dynamic configuration provided in an embodiment of the present invention. Figure 2This is a schematic diagram illustrating an application scenario of the dynamically configured credit matching method provided in this embodiment of the invention. The dynamically configured credit matching method is applied to a management server 10. This method is executed by application software installed on the management server 10. A network connection is established between the management server 10, the client 20, and the credit terminal 30 to transmit data. The management server 10 is the server-side component used to execute the dynamically configured credit matching method to perform credit matching for clients based on dynamic configuration. The credit terminal 30 is a terminal device that can send credit update information to the management server to update the credit matching database. The client 20 is a terminal device, such as a desktop computer, laptop, tablet, or mobile phone, that transmits data with the management server 10 to obtain the target credit channel and complete the credit business. Figure 1 As shown, the method includes steps S110 to S160.

[0037] S110. If credit update information is received from the credit terminal, the preset credit matching database is updated according to the credit update information.

[0038] If a credit update message is received from the credit granting terminal, the preset credit matching database is updated according to the credit update message. The credit granting terminal can send the credit update message to the management server. The management server is configured with a credit matching database, which is used to store credit filtering rules and credit groups. The management server can receive the credit update message and update the information stored in the credit matching database.

[0039] In one embodiment, such as Figure 3 As shown, step S110 includes sub-steps S111, S112 and S113.

[0040] S111. Update the parameters of the credit screening rules in the credit matching database according to the screening parameter update information contained in the credit update information; S112. Generate new credit channels according to the new channel update information contained in the credit update information and add them to the credit matching database; S113. Group and organize the credit channels in the credit matching database to update the credit groups contained in the credit matching database, and obtain the updated credit matching database.

[0041] Specifically, the credit matching database contains credit screening rules and credit groups corresponding to each customer group. First, it can be determined whether the credit update information includes updated screening parameters. If so, the parameters in the corresponding credit screening rules in the credit matching database can be updated based on the updated screening parameters. These parameters can be used to screen credit channels. Updating the credit screening rules applies to all credit channels, thus enabling unified configuration of credit screening rules applicable to all credit channels. If not, there is no need to update the credit screening rules in the credit matching database. Further, it can be determined whether the credit update information includes updated information on new channels. If so, it indicates that one or more new credit providers have been added. In this case, one or more new credit channels can be generated based on the updated information and added to the credit matching database. If not, there is no need to generate and add new credit channels. The credit rules are grouped and organized according to the newly added credit channels in the credit matching database and the credit channels currently included in each credit group. For example, the credit channels can be sorted according to their corresponding credit balance and single credit limit, and each credit channel can be grouped into the corresponding credit group according to the sorting result. This updates the credit groups contained in the credit matching database. This process of updating the credit matching database is also the process of dynamically configuring the credit rules.

[0042] S120. If a credit granting request is received from the client, the basic credit granting information corresponding to the credit granting request is obtained from the preset management information database.

[0043] If a credit request is received from a client, the system retrieves the corresponding basic credit information from a pre-configured management information database. The management server is configured with a management information database, which is used to store and manage customer-related information within the enterprise. The credit request includes customer-related identification information, such as the customer's ID number or customer code, which uniquely corresponds to the customer. Based on this identification information, the corresponding basic credit information can be retrieved from the management information database. This basic credit information includes customer qualification information and customer transaction information. This basic credit information can be used for credit analysis of the customer and for processing corresponding credit business.

[0044] S130. The credit scoring is performed on the basic credit information according to the preset credit scoring model to obtain the credit score value corresponding to the basic credit information.

[0045] Credit scoring is performed on the basic credit information according to a pre-set credit scoring model to obtain a credit score value corresponding to the basic credit information. To quantitatively assess the creditworthiness of different customers and provide targeted credit services based on their varying creditworthiness, a credit score can be performed on each customer based on their basic credit information. The resulting credit score value can then be used to comprehensively assess the customer's creditworthiness. The credit scoring model is a model that scores customers based on relevant customer information. The customer group classification model includes quantified feature information and a scoring neural network.

[0046] In one embodiment, such as Figure 4 As shown, step S130 includes sub-steps S131, S132 and S133.

[0047] S131. Extract the corresponding credit feature information from the credit base information based on the feature items contained in the feature quantification information.

