Credit use authorization management method and device, equipment and storage medium thereof

Abstract

The application discloses a credit use authorization control method and device, equipment and a storage medium thereof, and belongs to the technical field of Fintech. The credit use authorization control method comprises the following steps: receiving a credit use request sent by an associated terminal and determining the corresponding transaction type, so as to determine a target evaluation function matched with the credit use request in an evaluation function database; according to the target evaluation function, target transaction feature data corresponding to the credit use request is extracted, and a target weight coefficient is determined, wherein the target transaction feature data comprises one or more of a customer level, a transaction purpose, a merchant category and a merchant level; each target transaction feature data and each target weight coefficient are input into a credit authorization control model, an authorization result of the credit use request is obtained, and the authorization result is sent to the associated terminal. The application solves the technical problem of low work efficiency of the credit use transaction authorization in the prior art.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of financial technology (Fintech), in particular to a credit use authorization control method and device, equipment and a storage medium thereof. BACKGROUND

[0002] With the development of China's economy and society, the market shows explosive growth, and the integration of the Internet and finance further gives birth to a series of Internet credit businesses; with the advantages of the Internet, customers can complete all steps of loan application without leaving home, including understanding the application conditions of various loans, preparing application materials, and submitting loan applications and credit use, which can be efficiently completed on the Internet. At the same time, the corresponding transaction business supervision measures are not perfect, resulting in a high risk of Internet credit transactions, which not only limits the healthy development of the industry, but also brings great risks and hidden dangers to China's economy.

[0003] In view of the existing problems, the conventional way is to increase multiple databases and manual intervention of different job levels, so that different job levels manually interface different databases based on different terminals, thereby realizing credit use control; but this way needs mutual authorization between terminals of different job levels, resulting in a relatively complex authorization process of each node in the control process, and thus the work efficiency of credit use control is low.

[0004] The above content is only used to assist in understanding the technical solutions of the present application and does not represent the acknowledgement of the above content as prior art. SUMMARY

[0005] The main purpose of the present application is to provide a credit use authorization control method, device, equipment and storage medium, which aims to solve the technical problem of low work efficiency in conventional credit use authorization.

[0006] To achieve the above purpose, the present application provides a credit use authorization control method, which comprises:

[0007] receiving a credit use request sent by an associated terminal, determining a transaction type corresponding to the credit use request, and based on the transaction type, determining a target evaluation function in a preset evaluation function database that is adapted to the credit use request;

[0008] According to the target evaluation function, the target transaction feature data corresponding to the credit use request is extracted, and the target weight coefficient of each target transaction feature data for the credit use request is determined, wherein the target transaction feature data includes one or more of customer level, transaction purpose, merchant category and merchant level;

[0009] input the target transaction feature data and the target weight coefficients into a preset credit authorization control model to obtain an authorization result of the credit use request, and send the authorization result to the associated terminal.

[0010] Optionally, the step of determining a target evaluation function adaptive to the credit use request from a preset evaluation function database based on the transaction type comprises:

[0011] traversing each evaluation function in the preset evaluation function database to obtain a function traversal result;

[0012] determining the target evaluation function adaptive to the transaction type according to the function traversal result, wherein the preset evaluation function database comprises a private-to-private evaluation function and a private-to-business evaluation function.

[0013] Optionally, the step of extracting target transaction feature data corresponding to the credit use request and determining target weight coefficients of each target transaction feature data according to the target evaluation function comprises:

[0014] determining transaction feature data to be extracted and a target weight interval corresponding to each transaction feature data to be extracted according to the target evaluation function;

[0015] extracting target transaction feature data of the credit use request based on the transaction feature data to be extracted and determining a target feature index value corresponding to each target transaction feature data;

[0016] determining each target weight coefficient according to the target feature index value and the target weight interval.

[0017] Optionally, the step of determining transaction feature data to be extracted according to the target evaluation function comprises:

[0018] if the target evaluation function is a private-to-private evaluation function, the transaction feature data to be extracted is a customer level and a transaction purpose;

[0019] if the target evaluation function is a private-to-business evaluation function, the transaction feature data to be extracted is a customer level, a business category and a business level.

[0020] Optionally, the step of inputting the target transaction feature data and the target weight coefficients into a preset credit authorization control model to obtain an authorization result of the credit use request comprises:

[0021] input the target transaction feature data and the target weight coefficient to a preset credit authorization control model to obtain a credit authorization control group identifier matched with the credit use request;

[0022] According to the credit authorization control group identifier, a corresponding target credit authorization control group is called, and the target credit authorization control group is controlled to check the use amount and the use times of the credit use request;

[0023] If the check passes, it is determined that the authorization result of the credit use request is authorization success;

[0024] If the check fails, it is determined that the authorization result of the credit use request is authorization failure.

[0025] Optionally, before the step of determining the transaction type corresponding to the credit use request, the method further comprises:

[0026] determining the qualification information of the customer corresponding to the credit use request, and checking whether the credit use request passes based on the qualification information;

[0027] If the credit use request passes, the step of determining the transaction type corresponding to the credit use request is executed;

[0028] If the credit use request does not pass, it is determined that the authorization result of the credit use request is authorization failure.

[0029] Optionally, the step of sending the authorization result to the associated terminal comprises:

[0030] obtaining the remaining use amount and the remaining use times of the customer corresponding to the credit use request, and sending the remaining use amount, the remaining use times and the authorization result to the associated terminal.

[0031] The application also provides a credit use authorization control device, which comprises:

[0032] A determination module is configured to receive a credit use request sent by an associated terminal, determine a transaction type corresponding to the credit use request, and determine a target evaluation function adapted to the credit use request in a preset evaluation function database based on the transaction type;

[0033] An extraction module is configured to extract target transaction feature data corresponding to the credit use request according to the target evaluation function, and determine a target weight coefficient of each target transaction feature data for the credit use request, wherein the target transaction feature data comprises one or more of customer level, transaction purpose, merchant category and merchant level;

[0034] The sending module is configured to input each target transaction feature data and each target weight coefficient into a preset credit authorization control model, obtain an authorization result of the credit application request, and send the authorization result to the associated terminal.

[0035] The application further provides a credit application authorization control device, which comprises a memory, a processor, and a credit application authorization control program stored in the memory and executable on the processor.

[0036] The application further provides a storage medium, which is a computer readable storage medium, and the computer readable storage medium stores a credit application authorization control program. The credit application authorization control program is executed by a processor to implement the steps of the credit application authorization control method.

