CN116433356A

CN116433356A - User matching method and device, storage medium and electronic equipment

Info

Publication number: CN116433356A
Application number: CN202310268831.6A
Authority: CN
Inventors: 任政; 秦晓程; 何帅军; 李磊; 田海霞; 张富
Original assignee: Alipay Hangzhou Information Technology Co Ltd
Current assignee: Alipay Hangzhou Information Technology Co Ltd
Priority date: 2023-03-13
Filing date: 2023-03-13
Publication date: 2023-07-14

Abstract

The embodiment of the specification discloses a user matching method, a device, a storage medium and electronic equipment, wherein the embodiment of the specification firstly obtains at least one credit giving platform corresponding to a user from a credit giving platform set comprising a plurality of credit giving platforms through characteristic information of the user, and further obtains a target credit giving platform matched with the user according to transaction indexes of each credit giving platform in the at least one credit giving platform corresponding to the user and risks matched with the user under the condition that the target credit giving platform corresponding to each user in the user set is obtained and each credit giving platform in the credit giving platform set is matched with at least one user.

Description

User matching method and device, storage medium and electronic equipment

Technical Field

The present disclosure relates to the field of finance, and in particular, to a user matching method, apparatus, storage medium, and electronic device.

Background

In recent years, the affiliated affairs rapidly develop in China, the scale of users is continuously enlarged, and the credit-giving platforms for participating in the affiliated affairs are more and more. The features and requirements among different users are complex and various, the affiliated products provided among different credit giving platforms and business targets to be realized are complex, and business scenes applicable to each credit giving platform are different. Thus, the difficulty of distribution between multiple users and multiple trusted platforms is increasing. How to match a proper user group for the credit platform to achieve the business goal of the credit platform and match a proper credit platform for the user to meet the credit requirements of the user is one of the pain points of how to realize the cooperation of the affiliated matters.

Disclosure of Invention

The embodiment of the specification provides a user matching method, a device, a storage medium and electronic equipment, which can enhance the accuracy of user matching and improve the user matching efficiency. The technical scheme is as follows:

in a first aspect, embodiments of the present disclosure provide a user matching method, where the method includes:

acquiring characteristic information of each user in a user set, wherein the user set comprises a plurality of users;

acquiring at least one trust platform corresponding to the user from a trust platform set according to the characteristic information of the user, wherein the trust platform set comprises a plurality of trust platforms;

and acquiring a target credit giving platform matched with the user according to the transaction index of each credit giving platform in at least one credit giving platform corresponding to the user and the risk matched with the user until the target credit giving platform corresponding to each user in the user set is acquired, wherein each credit giving platform in the credit giving platform set is matched with at least one user.

In a second aspect, embodiments of the present disclosure provide a user matching apparatus, the apparatus including:

the user characteristic module is used for acquiring characteristic information of each user in a user set, and the user set comprises a plurality of users;

The first matching module is used for acquiring at least one trust platform corresponding to the user from a trust platform set according to the characteristic information of the user, wherein the trust platform set comprises a plurality of trust platforms;

and the second matching module is used for acquiring the target trust platform matched with the user according to the transaction index of each trust platform in at least one trust platform corresponding to the user and the risk matched with the user until the target trust platform corresponding to each user in the user set is acquired, and each trust platform in the trust platform set is matched with at least one user.

In a third aspect, the present description provides a computer storage medium storing a plurality of instructions adapted to be loaded by a processor and to perform the above-described method steps.

In a fourth aspect, the present description provides a computer program product storing a plurality of instructions adapted to be loaded by a processor and to perform the above-described method steps.

In a fifth aspect, embodiments of the present disclosure provide an electronic device, which may include: a processor and a memory; wherein the memory stores a computer program adapted to be loaded by the processor and to perform the above-mentioned method steps.

The technical scheme provided by some embodiments of the present specification has the following beneficial effects:

according to the embodiment of the specification, firstly, at least one credit giving platform corresponding to a user is obtained from a credit giving platform set comprising a plurality of credit giving platforms through characteristic information of the user, and further under the condition that a target credit giving platform corresponding to each user in the user set is obtained and each credit giving platform in the credit giving platform set is matched with at least one user, according to the transaction index of each credit giving platform in the at least one credit giving platform corresponding to the user and the risk matched with the user, the target credit giving platform matched with the user is obtained; in other words, in order to solve the complex problem of matching between a large-scale user and a large-scale credit-giving platform in a joint transaction, in the embodiment of the specification, a matching process is split into three stages of a user characteristic information acquisition process, a user and at least one credit-giving platform matching process, and a multi-objective optimization solving process, so that the complexity of the joint transaction, the diversity of user requirements and the diversity of credit-giving platform requirements are abstracted, the user requirements and the credit-giving platform requirements are flexibly configured as configuration items in the large-scale matching problem, the credit-giving platform and the user can be expanded and configured under different scenes, financial system crisis caused by the credit-giving platform in the matching process is avoided through risk control, and the matching between the large-scale user and the credit-giving platform is completed.

Drawings

In order to more clearly illustrate the embodiments of the present description or the technical solutions in the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are only some embodiments of the present description, and other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.

Fig. 1 is a schematic view of a scenario of a user matching method provided in an embodiment of the present disclosure;

fig. 2 is a flow chart of a user matching method according to an embodiment of the present disclosure;

fig. 3 is a schematic flow chart of obtaining at least one trust platform corresponding to a user according to an embodiment of the present disclosure;

fig. 4 is a schematic flow chart of a target trust platform corresponding to a user according to an embodiment of the present disclosure;

fig. 5 is a flow chart of a user matching method according to an embodiment of the present disclosure;

FIG. 6 is a schematic flow chart of acquiring multiple user sets according to an embodiment of the present disclosure;

fig. 7 is a flowchart of a user matching method according to an embodiment of the present disclosure;

Fig. 8 is a schematic structural diagram of a user matching device according to an embodiment of the present disclosure;

fig. 9 is a schematic structural diagram of an electronic device according to an embodiment of the present disclosure.

