WO2019019798A1

WO2019019798A1 - Loan product query device and method, and computer readable storage medium

Info

Publication number: WO2019019798A1
Application number: PCT/CN2018/089189
Authority: WO
Inventors: 何兵
Original assignee: 平安科技（深圳）有限公司
Priority date: 2017-07-25
Filing date: 2018-05-31
Publication date: 2019-01-31
Also published as: CN107871276A

Abstract

Disclosed is a loan product query device. The device comprises a memory, a processor, and a loan product query program which is stored in the memory and is able to run on the processor. The loan product query program implements the following steps when being executed by the processor: receiving a query request sent by a user and obtaining a loan condition and user information from the query request; searching loan products provided by loan mechanisms of the loan product database for a loan product which conforms to the loan condition; searching a loan user database for a similar user of the user according to the user information; and calculating a loan success rate of the matched loan product in the similar users and recommending the loan product with the loan success rate satisfying a preset condition to the user. The present application further provides a loan product query method and a computer readable storage medium, for solving the technical problem in the prior art of low query efficiency among loan products.

Description

Query device, method and computer readable storage medium for loan product

The present application is based on the priority of the Chinese Patent Application entitled "Inquiring Device, Method and Computer-Readable Storage Medium for Loan Products", which is filed on July 25, 2017, with the application number of 201710614464.5, which is filed on July 25, 2017. The entire content is incorporated herein by reference.

Technical field

The present application relates to the field of electronic information technology, and in particular, to a device, a method, and a computer readable storage medium for querying a loan product.

Background technique

At present, there are many types of loan products on the market. When users use loan products to find suitable loan products, they are not sure which loan products are suitable for them. It is often difficult to find the most suitable products from a large number of loan products. It takes a lot of time to choose a loan product, and the loan product selected by this untargeted selection method tends to have a low loan success rate when actually applying for a loan. It is necessary to re-find a large number of loan products to find and try again. Lending, resulting in inefficiency and poor user experience.

Summary of the invention

The present application provides a query device, a method and a computer readable storage medium for a loan product, the main purpose of which is to solve the technical problem of low query efficiency of loan products in the prior art.

To achieve the above object, the present application provides a query device for a loan product, the device comprising: a memory, a processor, and a query program of the loan product stored on the memory and operable on the processor, the loan When the product's query program is executed by the processor, the following steps are implemented:

Receiving a query request of the loan product sent by the user, and obtaining the loan condition and the user information from the query request;

Finding loan products that meet the loan conditions from the loan products provided by the loan institutions of the loan product database;

Finding a similar user of the user from the loan user database according to the user information;

Calculating the loan success rate of the matched loan product in the similar user found, and recommending the loan product whose loan success rate meets the preset condition to the user.

In addition, in order to achieve the above object, the present application further provides a method for querying a loan product, the method comprising:

In addition, in order to achieve the above object, the present application further provides a computer readable storage medium, where the query program of a loan product is stored, and the query program of the loan product is implemented by the processor as described above. The steps of the method of querying the loan product.

The query device, the method and the computer readable storage medium of the loan product provided by the application receive the query request of the loan product sent by the user, obtain the loan condition and user information selected by the user from the query request, and find the loan product database. The loan product matching the loan condition, and then searching for the user between the user information and the user information of the user that is larger than a preset threshold from the loan user database, and searching the found user as a similar user, and calculating the loan product found above. In the loan success rate of these similar users, the eligible loan product is recommended to the user. In this way, the user only needs to select the loan condition and the user information, and the system can automatically find the matching loan according to the above loan condition. Products, and according to the loan success rate of these products in the user database of the loan user, recommend the loan products that meet the conditions for the user, and realize the targeted recommendation of the appropriate loan products for the users according to the actual situation of the users, saving the savings. Users find loan products Time, and in this way targeted recommendation, greatly enhancing the user's success rate loans.

DRAWINGS

1 is a schematic diagram of a preferred embodiment of an inquiry device for a loan product of the present application;

2 is a flow chart of a first embodiment of a method for querying a loan product of the present application.

The object of the present application, the features and advantages of the present application will be further described with reference to the accompanying drawings.

Detailed ways

It is understood that the specific embodiments described herein are merely illustrative of the application and are not intended to be limiting.

The application provides a query device for a loan product. Referring to FIG. 1, a schematic diagram of a preferred embodiment of a query device for a loan product of the present application is shown.