[0037] This application discloses a method for credit disbursement authorization and control. It involves receiving credit disbursement requests from associated terminals, determining the transaction type corresponding to the request, and based on the transaction type, identifying a target evaluation function adapted to the credit disbursement request from a pre-set evaluation function database. Then, based on the target evaluation function, it extracts target transaction feature data corresponding to the credit disbursement request and determines the target weight coefficient of each target transaction feature data for the credit disbursement request. The target transaction feature data includes one or more of the following: customer level, transaction purpose, merchant category, and merchant grade. This method categorizes and automatically identifies the transaction type of the credit disbursement request. This system enables the retrieval of adaptive target evaluation functions for credit disbursement requests belonging to different transaction types. Based on these functions, it extracts the required transaction characteristic data, achieving automatic extraction and dynamic analysis of multi-dimensional and multi-angle data on credit disbursement requests. Furthermore, it inputs the transaction characteristic data and target weight coefficients into a pre-defined credit authorization control model. This model efficiently and automatically evaluates the credit disbursement authorization results to obtain accurate authorization outcomes for credit disbursement requests. This improves the accuracy and efficiency of credit disbursement authorization, achieving precise and efficient control over credit disbursement authorization. Conventional credit disbursement control relies on multiple databases and human intervention at different levels. This requires individuals at various levels to connect to and authorize different databases using different terminals, leading to complex authorization processes and low efficiency. Furthermore, the need for multiple nodes and human intervention increases uncertainties, reducing the security of credit disbursement control. This application, however, utilizes fully automated credit disbursement assessment and authorization to automatically extract multi-dimensional transaction feature data, eliminating the need for multi-terminal collaboration and human intervention at different levels. This reduces the risk of data leakage and improves the security and efficiency of credit disbursement control. Additionally, the application uses a transaction management system for credit disbursement authorization analysis... Easy-feature data includes partial and multi-dimensional information on customer and merchant dimensions, as well as overall interaction information between customers and merchants corresponding to transaction purposes and merchant categories. It can conduct comprehensive feature analysis of credit disbursement requests from the partial to the overall perspective and the correlation between multiple dimensions to obtain more comprehensive transaction features of credit disbursement. By using the weight ratio of different transaction features, it can accurately filter and analyze transaction feature data in the most practical way, comprehensively and accurately identify credit disbursement risks, and achieve a balance between credit disbursement risk control and customer experience, further improving customer experience and the accuracy of credit disbursement authorization control. Attached Figure Description

[0038] Figure 1 This is a schematic diagram of the structure of the credit disbursement authorization and control device in the hardware operating environment involved in the embodiments of this application;

[0039] Figure 2 A flowchart of the credit use authorization control method involved in the embodiment of the present application is shown in the figure;

[0040] Figure 3 A schematic diagram of the credit authorization control group involved in the embodiment of the present application is shown in the figure;

[0041] Figure 4 A schematic diagram of the complete embodiment flow involved in the embodiment of the present application is shown in the figure;

[0042] Figure 5 A schematic diagram of the framework structure of the credit use authorization control device involved in the embodiment of the present application is shown in the figure.

[0043] The implementation, functional features and advantages of the present application will be further described with reference to the embodiments and the accompanying drawings. DETAILED DESCRIPTION

[0044] It should be understood that the specific embodiments described herein are merely intended to explain the present application and not to limit the present application.

[0045] In addition, the description of "first", "second" and the like in the present application is only for the purpose of description and cannot be understood as indicating or implying the relative importance of the technical features or implicitly indicating the number of the technical features. Therefore, the features with "first", "second" can explicitly or implicitly include at least one of the features. In addition, "and / or" throughout the text includes three schemes, for example, A and / or B includes A technical solution, B technical solution, and A and B simultaneously satisfy the technical solution; in addition, the technical solutions of each embodiment can be combined with each other, but it must be based on the realization of ordinary skilled in the art, when the combination of technical solutions appears contradictory or unachievable, it should be considered that the combination of technical solutions does not exist, nor within the scope of protection claimed by the present application.

[0046] Reference Figure 1 , Figure 1 A schematic diagram of the credit use authorization control device structure of the hardware operating environment involved in the embodiment of the present application is shown in the figure.

[0047] As Figure 1As shown, the credit use authorization management device can include a processor 1001, such as a central processing unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. The communication bus 1002 is used to realize the connection and communication between the components. The user interface 1003 can include a display, an input unit such as a keyboard, and can also include a standard wired interface, a wireless interface. The network interface 1004 can optionally include a standard wired interface, a wireless interface (such as a wireless fidelity (WIreless-FIdelity, WI-FI) interface). The memory 1005 can be a high-speed random access memory (RAM) memory, or a stable non-volatile memory (Non-Volatile Memory, NVM), such as a disk memory. The memory 1005 can also be a storage device independent of the aforementioned processor 1001.

[0048] Those skilled in the art can understand that Figure 1 The structure shown in the figure does not constitute a limitation on the credit use authorization management device, and can include more or fewer components than the figure, or combine certain components, or different component arrangements.

[0049] As Figure 1 As shown, the memory 1005 as a storage medium can include an operating system, a data storage module, a network communication module, a user interface module, and a credit use authorization management program.

[0050] In Figure 1 In the credit use authorization management device shown in the figure, the network interface 1004 is mainly used for data communication with other devices; the user interface 1003 is mainly used for data interaction with the user; the processor 1001 and the memory 1005 in the credit use authorization management device of the present application can be arranged in the credit use authorization management device, and the credit use authorization management device calls the credit use authorization management program stored in the memory 1005 through the processor 1001, and performs the following operations:

[0051] Receiving a credit use request sent by an associated terminal, determining a transaction type corresponding to the credit use request, and based on the transaction type, determining a target evaluation function adapted to the credit use request in a preset evaluation function database;

[0052] According to the target evaluation function, target transaction feature data corresponding to the credit use request is extracted, and a target weight coefficient of each target transaction feature data for the credit use request is determined, wherein the target transaction feature data comprises one or more of a customer level, a transaction purpose, a merchant category, and a merchant level.

[0053] The target transaction feature data and the target weight coefficient are input into a preset credit authorization control model to obtain an authorization result of the credit use request, and the authorization result is sent to the associated terminal.

[0054] Further, the operation of determining a target evaluation function adapted to the credit use request in a preset evaluation function database based on the transaction type comprises:

[0055] Each evaluation function in the preset evaluation function database is traversed to obtain a function traversal result;

[0056] According to the function traversal result, the target evaluation function matched with the transaction type is determined, wherein the preset evaluation function database comprises a private-to-private evaluation function and a private-to-business evaluation function.

[0057] Further, the operation of extracting target transaction feature data corresponding to the credit use request and determining a target weight coefficient of each target transaction feature data for the credit use request according to the target evaluation function comprises:

[0058] According to the target evaluation function, the transaction feature data to be extracted and a target weight interval corresponding to each transaction feature data to be extracted are determined;

[0059] Based on the transaction feature data to be extracted, target transaction feature data of the credit use request is extracted, and a target feature index value corresponding to each target transaction feature data is determined;

[0060] According to the target feature index value and the target weight interval, each target weight coefficient is determined.