Detailed Description

The technical solutions in the embodiments of the present specification will be clearly and completely described below with reference to the drawings in the embodiments of the present specification, and it is apparent that the described embodiments are only some embodiments of the present specification, but not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are intended to be within the scope of the present disclosure.

In the description of the present specification, it should be understood that the terms "first," "second," and the like are used for descriptive purposes only and are not to be construed as indicating or implying relative importance. In the description of the present specification, it should be noted that, unless expressly specified and limited otherwise, "comprise" and "have" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those listed steps or elements but may include other steps or elements not listed or inherent to such process, method, article, or apparatus. The specific meaning of the terms in this specification will be understood by those of ordinary skill in the art in the light of the specific circumstances. In addition, in the description of the present specification, unless otherwise indicated, "a plurality" means two or more. "and/or", describes an association relationship of an association object, and indicates that there may be three relationships, for example, a and/or B, and may indicate: a exists alone, A and B exist together, and B exists alone. The character "/" generally indicates that the context-dependent object is an "or" relationship.

The present specification is described in detail below with reference to specific examples.

It should be noted that, information (including but not limited to user equipment information, user personal information, etc.), data (including but not limited to data for analysis, stored data, presented data, etc.), and signals according to the embodiments of the present disclosure are all authorized by the user or are fully authorized by the parties, and the collection, use, and processing of relevant data is required to comply with relevant laws and regulations and standards of relevant countries and regions. For example, user characteristic information, user information, and the like referred to in the present specification are acquired with sufficient authorization.

In recent years, the affiliated affairs rapidly develop in China, the scale of users is continuously enlarged, and the credit-giving platforms for participating in the affiliated affairs are more and more. Credit giving refers to funds directly provided by commercial banks to non-financial institution customers or guarantees made on compensation and payment responsibilities possibly generated by customers in related economic activities, including in-table transactions such as loans, trade financing, bill financing, financing lease, overdraft, various pad money and the like, and out-of-table transactions such as bill acceptance, issuing credit, warranty, reserve credit, credit warranty, bond issuing warranty, borrowing warranty, property sales with overtaking rights, unused irrevocable loan commitments and the like. In other words, a trusted platform is a platform that points to the user to provide funds support directly, or to guarantee the user's credit in the relevant economic activity to a third party, or may be understood as a transaction participant that provides a trusted service.

As shown in fig. 1, a schematic view of a scenario of a user matching method provided in an embodiment of the present disclosure is shown, where the schematic view of the architecture includes: a set of users 101, a matching platform 102 and a set of trusted platforms 103. The user set 101 includes a plurality of users, and the trust platform set 103 includes a plurality of trust platforms, including at least a trust platform 1031, a trust platform 1032, a trust platform 1033, and a trust platform 1034. It should be understood that the number of users and trusted platforms in the user set 101 and the trusted platform set 103 shown in fig. 1 is only illustrative, and the embodiment of the present disclosure is not limited in this respect.

The trusted platform included in the matching platform 102 and the trusted platform set 103 may be understood as a cluster formed by one server or multiple servers, where the matching platform 102 and each trusted platform are configured to receive a request or information through multiple interfaces set, and provide corresponding data or services based on the requested content of the request. The plurality of servers may be a plurality of physical servers, and the plurality of physical servers are independent in hardware; or multiple servers are in multiple virtual servers, the multiple virtual servers are deployed in the same hardware resource pool, and the deployment modes of the virtual servers include but are not limited to: VMware, virtual Box, and Virtual PC. The matching platform 102 is configured to execute a user matching method, and each trust platform in the trust platform set 103 is configured to provide trust services for users based on trust protocols corresponding to each trust platform.

The users corresponding to the user set 101 communicate with the matching platform 102 through the electronic device corresponding to each user. Electronic devices including, but not limited to, physical or virtual servers, mobile Stations (MSs), mobile Terminal devices (Mobile terminals), mobile phones (Mobile telephones), handsets (handsets), and portable devices (portable equipment), bluetooth headsets, smart watches, etc. may communicate with one or more core networks via a radio access network (Radio Access Network, RAN). For example, the electronic device may be a mobile phone (or "cellular" phone), or a portable, pocket, hand-held, computer-built-in or vehicle-mounted mobile device or apparatus, or a communication-enabled smart electronic watch. It is understood that the embodiment of the present disclosure is not limited to the type of electronic device described above.

In the embodiment of the present specification, the electronic device may further be provided with a display device, and the display device may be various devices capable of implementing a display function, for example: the display device may be a cathode ray tube display (Cathode raytubedisplay, CR), a Light-emitting diode display (Light-emitting diodedisplay, LED), an electronic ink screen, a liquid crystal display (Liquid crystal display, LCD), a plasma display panel (Plasma displaypanel, PDP), or the like. The user may utilize the display device on the electronic device to view the displayed text, picture, video, etc., and send an instruction to the electronic device through the display device, for example, by performing long-press or click or double-click operations on the display device of the electronic device, where the instruction includes sending, through the electronic device, the feature information corresponding to the user to the matching platform 102.