In this embodiment, the query device of the loan product may be a PC (Personal Computer), or may be a terminal device such as a smart phone, a tablet computer, or a portable computer.

The inquiry device of the loan product includes a memory 11, a processor 12, a communication bus 13, and a network interface 14. The memory 11 includes at least one type of readable storage medium including a flash memory, a hard disk, a multimedia card, a card type memory (for example, SD or DX memory, etc.), a random access memory (RAM), and a static memory. Random access memory (SRAM), read only memory (ROM), electrically erasable programmable read only memory (EEPROM), programmable read only memory (PROM), magnetic memory, magnetic disk, optical disk, and the like.

The memory 11 may in some embodiments be an internal storage unit of the inquiry device of the loan product, such as the hard disk or memory of the inquiry device of the loan product. The memory 11 may also be an external storage device of the inquiry device of the loan product in other embodiments, such as a plug-in hard disk equipped with a query device of the loan product, a smart memory card (SMC), and a secure digital (Secure) Digital, SD) cards, flash cards, etc. Further, the memory 11 may also include an internal storage unit of the inquiry device of the loan product and an external storage device. The memory 11 can be used not only for storing application software of a query device installed in a loan product and various types of data, such as codes of a query program of a loan product, but also for temporarily storing data that has been output or is to be output.

The processor 12, in some embodiments, may be a Central Processing Unit (CPU), controller, microcontroller, microprocessor or other data processing chip for running program code or processing stored in the memory 11. Data, such as the query procedure for executing loan products.

Communication bus 13 is used to implement connection communication between these components.

The network interface 14 can optionally include a standard wired interface, a wireless interface (such as a WI-FI interface), and is typically used to establish a communication connection between the device and other electronic devices.

Figure 1 shows only the query device for the loan product with components 11-14 and the query program for the loan product, but it should be understood that not all of the illustrated components are required to be implemented, and that more or less may be implemented instead. Component.

Optionally, the device may further include a user interface, the user interface may include a display, an input unit such as a keyboard, and the optional user interface may further include a standard wired interface and a wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch sensor, or the like. The display may also be suitably referred to as a display screen or display unit for displaying information processed in the inquiry device of the loan product and a user interface for displaying the visualization.

In the device embodiment shown in FIG. 1 , the memory 11 as a computer storage medium may include an operating system and a query program of the loan product; the network interface 14 is mainly used to connect the user terminal and perform data communication with the user terminal; When the processor 12 executes the query program of the loan product stored in the memory 11, the following steps are implemented:

The device proposed in this embodiment may be a server, and the server establishes a communication connection with a client installed on the user terminal, the device is deployed with a loan product database and a loan user database, wherein the loan product database stores the loan provided by the loan institution. Relevant data of products, among which lending institutions include third-party lending institutions. The relevant data of loan products include but are not limited to the following contents: loan institution, loan quota interval, loan interest rate interval, loan term interval, application process, application conditions, loan Agreement, etc. The loan user database mainly stores purchases recorded after the loan product is inquired through the device and purchased after the loan is purchased, for example, the purchase is successful or the purchase fails, and the recommended amount of the loan product and the number of users who successfully purchase the loan product are recommended. For the data maintenance in the loan user database, the data implementation provided by the above lending institution can be provided.

In this embodiment, a loan information inquiry interface may be set in the client, the interface is provided with a loan condition input box and a user information input box, and the loan condition input box and the user information input box may also be set as a drop-down box, and the user may The information that matches the information of the user is selected, wherein the user information includes but is not limited to the following information items: name, identity information, gender, age, income, education, occupation, and total assets of the individual. The above identity information may be information such as an identity card number that can be used to uniquely identify the user. The loan conditions include the loan amount and the loan term. Generally, the loan amount and loan term entered by the user are specific values. After the user selects the loan condition and the user information through the client, the query request for the loan product is generated and sent to the inquiry device of the loan product. After receiving the query request, the querying device obtains the loan condition and the user information from the query request. Then, according to the loan amount and loan term selected by the user, the eligible loan product is searched from the loan product database, wherein the loan amount and the term of the loan product in the database all contain a certain range of interval values, when searching for the loan product, According to the loan amount and the loan term, the loan product in the database is traversed, and the loan product range is selected to meet the loan amount selected by the user and the loan term interval meets the loan term selected by the user. The found loan products are cached in the memory 11, for example, an ID for identification is set for each loan product, and the ID of the found loan product is cached in the memory 11.