[0048] Feature quantification information refers to the specific information that quantifies customer-related characteristics. It contains multiple feature items and corresponding mapping quantification rules for each feature item. The feature attributes corresponding to each feature item can be extracted from the basic credit information based on the feature items contained in the feature quantification information, serving as credit feature information. Specifically, the basic credit information consists of customer qualification information and customer transaction information. Customer qualification information includes name, ID number, age, home address, mobile phone number, gender, issuing authority, occupation, industry, company address, marital status, annual income, and equipment type. Customer transaction information includes credit transaction time, transaction amount, repayment operations, number of credit failures, and credit transaction funder. The number of feature items contained in the feature quantification information should not exceed the number of items contained in the basic credit information.

[0049] In addition, after obtaining credit feature information, it is also possible to determine whether the credit feature information meets the credit access standards. For example, it can be determined whether the age value in the credit feature information is within the credit age range. If the age value is not within the credit age range, the customer is determined to be an unqualified customer.

[0050] S132. The credit granting feature information is quantified according to the feature quantization information to obtain the corresponding credit granting quantization feature.

[0051] Each feature attribute contained in the credit feature information is quantized according to the mapping quantization rule corresponding to each feature item in the feature quantization information to obtain the credit quantization feature. The credit quantization feature is the information that uses numerical values ​​to quantify each feature attribute.

[0052] Specifically, for feature attributes represented in non-numerical form, the mapping quantization rule consists of multiple sets of mapping relationships corresponding to the corresponding feature item. Each set of mapping relationships contains a feature attribute and a corresponding feature value. For example, if all feature attributes corresponding to the feature item "occupation" are non-numerical, then the multiple sets of mapping relationships it contains can be represented as: white-collar worker -0.55, blue-collar worker -0.45, public servant -0.7, college student -0.25, etc. If the feature attribute corresponding to the feature item "occupation" in a customer's credit feature information is "white-collar worker", then the corresponding feature value can be obtained as "0.55". For feature attributes represented in numerical form, the mapping quantization rule consists of a mapping quantization formula corresponding to the corresponding feature item. The mapping quantization formula converts the corresponding feature attribute into a decimal within [0,1] for representation, thus obtaining the corresponding feature value. By combining the feature values ​​corresponding to each feature attribute in the credit feature information obtained by the above method, the corresponding credit quantification feature can be obtained.

[0053] S133. Input the credit quantification features into the scoring neural network to perform credit scoring and obtain the corresponding credit score value.

[0054] The obtained credit quantification features can be input into a scoring neural network for credit scoring, yielding a credit score value corresponding to the credit quantification features. This credit score value can be used to comprehensively evaluate a customer's creditworthiness. The scoring neural network can be an intelligent neural network built based on artificial intelligence. It can consist of an input layer, multiple intermediate layers, and an output layer. The input layer is connected to the first intermediate layer, the intermediate layers are connected to their adjacent intermediate layers, and the last intermediate layer is connected to the output layer through association formulas, all of which can be expressed as linear functions. The input layer can contain multiple input nodes, the number of which can be equal to the number of feature terms contained in the feature quantification information. Each input node can be used to input a corresponding feature value from the credit quantification features. The output layer contains one output node, and the output value of the output node is the corresponding credit score value. The input layer takes multiple feature values ​​contained in the credit quantification features as input, and the nodes contained in the scoring neural network perform correlation calculations. The output node then outputs the corresponding credit score value. The credit score value ranges from [0,1]. The closer the credit score value is to "1", the better the creditworthiness of the customer. The closer it is to "0", the worse the creditworthiness of the customer.

[0055] In addition, before using the scoring neural network for credit scoring, the initial neural network can be iteratively trained using a pre-set training dataset in the associated server. The training dataset consists of multiple training data points, each of which can be used to train the initial neural network once. Through iterative training, the trained scoring neural network can be obtained.

[0056] S140. Obtain alternative credit matching information that matches the credit score and the credit request from the credit matching database.

[0057] The credit matching database contains credit screening rules and credit groups corresponding to multiple customer groups. The credit request includes the credit limit entered by the customer, which is the credit limit value that the customer expects to obtain. Credit screening rules and credit groups that match the credit score and credit request can be obtained as alternative credit matching information.