In this embodiment of the present disclosure, the matching platform 102 is configured to obtain, through an electronic device corresponding to each user in the user set 102, feature information of the user, where the feature information of the user may be understood as information for characterizing an identity of the user and evaluating a trust qualification of the user; further, the matching platform 102 obtains transaction indexes and trust requirements corresponding to the multiple trust platforms included in the trust platform set 103, for example, transaction indexes and trust requirements corresponding to the trust platform 1031, transaction indexes and trust requirements corresponding to the trust platform 1032, and transaction indexes and trust requirements corresponding to the trust platform 1033; the matching platform 102 obtains at least one trust platform corresponding to the user from the trust platform set 103, for example, trust platforms corresponding to the user 1011 in the trust platform set 103 are trust platform 1031 and trust platform 1032; further, the matching platform 102 obtains a trust platform that ultimately carries out trust for the user from at least one trust platform corresponding to the user, for example, a target trust platform corresponding to the user 1011 is the trust platform 102.

The plurality of terminal devices corresponding to the user set 101, the matching platform 102, and the plurality of trust platforms may communicate through communication links established based on a communication protocol, for example: gRPC Protocol, gRPC is a high-performance, general open-source remote server call (Remote Procedure Call, RPC) framework, which is mainly developed for mobile applications and designed based on HTTP/2 Protocol standards, is developed based on Protocol Buffers (PB) serialization protocols, and supports numerous development languages. The communication link may be a wireless communication link or a wired communication link, for example: the wired communication link may include an optical fiber, twisted pair or coaxial cable, and the WIreless communication link may include a Bluetooth communication link, a WIreless-FIdelity (Wi-Fi) communication link, a microwave communication link, or the like.

Because the characteristics and the requirements among different users are complex and various, and the affiliated products provided among different credit giving platforms and the business targets to be realized are complex, the business scenes applicable to each credit giving platform are different, and the distribution difficulty among a plurality of users and a plurality of credit giving platforms is increased continuously. Therefore, how to match the appropriate user group for the credit platform to achieve the transaction target of the credit platform and match the appropriate credit platform for the user to meet the credit requirements of the user is one of the pain points of how to realize the joint transaction matching.

In one embodiment, as shown in fig. 2, a user matching method is presented for embodiments of the present description, which may be implemented in dependence on a computer program, and may be run on a von neumann system-based user matching device. The computer program may be integrated in the application or may run as a stand-alone tool class application.

Specifically, the user matching method comprises the following steps:

s102, acquiring characteristic information of each user in the user set.

The characteristic information of the user can be understood as information for characterizing the identity of the user and evaluating the creditability of the user. For example, the characteristic information of the user includes at least one or more of the following information: geographic location information, subscriber credit information, interest rate information, and business attribute information. The geographic position information represents the address position of the user, the user credit line information represents the credit line of the user history trusted or the residual credit line or other credit line data, the interest rate information represents the interest rate data such as the interest rate of the user history trusted, and the operational characteristic information represents the operational property of the user, for example, the user works for individual users or on the market.

For another example, the characteristic information of the user may further include user equipment data, user basic data, user lending behavior data, and user risk violation data. The user equipment data includes data such as equipment location class data, activity classification data, application list data and the like, for example, the number of times of application behavior installation in the last three months, the number of times of application uninstallation in the last three months and the like. The user basic data is data such as occupation, academic and the like provided when the user carries out trust evaluation. The user loan behavior data is data generated when the user performs loan behavior, such as loan amount, loan duration, loan times and the like. The risk default data of the user is data generated when the user breaks the default, such as overdue amount, overdue duration and the like. Frequent user position change, multiple downloads of loan APP and the like, relatively worse user qualification, high risk, rejection of the credit giving evaluation of the user by the credit giving platform, in other words, poor credit giving qualification of the user, relatively better user qualification, low risk, passing of the credit giving evaluation of the user by the credit giving platform, namely, good credit giving qualification of the user.

In one embodiment, the method for obtaining the feature information of each user in the user set may be that the user sends the feature information of the user to the terminal device through the terminal device corresponding to the user, and the terminal device sends the feature information of the user to the matching platform. For example, the user sends the characteristic information of the user to the terminal device through an input device or a display device of the terminal device in a touch, remote control, voice or click mode, or the user authorizes the terminal device, so that the terminal device can acquire the characteristic information of the user, for example, the user authorizes the terminal device in a mode of facial recognition or fingerprint recognition, so that the terminal device acquires the characteristic information of the user at a local memory or other platform based on the authorization of the user.

In another embodiment, obtaining feature information of each user in the set of users includes: and acquiring the characteristic information to be screened of the user through the authorization of the user, and acquiring the characteristic information in the characteristic information to be screened through preset conditions. The preset condition may be a privacy protection algorithm or other preset condition. The user authorizes the matching platform so that the matching platform can acquire the characteristic information to be screened of the user, for example, the user authorizes the matching platform in a mode of facial recognition or fingerprint recognition, and the matching platform acquires the characteristic information to be screened at a local memory or other platforms. Further, the matching platform only acquires the characteristic information in the characteristic information to be screened through preset conditions, wherein the characteristic information to be screened comprises the characteristic information and other information related to the user. For example, the user authorizes the corresponding feature information to be screened to include height data, fingerprint data and identity data of the user, and only obtains the identity data in the feature information to be screened as the feature information through preset conditions.

In this embodiment, only the feature information in the feature information to be screened is obtained through the preset condition, so that the privacy of the user can be effectively protected, and the possibility of revealing and damaging the privacy data of the user can be reduced.

S104, according to the characteristic information of the user, acquiring at least one trust platform corresponding to the user from the trust platform set.

And according to the characteristic information corresponding to the user, acquiring at least one credit giving platform corresponding to the user from a plurality of credit giving platforms included in the credit giving platform set, and taking the at least one credit giving platform corresponding to the user as the credit giving platform in the credit giving platform set corresponding to the user.

