CN112241915A

CN112241915A - Loan product generation method and device

Info

Publication number: CN112241915A
Application number: CN202011025392.9A
Authority: CN
Inventors: 韦婷婷
Original assignee: China Construction Bank Corp
Current assignee: China Construction Bank Corp
Priority date: 2020-09-25
Filing date: 2020-09-25
Publication date: 2021-01-19

Abstract

The invention discloses a method and a device for generating loan products, and relates to the technical field of computers. One embodiment of the method comprises: receiving a loan request of a user; inquiring economic data of a user from a credit granting database according to a user identifier in a loan request, calling a model library, and extracting an influence factor model so as to input the economic data into the influence factor model to obtain loan influence factor data of the user; calling a matching engine to calculate the loan interest rate of the user according to the loan influence factor data and the loan demand information in the loan request; and generating and outputting the loan products of the user according to the loan interest rate. The implementation mode can perform targeted loan pricing, develop high-quality customers, provide targeted loan prices for different types of customers, and enable the user experience to be better, so that the profitability and the competitiveness are guaranteed.

Description

Loan product generation method and device

Technical Field

The invention relates to the technical field of computers, in particular to a method and a device for generating loan products.

Background

Loan pricing (determining the interest rate of a loan) is a very important step in creating a loan product. Loan pricing is directly related to bank operations and revenue. In the prior art, banks commonly adopt a loan pricing method which is floated with reference to the standard interest rate of the central bank.

In the process of implementing the invention, the inventor finds that at least the following problems exist in the prior art:

the prior art loan pricing methods often do not consider external factors (such as customer bearing capacity) that affect the price of a bank for issuing credit loans, which may cause unreasonable pricing and fail to achieve targeted loan pricing.

Disclosure of Invention

In view of this, embodiments of the present invention provide a method and an apparatus for generating a loan product, which can perform targeted loan pricing, develop high-quality customers, provide targeted loan prices for different types of customers, and enable users to experience better, thereby ensuring profitability and competitiveness.

To achieve the above object, according to an aspect of an embodiment of the present invention, there is provided a method of generating a credit product, including:

receiving a loan request of a user;

inquiring economic data of the user from a credit granting database according to the user identification in the loan request, calling a model library, and extracting an influence factor model so as to input the economic data into the influence factor model to obtain loan influence factor data of the user;

calling a matching engine to calculate the loan interest rate of the user according to the loan influence factor data and the loan demand information in the loan request;

and generating and outputting the loan products of the user according to the loan interest rate.

Optionally, inputting the economic data into the influence factor model to obtain loan influence factor data of the user, including:

inputting the economic data into a trained user portrait model, and outputting to obtain the user identity type of the user; inputting the economic data into a trained user credit scoring model, and outputting to obtain user risk information of the user;

taking the user identity type and the user risk information as loan influence factor data of the user;

wherein the economic data comprises asset data and economic behavior data of the user.

Optionally, invoking a matching engine to calculate a loan interest rate of the user according to the loan factor data and the loan requirement information in the loan request, including:

calling the matching engine to judge the loan interest rate type of the user according to the loan influence factor data and the loan demand information, and calling the matching engine to obtain a corresponding interest rate calculation function from a parameter configuration library by inquiring according to the loan interest rate type;

calculating the loan interest rate of the user based on the interest rate calculation function according to the loan influence factor data and the loan demand information;

wherein the loan requirement information comprises: repayment type, loan scene type.

Optionally, calling the matching engine to determine the loan interest rate type of the user according to the loan influence factor data and the loan demand information, including:

judging the loan interest rate type of the user with the repayment period exceeding a preset time length in the repayment types as a first non-preferential interest rate type;

judging the user identity type as a second non-preferential interest rate type according to the loan interest rate type of the user with the specific identity;

and judging the loan interest rate type of the user whose repayment period does not exceed the preset time length and whose user identity type does not belong to the specific identity in the repayment types as the preferential interest rate type.