[0058] In one embodiment, such as Figure 5 As shown, step S140 includes sub-steps S141 and S142.

[0059] S141. Based on the preset customer group classification and matching information, classify and match the credit score and the credit limit in the credit request to obtain the corresponding target customer group.

[0060] Customers can be categorized based on customer group classification matching information. This means matching credit scores and credit limits based on customer group classification matching information to identify target customer groups that match the current customer. Customers belonging to the same group share similar characteristics. For example, customer group classifications could include high-quality high credit usage, medium-quality high credit usage, low-quality high credit usage, high-quality medium credit usage, medium-quality medium credit usage, low-quality medium credit usage, high-quality low credit usage, medium-quality low credit usage, and low-quality low credit usage. For instance, the matching information for "high-quality" corresponds to an annual income of 100,000-200,000 yuan and a credit score greater than 0.6, or an annual income greater than 200,000 yuan and a credit score greater than 0.4. The matching information for "high credit usage" corresponds to a credit limit greater than 60,000 yuan. Therefore, the target customer group corresponding to the current customer can be determined by matching based on the current customer's credit score, credit limit, and annual income.

[0061] S142. Obtain credit screening rules and credit groups that match the target customer group from the credit matching database, and determine them as the corresponding candidate credit matching information.

[0062] Credit screening rules matching the target customer group and a credit group corresponding to the target customer can be obtained from the credit matching database, thus obtaining alternative credit matching information that matches the credit score and the credit request.

[0063] S150. Select target credit channels that match the basic credit information from the candidate credit matching information based on the basic credit information.

[0064] Based on the basic credit information, target credit channels that match the basic credit information are selected from the candidate credit matching information. Specifically, the candidate credit matching information includes corresponding credit screening rules and credit groups. Credit channels included in the credit groups can be screened according to the credit screening rules and basic credit information to obtain credit channels that match the basic credit information as target credit channels.

[0065] In one embodiment, such as Figure 6 As shown, step S150 includes sub-steps S151 and S152.

[0066] S151. The credit basic information is judged according to the credit screening rules in the candidate credit matching information, so as to obtain the corresponding exclusion label according to the judgment result.

[0067] The credit screening rules contain multiple exclusion conditions. It can be determined in turn whether the basic credit information meets each exclusion condition in the credit screening rules. If the basic credit information meets a certain exclusion condition, the exclusion label corresponding to the exclusion condition is recorded. If the basic credit information does not meet a certain exclusion condition, there is no need to record the exclusion label corresponding to the exclusion condition.

[0068] For example, one exclusion condition is whether the first three digits of the mobile phone number in the credit granting information are the same as "184", "178", or "172". If the first three digits of the mobile phone number in the credit granting information are the same as "184", "178", or "172", it means that the credit granting information meets the exclusion condition. Then, the exclusion label corresponding to the exclusion condition is recorded: Company A channel. Then, credit granting channels that match Company A channel need to be screened out from the credit granting group.

[0069] S152. Obtain credit channels that match the exclusion label from the credit groups of the candidate credit matching information and filter them out. Determine the remaining credit channels after filtering out as target credit channels that match the basic credit information.

[0070] Credit channels that match the exclusion labels can be obtained from the credit groups and filtered out. The remaining credit channels after filtering out the credit groups are determined as target credit channels that match the basic credit information.

[0071] In one embodiment, such as Figure 7 As shown, step S152 is followed by steps S153, S154, S155 and S155.

[0072] S153. Determine whether the number of target credit channels is zero; S154. If the number of target credit channels is not zero, execute the step of sending the target credit channels to the client; S155. If the number of target credit channels is zero, determine whether the number of credit failures in the customer transaction information is not greater than a preset threshold; S156. If the number of credit failures is greater than the threshold, change the credit limit in the credit request and return to execute the step of obtaining alternative credit matching information that matches the credit score and the credit request from the credit matching database.