The embodiment of the specification further comprises cross matching the user set and the credit giving platform set, namely, acquiring at least one credit giving platform corresponding to each user and at least one user corresponding to each credit giving platform, so that the target credit giving platform corresponding to each user in the user set is ensured according to a cross matching result, and each credit giving platform in the credit giving platform set is matched with at least one user.

In one embodiment, at least one trust platform corresponding to the user is obtained from the trust platform set according to the characteristic information of the user and the trust requirement of each trust platform in the trust platform set. Each trust platform has preset trust requirement which can be understood as the condition of screening trust users. For example, the trust platform requires that the user be between 30 and 40 years old, that the user have a fixed asset of over 50 ten thousand, or that the number of violations of the user be less than 10. It will be appreciated that the trust requirements of the trust platforms described above are merely examples, and that trust requirements between each trust platform may be the same or different or partially different.

Specifically, according to the trust requirement of each trust platform in the trust platform set, judging whether the characteristic information of the user meets the trust requirement of the trust platform; if the characteristic information of the user meets the credit giving requirements of the credit giving platform, determining the credit giving platform meeting the credit giving requirements as the credit giving platform corresponding to the user.

Fig. 3 is a schematic flow chart of obtaining at least one trust platform corresponding to a user according to an embodiment of the present disclosure, as shown in fig. 3. The feature information 2011 corresponding to the user 201 is acquired, where the feature information 2011 at least includes geographic location information, user credit line information, interest rate information and business feature information. Further, the trust request corresponding to the trust platform is acquired from the trust platform set 202, for example, the trust request of the trust platform 2021, the trust request of the trust platform 2022, the trust request of the trust platform 2023, the trust request of the trust platform 2024, etc. are acquired. Further, according to the trust requirement of each trust platform, the trust platform that the user 201 meets the trust requirement is evaluated according to the characteristic information 2011 of the user 201, for example, the trust platform 203 corresponding to the user 201 includes the trust platform 2021, the trust platform 2022, the trust platform 2025, and the like.

S106, according to the transaction index of each trust platform in at least one trust platform corresponding to the user and the risk matched with the user, acquiring a target trust platform matched with the user until the target trust platform corresponding to each user in the user set is acquired, and each trust platform in the trust platform set is matched with at least one user.

After the user is matched with at least one credit giving platform, the financial system crisis of the credit giving platform is avoided through active risk control. In S104, the user may be matched with multiple trust platforms, but due to compliance requirements, the user may only be supported by one trust platform, so that an optimal solution of the final trust platform is required, that is, a target trust platform corresponding to the user is selected. In the process, the target solution is calculated for the large-scale users and the large-scale trust platforms at the same time, in the calculation process, the transaction index of each trust platform can be flexibly selected, the target trust platform matched with the user is obtained according to risk control, the target trust platform corresponding to each user in the user set is met, and each trust platform in the trust platform set is matched with at least one user.

In this illustrative embodiment, the transaction indicator of the trusted platform includes at least one of: branch failure rate, balance failure rate, and financial failure rate. It will be appreciated that each transaction indicator also corresponds to a plurality of time granularities, e.g., a plurality of time granularities including month, quarter and year, in other words, the transaction indicators of the trusted platform include monthly branch usage fraction, quarterly branch usage fraction and yearly branch usage fraction, and also include monthly balance fraction, quarterly balance fraction and yearly balance fraction.

Specifically, transaction indexes of each trust platform in at least one trust platform corresponding to a user are obtained; predicting risks that the users meet transaction indexes of the trust platform after being matched with the trust platform corresponding to the users respectively; and acquiring a target credit giving platform matched with the user according to the risk between each credit giving platform in at least one credit giving platform corresponding to the user and the user.

Fig. 4 is a schematic flow chart of a target trust platform corresponding to a user according to an embodiment of the present disclosure, as shown in fig. 4. According to S104, the trust platform 203 corresponding to the user 201 includes trust platform 2021, trust platform 2022, trust platform 2025, trust platform 2028, etc., the transaction index of each trust platform in at least one trust platform corresponding to the user 201 is obtained, the risk that the transaction index of the trust platform is satisfied after the user 201 is matched with the trust platform 2021, trust platform 2022, trust platform 2025, and trust platform 2028 respectively is predicted, and the target trust platform matched with the user 201 is obtained as trust platform 2025 according to the multiple risks and the condition that the target trust platform corresponding to each user in the user set is satisfied and each trust platform matched with at least one user in the trust platform set.

And predicting risks of meeting transaction indexes of the trust platform after the users are respectively matched with the trust platform corresponding to the users through the risk artificial intelligent model. The artificial intelligence model may be a neural network-based risk scoring model. Specifically, a 3-layer neural network is built, and the structure of the 3-layer neural network is as follows: input layer-hidden layer-output layer, wherein the input layer receives a plurality of transaction indexes selected by risk assessment: branch failure rate, balance failure rate and financial failure rate; the hidden layer extracts characteristics from the index data received by the input layer; the output layer maps the features extracted by the hidden layer to risk scores. Taking the change of the branch failure rate of the credit platform after the user is matched with the credit platform as a sample, taking the scores of a plurality of characteristic information of the user as labels, and training the process: one or more convolution layers in the risk artificial intelligent model extract feature vectors from a plurality of feature information of a sample user, map the feature vectors into risk scores, and compare the risk scores with the change of the branch reject ratio of the credit platform after the real user is matched with the credit platform. The connection weight and the threshold value are initialized within the range of (0, 1), then the sample is trained, and the connection weight and the threshold value (chain derivation) are updated after the model output result is obtained so that the loss function is minimized. The loss function may take various forms, such as a 0-1 loss function, a square loss function, an absolute value loss function, a logarithmic loss function, and so forth.