Optionally, when the loan interest rate type is a first non-preferential interest rate type, calculating the loan interest rate of the user based on the interest rate calculation function according to the loan influence factor data and the loan demand information, and including:

inquiring corresponding bottom line interest rate parameters and bottom line interest rate functions in the parameter configuration library according to the user identity type and the loan demand information, and calculating to obtain the bottom line interest rate based on the bottom line interest rate parameters and the bottom line interest rate functions;

according to the user identity type, inquiring a corresponding identity interest rate parameter and an identity interest rate function in the parameter configuration library, and calculating the identity interest rate of the user based on the identity interest rate parameter and the identity interest rate function;

and taking the larger value of the bottom line interest rate and the identity interest rate as the loan interest rate of the user.

Optionally, when the loan interest rate type is a second non-preferential interest rate type, calculating the loan interest rate of the user based on the interest rate calculation function according to the loan influence factor data and the loan demand information, and including:

according to the specific identity of the user and the loan scene type, inquiring in the parameter configuration library to obtain a corresponding specific interest rate;

and taking the smaller value of the identity interest rate and the specific interest rate as a first smaller value, and taking the larger value of the first smaller value and the bottom line interest rate as the loan interest rate.

Optionally, when the loan interest rate type is a preferential interest rate type, calculating the loan interest rate of the user based on the interest rate calculation function according to the loan influence factor data and the loan demand information, including:

inquiring the discount type which is met by the loan scene type according to the loan scene type, inquiring the discount parameter and the discount rate function which correspond to the discount type in the parameter configuration library, calculating the discount rate which corresponds to the discount type based on the discount parameter and the discount rate function, and taking the minimum value from the calculation as the optimal rate of the user; inquiring a risk adjustment function in the parameter configuration library, adjusting the optimal interest rate based on the risk adjustment function according to the user risk information, and taking the adjusted optimal interest rate as the scene interest rate;

and taking the smaller value of the identity interest rate and the scene interest rate as a second smaller value, and taking the larger value of the second smaller value and the bottom line interest rate as the loan interest rate.

Optionally, before querying economic data of the user from a credit granting database according to the user identifier in the loan request, invoking a model library, and extracting an influence factor model to input the economic data into the influence factor model to obtain loan influence factor data of the user, the method further includes:

confirming that the user does not open an account; if not, the user can not select the specific application,

inquiring to obtain the current execution interest rate of the user according to the account opening information of the user, and taking the execution interest rate as the loan interest rate; and generating and outputting the loan products of the user according to the loan interest rate.

confirming that the credit limit of the user loan is allowed to pass based on the credit granting database; wherein the amount is non-zero.

Optionally, before generating and outputting the loan product of the user according to the loan interest rate, the method further includes:

and confirming that the loan of the user passes the approval based on the exclusion policy, credit investigation and credit granting database.

Optionally, generating and outputting a loan product of the user according to the loan interest rate, including:

according to the loan interest rate and based on the repayment type in the loan demand information, calculating a bill date and a repayment date of the repayment of the user and the amount of the interest corresponding to each repayment date;

and outputting and displaying the repayment type, the bill date, the repayment date and the principal amount corresponding to each repayment date as a repayment plan of the loan product of the user.

According to still another aspect of an embodiment of the present invention, there is provided a loan product generation apparatus including:

the receiving module is used for receiving a loan request of a user;

the influence factor determining module is used for inquiring the economic data of the user from a credit database according to the user identification in the loan request, calling a model library, and extracting an influence factor model so as to input the economic data into the influence factor model to obtain the loan influence factor data of the user;

the interest rate calculating module is used for calling a matching engine to calculate the loan interest rate of the user according to the loan influence factor data and the loan demand information in the loan request;

and the generating module is used for generating and outputting the loan products of the user according to the loan interest rate.

Optionally, the determining influence factor module inputs the economic data into the influence factor model to obtain loan influence factor data of the user, including:

Optionally, the interest rate calculating module invokes a matching engine to calculate the interest rate of the user according to the loan influence factor data and the loan demand information in the loan request, where the interest rate calculating module includes:

Optionally, the interest rate calculating module calls the matching engine to determine the loan interest rate type of the user according to the loan influence factor data and the loan demand information, and the interest rate calculating module includes:

Optionally, when the loan interest rate type is a first non-preferential interest rate type, the calculating interest rate module calculates the loan interest rate of the user based on the interest rate calculating function according to the loan influence factor data and the loan demand information, and includes:

Optionally, when the loan interest rate type is a second non-preferential interest rate type, the calculating interest rate module calculates the loan interest rate of the user based on the interest rate calculating function according to the loan influence factor data and the loan demand information, and includes:

Optionally, when the loan interest rate type is a benefit rate type, the interest rate calculation module calculates the loan interest rate of the user based on the interest rate calculation function according to the loan influence factor data and the loan demand information, and includes:

Optionally, the determining influence factor module, before querying economic data of the user from a credit granting database according to the user identifier in the loan request, calls a model library, and extracts an influence factor model to input the economic data into the influence factor model and obtain loan influence factor data of the user, further includes:

and inquiring according to the account opening information of the user to obtain the current execution interest rate of the user, taking the execution interest rate as the loan interest rate, and generating and outputting loan products of the user according to the loan interest rate.

According to another aspect of an embodiment of the present invention, there is provided electronic apparatus for creating a loan product, including:

one or more processors;

a storage device for storing one or more programs,

when executed by the one or more processors, cause the one or more processors to implement the method for creating a loan product provided by the invention.

According to still another aspect of an embodiment of the present invention, there is provided a computer-readable medium on which a computer program is stored, the program, when executed by a processor, implementing the method for generating a loan product provided by the present invention.

One embodiment of the above invention has the following advantages or benefits: because the technical means of determining loan influence factor data according to the loan request calling model base, calling the matching engine according to the loan influence factor data and the user requirements to classify the users, and calculating the loan interest rates of various users to generate corresponding loan products are adopted, the technical problem of unreasonable loan pricing caused by lack of consideration of external factors during loan pricing in the prior art is solved, and further targeted loan pricing can be performed, user experience is better, and therefore profitability and competitiveness are guaranteed.

Further effects of the above-mentioned non-conventional alternatives will be described below in connection with specific embodiments.

Drawings

The drawings are included to provide a better understanding of the invention and are not to be construed as unduly limiting the invention. Wherein:

fig. 1 is a schematic view of the main flow of a loan product generation method according to a first embodiment of the invention;

FIG. 2 is a schematic view of the main flow of a method of calculating a loan interest rate according to a second embodiment of the invention;

FIG. 3 is a schematic view of the main flow of a method of classifying users and calculating loan interest rates according to a third embodiment of the present invention;

fig. 4 is a schematic diagram of the main blocks of the loan product generation apparatus according to the embodiment of the invention;

FIG. 5 is an exemplary system architecture diagram in which embodiments of the present invention may be employed;

fig. 6 is a schematic block diagram of a computer system suitable for use with a terminal device or server implementing an embodiment of the invention.

Detailed Description

Exemplary embodiments of the present invention are described below with reference to the accompanying drawings, in which various details of embodiments of the invention are included to assist understanding, and which are to be considered exemplary only. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the invention. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.

Fig. 1 is a schematic view of the main flow of a loan product creation method according to a first embodiment of the invention, and as shown in fig. 1, includes:

step S101, receiving a loan request of a user;

step S102, according to a user identification in a loan request, inquiring economic data of a user from a credit granting database, calling a model library, and extracting an influence factor model so as to input the economic data into the influence factor model to obtain loan influence factor data of the user;

step S103, calling a matching engine to calculate and obtain the loan interest rate of the user according to the loan influence factor data and the loan demand information in the loan request;

and step S104, generating and outputting the loan products of the user according to the loan interest rate.

Various data which may influence the user loan can be obtained according to the user identification in the loan request; various data influencing the user loan can be obtained from a credit granting database in a bank, and also can be obtained from a third-party interface accessed by the bank in some practical applications, so that the user can be subjected to targeted loan pricing from multiple dimensions according to the data;

the method provided by the invention can be used for pertinently pricing loans, developing high-quality customers, providing targeted loan prices for different types of customers, and ensuring better user experience, thereby ensuring the profitability and the competitiveness.

In some embodiments, inputting the economic data into the factor-of-influence model to obtain loan factor-of-influence data for the user comprises:

inputting the economic data into a trained user portrait model, and outputting to obtain the user identity type of the user; inputting the economic data into a trained user credit scoring model, and outputting to obtain user risk information of the user; taking the user identity type and the user risk information as loan influence factor data of the user;

The model base can comprise models related to multiple dimensions, such as a user drawing model capable of classifying the identities of user groups and a credit scoring model capable of evaluating the risks of users; a new dimensional model can be added according to actual conditions, existing historical data are used for training, and the trained model is stored in a model base for use.