[0061] Further, the operation of determining the transaction feature data to be extracted according to the target evaluation function comprises:

[0062] If the target evaluation function is a private-to-private evaluation function, the transaction feature data to be extracted is a customer level and a transaction purpose;

[0063] If the target evaluation function is a private-to-business evaluation function, the transaction feature data to be extracted is a customer level, a merchant category, and a merchant level.

[0064] Further, the operation of inputting each of the target transaction feature data and each of the target weight coefficient into a preset credit authorization control model to obtain an authorization result of the credit consumption request comprises:

[0065] inputting each of the target transaction feature data and each of the target weight coefficient into a preset credit authorization control model to obtain a credit authorization control group identifier matched with the credit consumption request;

[0066] calling a corresponding target credit authorization control group according to the credit authorization control group identifier, and controlling the target credit authorization control group to verify a consumption amount and a consumption frequency of the credit consumption request;

[0067] if the verification is passed, determining that the authorization result of the credit consumption request is authorization success;

[0068] if the verification is not passed, determining that the authorization result of the credit consumption request is authorization failure.

[0069] Further, the processor 1001 can call the credit consumption authorization control program stored in the memory 1005, and further perform the following operations:

[0070] Before the operation of determining the transaction type corresponding to the credit consumption request, further comprising:

[0071] determining the qualification information of the customer corresponding to the credit consumption request, and verifying whether the credit consumption request is passed based on the qualification information;

[0072] if the credit consumption request is passed, performing the operation of determining the transaction type corresponding to the credit consumption request;

[0073] if the credit consumption request is not passed, determining that the authorization result of the credit consumption request is authorization failure.

[0074] Further, the operation of sending the authorization result to the associated terminal comprises:

[0075] obtaining the remaining consumption amount and the remaining consumption frequency of the customer corresponding to the credit consumption request, and sending the remaining consumption amount, the remaining consumption frequency and the authorization result to the associated terminal.

[0076] Based on the above structure, various embodiments of the credit consumption authorization control method are proposed.

[0077] Reference Figure 2 , Figure 2 is a flowchart of the first embodiment of the credit consumption authorization control method.

[0078] In the embodiment, the execution subject of the credit use authorization control method can be a credit use authorization control device or a credit use authorization control apparatus. The credit use authorization control device can be a terminal device or a server. The credit use authorization control apparatus can be integrated on a terminal device with a data processing function, such as a smart phone or a tablet computer. In the embodiment, the execution subject is not limited. In order to facilitate the description, the description of each embodiment is omitted. In the embodiment, the credit use authorization control method comprises:

[0079] In step S10, a credit use request sent by an associated terminal is received, a transaction type corresponding to the credit use request is determined, and a target evaluation function suitable for the credit use request is determined in a preset evaluation function database based on the transaction type.

[0080] In order to avoid the situation that a customer has no ability or no willingness to repay a loan after the loan, a bank or other financial institution often needs to perform credit use risk analysis on a private customer or an enterprise applying for a loan to determine the available credit use amount and use times of the customer, so as to determine whether to authorize the current credit use request according to the credit use amount and use times. Therefore, if a credit use request sent by a customer through an associated terminal is received, the transaction type of the credit use request is analyzed, and an evaluation function suitable for the credit use request is selected from a preset evaluation function database for credit risk evaluation according to the transaction type of the credit use request.

[0081] In the embodiment, it should be noted that the credit use authorization control refers to performing multi-dimensional and multi-angle credit risk evaluation on the initiator of the credit use request to determine the credit use amount and use times standard that meets the demand of the initiator of the credit use request under a low risk degree, and determining whether to authorize the credit use request according to the determined credit use amount and use times standard, so as to realize full-automatic and accurate control of the credit use request.

[0082] Credit risk refers to the possibility that a borrower, a security issuer or a transaction counterparty is unwilling or unable to perform a contract condition due to various reasons, resulting in a breach of contract, and causing a bank, an investor or a transaction counterparty to suffer losses.

[0083] The credit use request refers to a loan use application initiated by a customer through an associated terminal. The credit use request can be a loan use application initiated through the Internet, that is, the customer completes the loan application through the Internet. The credit use request can include a use amount, a transaction type, a transaction purpose, a transaction merchant category, a customer level, and the like, which are not limited in the embodiment. The associated terminal refers to a terminal for sending the credit use request, which can be a terminal that can be connected to a network, such as a mobile phone, a notebook computer, a tablet computer, and the like.

[0084] The transaction type is determined according to the nature of the transaction corresponding to the credit consumption request, and can include private-to-private transactions, private-to-business transactions, etc.; wherein the private-to-private transaction can also be referred to as a cash transaction, which refers to a transaction between two private accounts, such as cash withdrawal, money transfer, and red envelope sending; the private-to-business transaction can also be referred to as a non-cash transaction, which refers to a transaction between a private account and a business account or a company account, and the business account can be a supermarket, a hotel, an airline, a restaurant, etc., which is not limited in the embodiment.

[0085] The credit consumption limit and the consumption frequency refer to the transaction limit and the transaction limit times set by the initiator of the credit consumption request, i.e., the maximum transaction limit and the transaction times that the initiator can apply within a certain period of time; wherein the consumption limit can include single consumption limit, daily consumption limit, weekly consumption limit, monthly consumption limit, and annual consumption limit, and the consumption frequency can include daily consumption frequency, weekly consumption frequency, monthly consumption frequency, and annual consumption frequency, which is not limited in the embodiment.

[0086] The evaluation function database contains various evaluation functions, which are function models used to evaluate the overall and local performance of the credit consumption request, and are commonly used in credit risk evaluation, such as loan approval, credit limit, and risk pricing; in the embodiment, different transaction types can correspond to different evaluation functions, for example, private-to-private evaluation functions are suitable for private-to-private transactions, and private-to-business evaluation functions are suitable for private-to-business transactions; optionally, the private-to-private evaluation functions and the private-to-business evaluation functions can also include evaluation functions for consumption limit and consumption frequency evaluation. The target evaluation function refers to the evaluation function adapted to the credit consumption request.

[0087] In a feasible implementation, before the step of determining the transaction type corresponding to the credit consumption request in step S10, the method further includes:

[0088] In step S11, the qualification information of the customer corresponding to the credit consumption request is determined, and based on the qualification information, it is verified whether the credit consumption request is passed;

[0089] If the credit consumption request sent by the client through the associated terminal is received, the qualification information of the client corresponding to the credit consumption request is obtained, and according to the obtained qualification information, it is verified whether the credit consumption request can be passed, so as to ensure that the current credit consumption request is normally initiated, rather than malicious operation by irrelevant personnel or malicious personnel; wherein the qualification information can include account status, total remaining limit of the account, credit level of the account, etc., wherein the qualification information can be called from the associated terminal or from the cloud where the qualification information is stored, which is not limited in the embodiment.