Then, a similar user of the user is looked up from the loan user database maintained in the device. There are various ways to find a similar user of the user from the loan user database, and two of the embodiments are described below. Hereinafter, for convenience of explanation, the user in the loan user database is simply referred to as a historical user, and the user who sends the query request is simply referred to as the requesting user.

In the first mode, each information item in the user information of the user is scored according to a preset scoring rule; and the user's score is calculated according to the score of each information item and the preset weight of each information item. Finding a similar user of the user from the loan user database based on the calculated score.

The device assigns different weights to each of the above information items in advance, and the weight is determined according to the effect of the information item on the success of the loan. The greater the effect, the greater the weight assigned to the information item, and all the information items. The sum of the weights is 1. For example, the weights for the above six information items, gender, age, education, occupation, income, and total assets are 0.1, 0.1, 0.1, 0.2, 0.2, and 0.3, respectively.

For each information item, the interval is divided according to the possible values of the information item. For example, the gender is divided into {male, female}, and the age is divided into {18 years old, 18 years old to 25 years old, 25 years old to 35 years old. 35 to 45 years old, 45 to 55 years old, 55 years old or older}, education can be divided into {literate, junior high school and below, high school, university, graduate students and above}.

In this embodiment, each information item is divided into a plurality of information item intervals, and each information item interval is scored. When the information item in the user information is scored, the information item interval to which the information item belongs is determined, and the preset score corresponding to the information item interval is used as the user's score on the information item. The following is a percentage system. For example, the education is divided into the above five information items. The scores set for the five information items are: illiterate 30 points, junior high school and below 60 points, high school 70 points, and university 80 points. , graduate students and above 90 points. Assuming that the requested user's academic qualification is a university, the score on the information item of the academic qualification is 80 points. The scores of the respective information items of the user information are respectively obtained in the above manner, and then the score of the user is calculated.

Assume that the user information includes n items of information, score information items of the i-th to _i S, i th preset information item is weighted K _i, then the _total score S can be calculated according to the formula of the user:

Where 1 ≤ i ≤ n,

The historical user stored in the loan user database also has a score calculated according to the above formula. When searching for a similar user of the requesting user, the historical user who has a difference from the score of the requesting user that is smaller than the preset difference is used as the requesting user. Similar users.

In the above embodiment, the information item section divided for each information item may be scored in advance according to the loan situation of the historical user. Moreover, as the number of historical users stored in the loan user database increases, the score of the information item interval can be dynamically adjusted.

It can be understood that the name and identity information (such as the ID number) cannot reflect the degree of similarity between the user information and the success rate of the user's application for the loan, and therefore is not used as a basis for finding similar users.

Method 2, determining an information item interval to which each information item of the user belongs;

Filtering users in the loan user database according to the determined information item interval to obtain users whose information items meet the determined information item interval;

The filtered user is taken as a similar user of the user.

In this embodiment, the information item section to which each information item belongs is determined according to the user information of the requesting user. A historical user whose information item meets the above information item interval is searched from the database as a similar user of the requesting user.

For example, the user information of the requesting user is: male is male, age is 32, education is master's degree, occupation is doctor, income is 10,000/year, and personal total assets are 100,000. Further, the information item sections to which the user information belongs are identified: the gender belongs to the interval {male}, the age belongs to the interval {25 to 35 years old, and the education belongs to the interval {graduate and above}. According to the information item interval confirmed above, the qualified historical users are selected from the loan user database, and specifically, the information items are screened hierarchically according to each information item. Specifically, all historical users who meet the gender as the male are selected in the database, and then The users who are aged 25 to 35 are selected from the screening results, and so on, until the historical users who match the information items of the requesting user are selected.

The manner of obtaining the similar user of the requesting user is only for example. In other embodiments, other algorithms may be used to search for a similar user from the historical user as a similar user.

After finding similar users, the number of applications of the loan products found in the loan product database and the number of successful purchases are counted; the recommended success rate of the loan products is calculated according to the number of applications and the number of successful purchases, and the success rate of the loan is the highest. The loan product is recommended to the user.

For example, according to the loan conditions of the user, there are ten matching loan products found in the loan product database, and the loan product A is taken as an example. Among the statistically similar users, the loan product A is recommended for the user and the user applies to the lending institution. The number of users of the loan product A, that is, the number of applications for it, and then count the number of users who apply for the loan product A and the final loan is successful, that is, the number of successful purchases, and the number of successful purchases in the number of applications is the loan. The recommended success rate of Product A, in this way, calculates the loan success rate of the loan product found in the loan product database.