In some embodiments, invoking a matching engine to calculate the loan interest rate of the user according to the loan factor data and the loan requirement information in the loan request, includes:

After determining the influence factor data of the user loan, calling a matching engine to calculate the specific loan interest rate; the users can be classified according to the identity types of the users and the loan requirements of the users, and then corresponding parameters and functions are called according to the classified types to calculate so as to obtain the loan interest rate of the users.

In some embodiments, before querying economic data of the user from a credit granting database according to the user identifier in the loan request, invoking a model library, and extracting an influence factor model to input the economic data into the influence factor model to obtain loan influence factor data of the user, the method further includes:

confirming that the user does not open an account; if not, inquiring to obtain the current execution interest rate of the user according to the account opening information of the user, and taking the execution interest rate as the loan interest rate; and generating and outputting the loan products of the user according to the loan interest rate.

Whether the user opens an account can be judged according to the user identification; when the user is confirmed to have opened an account, the current execution interest rate of the user can be directly inquired, the execution interest rate is used as the loan interest rate of the loan request, and a loan product is generated for the user according to the loan interest rate.

Fig. 2 is a schematic view of the main flow of a method for calculating a loan interest rate according to a second embodiment of the present invention, as shown in fig. 2, including:

step S201, judging whether a user opens an account; specifically, the query and judgment can be carried out according to the user identification in the loan request; if not, executing step S202; if yes, go to step S205;

step S202, determining loan influence factor data according to user information; specifically, the required user information (such as economic data of the user) can be searched according to the user identification, and then the data of each loan influence factor is determined;

step S203, judging the loan interest rate type of the user according to the loan influence factor data of the user and the loan requirement of the user; specifically, a matching engine may be invoked for the determination;

step S204, calling parameters and calculation functions corresponding to the loan interest rate types, and calculating the loan interest rate of the user; specifically, a matching engine can be called to obtain corresponding parameters and a calculation function, and then the loan interest rate of the user is calculated; (ii) a

And step S205, inquiring and obtaining the current execution interest rate according to the account opening information, and using the current execution interest rate as the loan interest rate of the user.

In some embodiments, invoking the matching engine to determine the loan interest rate type of the user according to the loan impact factor data and the loan requirement information includes:

The preset duration can be adjusted according to actual conditions, such as data of 12 months, 18 months and the like; when the repayment period requested by the user exceeds the preset time length, the loan product risk requested by the user is considered to be larger, and the user is not allowed to enjoy the preferential interest rate;

the specific identity can be adjusted according to actual conditions, such as farmer identity and other data; when the user identity type belongs to a specific identity, the loan interest rate can be directly used as the loan interest rate according to the interest rate corresponding to the identity;

when the repayment period requested by the user exceeds the preset time length and the user identity type belongs to the specific identity, after the loan interest rates corresponding to the two types are calculated, the larger value or the smaller value or the compromise value can be selected as the loan interest rate of the user according to the actual condition of the user;

when the repayment period of the user does not exceed the preset time length and the user identity type does not belong to the specific identity, the user can inquire the offer type according to the scene of requesting loan, and the loan interest rate of the user can be calculated according to the offer type.

In some embodiments, when the loan interest rate type is a first non-preferential interest rate type, calculating the loan interest rate of the user based on the interest rate calculation function according to the loan influence factor data and the loan demand information, including:

In some embodiments, when the loan interest rate type is a second non-preferential interest rate type, calculating the loan interest rate of the user based on the interest rate calculation function according to the loan influence factor data and the loan demand information, including:

In some embodiments, when the loan interest rate type is a benefit rate type, calculating the loan interest rate of the user based on the interest rate calculation function according to the loan influence factor data and the loan demand information, including:

For the three types of users, a matching engine can be called to inquire corresponding parameters and functions in a parameter configuration library according to loan influence factor data and loan demand information of the users, interest rate calculation is carried out, and targeted loan interest rate pricing is achieved.