[0090] In an implementation, if the account status of the client corresponding to the credit use request is normal, the total remaining balance of the account is greater than or equal to the use amount of the credit use request, the account is not in the preset blacklist, the credit level of the account meets the preset credit level standard, and the account does not have fraudulent behavior, etc., it is determined that the credit use request is passed; otherwise, if any of the above conditions is not met, it is determined that the credit use request is not passed.

[0091] In step S12, if the credit use request is passed, a step of determining the transaction type corresponding to the credit use request is performed.

[0092] In step S13, if the credit use request is not passed, it is determined that the authorization result of the credit use request is authorization failure.

[0093] If the credit use request is passed according to the qualification information, it indicates that the account qualification of the initiator of the credit use request is good, which meets the basic requirements of the loan, and the loan can be performed. Then, a step of determining the transaction type corresponding to the credit use request is performed. If the credit use request is not passed according to the qualification information, it indicates that the account qualification of the initiator of the credit use request is poor, and the risk assessment level of the loan is high. After the loan, there is no ability or willingness to repay, which does not meet the basic requirements of the loan. Then, it is determined that the authorization result of the credit use request is authorization failure, that is, the current loan is not approved.

[0094] In the embodiment, by obtaining the qualification information of the client corresponding to the credit use request, it is automatically verified whether the credit use request is passed, that is, whether the loan can be performed. The automatic basic evaluation of the credit use request is realized to ensure that the initiator of the current credit use request has the loan qualification. Through the qualification information, the loan application of the blacklisted client or the client with poor credit is quickly screened out. When the initiator of the loan has the loan qualification, it is further determined whether the client meets the specific use amount and use frequency standards, thereby improving the work efficiency of the credit use authorization control.

[0095] In an implementation, in step S10, based on the transaction type, a target evaluation function adapted to the credit use request is determined in a preset evaluation function database, which includes the following steps.

[0096] In step S14, each evaluation function in the preset evaluation function database is traversed to obtain a function traversal result.

[0097] In step S15, the target evaluation function matched with the transaction type is determined according to the function traversal result, wherein the preset evaluation function database includes a private-to-private evaluation function and a private-to-business evaluation function.

[0098] In the embodiment, the preset evaluation function database is preset with a plurality of evaluation functions adapted to different transaction types, in order to determine the target evaluation function adapted to the current credit consumption request, the plurality of preset evaluation functions are sequentially accessed, each access can obtain a function traversal result, so as to determine whether the currently accessed evaluation function matches the transaction type of the credit consumption request through the function traversal result; if matched, the evaluation function is determined as the target evaluation function, and the next evaluation function is stopped from being accessed; if not matched, the next evaluation function is continuously accessed.

[0099] The evaluation functions preset in the preset evaluation function database can include: private-to-private class evaluation functions and private-to-business class evaluation functions; the private-to-private class evaluation functions are adapted to private-to-private class transactions, and the private-to-business class evaluation functions are adapted to private-to-business class transactions; wherein the private-to-private class evaluation functions further include: private-to-private class quota evaluation functions and private-to-private class frequency evaluation functions, which are respectively used for evaluating the consumption quota and the consumption frequency of private-to-private class transactions; the private-to-business class evaluation functions further include: private-to-business class quota evaluation functions and private-to-business class frequency evaluation functions, which are respectively used for evaluating the consumption quota and the consumption frequency of private-to-business class transactions.

[0100] In an implementable embodiment, different evaluation functions correspond to different transaction feature data to be extracted and different weight coefficient intervals.

[0101] In the embodiment, by traversing each evaluation function in the preset evaluation function database, a function traversal result is obtained, so as to determine the target evaluation function matched with the transaction type, and automatic and rapid identification and retrieval of the target evaluation function adapted to the credit consumption request are realized; by classifying the evaluation function types, the adaptation degree between the evaluation functions and the credit consumption request is improved, and then by extracting key feature data of different dimensions, deep and accurate analysis of different credit consumption requests is realized, so that comprehensive and accurate credit consumption risk identification is realized, the accuracy of credit consumption authorization control is further improved, and by automatic traversal of the preset evaluation function database, multi-node and manual intervention are not required, the safety and work efficiency of credit consumption control are improved.

[0102] Step S20: according to the target evaluation function, extracting target transaction feature data corresponding to the credit consumption request, and determining a target weight coefficient of each target transaction feature data for the credit consumption request, wherein the target transaction feature data includes one or more of customer level, transaction purpose, merchant category and merchant level;

[0103] According to the target evaluation function, the transaction feature data required for this credit risk evaluation is determined and data extraction is performed, and then data analysis is performed on the extracted transaction feature data to determine the characteristic index value corresponding to each transaction feature data; the target evaluation function also includes a preset weight interval corresponding to each transaction feature data, and according to the extracted transaction feature data and / or the characteristic index value corresponding to the transaction feature data, the target weight coefficient corresponding to each transaction feature data is determined.

[0104] The transaction feature data is the feature data of the transaction parties of the credit use request extracted according to the requirements of the target evaluation function; the transaction feature data can be real-time feature data, for example, the real-time transaction purpose corresponding to the current transaction; the transaction feature data can also be historical feature data, for example, when evaluating the natural month use amount in the use amount, the historical transaction purpose data of the client in the last month can be extracted; the time corresponding to the extracted data can be one week, one month, one year, etc., and the present embodiment does not limit this.

[0105] The target transaction feature data includes one or more of the client level, the transaction purpose, the merchant category and the merchant level.

[0106] The client level is the level division after comprehensive evaluation according to the historical income, historical liabilities, historical credit performance, historical fraud performance and other information of the client; for example, the information of all associated clients is extracted for client level evaluation, and the historical income, historical liabilities, historical credit performance, historical fraud performance and other information of the client are converted into scores to determine the total level score of each associated client, and the total level score is sorted to divide the client into five levels from high to low; accordingly, the higher the level of the client, the higher the characteristic index value corresponding to the client level transaction feature data.

[0107] The transaction purpose refers to the transfer, cash withdrawal, red packet sending and other transaction methods of the transaction parties in the private-to-private transaction; it should be understood that the characteristic index value corresponding to each transaction purpose transaction feature data is related to the target evaluation function used for evaluation, and the characteristic index value can be determined according to the target evaluation function used; for example, when using the private-to-private amount evaluation function, the amount of transfer is usually higher than the amount of red packet sending, and accordingly the characteristic index value corresponding to the transfer is higher than the characteristic index value corresponding to the red packet sending; when using the private-to-private frequency evaluation function, the frequency of red packet sending is usually higher than the frequency of transfer, and accordingly the characteristic index value corresponding to the red packet sending is higher than the characteristic index value corresponding to the transfer.