In this embodiment, recommending the loan product that meets the preset condition to the user may include: recommending the loan product with the highest loan success rate to the user, or selecting a plurality of loan products with a loan success rate greater than a preset threshold. It is recommended to the user, and the user chooses the most suitable one.

As an implementation manner, if there are multiple loan products with the highest loan success rate, the lending institution that obtains the plurality of loan products is obtained, and it is determined whether, among the plurality of loan products, the lending institution belongs to the default lending institution. The loan product, if any, recommends the loan product belonging to the default lending institution to the user. If not, the plurality of loan products are recommended to the user, and the user selects according to the need. In this way, it is possible to preferably recommend the loan product of the lending institution set by the system; or, as another implementation manner, the plurality of loan products with a loan success rate greater than a preset threshold according to the loan success rate from high to low Arranging sequentially, and recommending the plurality of loan products to the user, the user may according to the loan success rate and collect related information displayed in the loan product, such as a loan institution, a loan amount interval, a loan interest rate interval, a loan term interval, Appropriate loan products are selected for the application process, application conditions, loan agreement, etc.

After receiving the recommended loan product, the user may initiate a loan application to the lending institution based on the platform provided by the third-party platform or the corresponding lending institution, and the lending institution will review the user's data and provide a corresponding loan interest rate. If the user's loan is successful, the result can be fed back to the device through the client, so that the device maintains the loan user database through the received loan result. Or the third party lending institution feeds back the loan result to the device after the user loan is successful, and the device updates the user loan result to the loan user database.

The query device for the loan product proposed in this embodiment receives the query request of the loan product sent by the user, obtains the loan condition and user information selected by the user from the query request, and finds the loan product matching the loan condition from the loan product database. And then, from the loan user database, look up the user between the user information and the user information of the user that is larger than a preset threshold, and use the found user as a similar user to calculate the loan of the above-mentioned found loan product among the similar users. Success rate, recommend eligible loan products to users. In this way, the user only needs to select loan conditions and user information, and the system can automatically find matching loan products according to the above loan conditions, and according to the loan user database. The success rate of the loan for these products by the historical user loans, for the user to recommend the loan products that meet the conditions for the successful loan, realizes the targeted recommendation of the appropriate loan products for the users according to the actual situation of the users, and saves the time for the users to find the loan products. And through this targeting The recommended way to greatly improve the user's success rate loans.

Further, in another embodiment, the processor is further configured to execute a query procedure of the loan product, after the step of searching for the loan product that meets the loan condition from the loan product provided by each lending institution of the loan product database, The following steps are also implemented:

Obtaining the identity information of the user from the user information, and querying, according to the identity information, the personal credit level of the user from the credit information database;

And filtering, according to the personal credit rating, the found loan product that meets the loan condition to filter out the loan product that does not match the personal credit rating, and executing the calculated matching loan based on the filtered loan product. The step of recommending, by the product, the loan success rate among the similar users, and recommending the loan product whose loan success rate meets the preset condition to the user.

In this embodiment, since different loan products have different requirements on the credit level of the user, after finding the loan product matching the loan condition from the loan product database, according to the identity information in the user information, such as the ID number, the credit information is obtained. The data is searched for the credit level of the user, and the loan product whose credit rating is higher than the credit rating of the user is filtered out, and the matched loan product is calculated according to the filtered loan product. The success rate of the loan to a similar user, for example, 10 matching loan products found, checked by the credit rating of the user's credit rating and the loan product, and the loan with the credit level mismatch is deleted. The product, assuming that there are only 3 remaining after filtering, then in the subsequent calculation of the loan success rate, it is only necessary to calculate the loan success rate of the three loan products among similar users.

Further, in other embodiments, if the loan condition includes a loan amount and a loan term, the identity information of the user is obtained from the user information, and the information is queried from the credit database based on the identity information. Before the step of the user's personal credit level, it is first determined whether the loan amount in the loan condition is greater than a preset amount, and if so, obtaining the identity information of the user from the user information, based on the identity information from the credit information database The step of querying the user's personal credit rating, if not, performing the step of finding a similar user. In the case of a small loan amount, the personal credit information of the user may not be checked to improve the user's loan success rate.