In another embodiment, a target trust platform matched with a user is obtained according to the transaction index of each trust platform in at least one trust platform corresponding to the user and the risk, benefit and scale matched with the user. Until a target credit granting platform corresponding to each user in the user set is obtained, and each credit granting platform in the credit granting platform set is matched with at least one user. The benefits are understood to be the benefits generated by the trust service provided to the user by the trust platform, and the scale is understood to be the specific content of the trust service provided to the user by the trust platform.

For example, the scale refers to the borrowing amount provided by the credit giving platform to the user, and the benefit is understood to be the annual rate corresponding to the borrowing amount provided by the credit giving platform to the user. In the process of matching calculation, the scale and the benefit corresponding to the matching between the trust platform and the user can be set to comprise various schemes, and it can be understood that the association relationship exists among the specific content of the benefit, the specific content of the scale and the numerical value of the risk, and the association relationship exists between the trust platform and the transaction index meeting the trust platform.

In this embodiment, the risk, benefit and scale of matching each trust platform with the user are comprehensively considered to obtain the target trust platform matched with the user until the matching between the large-scale user and the large-scale trust platform is completed, the matching result is more accurate, and the requirements of each user and each trust platform are more satisfied.

In one embodiment, as shown in fig. 5, a user matching method is presented for embodiments of the present description, which may be implemented in dependence on a computer program, and may be run on a von neumann system-based user matching device. The computer program may be integrated in the application or may run as a stand-alone tool class application.

Specifically, the user matching method comprises the following steps:

s202, acquiring an original user set.

The original user set may be understood as a set of users on the matching platform waiting to be matched with the trusted platform. For example, the user logs in the matching platform to authorize the original feature information to the matching platform, waits for the matching platform to match with the credit giving platform according to the original feature information corresponding to the user, and obtains the credit giving service provided by the credit giving platform after the matching is successful.

S204, dividing the original user set into user sets corresponding to each first admission condition according to the plurality of first admission conditions.

The matching platform can divide a part of users meeting the first admission condition in the original user set into user sets corresponding to the first admission condition by setting the first admission condition, and specific contents corresponding to different first admission conditions are not identical. For example, different first admission conditions correspond to different credit data, and according to a plurality of first admission conditions, the original user set is at least divided into three levels of user set with good credit data, general credit data and poor credit data. For another example, according to the data of the current large disk, different first admission conditions correspond to different channels, so that the original user set is divided into user sets corresponding to a plurality of channels.

S206, obtaining the characteristic information of each user in the user set.

Specifically, original characteristic information of each user in the user set is obtained, and characteristic information of each user in the user set is obtained according to channel information corresponding to the first admission condition corresponding to the user set and the original characteristic information of each user.

The original characteristic information of the user can be understood as user basic information acquired by the matching platform after the user authorizes the matching platform, such as geographical position information of the user, user limit information, interest rate information and operational characteristic information, or equipment data of the user, user basic data, user lending behavior data, risk default data of the user and the like. Because of different channels corresponding to different first admission conditions, original characteristic information of users is modified through channel information corresponding to each first admission condition, so that characteristic information of each user in a user set is obtained. For example, the first admission condition corresponds to the user with poor credit data, and provides a guarantee service for the user with poor credit data through a guarantee channel, so that the original feature data of the user set corresponding to the first admission condition includes the poor credit data, but the channel information of the first admission condition provides a guarantee for the user in the user set, so as to obtain the feature information corresponding to each user in the user set; and the other user with better credit information corresponding to the first admission condition is null, so that the original characteristic information and the characteristic information of each user in the user set corresponding to the first admission condition are the same.

In this embodiment, the feature information of each user in the user set is obtained based on the original feature information of each user through the channel information corresponding to the first admission condition, for example, a guarantee channel is used to provide a guarantee for the user in the user set with poor credit investigation data, so that the probability that the user in the user set passes through the credit investigation platform for credit investigation is improved, and the probability that the credit investigation platform set has a systematic financial crisis is reduced.

S208, according to the characteristic information of the user, at least one trust platform corresponding to the user is obtained from the trust platform set.

See S104 above, and will not be described here again.

S210, according to transaction indexes of each trust platform in at least one trust platform corresponding to a user and risks matched with the user, acquiring a target trust platform matched with the user until the target trust platform corresponding to each user in a user set is acquired, wherein each trust platform in the trust platform set is matched with at least one user.

See S106 above, and will not be described again here.

Fig. 6 is a schematic flow chart of acquiring a plurality of user sets according to an embodiment of the present disclosure, as shown in fig. 6. The original user set 301 is acquired, the original user set 301 is divided into a plurality of user sets according to a plurality of first admission conditions, for example, as shown in fig. 3, the original user set 301 is divided into user sets 3011 according to a first admission condition 3021, the original user set 301 is divided into user sets 3012 according to a first admission condition 3022, and the original user set 301 is divided into user sets 3013 according to a first admission condition 3023.

Further, each user set is matched with the trust platform set 303, and each user in the user set corresponds to a target trust platform, and each trust platform in the trust platform set 303 is matched with at least one user in each user set. For example, the set of users 3011 is matched with the set of trust platforms 303 such that each trust platform in the set of trust platforms 303 matches at least one user in the set of users 3011, and the set of users 3012 is matched with the set of trust platforms 303 such that each trust platform in the set of trust platforms 303 matches at least one user in the set of users 3012.