[0108] The merchant category is a division of merchants according to the fields described by each merchant, including but not limited to supermarkets, hotels, restaurants, medical care, beauty, travel, etc. When performing data analysis, historical data of different merchant categories can be analyzed and classified to determine the corresponding characteristic index value. For example, the historical usage frequency of different merchants in credit consumption transactions is counted and ranked, or the historical total amount of different merchants in credit consumption transactions is counted and ranked, etc. The present embodiment does not limit this. It should be understood that the characteristic index value corresponding to the merchant category transaction characteristic data is related to the target evaluation function used for evaluation, and the characteristic index value can be determined according to the target evaluation function used.

[0109] The merchant level is a level division based on a comprehensive evaluation of the transaction history, default record, transaction anomaly rate, fraud rate, etc. of the merchant. For example, the information of all associated merchants is extracted for merchant level evaluation, and the transaction history, default record, transaction anomaly rate, fraud rate, etc. of the merchant are converted into scores to determine the total score of each associated merchant, and the total score is sorted to divide the merchant into 5 levels from high to low. The higher the level of the merchant, the higher the characteristic index value corresponding to the merchant level transaction characteristic data.

[0110] The characteristic index value is an embodiment of the quantitative characteristic of the extracted transaction characteristic data. It should be understood that the characteristic index value corresponding to each transaction characteristic data is related to the target evaluation function used for evaluation, and the characteristic index value can be determined according to the target evaluation function used.

[0111] In step S30, each target transaction characteristic data and each target weight coefficient are input into a pre-set credit authorization control model to obtain an authorization result of the credit consumption request, and the authorization result is sent to the associated terminal.

[0112] The obtained transaction characteristic data and the target weight coefficient corresponding to each transaction characteristic data are input into a pre-trained credit authorization control model. The credit authorization control model outputs an authorization result obtained after evaluating and verifying the credit consumption request. If the verification is passed, i.e. the amount and historical times of the credit consumption request meet the consumption limit and consumption times, the authorization result is authorization success. If the verification is not passed, i.e. the amount and / or historical times of the credit consumption request do not meet the consumption limit and consumption times, the authorization result is authorization failure, and then the authorization result is sent back to the associated terminal to inform the authorization result and the reason.

[0113] The credit authorization control model is developed from the perspective of natural persons, i.e., customers, and then a classification model is established based on corresponding transaction feature data of the natural persons or customers as samples through classification algorithms such as logistic regression, GBDT (Gradient Boosting Decision Tree), XGBoost (eXtreme Gradient Boosting), etc. The credit authorization control model can calculate the credit limit and the number of times of use that meet the customer's demand under the premise of low risk, and achieve a balance between credit use risk prevention and control and customer experience.

[0114] In an implementable embodiment, historical transaction feature data of the associated customer is acquired as a training sample; the training sample is input into the credit authorization control model to be trained to determine a credit authorization control model prediction result of the training sample; based on the credit authorization control model prediction result, a credit authorization control model prediction loss corresponding to the credit authorization control model to be trained is calculated to iteratively optimize the credit authorization control model to be trained, and obtain the credit authorization control model.

[0115] In another implementable embodiment, the step S30 of sending the authorization result to the associated terminal comprises:

[0116] In step S40, the remaining credit limit and the remaining number of times of use of the customer corresponding to the credit use request are acquired, and the remaining credit limit, the remaining number of times of use, and the authorization result are sent to the associated terminal.

[0117] The remaining credit limit and the remaining number of times of use of the customer corresponding to the credit use request are acquired, and the remaining credit limit, the remaining number of times of use, and the authorization result are sent to the associated terminal to inform the customer of the authorization result and the reason. For example, the remaining credit limit, the remaining number of times of use, and the authorization result can be sent to the associated terminal to inform the customer of the authorization result. If the authorization result is a failure, a detailed evaluation report can be generated according to the evaluation result to inform the customer of the specific reason for the authorization failure and feasible improvement measures, etc., which are not limited in this embodiment.

[0118] In this embodiment, the remaining credit limit, the remaining number of times of use, and the authorization result are fed back in real time to timely inform the customer of the credit use result, and further improve the user experience and the work efficiency of credit use control.

[0119] In the embodiment, compared with the conventional credit use control, the credit use control is realized by increasing the number of databases and the manual intervention of different positions, which requires different positions to manually connect and authorize different databases based on different terminals, resulting in complex authorization process of each node and low work efficiency. Moreover, the increase of multiple nodes and manual intervention increases the uncertainty, thereby reducing the security of the credit use control. The credit use evaluation and authorization in the present application can automatically extract multi-dimensional transaction feature data without the need for multi-terminal cooperation and manual intervention of different positions, thereby reducing the risk of data leakage and improving the security and work efficiency of the credit use control. Meanwhile, the transaction feature data used for credit use authorization analysis in the present application includes local and multi-dimensional information of customer dimension and merchant dimension, as well as overall interaction information between customers and merchants corresponding to transaction purpose and merchant category. The credit use request can be analyzed in a comprehensive manner based on the correlation between local and overall information and multiple dimensions to obtain more comprehensive transaction features of the credit use. The transaction feature data is accurately selected and analyzed in a manner most suitable for the actual situation based on the weight proportion between different transaction features, so as to comprehensively and accurately identify the credit use risk and balance the credit use risk prevention and control and customer experience, thereby further improving the customer experience and the accuracy of the credit use authorization control.

[0120] Further, based on the first embodiment, the second embodiment of the credit use authorization control method is provided. In the embodiment, step S20 includes:

[0121] Step S21, according to the target evaluation function, determining the transaction feature data to be extracted and the target weight interval corresponding to each transaction feature data to be extracted;

[0122] Each target evaluation function can correspond to different transaction feature data to be extracted, and each transaction feature data to be extracted corresponds to a different weight interval when evaluated.

[0123] For example, the target evaluation function is a private-to-private evaluation function, the transaction feature data to be extracted is a customer level and a transaction purpose, the target weight interval corresponding to the customer level is 50-70%, and the target weight interval corresponding to the transaction purpose is 30-40%. If the target evaluation function is a private-to-merchant evaluation function, the transaction feature data to be extracted is a customer level, a merchant category, and a merchant level. In the private-to-merchant evaluation function, the level and category of the transaction merchant play a crucial role in addition to the evaluation of the customer of the credit use request. Therefore, in the private-to-merchant evaluation function, the target weight interval of the customer level is reduced by 30-50% compared with the private-to-private evaluation function, the target weight interval of the merchant category is 20-30%, and the target weight interval of the merchant level is 20-40%.