Optionally, in other embodiments, the query program of the loan product may also be divided into one or more modules, one or more modules are stored in the memory 11 and executed by one or more processors (this implementation) The example is executed by the processor 12) to complete the application. A module referred to in this application refers to a series of computer program instruction segments capable of performing a specific function, and is more suitable than the program for describing the execution process of the message pushing device in the inquiry device of the loan product.

For example, in an embodiment, the query program of the loan product may be divided into an acquisition module, a first query module, a second query module, a calculation module, and a recommendation module, wherein the acquisition module is configured to receive a loan product sent by the user. The query request, the loan condition and the user information are obtained from the query request; the first query module is configured to search for a loan product that meets the loan condition from the loan product provided by each lending institution of the loan product database, The second query module is configured to search for a similar user of the user from the loan user database according to the user information, where the calculating module is configured to calculate a loan success rate of the matched loan product in the similar user that is found, The recommendation module is configured to recommend the loan product whose loan success rate meets the preset condition to the user.

In addition, the present application also provides a method for querying a loan product. Referring to FIG. 2, it is a flowchart of a first embodiment of a method for querying a loan product of the present application.

In this embodiment, the method for querying the loan product includes:

Step S10: Receive a query request of the loan product sent by the user, and obtain loan conditions and user information from the query request.

Step S20: Find a loan product that meets the loan condition from the loan products provided by each loan institution of the loan product database;

Step S30, searching for a similar user of the user from the loan user database according to the user information;

Step S40: Calculate the loan success rate of the matched loan product in the similar user that is found, and recommend the loan product whose loan success rate meets the preset condition to the user.

The method proposed in this embodiment may be executed by a server, and the server establishes a communication connection with a client installed on the user terminal, where the loan product database and the loan user database are deployed, wherein the loan product database stores the loan. Relevant data on loan products provided by the organization. The loan institutions include third-party lending institutions. The relevant data of loan products include but are not limited to the following contents: loan institutions, loan quota intervals, loan interest rate intervals, loan term intervals, application procedures, Application conditions, loan agreement, etc. The loan user database mainly stores purchases recorded after the user queries the loan product through the server and purchases the loan, for example, the purchase success or the purchase failure, and counts the recommended amount of the loan product and the number of users who successfully purchase the loan product among the recommended users. For the data maintenance in the loan user database, the data implementation provided by the above lending institution can be provided.

In this embodiment, the user may set a loan information query interface in the client, the interface is provided with a loan condition input box and a user information input box, and the loan condition input box and the user information input box may also be set as a drop-down box, the user Information from which the user's information can be selected can be selected, wherein the user information includes, but is not limited to, the following information items: name, identity information, gender, age, income, education, occupation, and personal total assets. The above identity information may be information such as an identity card number that can be used to uniquely identify the user. The loan conditions include the loan amount and the loan term. Generally, the loan amount and loan term entered by the user are specific values. After the user selects the loan condition and the user information through the client, the query request for the loan product is generated and sent to the inquiry method of the loan product. After receiving the query request, the query method obtains the loan condition and the user information from the query request. Then, according to the loan amount and loan term selected by the user, the eligible loan product is searched from the loan product database, wherein the loan amount and the term of the loan product in the database all contain a certain range of interval values, when searching for the loan product, According to the above loan amount and the loan term, traverse the loan products in the database, select the loan product that meets the loan quota selected by the user, the loan term interval meets the loan term selected by the user, and caches the found loan product, for example, for each loan product. A loan product is set to identify the ID and cache the ID of the loan product found.

For each information item, the interval is divided according to the possible values of the information item. For example, the gender is divided into {male, female}, and the age is divided into {18 years old, 18 years old to 25 years old, 25 years old to 35 years old. 35 to 45 years old, 45 to 55 years old, 55 years old or older}, education can be divided into {literacy, junior high school and below, high school, university, graduate students and above}.

Where 1 ≤ i ≤ n,

The filtered user is taken as a similar user of the user.

For example, the user information of the requesting user is: male is male, age is 32, education is master's degree, occupation is doctor, income is 10,000/year, and personal total assets are 100,000. Further, each information item section to which the user's information belongs is confirmed: the gender belongs to the interval {male}, the age belongs to the interval {25 to 35 years old, and the education belongs to the interval {graduate and above}. According to the information item interval confirmed above, the qualified historical users are selected from the loan user database, and specifically, the information items are screened hierarchically according to each information item. Specifically, all historical users who meet the gender as the male are selected in the database, and then The users who are aged 25 to 35 are selected from the screening results, and so on, until the historical users who match the information items of the requesting user are selected.