[0073] After obtaining the target credit channel, it can be further determined whether the number of target credit channels is zero. If it is not zero, it is sent to the client. If the number of target credit channels is zero, it means that there is no credit channel in the customer's customer group that meets the customer's conditions. It can be further determined whether the number of credit failures in the customer's transaction information is not greater than a preset threshold. For example, the threshold can be configured to 10 times. If the number of credit failures is greater than the threshold, the credit limit in the credit request is changed. For example, the original credit limit is divided by 2 to get a new credit limit and the credit request is changed. Then, the execution step S140 is returned. The customer group can be reclassified based on the modified credit limit. That is, the customer group that matches the customer is obtained again to redetermine the target credit channel. If the number of credit failures is greater than the threshold, the number of credit failures is incremented by one and a prompt message that the target credit channel cannot be obtained is sent to the client.

[0074] S160. Send the target credit channel to the client.

[0075] The obtained target credit channel is the credit channel that matches the current customer's credit qualifications. The target credit channel can be sent to the client. Specifically, credit push information can be generated based on the target credit channel and pushed to the client. After receiving the credit push information through the client, the customer can select the target credit channel contained in the credit push information and then handle the corresponding credit business according to the customer's selection.

[0076] In one embodiment, such as Figure 8 As shown, steps S160 are followed by steps S170 and S180.

[0077] S170. If the client receives channel selection information based on the target credit channel, process the credit business according to the channel selection information and record the process to obtain the corresponding processing record information; S180. Update the customer transaction information corresponding to the channel selection information in the management information database according to the processing record information.

[0078] If the channel selection information is received from the client, a corresponding credit agreement is signed with the client based on the channel selection information and the credit business is processed. The process of processing the business is recorded to obtain the processing record information. Based on the processing record information, the customer transaction information stored in the management information database that matches the customer is updated. When granting credit to the customer again in the future, the updated customer transaction information in the management information database can be used.

[0079] The technical methods in this application can be applied to smart finance scenarios where credit matching for customers is based on dynamic configuration.

[0080] In the dynamically configured credit matching method provided in this embodiment of the invention, the pre-set credit matching database is updated according to credit update information from the credit terminal. Basic credit information corresponding to the credit request from the client is obtained from the management information database, and a credit score is obtained through further credit scoring. Alternative credit matching information corresponding to the credit request and credit score is obtained from the credit matching database, and the target credit channel is selected from the alternative credit matching information based on basic life insurance information and sent to the client. Through this method, the credit matching rules contained in the credit matching database can be dynamically configured based on credit update information, and the credit request and credit score can be intelligently matched based on the dynamically configured credit matching rules to select the target credit channel. By dynamically configuring and updating the credit matching rules in a timely manner, the flexibility of obtaining credit channels during credit matching is greatly improved, and the efficiency and accuracy of credit matching are also enhanced.

[0081] This invention also provides a dynamically configured credit matching device, which can be configured in the management server 10. This dynamically configured credit matching device is used to execute any of the aforementioned embodiments of the dynamically configured credit matching method. Specifically, please refer to... Figure 9 , Figure 9 This is a schematic block diagram of a credit matching device based on dynamic configuration provided in an embodiment of the present invention.

[0082] like Figure 9 As shown, the credit matching device 100 based on dynamic configuration includes an authorized matching database update unit 110, a credit basic information acquisition unit 120, a credit score acquisition unit 130, a candidate credit matching information acquisition unit 140, a target credit channel acquisition unit 150, and a target credit channel sending unit 160.

[0083] The authorization matching database update unit 110 is used to update the preset authorization matching database according to the authorization update information received from the authorization terminal.

[0084] In one specific embodiment, the authorization matching database update unit 110 includes sub-units: a parameter update unit, used to update the parameters of the credit screening rules in the credit matching database according to the screening parameter update information contained in the credit update information; a channel addition unit, used to generate new credit channels according to the new channel update information contained in the credit update information and add them to the credit matching database; and a grouping and sorting unit, used to group and sort the credit channels in the credit matching database to update the credit groups contained in the credit matching database, thereby obtaining the updated credit matching database.

[0085] The credit granting basic information acquisition unit 120 is used to acquire the credit granting basic information corresponding to the credit granting request from a preset management information database if a credit granting request is received from the client.

[0086] The credit score acquisition unit 130 is used to perform credit scoring on the basic credit information according to a preset credit scoring model, so as to obtain a credit score value corresponding to the basic credit information.