[0124] In an implementation, step S21, the step of determining the transaction characteristic data to be extracted according to the target evaluation function comprises:

[0125] Step S211, if the target evaluation function is a private-to-private evaluation function, the transaction characteristic data to be extracted is: customer level and transaction purpose.

[0126] If the target evaluation function is a private-to-private evaluation function, it indicates that the transaction type of the credit use request is a private-to-private transaction, and then when performing credit use risk assessment, the customer of the credit use request is extracted and analyzed for transaction characteristic data; the transaction characteristic data to be extracted includes: customer level and transaction purpose.

[0127] Step S212, if the target evaluation function is a private-to-business evaluation function, the transaction characteristic data to be extracted is: customer level, business category, and business level.

[0128] If the target evaluation function is a private-to-business evaluation function, it indicates that the transaction type of the credit use request is a private-to-business transaction, and then when performing credit use risk assessment, in addition to extracting the transaction characteristic data of the customer of the credit use request, the transaction characteristic data of the other party of the transaction, i.e., the business, also needs to be extracted to avoid damage to the interests of the customer by some businesses with high risk levels; the transaction characteristic data to be extracted includes: customer level, business category, and business level.

[0129] In this embodiment, based on the transaction type, the target evaluation function suitable for the credit use request is determined; and then according to the suitable target evaluation function, the target transaction characteristic data corresponding to the credit use request is automatically extracted; by classifying and identifying the transaction type of the credit use request, automatic calling of the target evaluation function suitable for the credit use request belonging to different transaction types is realized, and then the required transaction characteristic data is extracted according to the suitable target evaluation function, multi-dimensional and multi-angle data extraction of the credit use request is realized, and then comprehensive and accurate credit use risk identification is performed, further improving the accuracy of credit use authorization control, and the data extraction and evaluation process is fully automated, without the need for multi-node and manual intervention, further improving the security and work efficiency of credit use control.

[0130] Step S22, based on the transaction characteristic data to be extracted, the target transaction characteristic data of the credit use request is extracted, and the target characteristic index value corresponding to each target transaction characteristic data is determined.

[0131] According to the target evaluation function required to extract transaction feature data, the target transaction feature data of the transaction parties of the credit use request is extracted, and the extracted data is analyzed to determine the target feature index value corresponding to each target transaction feature data, wherein the target feature index value includes: customer level feature index value, transaction purpose feature index value, merchant category feature index value and merchant level feature index value.

[0132] For example, the customer level in the transaction feature data is five levels, and the customer level of the credit use transaction application is level one, that is, the highest level, so the customer level feature index value is 100.

[0133] In an embodiment, step S22, based on the transaction feature data required to be extracted, the step of extracting the target transaction feature data of the credit use request further includes:

[0134] Step S221, based on the transaction feature data required to be extracted, determining the transaction feature database storing each transaction feature data required to be extracted;

[0135] Step S222, sending a data extraction request to each transaction feature database and extracting the target transaction feature data stored in each transaction feature database.

[0136] In this embodiment, by automatically sending a data extraction request to the transaction feature database storing the transaction feature data, the data extraction permission is obtained, and each transaction feature data is automatically extracted without the intervention of different levels of artificial intervention, thereby improving the work efficiency of the credit use authorization control;

[0137] Step S23, determining each target weight coefficient according to the target feature index value and the target weight interval.

[0138] Taking the middle value of each target weight interval as a reference, the corresponding target feature value is adjusted to determine the target weight coefficient corresponding to each target feature data, wherein the target feature value and the target weight coefficient are in a positive proportional relationship.

[0139] The target weight coefficient includes: customer level weight coefficient, transaction purpose weight coefficient, merchant category weight coefficient and merchant level weight coefficient.

[0140] For example, if the target weight interval corresponding to the customer level is 50-70%, the base is 60%; then, combined with the target characteristic value, if the customer level in the target transaction characteristic data is level 1, the target characteristic value is determined to be 100, and then combined with the target characteristic value 100, the weight coefficient is adjusted upwards from 60% to determine the final target weight coefficient to be 70%; correspondingly, if the target characteristic value is lower, the weight coefficient is adjusted downwards from 60%, and the specific adjustment ratio is adjusted according to the proportion of the target characteristic value.

[0141] In an implementable embodiment, it should be understood that the sum of all target weight coefficients of the target evaluation function is 1 (100%), therefore, after determining the target weight coefficients corresponding to each target characteristic value in the target evaluation function, the target weight coefficients are corrected based on the proportional relationship between each target characteristic value in the target evaluation function.

[0142] For example, the target evaluation function is a private-to-private evaluation function, the target characteristic values include a customer level characteristic index value 80 and a transaction purpose characteristic index value 50, and the corresponding customer level weight coefficient is 75% and the transaction purpose weight coefficient is 38%; and the sum of the customer level weight coefficient 75% and the transaction purpose weight coefficient 35% is 110%>100%, therefore, according to the proportional relationship between the customer level characteristic index value 80 and the transaction purpose characteristic index value 50, the customer level weight coefficient and the transaction purpose weight coefficient are correspondingly reduced to realize the correction of the target weight coefficients.

[0143] In the present embodiment, according to the target evaluation function, the transaction characteristic data to be extracted is determined, as well as the target weight interval corresponding to each of the transaction characteristic data to be extracted, then based on the transaction characteristic data to be extracted, the target transaction characteristic data of the credit consumption request is extracted, and the target characteristic index value corresponding to each of the target transaction characteristic data is determined, and then according to the target characteristic index value and the target weight interval, the target weight coefficient of each is determined; the transaction characteristic data used for credit consumption authorization analysis in the present application contains local, multi-dimensional information of customer dimension and merchant dimension, and overall interaction information between customers and merchants corresponding to transaction purpose and merchant category, which can perform comprehensive feature analysis on the credit consumption request through the correlation between local and overall and multiple dimensions, to obtain more comprehensive transaction characteristics of credit consumption; and through the weight proportion between different transaction characteristics, the transaction characteristic data is accurately selected and analyzed in the most practical way, the credit consumption risk is comprehensively and accurately identified, the balance between credit consumption risk prevention and control and customer experience is realized, the accuracy of credit consumption authorization control is further improved, and the safety and work efficiency of credit consumption control are further improved.

[0144] Further, based on the first and / or second embodiments described above, a third embodiment of the credit use authorization control method is proposed. In this embodiment, step S30 includes:

[0145] Step S31, input each of the target transaction feature data and each of the target weight coefficient into a pre-set credit authorization control model to obtain a credit authorization control group identifier matched with the credit use request.

[0146] The obtained target transaction feature data and each target weight coefficient are input into the pre-trained credit authorization control model. The credit authorization control model determines the credit authorization control group matched with the credit use request according to the target transaction feature data and the target weight coefficient, and outputs the identifier of the credit authorization control group. Referring to Figure 3 .