In this embodiment, the reasonability of user allocation among the plurality of trust platforms may be improved by dividing the plurality of original user sets into a plurality of user sets according to the plurality of first admission conditions and matching each user set with the trust platform set. For example, the original user set is divided into two general user sets of credit information data with good credit information data, and the two user sets are matched with the credit platform sets respectively, so that each credit platform is at least matched with users in one user set with good credit information data and at least matched with users in one general user set with credit information data, and the overall risk of the credit platform sets is controlled.

In one embodiment, according to a preset period, acquiring actual data and target data of a transaction index of each trust platform in a trust platform set; according to the actual data and the target data of the transaction index of each credit platform, a plurality of first admission conditions are adjusted to obtain a plurality of second admission conditions; and dividing the original user set into user sets corresponding to each second admission condition according to the plurality of second admission conditions.

Specifically, after the original user set is divided into a plurality of user sets according to a plurality of first admission conditions and each user set is matched with the credit platform set, the matched target credit platform of each user after the matching, and the actual data and the target data of the transaction index of each credit platform are recorded. The transaction index of the trusted platform at least comprises one of the following: branch failure rate, balance failure rate, and financial failure rate. It will be appreciated that each transaction indicator also corresponds to a plurality of time granularities, e.g., a plurality of time granularities including month, quarter and year, in other words, the transaction indicators of the trusted platform include monthly branch usage fraction, quarterly branch usage fraction and yearly branch usage fraction, and also include monthly balance fraction, quarterly balance fraction and yearly balance fraction.

And further adjusting the plurality of first admission conditions according to the actual data and the target data of the transaction index of each credit platform to obtain a plurality of second admission conditions. For example, the plurality of first admission conditions include a small number of times of default, a general number of times of default and a large number of times of default, a matching record of the user set and the credit platform set is obtained according to the first admission conditions, actual data and target data of a transaction index of each credit platform are obtained after a preset period, for example, actual data and target data of a credit platform with poor utilization rate are obtained after a preset period, when a difference between the actual data and the target data of the credit platform is greater than a preset threshold, the plurality of first admission conditions are adjusted to obtain a second admission condition, for example, the plurality of second admission conditions include a small number of times of default and a large number of fixed assets, a general number of times of default and a large number of fixed assets, a small number of times of default and a small number of fixed assets, and the like, namely, the first admission conditions are refined on the basis of the first admission conditions, and the original user set is divided into the user sets corresponding to each second admission condition according to the plurality of second admission conditions.

And matching the user set corresponding to each second admission condition with the trust platform set. The embodiment further comprises obtaining a matching record of the user set and the trust platform set according to the first admission conditions, and matching the user set corresponding to each second admission condition with the trust platform set. For example, when the user set obtained according to the first admission condition is matched with the credit platform set, the user in the user set with better credit data is matched with the target credit platform A, and when the user set corresponding to the second admission condition is matched with the credit platform set, the user is matched with the target credit platform B, so that the risk of the target credit platform B is reduced.

In other words, the embodiment continuously adjusts the matching between the user and the credit platform by dynamically adjusting the specific content of the admission condition and according to the matching record of each time the user set and the credit platform set, thereby improving the rationality of the matching and controlling the risk of the credit platform.

In one embodiment, as shown in fig. 7, a user matching method is presented for embodiments of the present description, which may be implemented in dependence on a computer program, and may be run on a von neumann system-based user matching device. The computer program may be integrated in the application or may run as a stand-alone tool class application.

Specifically, the user matching method comprises the following steps:

s302, acquiring characteristic information of a user.

The feature information of the user is obtained by specifying the admittance condition, the non-admittance condition, the channel admittance condition and the channel information, see S202 and S204, which are not described here.

S304, obtaining at least one corresponding trust platform through preference matching.

The configuration table of the trust platform, that is, the preference of the trust platform, is obtained to obtain at least one trust platform corresponding to the user, see S104, which is not described herein.

S306, calculating a target solution.

And according to the user parameters, the credit platform parameters and the large disc parameters, performing target solution calculation on at least one credit platform corresponding to the user, wherein the target solution calculation is performed on the credit platform corresponding to the user, and the step is S106.

S308, obtaining a target credit giving platform corresponding to the user.

According to the transaction index of each trust platform in at least one trust platform corresponding to the user and the risk matched with the user, a target trust platform matched with the user is obtained, at least one user is matched with each trust platform in the trust platform set, the matching result of the user is recorded, and the characteristic information of the user is dynamically adjusted and obtained based on the periodic task, and is described in S210.

The following are device embodiments of the present specification that may be used to perform method embodiments of the present specification. For details not disclosed in the device embodiments of the present specification, please refer to the method embodiments of the present specification.

Referring to fig. 8, a schematic structural diagram of a user matching device according to an exemplary embodiment of the present disclosure is shown. The user matching means may be implemented as all or part of the device by software, hardware or a combination of both. The user matching means comprises a user characteristics module 801, a first matching module 802 and a second matching module 803.

A user feature module 801, configured to obtain feature information of each user in a user set, where the user set includes a plurality of users;

the first matching module 802 is configured to obtain, according to the feature information of the user, at least one trust platform corresponding to the user from a trust platform set, where the trust platform set includes a plurality of trust platforms;

and the second matching module 803 is configured to obtain a target trust platform matched with the user according to the transaction index of each trust platform in the at least one trust platform corresponding to the user and the risk matched with the user, until the target trust platform corresponding to each user in the user set is obtained, and each trust platform in the trust platform set is matched with at least one user.

In one embodiment, the second matching module 803 includes:

the index acquisition unit is used for acquiring the transaction index of each trust platform in at least one trust platform corresponding to the user;

the risk prediction unit is used for predicting the risk that the user meets the transaction index of the credit platform after being matched with the credit platform corresponding to the user respectively;

the target matching unit is used for acquiring target credit giving platforms matched with the user according to the risk between each credit giving platform in at least one credit giving platform corresponding to the user and the user.