[0087] In one specific embodiment, the credit score acquisition unit 130 includes subunits: a credit feature information extraction unit, used to extract corresponding credit feature information from the credit base information based on the feature items contained in the feature quantification information; a credit quantification feature acquisition unit, used to quantify the credit feature information based on the feature quantification information to obtain corresponding credit quantification features; and a credit scoring unit, used to input the credit quantification features into the scoring neural network to perform credit scoring and obtain the corresponding credit score value.

[0088] The alternative credit matching information acquisition unit 140 is used to acquire alternative credit matching information that matches the credit score and the credit request from the credit matching database.

[0089] In one specific embodiment, the alternative credit matching information acquisition unit 140 includes sub-units: a target customer group acquisition unit, used to classify and match the credit score and the credit limit in the credit request according to preset customer group classification and matching information, so as to obtain the corresponding target customer group; and a matching information acquisition unit, used to obtain credit screening rules and credit groups that match the target customer group from the credit matching database, and determine them as the corresponding alternative credit matching information.

[0090] The target credit channel acquisition unit 150 is used to select target credit channels that match the credit basic information from the candidate credit matching information based on the credit basic information.

[0091] In one specific embodiment, the target credit channel acquisition unit 150 includes sub-units: an exclusion tag acquisition unit, used to judge the basic credit information according to the credit screening rules in the candidate credit matching information, so as to obtain the corresponding exclusion tag according to the judgment result; and a credit channel screening unit, used to obtain the credit channels that match the exclusion tag from the credit groups of the candidate credit matching information and screen them out, and determine the remaining credit channels after screening as the target credit channels that match the basic credit information.

[0092] In one specific embodiment, the target credit channel acquisition unit 150 includes sub-units: a quantity judgment unit, used to determine whether the quantity of the target credit channels is zero; if the quantity of the target credit channels is not zero, execute the step of sending the target credit channels to the client; a credit failure count judgment unit, used to determine whether the number of credit failures in the customer transaction information is not greater than a preset count threshold if the quantity of the target credit channels is zero; and a return execution unit, used to change the credit limit in the credit request and return to execute the step of obtaining alternative credit matching information that matches the credit score and the credit request from the credit matching database if the number of credit failures is greater than the count threshold.

[0093] The target credit channel sending unit 160 is used to send the target credit channel to the client.

[0094] In one specific embodiment, the credit matching device 100 based on dynamic configuration further includes a subunit: a processing record information acquisition unit, used to process credit business and record the processing process to obtain corresponding processing record information if the client receives channel selection information fed back by the client according to the target credit channel; and a customer transaction information update unit, used to update the customer transaction information corresponding to the channel selection information in the management information database according to the processing record information.

[0095] The credit matching device based on dynamic configuration provided in this embodiment of the invention applies the aforementioned credit matching method based on dynamic configuration. It updates the preset credit matching database based on credit update information from the credit terminal, retrieves basic credit information corresponding to the credit request from the client from the management information database, and further performs credit scoring to obtain a credit score value. It then retrieves candidate credit matching information corresponding to the credit request and credit score value from the credit matching database, and filters the target credit channel from the candidate credit matching information based on basic life insurance information and sends it to the client. Through this method, the credit matching rules contained in the credit matching database can be dynamically configured based on credit update information, and the credit request and credit score value can be intelligently matched based on the dynamically configured credit matching rules to filter the target credit channel. By dynamically configuring and updating the credit matching rules in a timely manner, the flexibility of obtaining credit channels during credit matching is greatly improved, and the efficiency and accuracy of credit matching are also enhanced.

[0096] The aforementioned credit matching device based on dynamic configuration can be implemented as a computer program, which can, for example... Figure 10 It runs on the computer device shown.

[0097] Please see Figure 10 , Figure 10 This is a schematic block diagram of a computer device provided in an embodiment of the present invention. The computer device may be a management server 10 for executing a dynamically configured credit matching method to perform credit matching for clients based on dynamic configuration.

[0098] See Figure 10 The computer device 500 includes a processor 502, a memory, and a network interface 505 connected via a system bus 501. The memory may include a storage medium 503 and internal memory 504.