FIG. 3 is a schematic view of the main flow of a method of classifying users and calculating loan interest rates according to a third embodiment of the invention, as shown in FIG. 3, including;

step S301, classifying users according to loan influence factor data and loan demand information; specifically, a matching engine may be invoked for classification; as shown in the figure, the classified execution steps are respectively: steps S302 to S304, steps S305 to S306, and steps S308 to S310;

step S302, when the repayment deadline of the user exceeds a preset duration, determining that the repayment deadline of the user is a first non-preferential interest rate type;

step S303, calling corresponding parameters and functions, and calculating the baseline interest rate and the identity interest rate of the first non-preferential interest rate type user;

step S304, taking the larger value of the bottom line interest rate and the identity interest rate as the credit and debit interest rate of the user;

s305, when the user identity type belongs to a specific identity, determining that the user identity type is a second non-preferential interest rate type;

step S306, calling corresponding parameters and functions, and calculating the baseline interest rate, the identity interest rate and the specific interest rate of the second non-preferential interest rate type user;

step S307, taking the smaller value of the identity interest rate and the specific interest rate as a first smaller value, and taking the larger value of the first smaller value and the bottom line interest rate as a loan interest rate;

step S308, when the repayment deadline of the user does not exceed the preset duration and the identity type of the user does not belong to a specific identity, determining that the repayment deadline is a preferential interest rate type;

step S309, calling corresponding parameters and functions, and calculating the baseline interest rate, the identity interest rate and the scene interest rate of the preferential interest rate type user;

and S310, taking the smaller value of the identity interest rate and the scene interest rate as a first smaller value, and taking the larger value of the first smaller value and the bottom line interest rate as the loan interest rate.

In some embodiments, before querying economic data of the user from a credit granting database according to the user identifier in the loan request, invoking a model library, and extracting an influence factor model to input the economic data into the influence factor model to obtain loan influence factor data of the user, the method further includes: confirming that the credit limit of the user loan is allowed to pass based on the credit granting database; wherein the quota is a non-zero quota.

Specifically, the preliminary limit of the client can be calculated according to limit condition data and a limit generation model set in the line based on personal in-line data of the client, social security data/public credit information center data/local tax office data authorized to be used by the client, and scene access data provided by a scene loan third party. To prevent multiple credits and over-credits, some inline loan amounts of the customer may be deducted. In addition, customers with high risk such as quick in-line credits, overdue many times, etc. may not be given any value. If the customer can pass these rules, then the credit admission can pass.

After a user initiates a loan application through an electronic channel provided by a bank, the system can develop the condition and rule of credit admission according to available comprehensive information and data of the client and set the condition and rule as standardized parameters, and then the system can automatically judge whether the client is allowed to access according to the standardized parameters. Such as: if the client is listed in the internal control list of the bad client in the line of the client or the age does not meet the parameter requirement, the credit line is not allowed to pass. And after the credit is allowed to pass, the scientific and technical system carries out real-time approval (synchronous interest rate generation) according to the set approval model. In real-time approval, whether the credit of the client meets certain conditions, whether the client can pass the auditing of the anti-fraud verification model, and the like are generally inquired (parameters can be set so as to control the approval passing rate).

In some embodiments, before generating and outputting the loan product of the user according to the loan interest rate, the method further comprises:

Specifically, the client may be blacklisted and/or checked for in-line fusing; in some practical applications, a multi-dimensional risk scoring model may be used for scoring, and the score is compared with a corresponding threshold value to obtain a result of rejection or passing; and auditing can be carried out according to the client authorized checking client bank credit deduction and external loan deduction and access scene type featured approval rules (such as calculating the income-liability ratio of the client).

In some embodiments, generating and outputting the loan product of the user according to the loan interest rate comprises:

Fig. 4 is a schematic diagram of the main blocks of the loan product generation apparatus according to the embodiment of the invention, and as shown in fig. 4, the loan product generation apparatus 400 includes:

a receiving module 401, configured to receive a loan request of a user;

an influence factor determining module 402, configured to query economic data of the user from a credit granting database according to the user identifier in the loan request, call a model library, and extract an influence factor model, so as to input the economic data into the influence factor model, thereby obtaining loan influence factor data of the user;

the interest rate calculating module 403 is configured to invoke a matching engine to calculate the loan interest rate of the user according to the loan influence factor data and the loan demand information in the loan request;

and the generating module 404 is used for generating and outputting the loan products of the user according to the loan interest rate.