After receiving the recommended loan product, the user may initiate a loan application to the lending institution based on the platform provided by the third-party platform or the corresponding lending institution, and the lending institution will review the user's data and provide a corresponding loan interest rate. If the user's loan is successful, the result can be fed back to the server through the client, so that the server can maintain the loan user database through the received loan result. Or, after the user loan is successful, the third-party lending institution feeds back the loan result to the server, and the server updates the user loan result to the loan user database.

The query method for the loan product proposed in this embodiment receives the query request of the loan product sent by the user, obtains the loan condition and user information selected by the user from the query request, and finds the loan product matching the loan condition from the loan product database. And then, from the loan user database, look up the user between the user information and the user information of the user that is larger than a preset threshold, and use the found user as a similar user to calculate the loan of the above-mentioned found loan product among the similar users. Success rate, recommend eligible loan products to users. In this way, the user only needs to select loan conditions and user information, and the system can automatically find matching loan products according to the above loan conditions, and according to the loan user database. The success rate of the loan for these products by the historical user loans, for the user to recommend the loan products that meet the conditions for the successful loan, realizes the targeted recommendation of the appropriate loan products for the users according to the actual situation of the users, and saves the time for the users to find the loan products. And through this targeting Sexual recommendation methods greatly improve the user's loan success rate.

Further, in another embodiment, after step S20, the method further includes the following steps:

In this embodiment, since different loan products have different requirements on the credit level of the user, after finding the loan product matching the loan condition from the loan product database, according to the identity information in the user information, such as the ID number, the credit information is obtained. The data is searched for the credit level of the user, and the loan product whose credit rating is higher than the credit rating of the user is filtered out, and the matched loan product is calculated according to the filtered loan product. The success rate of the loan among the similar users, for example, 10 matching loan products found in step S20, and the credit level of the user's credit rating and the demand for the loan product are checked, and the credit level is deleted. For mismatched loan products, assuming only 3 remaining after filtering, then in the subsequent calculation of the loan success rate, it is only necessary to calculate the loan success rate of the three products among similar users.

Further, in other embodiments, if the loan condition includes a loan amount and a loan term, the identity information of the user is obtained from the user information, and the information is queried from the credit database based on the identity information. Before the step of the user's personal credit level, it is first determined whether the loan amount in the loan condition is greater than a preset amount, and if so, obtaining the identity information of the user from the user information, based on the identity information from the credit information database The step of querying the personal credit level of the user is performed, otherwise, step S30 is performed. In the case of a small loan amount, the personal credit information of the user may not be checked to improve the user's loan success rate.

In addition, the embodiment of the present application further provides a computer readable storage medium, where the query program of the loan product is stored on the computer readable storage medium, and the query program of the loan product is executed by the processor to:

Further, when the query program of the loan product is executed by the processor, the following operations are also implemented:

Determining an information item interval to which each information item in the user information of the user belongs;

Calculating a similarity between the user in the loan user database and the user according to the information item interval and the weight assigned to each information item, and searching for a similarity greater than a preset threshold according to the calculated similarity as a similar user .

Counting the number of applications and the number of successful purchases of the loan product found in the loan product database among the similar users;

Calculating the recommended success rate of the loan product according to the number of applications and the number of successful purchases, and recommending the loan product with the highest loan success rate to the user.

It is to be understood that the term "comprises", "comprising", or any other variants thereof, is intended to encompass a non-exclusive inclusion, such that a process, apparatus, article, or method that comprises a series of elements includes those elements. It also includes other elements not explicitly listed, or elements that are inherent to such a process, device, item, or method. An element that is defined by the phrase "comprising a ..." does not exclude the presence of additional equivalent elements in the process, the device, the item, or the method that comprises the element.

The serial numbers of the embodiments of the present application are merely for the description, and do not represent the advantages and disadvantages of the embodiments. Through the description of the above embodiments, those skilled in the art can clearly understand that the foregoing embodiment method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be through hardware, but in many cases, the former is better. Implementation. Based on such understanding, the technical solution of the present application, which is essential or contributes to the prior art, may be embodied in the form of a software product stored in a storage medium (such as ROM/RAM as described above). , a disk, an optical disk, including a number of instructions for causing a terminal device (which may be a mobile phone, a computer, a server, or a network device, etc.) to perform the methods described in the various embodiments of the present application.