[0099] The storage medium 503 may store an operating system 5031 and a computer program 5032. When the computer program 5032 is executed, it causes the processor 502 to execute a dynamically configured trust matching method, wherein the storage medium 503 may be a volatile storage medium or a non-volatile storage medium.

[0100] The processor 502 provides computing and control capabilities to support the operation of the entire computer device 500.

[0101] The internal memory 504 provides an environment for the execution of the computer program 5032 in the storage medium 503. When the computer program 5032 is executed by the processor 502, the processor 502 can execute a dynamically configured trust matching method.

[0102] This network interface 505 is used for network communication, such as providing data transmission. Those skilled in the art will understand that... Figure 10 The structure shown is merely a block diagram of a portion of the structure related to the present invention and does not constitute a limitation on the computer device 500 to which the present invention is applied. The specific computer device 500 may include more or fewer components than shown in the figure, or combine certain components, or have different component arrangements.

[0103] The processor 502 is used to run the computer program 5032 stored in the memory to implement the corresponding functions in the above-described credit matching method based on dynamic configuration.

[0104] Those skilled in the art will understand that Figure 10 The embodiments of the computer device shown do not constitute a limitation on the specific configuration of the computer device. In other embodiments, the computer device may include more or fewer components than illustrated, or combine certain components, or have different component arrangements. For example, in some embodiments, the computer device may include only memory and a processor. In such embodiments, the structure and function of the memory and processor are different from those shown. Figure 10 The embodiments shown are consistent and will not be described again here.

[0105] It should be understood that, in this embodiment of the invention, the processor 502 may be a Central Processing Unit (CPU), or it may be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0106] In another embodiment of the invention, a computer-readable storage medium is provided. This computer-readable storage medium may be volatile or non-volatile. The computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps included in the dynamically configured trust matching method described above.

[0107] Those skilled in the art will readily understand that, for the sake of convenience and brevity, the specific working processes of the devices, apparatuses, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here. Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in terms of function in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this invention.

[0108] In the embodiments provided by this invention, it should be understood that the disclosed devices, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. Units with the same function may be grouped into one unit. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. In addition, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interfaces, devices, or units, or it may be an electrical, mechanical, or other form of connection.

[0109] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of the embodiments of the present invention, depending on actual needs.

[0110] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0111] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a computer-readable storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned computer-readable storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), magnetic disks, or optical disks.

[0112] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present invention, and these modifications or substitutions should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A credit matching method based on dynamic configuration, characterized in that, Applied in a management server, the management server establishes a network connection with the client and the authorized terminal to realize the transmission of data information. The method includes: If a credit update message is received from the credit terminal, the preset credit matching database is updated according to the credit update message; If a credit granting request is received from a client, the system retrieves the basic credit granting information corresponding to the credit granting request from a pre-set management information database. The credit scoring is performed on the basic credit information according to the preset credit scoring model to obtain the credit score value corresponding to the basic credit information; Obtain alternative credit matching information that matches the credit score and the credit request from the credit matching database; Based on the basic credit information, target credit channels that match the basic credit information are selected from the candidate credit matching information; Send the target credit channel to the client; The step of updating the preset credit matching database according to the credit update information includes: The parameters of the credit screening rules in the credit matching database are updated according to the screening parameter update information contained in the credit update information; New credit channels are generated based on the new channel update information contained in the credit update information, and added to the credit matching database; The credit channels in the credit matching database are grouped and organized to update the credit groups contained in the credit matching database, resulting in an updated credit matching database. The grouping and organization includes: grouping and organizing the credit channels according to the newly added credit channels in the credit matching database and the credit channels currently contained in each credit group; sorting the credit channels according to the credit balance and single credit limit corresponding to each credit channel; and grouping each credit channel into the corresponding credit group according to the sorting result. The step of obtaining alternative credit matching information that matches the credit score and the credit request from the credit matching database includes: The credit score and the credit limit in the credit request are classified and matched according to the preset customer group classification and matching information to obtain the corresponding target customer group; the credit matching database includes credit screening rules and credit groups corresponding to multiple customer groups, and customers belonging to the same customer group have similar characteristics. Retrieve credit screening rules and credit groups that match the target customer group from the credit matching database, and determine them as the corresponding candidate credit matching information.