In one embodiment, the second matching module 803 includes:

and the balance matching unit is used for acquiring the target trust platform matched with the user according to the transaction index of each trust platform in at least one trust platform corresponding to the user and the risk, income and scale matched with the user.

In one embodiment, the transaction index of the trusted platform includes at least one of the following: branch failure rate, balance failure rate, and financial failure rate.

In one embodiment, the user matching apparatus further comprises:

the original user module is used for acquiring an original user set;

And the admission dividing module is used for dividing the original user set into user sets corresponding to each first admission condition according to a plurality of first admission conditions.

In one embodiment, user characteristics module 801 includes:

the original feature unit is used for acquiring original feature information of each user in the user set;

and the admission characteristic unit is used for obtaining the characteristic information of each user in the user set according to the channel information corresponding to the first admission condition corresponding to the user set and the original characteristic information of each user.

In one embodiment, the user matching apparatus further comprises:

the period acquisition module is used for acquiring actual data and target data of the transaction index of each trust platform in the trust platform set according to a preset period;

the condition adjustment module is used for adjusting the plurality of first admission conditions according to the actual data and the target data of the transaction index of each trust platform to obtain a plurality of second admission conditions;

and the division adjustment module is used for dividing the original user set into user sets corresponding to each second admission condition according to the plurality of second admission conditions.

In one embodiment, the characteristic information of the user includes at least one of the following: geographic location information, subscriber credit information, interest rate information, and business attribute information.

In one embodiment, user characteristics module 801 includes:

the authorization acquisition unit is used for acquiring the characteristic information to be screened of the user through the authorization of the user;

the preset acquisition unit is used for acquiring the characteristic information in the characteristic information to be screened through preset conditions.

In one embodiment, the first matching module 802 includes:

the feature matching unit is used for acquiring at least one trust platform corresponding to the user from the trust platform set according to the feature information of the user and the trust requirement of each trust platform in the trust platform set.

In one embodiment, the feature matching unit includes:

the requirement judging subunit is used for judging whether the characteristic information of the user meets the credit giving requirements of the credit giving platforms according to the credit giving requirements of each credit giving platform in the credit giving platform set;

and the feature matching subunit is used for determining the trusted platform meeting the trusted requirement as the trusted platform corresponding to the user if the feature information of the user meets the trusted requirement of the trusted platform.

It should be noted that, when the user matching apparatus provided in the foregoing embodiment performs the user matching method, only the division of the foregoing functional modules is used as an example, and in practical application, the foregoing functional allocation may be performed by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules, so as to complete all or part of the functions described above. In addition, the user matching device provided in the above embodiment and the user matching method embodiment belong to the same concept, which embody the detailed implementation process in the method embodiment, and are not described herein again.

The foregoing embodiment numbers of the present specification are merely for description, and do not represent advantages or disadvantages of the embodiments.

The embodiments of the present disclosure further provide a computer storage medium, where a plurality of instructions may be stored, where the instructions are adapted to be loaded by a processor and executed by the processor to perform the user matching method as described in the embodiments of fig. 1 to fig. 6, and the specific execution process may refer to the specific description of the embodiments of fig. 1 to fig. 6, which is not repeated herein.

The present disclosure further provides a computer program product, where at least one instruction is stored, where the at least one instruction is loaded by the processor and executed by the processor to perform the user matching method according to the embodiment shown in fig. 1 to fig. 6, and the specific execution process may refer to the specific description of the embodiment shown in fig. 1 to fig. 6, which is not repeated herein.

Referring to fig. 9, a schematic structural diagram of an electronic device is provided in an embodiment of the present disclosure. As shown in fig. 9, the electronic device 900 may include: at least one processor 901, at least one network interface 904, a user interface 903, memory 905, at least one communication bus 902.

Wherein a communication bus 902 is employed to facilitate a coupled communication between the components.

The user interface 903 may include a Display screen (Display) and a Camera (Camera), and the optional user interface 903 may further include a standard wired interface and a wireless interface.

The network interface 904 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface), among others.

Processor 901 may include one or more processing cores, among other things. The processor 901 connects various portions of the overall server 900 using various interfaces and lines, executing various functions of the server 900 and processing data by executing or executing instructions, programs, code sets, or instruction sets stored in the memory 905, and invoking data stored in the memory 905. Alternatively, the processor 901 may be implemented in hardware in at least one of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), programmable logic array (Programmable Logic Array, PLA). The processor 901 may integrate one or a combination of several of a central processing unit (Central Processing Unit, CPU), an image processor (Graphics Processing Unit, GPU), and a modem, etc. The CPU mainly processes an operating system, a user interface, an application program and the like; the GPU is used for rendering and drawing the content required to be displayed by the display screen; the modem is used to handle wireless communications. It will be appreciated that the modem may not be integrated into the processor 901 and may be implemented by a single chip.

The Memory 905 may include a random access Memory (Random Access Memory, RAM) or a Read-Only Memory (Read-Only Memory). Optionally, the memory 905 includes a non-transitory computer readable medium (non-transitory computer-readable storage medium). The memory 905 may be used to store instructions, programs, code, sets of codes, or sets of instructions. The memory 905 may include a stored program area and a stored data area, wherein the stored program area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playing function, an image playing function, etc.), instructions for implementing the above-described respective method embodiments, etc.; the storage data area may store data or the like involved in the above respective method embodiments. The memory 905 may also optionally be at least one storage device located remotely from the processor 901. As shown in fig. 9, an operating system, a network communication module, a user interface module, and a user matching application program may be included in the memory 905, which is a type of computer storage medium.