In some embodiments, the determining influence factor module inputs the economic data into the influence factor model to obtain loan influence factor data for the user, including:

In some embodiments, the calculating interest rate module invokes a matching engine to calculate the loan interest rate of the user according to the loan influence factor data and the loan demand information in the loan request, including:

In some embodiments, the determining influence factor module, before querying economic data of the user from a credit granting database according to the user identifier in the loan request, calls a model library, and extracts an influence factor model to input the economic data into the influence factor model and obtain loan influence factor data of the user, further includes:

In some embodiments, the determining the loan interest rate type of the user by the matching engine according to the loan influence factor data and the loan requirement information by the interest rate calculation module includes:

In some embodiments, when the loan interest rate type is a first non-preferential interest rate type, the interest rate calculation module calculates the loan interest rate of the user based on the interest rate calculation function according to the loan influence factor data and the loan demand information, and includes:

In some embodiments, when the loan interest rate type is a second non-preferential interest rate type, the interest rate calculation module calculates the loan interest rate of the user based on the interest rate calculation function according to the loan influence factor data and the loan demand information, and includes:

In some embodiments, when the loan interest rate type is a benefit rate type, the calculating interest rate module calculates the loan interest rate of the user based on the interest rate calculating function according to the loan influence factor data and the loan demand information, and includes:

After a user initiates a loan application through an electronic channel provided by a bank, the system can develop the condition and rule of credit admission according to available comprehensive information and data of the client and set the condition and rule as standardized parameters, and then the system can automatically judge whether the client is allowed to access according to the standardized parameters. Such as: if the client is listed in the internal control list of the bad client in the line of the client or the age does not meet the parameter requirement, the credit line is not allowed to pass. And after the credit is allowed to pass, the scientific and technical system carries out real-time approval (synchronous interest rate generation) according to the set approval model. In real-time approval, whether the credit of the client meets certain conditions and/or whether the client can pass the verification of the anti-fraud verification model and the like are generally inquired (parameters can be set so as to control the approval passing rate).

Specifically, the client may be blacklisted and/or checked for in-line fusing; in some practical applications, a multi-dimensional risk scoring model may be used for scoring, and the score is compared with a corresponding threshold value to obtain a result of rejection or passing; and auditing can be carried out according to a characteristic approval rule (such as calculating the income-liability ratio of the client) of a client authorized to check the credit deduction and external loan deduction of the client or access scene class.

Fig. 5 illustrates an exemplary system architecture 500 of a method or apparatus for generating a loan product to which embodiments of the invention may be applied.

As shown in FIG. 5, the system architecture 500 may include

terminal devices

501, 502, 503, a network 504, and a server 505 for the generation of loan products. The network 504 serves to provide a medium for communication links between the

terminal devices

501, 502, 503 and the server 505. Network 504 may include various connection types, such as wired, wireless communication links, or fiber optic cables, to name a few.

The user may use the

terminal devices

501, 502, 503 to interact with a server 505 over a network 504 to receive or send messages or the like. The

terminal devices

501, 502, 503 may have various communication client applications installed thereon, such as a web browser application, a search application, an instant messaging tool, a mailbox client, and the like.

The

terminal devices

501, 502, 503 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smart phones, tablet computers, laptop portable computers, desktop computers, and the like.

The server 505 may be a server providing various services, such as a background management server (for example only) providing support for websites browsed by users using the

terminal devices

501, 502, 503. The background management server can analyze and process the received data such as the product information inquiry request and the like, and feed back the processing result to the terminal equipment.

It should be noted that the method for generating a loan product provided by the embodiment of the present invention is generally executed by the server 505, and accordingly, the device for generating a loan product is generally disposed in the server 505.

It should be understood that the number of terminal devices, networks, and servers in fig. 5 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.

Referring now to FIG. 6, a block diagram of a computer system 600 suitable for use with a terminal device implementing an embodiment of the invention is shown. The terminal device shown in fig. 6 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present invention.

As shown in fig. 6, the computer system 600 includes a Central Processing Unit (CPU)601 that can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM)602 or a program loaded from a storage section 608 into a Random Access Memory (RAM) 603. In the RAM 603, various programs and data necessary for the operation of the system 600 are also stored. The CPU 601, ROM 602, and RAM 603 are connected to each other via a bus 604. An input/output (I/O) interface 605 is also connected to bus 604.