2. The credit matching method based on dynamic configuration according to claim 1, characterized in that, The customer group classification model includes feature quantification information and a scoring neural network. The step of performing credit scoring on the basic credit information according to a preset credit scoring model to obtain a credit score value corresponding to the basic credit information includes: The corresponding credit feature information is extracted from the credit base information based on the feature items contained in the feature quantification information. The credit granting feature information is quantified based on the feature quantification information to obtain the corresponding credit granting quantification feature; The credit quantification features are input into the scoring neural network to obtain the corresponding credit score value.

3. The credit matching method based on dynamic configuration according to claim 1, characterized in that, The step of selecting target credit channels that match the basic credit information from the candidate credit matching information based on the basic credit information includes: The basic credit information is judged according to the credit screening rules in the candidate credit matching information, and the corresponding exclusion label is obtained according to the judgment result; Credit channels that match the exclusion label are obtained from the credit groups of the candidate credit matching information and filtered out. The remaining credit channels after filtering are determined as target credit channels that match the basic credit information.

4. The credit matching method based on dynamic configuration according to claim 3, characterized in that, After obtaining credit channels matching the exclusion label from the credit groups of the candidate credit matching information and filtering them out, and determining the remaining credit channels after filtering as target credit channels matching the basic credit information, the method further includes: Determine whether the number of the target credit channels is zero; If the number of target credit channels is not zero, execute the step of sending the target credit channels to the client; If the number of target credit channels is zero, determine whether the number of credit failures in the customer transaction information is not greater than a preset threshold. If the number of credit failures exceeds the threshold, the credit limit in the credit request is changed and the process returns to the step of retrieving alternative credit matching information from the credit matching database that matches the credit score and the credit request.

5. The credit matching method based on dynamic configuration according to claim 1, characterized in that, After sending the target credit channel to the client, the process further includes: If the client receives channel selection information based on the target credit channel, the credit business is processed according to the channel selection information and the processing process is recorded to obtain the corresponding processing record information. The customer transaction information corresponding to the channel selection information in the management information database is updated based on the processing record information.

6. A credit matching device based on dynamic configuration, characterized in that, The device is configured in a management server, and the management server establishes a network connection with the client and the authorized terminal to realize the transmission of data information. The device includes: The authorization matching database update unit is used to update the preset authorization matching database according to the authorization update information received from the authorization terminal if authorization update information is received. The credit granting basic information acquisition unit is used to obtain the credit granting basic information corresponding to the credit granting request from a preset management information database if a credit granting request is received from the client. The credit score acquisition unit is used to perform credit scoring on the basic credit information according to a preset credit scoring model, so as to obtain a credit score value corresponding to the basic credit information. The alternative credit matching information acquisition unit is used to acquire alternative credit matching information that matches the credit score and the credit request from the credit matching database. The target credit channel acquisition unit is used to filter out the target credit channel that matches the credit basic information from the candidate credit matching information based on the credit basic information. The target credit channel sending unit is used to send the target credit channel to the client; The step of updating the preset credit matching database according to the credit update information includes: The parameters of the credit screening rules in the credit matching database are updated according to the screening parameter update information contained in the credit update information; New credit channels are generated based on the new channel update information contained in the credit update information, and added to the credit matching database; The credit channels in the credit matching database are grouped and organized to update the credit groups contained in the credit matching database, resulting in an updated credit matching database. The grouping and organization includes: grouping and organizing the credit channels according to the newly added credit channels in the credit matching database and the credit channels currently contained in each credit group; sorting the credit channels according to the credit balance and single credit limit corresponding to each credit channel; and grouping each credit channel into the corresponding credit group according to the sorting result. The step of obtaining alternative credit matching information that matches the credit score and the credit request from the credit matching database includes: The credit score and the credit limit in the credit request are classified and matched according to the preset customer group classification and matching information to obtain the corresponding target customer group; the credit matching database includes credit screening rules and credit groups corresponding to multiple customer groups, and customers belonging to the same customer group have similar characteristics. Retrieve credit screening rules and credit groups that match the target customer group from the credit matching database, and determine them as the corresponding candidate credit matching information.

7. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the dynamically configured credit matching method as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the dynamically configured credit matching method as described in any one of claims 1 to 5.

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