The above is only a preferred embodiment of the present application, and is not intended to limit the scope of the patent application, and the equivalent structure or equivalent process transformations made by the specification and the drawings of the present application, or directly or indirectly applied to other related technical fields. The same is included in the scope of patent protection of this application.

Claims

A query device for a loan product, comprising: a memory, a processor, and a query program of a loan product stored on the memory and operable on the processor, the query of the loan product The program implements the following steps when executed by the processor:

Receiving a query request of the loan product sent by the user, and obtaining the loan condition and the user information from the query request;

Finding loan products that meet the loan conditions from the loan products provided by the loan institutions of the loan product database;

Finding a similar user of the user from the loan user database according to the user information;

Calculating the loan success rate of the matched loan product in the similar user found, and recommending the loan product whose loan success rate meets the preset condition to the user.
The inquiring device for a loan product according to claim 1, wherein the processor is further configured to execute an inquiry procedure of the loan product to find a match in a loan product provided by each lending institution of the loan product database. After the steps of the loan product of the loan condition, the following steps are also implemented:

Obtaining the identity information of the user from the user information, and querying, according to the identity information, the personal credit level of the user from the credit information database;

And filtering, according to the personal credit rating, the found loan product that meets the loan condition to filter out the loan product that does not match the personal credit rating, and executing the calculated matching loan based on the filtered loan product. The step of recommending, by the product, the loan success rate among the similar users, and recommending the loan product whose loan success rate meets the preset condition to the user.
The query program apparatus for a loan product according to claim 1, wherein said step of searching for a similar user of said user from said loan user database based on said user information comprises:

Rate each information item in the user information of the user according to a preset scoring rule;

Calculating the score of the user according to the scores of the information items and the preset weights of the information items;

Finding similar users of the user from the loan user database based on the calculated score.
The inquiring device for a loan product according to claim 1, wherein the loan product in which the matching loan product is found in the similar user and the loan success rate meets the preset condition is calculated. The steps recommended to the user include:

Counting the number of applications and the number of successful purchases of the loan product found in the loan product database among the similar users;

Calculating the recommended success rate of the loan product according to the number of applications and the number of successful purchases, and recommending the loan product with the highest loan success rate to the user.
The inquiring device for a loan product according to claim 2, wherein the loan product in which the matching loan product is found in the similar user, and the loan success rate meets the preset condition The steps recommended to the user include:

Counting the number of applications and the number of successful purchases of the loan product found in the loan product database among the similar users;

Calculating the recommended success rate of the loan product according to the number of applications and the number of successful purchases, and recommending the loan product with the highest loan success rate to the user.
The inquiring device for a loan product according to claim 3, wherein the loan product in which the matching loan product is found in the similar user and the loan success rate meets the preset condition is calculated. The steps recommended to the user include:

Counting the number of applications and the number of successful purchases of the loan product found in the loan product database among the similar users;

Calculating the recommended success rate of the loan product according to the number of applications and the number of successful purchases, and recommending the loan product with the highest loan success rate to the user.
The inquiry device for a loan product according to claim 4, wherein the user information includes the following information items: gender, age, education, occupation, income, personal total assets, and identity information.
A method for querying a loan product, characterized in that the method comprises:

Receiving a query request of the loan product sent by the user, and obtaining the loan condition and the user information from the query request;

Finding loan products that meet the loan conditions from the loan products provided by the loan institutions of the loan product database;

Finding a similar user of the user from the loan user database according to the user information;

Calculating the loan success rate of the matched loan product in the similar user found, and recommending the loan product whose loan success rate meets the preset condition to the user.
The method for inquiring a loan product according to claim 8, wherein after the step of finding a loan product that meets the loan condition from the loan product provided by each lending institution of the loan product database, the method further includes :

Obtaining the identity information of the user from the user information, and querying, according to the identity information, the personal credit level of the user from the credit information database;

And filtering, according to the personal credit rating, the found loan product that meets the loan condition to filter out the loan product that does not match the personal credit rating, and executing the calculated matching loan based on the filtered loan product. The step of recommending, by the product, the loan success rate among the similar users, and recommending the loan product whose loan success rate meets the preset condition to the user.
The method for querying a loan product according to claim 8, wherein the step of searching for a similar user of the user from the loan user database according to the user information comprises:

Rate each information item in the user information of the user according to a preset scoring rule;

Calculating the score of the user according to the scores of the information items and the preset weights of the information items;

Finding similar users of the user from the loan user database based on the calculated score.
The method for inquiring a loan product according to claim 8, wherein the calculating the loan success rate of the matched loan product in the similar user and finding the loan product with the loan success rate meeting the preset condition The steps recommended to the user include:

Counting the number of applications and the number of successful purchases of the loan product found in the loan product database among the similar users;

Calculating the recommended success rate of the loan product according to the number of applications and the number of successful purchases, and recommending the loan product with the highest loan success rate to the user.
The method for inquiring a loan product according to claim 9, wherein the calculating the loan success rate of the matched loan product in the similar user and finding the loan product with the loan success rate meeting the preset condition The steps recommended to the user include:

Counting the number of applications and the number of successful purchases of the loan product found in the loan product database among the similar users;

Calculating the recommended success rate of the loan product according to the number of applications and the number of successful purchases, and recommending the loan product with the highest loan success rate to the user.
The method for inquiring a loan product according to claim 10, wherein the calculating the loan success rate of the matched loan product in the similar user and finding the loan product with the loan success rate meeting the preset condition The steps recommended to the user include:

Counting the number of applications and the number of successful purchases of the loan product found in the loan product database among the similar users;

Calculating the recommended success rate of the loan product according to the number of applications and the number of successful purchases, and recommending the loan product with the highest loan success rate to the user.
The method for querying a loan product according to claim 11, wherein the user information includes the following information items: gender, age, education, occupation, income, personal total assets, and identity information.
A computer readable storage medium, wherein the computer readable storage medium stores a query program of a loan product, and when the query program of the loan product is executed by the processor, the following steps are implemented:

Receiving a query request of the loan product sent by the user, and obtaining the loan condition and the user information from the query request;

Finding loan products that meet the loan conditions from the loan products provided by the loan institutions of the loan product database;

Finding a similar user of the user from the loan user database according to the user information;

Calculating the loan success rate of the matched loan product in the similar user found, and recommending the loan product whose loan success rate meets the preset condition to the user.
The computer readable storage medium according to claim 15, wherein said processor is further configured to execute a query procedure of said loan product to find a match in a loan product provided from each lending institution of the loan product database After the steps of the loan product of the loan condition, the following steps are also implemented:

Obtaining the identity information of the user from the user information, and querying, according to the identity information, the personal credit level of the user from the credit information database;

And filtering, according to the personal credit rating, the found loan product that meets the loan condition to filter out the loan product that does not match the personal credit rating, and executing the calculated matching loan based on the filtered loan product. The step of recommending, by the product, the loan success rate among the similar users, and recommending the loan product whose loan success rate meets the preset condition to the user.
The computer readable storage medium according to claim 15, wherein the step of searching for a similar user of the user from a loan user database according to the user information comprises:

Rate each information item in the user information of the user according to a preset scoring rule;

Calculating the score of the user according to the scores of the information items and the preset weights of the information items;

Finding similar users of the user from the loan user database based on the calculated score.
The computer readable storage medium according to claim 15, wherein the calculation of the loan success rate of the matched loan product in the similar user found and the loan success rate satisfying the preset condition The steps recommended to the user include:

Counting the number of applications and the number of successful purchases of the loan product found in the loan product database among the similar users;

Calculating the recommended success rate of the loan product according to the number of applications and the number of successful purchases, and recommending the loan product with the highest loan success rate to the user.
The computer readable storage medium according to claim 16, wherein the calculating the loan success rate of the matched loan product in the similar user and finding the loan product with the loan success rate meeting the preset condition The steps recommended to the user include:

Counting the number of applications and the number of successful purchases of the loan product found in the loan product database among the similar users;

Calculating the recommended success rate of the loan product according to the number of applications and the number of successful purchases, and recommending the loan product with the highest loan success rate to the user.
The computer readable storage medium according to claim 17, wherein said calculating a loan product in which said matching loan product finds a similar loan success rate and said loan success rate meets a preset condition The steps recommended to the user include:

Counting the number of applications and the number of successful purchases of the loan product found in the loan product database among the similar users;

Calculating the recommended success rate of the loan product according to the number of applications and the number of successful purchases, and recommending the loan product with the highest loan success rate to the user.