[0147] The credit authorization control group is a control group for checking and managing the use amount and the use frequency of each credit use request. Each credit use request corresponds to an adaptive credit authorization control group. The matched credit authorization control group refers to the credit authorization control group that can meet the credit demand of the customer to the maximum extent on the basis of a lower risk level. Each credit authorization control group can correspond to different use amounts and use frequencies.

[0148] In an embodiment, the corresponding feature index value is determined according to the obtained transaction feature data, and then the risk score of the credit use request is calculated according to the feature index value and the weight coefficient. The risk score is input into the pre-trained credit authorization control model to obtain the authorization result of the credit use request.

[0149] In another embodiment, the credit authorization control model can output specific use amount and use frequency after evaluating the credit use request, which can include single use amount, natural day use amount, natural week use frequency, etc. Then, a credit authorization control group is set as a target credit authorization control group, and the target credit authorization control group checks the use amount and the use frequency of the credit use request to determine the authorization result.

[0150] In another possible implementation, the natural weekly spending limit, the natural monthly spending limit, the natural annual spending limit, and the number of spending times of each customer are usually fixed; therefore, historical transaction feature data of each time period can be extracted according to a preset time, new risk assessment can be performed by the credit authorization control model, and the natural weekly spending limit, the natural monthly spending limit, the natural annual spending limit, and the number of spending times, which are relatively fixed, can be re-determined. For the single spending limit, real-time risk assessment can be performed according to each initiated credit spending request to determine a suitable single spending limit. Compared with the conventional credit spending authorization control implemented according to customer credit or transaction type, the standard setting of the spending limit and the number of spending times is relatively fixed, and it is difficult to implement differentiated credit spending authorization control according to the actual transaction situation, resulting in a relatively low accuracy of the credit spending authorization control. In the present application, the standard setting of the spending limit and the number of spending times in the implementation of the credit spending authorization control can be differentiated and accurately controlled according to the actual transaction situation. For example, the customer level of the customer is high, and the corresponding spending limit is high. However, if the current credit spending request belongs to a private-to-business transaction, and the merchant level of the corresponding merchant is low, that is, the risk level of the merchant is high. At this time, the spending limit set by the present application in real time and differentiation avoids large transactions between the user and the merchant, greatly reduces the economic loss that the user may cause, and protects the safety of the customer and the lender.

[0151] In step S32, the corresponding target credit authorization control group is called according to the credit authorization control group identifier, and the target credit authorization control group is controlled to verify the spending limit and the number of spending times of the credit spending request.

[0152] The target credit authorization control group is screened from a plurality of preset credit authorization control groups according to the credit authorization control group identifier, so that the target credit authorization control group verifies the spending limit and the number of spending times of the credit spending request.

[0153] The verification is to obtain the single spending amount of the credit spending request, and the daily used amount, the weekly used amount, the monthly used amount, the annual used amount, the daily used number of times, the weekly used number of times, the monthly used number of times, and the annual used number of times of the customer of the credit spending request; and the used amount and the used number of times are compared with the spending limit and the number of spending times standard set by the target credit authorization control group, wherein the spending limit standard set by the target credit authorization control group includes: single spending limit, natural daily spending limit, natural weekly spending limit, natural monthly spending limit, natural annual spending limit, etc.; the number of spending times standard can include: natural daily number of spending times, natural weekly number of spending times, natural monthly number of spending times, natural annual number of spending times, etc.; if all are less than or equal to, it is determined that the verification passes; if any is greater than, it is determined that the verification fails.

[0154] Step S33, if the verification passes, it is determined that the authorization result of the credit use request is authorization success;

[0155] Step S34, if the verification fails, it is determined that the authorization result of the credit use request is authorization failure.

[0156] If the verification passes, it indicates that the single use amount of the credit use request, and other use amounts and use times do not exceed the use amount and use time standards set by the target credit authorization control group, and the loan can continue, it is determined that the authorization result of the credit use request is authorization success, and the disbursement is made according to the credit use request; if the verification fails, it indicates that any one or more of the single use amount of the credit use request, or other use amounts and use times exceeds the use amount and use time standards set by the target credit authorization control group, and the loan cannot be made according to the credit use request, it is determined that the authorization result of the credit use request is authorization failure, and the credit use request is ended.

[0157] In the embodiment, compared with the credit use authorization control implemented according to the customer credit or the transaction type, the standards of the use amount and the use time are relatively fixed, and it is difficult to implement differentiated and dynamic credit use authorization control according to the actual transaction situation, resulting in low accuracy of the credit use authorization control; in the present application, the standards of the use amount and the use time set when implementing the credit use authorization control can be dynamically differentiated and accurately controlled according to the actual transaction situation; for example, the customer level of the customer is high, and the corresponding use amount is high, but if the credit use request belongs to a private-to-business transaction, and the merchant level of the corresponding merchant is low, that is, the risk level of the merchant is high; at this time, the use amount set by the present application in real time and differentiation avoids large transactions between the user and the merchant, greatly reduces the economic loss that the user may cause, and protects the fund safety of the customer and the lending party; the balance between credit use risk prevention and control and customer experience is achieved, the accuracy of the credit use authorization control is further improved, and the extraction and evaluation process of the data are fully automated, without the need for multi-node and manual intervention, and the safety and work efficiency of the credit use control are further improved.

[0158] Further, based on the first, second and / or third embodiments described above, a more complete embodiment of the credit use authorization control method of the present application is proposed, in which Figure 4 :

[0159] The client initiates a credit consumption request through a client-associated terminal, and a credit consumption authorization control device judges the transaction type of the credit consumption request; if it is a private-to-private transaction, the obtained transaction characteristic data includes: client level and transaction purpose; if it is a private-to-business transaction, the obtained transaction characteristic data includes: client level, business category and business level; then, according to the obtained transaction characteristic data, multi-dimensional evaluation of credit consumption risk is carried out, an evaluation-adapted authorization control group identifier is output through a credit authorization control model, and then a target authorization control group is called according to the authorization control group identifier to verify the consumption amount and the consumption frequency of the credit consumption request; wherein the consumption amount includes: single limit, daily limit, weekly limit, monthly limit and annual limit (the limit is the consumption amount); the consumption frequency includes: daily limit, weekly limit, monthly limit and annual limit (the limit is the consumption frequency); and an authorization result of the credit consumption request is output according to the verification result, pass or fail.

[0160] Further, the application embodiment further provides a credit consumption authorization control device, referring to Figure 5 , the credit consumption authorization control device is applied to a credit consumption authorization control device, and the credit consumption authorization control device comprises:

[0161] A determination module 10 is configured to receive a credit consumption request sent by an associated terminal, determine the transaction type corresponding to the credit consumption request, and determine a target evaluation function adapted to the credit consumption request in a preset evaluation function database based on the transaction type;

[0162] An extraction module 20 is configured to extract target transaction characteristic data corresponding to the credit consumption request according to the target evaluation function, and determine a target weight coefficient of each target transaction characteristic data for the credit consumption request, wherein the target transaction characteristic data includes one or more of client level, transaction purpose, business category and business level;

[0163] A sending module 30 is configured to input each target transaction characteristic data and each target weight coefficient into a preset credit authorization control model, obtain an authorization result of the credit consumption request, and send the authorization result to the associated terminal.