In the electronic device 900 shown in fig. 9, the user interface 903 is mainly used for providing an input interface for a user, and acquiring data input by the user; and processor 901 may be operable to invoke a user matching application stored in memory 905 and to specifically perform the following operations:

In one embodiment, the processor 901 executes the transaction index according to each trust platform in the at least one trust platform corresponding to the user and the risk matched with the user, obtains the target trust platform matched with the user, and specifically executes:

acquiring a transaction index of each trust platform in at least one trust platform corresponding to the user;

predicting risks that the users meet transaction indexes of the trust platform after being respectively matched with the trust platform corresponding to the users;

And acquiring a target credit giving platform matched with the user according to the risk between each credit giving platform in at least one credit giving platform corresponding to the user and the user.

and acquiring a target trust platform matched with the user according to the transaction index of each trust platform in at least one trust platform corresponding to the user and the risk, income and scale matched with the user.

In one embodiment, before executing the step of obtaining the feature information of each user in the user set, the processor 901 further executes:

acquiring an original user set;

and dividing the original user set into user sets corresponding to each first admission condition according to a plurality of first admission conditions.

In one embodiment, the processor 901 performs the obtaining the feature information of each user in the user set, specifically performing:

Acquiring original characteristic information of each user in a user set;

and obtaining the characteristic information of each user in the user set according to the channel information corresponding to the first admission condition corresponding to the user set and the original characteristic information of each user.

In one embodiment, the processor 901 executes the transaction index according to each trust platform in the at least one trust platform corresponding to the user and the risk matched with the user, obtains the target trust platform matched with the user until the target trust platform corresponding to each user in the user set is obtained, and after each trust platform in the trust platform set is matched with at least one user, further executes:

acquiring actual data and target data of the transaction index of each trust platform in the trust platform set according to a preset period;

according to the actual data and the target data of the transaction index of each trust platform, adjusting the plurality of first admission conditions to obtain a plurality of second admission conditions;

and dividing the original user set into user sets corresponding to each second admission condition according to the plurality of second admission conditions.

acquiring feature information to be screened of the user through the authorization of the user;

and acquiring the characteristic information in the characteristic information to be screened through a preset condition.

In one embodiment, the processor 901 executes the step of obtaining at least one trust platform corresponding to the user from the trust platform set according to the feature information of the user, and specifically executes the steps of:

and acquiring at least one trust platform corresponding to the user from the trust platform set according to the characteristic information of the user and the trust requirement of each trust platform in the trust platform set.

In one embodiment, the processor 901 executes the trust request according to the feature information of the user and each trust platform in the trust platform set, obtains at least one trust platform corresponding to the user from the trust platform set, and specifically executes the steps of:

judging whether the characteristic information of the user meets the credit giving requirements of the credit giving platforms according to the credit giving requirements of each credit giving platform in the credit giving platform set;

if the characteristic information of the user meets the trust request of the trust platform, determining the trust platform meeting the trust request as the trust platform corresponding to the user.

Those skilled in the art will appreciate that implementing all or part of the above-described methods in accordance with the embodiments may be accomplished by way of a computer program stored on a computer readable storage medium, which when executed may comprise the steps of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a read-only memory, a random access memory, or the like.

The foregoing disclosure is only illustrative of the preferred embodiments of the present invention and is not to be construed as limiting the scope of the claims, which follow the meaning of the claims of the present invention.

Claims

1. A method of user matching, the method comprising:

2. The method for matching users according to claim 1, wherein the obtaining the target trusted platform matched by the users according to the transaction index of each trusted platform in the at least one trusted platform corresponding to the users and the risk matched by the users comprises:

3. The method for matching users according to claim 1, wherein the obtaining the target trusted platform matched by the users according to the transaction index of each trusted platform in the at least one trusted platform corresponding to the users and the risk matched by the users comprises:

4. The user matching method of claim 1, wherein the transaction index of the trusted platform comprises at least one of the following: branch failure rate, balance failure rate, and financial failure rate.

5. The method for matching users according to claim 1, further comprising, before the step of obtaining the feature information of each user in the user set:

acquiring an original user set;

6. The method for matching users according to claim 5, wherein the obtaining feature information of each user in the user set includes:

acquiring original characteristic information of each user in a user set;

7. The method for matching users according to claim 5, wherein the step of obtaining the target trusted platform matched by the user according to the transaction index of each trusted platform in the at least one trusted platform corresponding to the user and the risk matched with the user until the target trusted platform corresponding to each user in the user set is obtained, and after each trusted platform in the trusted platform set is matched with at least one user, further comprises:

8. The user matching method of claim 1, wherein the characteristic information of the user includes at least one of: geographic location information, subscriber credit information, interest rate information, and business attribute information.

9. The method for matching users according to claim 1, wherein the obtaining feature information of each user in the user set includes:

10. The method for matching users according to claim 1, wherein the step of obtaining at least one trust platform corresponding to the user from a trust platform set according to the feature information of the user includes:

11. The method for matching users according to claim 10, wherein the step of obtaining at least one trust platform corresponding to the user from the trust platform set according to the characteristic information of the user and the trust requirement of each trust platform in the trust platform set includes:

12. A user matching apparatus, the apparatus comprising:

13. A computer storage medium storing a plurality of instructions adapted to be loaded by a processor and to perform the method steps of any one of claims 1 to 11.

14. A computer program product storing a plurality of instructions adapted to be loaded by a processor and to perform the method steps of any of claims 1 to 11.

15. An electronic device, comprising: a processor and a memory; wherein the memory stores a computer program adapted to be loaded by the processor and to perform the method steps of any of claims 1-11.