[0164] The credit consumption authorization control device specific implementation manner of the application is basically the same as each embodiment of the credit consumption authorization control method described above, and will not be repeated here.

[0165] It should be noted that, in the present document, the terms "comprises", "comprising", or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but can also include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element preceded by "comprises a" does not, without more constraints, foreclose the existence of additional identical elements in the process, method, article, or apparatus that comprises the element.

[0166] From the above description of the embodiments, it is clear that the above-mentioned method of the embodiments can be realized by means of software plus a necessary general hardware platform, and of course can also be realized by hardware, but in many cases the former is a better embodiment. Based on such understanding, the technical solutions of the present application can be embodied in the form of a software product in essence or in the form of a part of the prior art that makes a contribution. The computer software product is stored in a storage medium such as a ROM / RAM, a magnetic disk, or an optical disk, and includes a plurality of instructions for causing a terminal device (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the method described in each embodiment of the present application.

[0167] The above is only a preferred embodiment of the present application, and does not limit the patent scope of the present application, and any equivalent structure or equivalent process transformation using the content of the present application specification and drawings, or direct or indirect application in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. A method for authorizing and controlling credit disbursement, characterized in that, The credit disbursement authorization and control method includes the following steps: Receive a credit disbursement request sent by an associated terminal, determine the transaction type corresponding to the credit disbursement request, and based on the transaction type, determine a target evaluation function that is compatible with the credit disbursement request from a preset evaluation function database. The transaction type includes private-to-private transactions and private-to-commercial transactions. Based on the target evaluation function, target transaction feature data corresponding to the credit disbursement request is extracted, and the target weight coefficient of each target transaction feature data for the credit disbursement request is determined. The target transaction feature data includes one or more of the following: customer level, transaction purpose, merchant category, and merchant grade. The target transaction feature data and the target weight coefficients are input into a preset credit authorization control model to obtain the authorization result of the credit disbursement request, and the authorization result is sent to the associated terminal. The step of determining the target evaluation function that matches the credit disbursement request in the preset evaluation function database based on the transaction type includes: Iterate through each evaluation function in the pre-defined evaluation function database to obtain the function traversal results; Based on the function traversal results, the target evaluation function that matches the transaction type is determined. The preset evaluation function database includes: private-to-private evaluation functions and private-to-commercial evaluation functions.

2. The credit disbursement authorization and control method as described in claim 1, characterized in that, The step of extracting the target transaction feature data corresponding to the credit disbursement request according to the target evaluation function, and determining the target weight coefficient of each of the target transaction feature data for the credit disbursement request includes: Based on the target evaluation function, determine the transaction feature data to be extracted, and the target weight range corresponding to each of the transaction feature data to be extracted; Based on the transaction feature data to be extracted, extract the target transaction feature data of the credit disbursement request, and determine the target feature index value corresponding to each of the target transaction feature data. Based on the target feature index value and the target weight range, determine each target weight coefficient.

3. The credit disbursement authorization and control method as described in claim 2, characterized in that, The step of determining the transaction feature data to be extracted based on the target evaluation function includes: If the target evaluation function is a private-to-private evaluation function, then the transaction feature data to be extracted are: customer level and transaction purpose; If the target evaluation function is a private-to-commercial evaluation function, then the transaction feature data to be extracted are: customer level, merchant category, and merchant grade.

4. The credit disbursement authorization and control method as described in claim 1, characterized in that, The step of inputting the target transaction feature data and the target weight coefficients into a preset credit authorization control model to obtain the authorization result of the credit disbursement request includes: The target transaction feature data and the target weight coefficient are input into the preset credit authorization control model to obtain the credit authorization control group identifier that matches the credit disbursement request; The corresponding target credit authorization control group is invoked according to the credit authorization control group identifier, and the target credit authorization control group is controlled to verify the disbursement amount and disbursement frequency of the credit disbursement request; If the verification passes, the authorization result of the credit disbursement request is determined to be successful. If the verification fails, the authorization result of the credit disbursement request is determined to be authorization failure.

5. The credit disbursement authorization and control method as described in claim 1, characterized in that, Before the step of determining the transaction type corresponding to the credit disbursement request, the method further includes: Determine the credit disbursement request's customer qualification information, and based on the qualification information, verify whether the credit disbursement request is approved; If the credit disbursement request is approved, then the step of determining the transaction type corresponding to the credit disbursement request is executed; If the credit disbursement request is not approved, the authorization result of the credit disbursement request is determined to be authorization failure.

6. The credit disbursement authorization and control method as described in claim 1, characterized in that, The step of sending the authorization result to the associated terminal includes: Obtain the remaining credit limit and remaining number of credit transactions for the customer corresponding to the credit transaction request, and send the remaining credit limit, the remaining number of credit transactions, and the authorization result to the associated terminal.

7. A credit disbursement authorization and control device, characterized in that, The device includes: The determining module is used to receive a credit disbursement request sent by an associated terminal, determine the transaction type corresponding to the credit disbursement request, and, based on the transaction type, determine a target evaluation function adapted to the credit disbursement request from a preset evaluation function database. The transaction type includes private-to-private transactions and private-to-commercial transactions. The determining module is also used to traverse each evaluation function in the preset evaluation function database to obtain the function traversal result; and, based on the function traversal result, determine the target evaluation function that matches the transaction type. The preset evaluation function database includes private-to-private evaluation functions and private-to-commercial evaluation functions. The extraction module is used to extract the target transaction feature data corresponding to the credit disbursement request according to the target evaluation function, and determine the target weight coefficient of each of the target transaction feature data for the credit disbursement request, wherein the target transaction feature data includes one or more of the following: customer level, transaction purpose, merchant category and merchant grade; The sending module is used to input the target transaction feature data and the target weight coefficients into a preset credit authorization control model, obtain the authorization result of the credit disbursement request, and send the authorization result to the associated terminal.

8. A credit disbursement authorization and control device, characterized in that, The device includes: a memory, a processor, and a credit disbursement authorization control program stored in the memory and executable on the processor, the credit disbursement authorization control program being configured to implement the steps of the credit disbursement authorization control method as described in any one of claims 1 to 6.

9. A storage medium, characterized in that, The storage medium stores a credit disbursement authorization control program, which, when executed by a processor, implements the steps of the credit disbursement authorization control method as described in any one of claims 1 to 6.

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