The following components are connected to the I/O interface 605: an input portion 606 including a keyboard, a mouse, and the like; an output portion 607 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage section 608 including a hard disk and the like; and a communication section 609 including a network interface card such as a LAN card, a modem, or the like. The communication section 609 performs communication processing via a network such as an internet. The driver 610 is also connected to the I/O interface 605 as needed. A removable medium 611 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 610 as necessary, so that a computer program read out therefrom is mounted in the storage section 608 as necessary.

In particular, according to the embodiments of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such embodiments, the computer program may be downloaded and installed from a network through the communication section 609, and/or installed from the removable medium 611. The computer program performs the above-described functions defined in the system of the present invention when executed by the Central Processing Unit (CPU) 601.

It should be noted that the computer readable medium shown in the present invention can be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present invention, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present invention, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.

The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

The modules described in the embodiments of the present invention may be implemented by software or hardware. The described modules may also be provided in a processor, which may be described as: a processor includes a receiving module, a determining influence factor module, a calculating interest rate module, and a generating module. The names of these modules do not form a limitation on the modules themselves in some cases, and for example, the receiving module may also be described as a "module that sends a user loan request acquisition request to a connected service terminal".

As another aspect, the present invention also provides a computer-readable medium that may be contained in the apparatus described in the above embodiments; or may be separate and not incorporated into the device. The computer readable medium carries one or more programs which, when executed by a device, cause the device to comprise: step S101, receiving a loan request of a user; step S102, according to a user identification in a loan request, inquiring economic data of the user from a credit granting database, calling a model library, and extracting an influence factor model so as to input the economic data into the influence factor model to obtain loan influence factor data of the user; step S103, calling a matching engine to calculate the loan interest rate of the user according to the loan influence factor data and the loan demand information in the loan request; and step S104, generating and outputting the loan products of the user according to the loan interest rate.

According to the technical scheme of the embodiment of the invention, because the technical means of determining loan influence factor data according to the loan request calling model base, classifying users according to the loan influence factor data and the user requirements calling the matching engine, and calculating the loan interest rates of various users to generate corresponding loan products is adopted, the technical problem of unreasonable loan pricing caused by lack of external factors during loan pricing in the prior art is solved, and further targeted loan pricing can be realized, so that the user experience is better, and the profitability and the competitiveness are ensured.

The above-described embodiments should not be construed as limiting the scope of the invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations, and substitutions may occur depending on design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for creating a loan product, comprising:

receiving a loan request of a user;

2. The method of claim 1, wherein inputting the economic data into the influential model, resulting in loan influential data for the user, comprises:

3. The method of claim 1, wherein invoking a matching engine to calculate the loan interest rate of the user based on the loan factor data and loan requirement information in the loan request comprises:

4. The method of claim 3, wherein invoking the matching engine to determine the loan interest rate type of the user based on the loan impact factor data and the loan requirement information comprises:

and judging the loan interest rate type of the user whose repayment period does not exceed the preset time length and whose user identity type does not belong to the specific identity as the preferential interest rate type.

5. The method of claim 4, wherein when the loan interest rate type is a first non-preferential interest rate type, calculating the user's loan interest rate based on the interest rate calculation function according to the loan impact factor data and the loan demand information, comprising:

6. The method of claim 4, wherein when the loan interest rate type is a second non-preferential interest rate type, calculating the user's loan interest rate based on the interest rate calculation function according to the loan impact factor data and the loan demand information, comprising:

7. The method of claim 4, wherein when the loan interest rate type is a preferential interest rate type, calculating the user's loan interest rate based on the interest rate calculation function according to the loan impact factor data and the loan demand information, comprises:

8. The method according to claim 1, wherein before querying the economic data of the user from a credit granting database according to the user identifier in the loan request, invoking a model library, extracting an influence factor model, and inputting the economic data into the influence factor model to obtain the loan influence factor data of the user, further comprising:

9. The method according to claim 1, wherein before querying the economic data of the user from a credit granting database according to the user identifier in the loan request, invoking a model library, extracting an influence factor model, and inputting the economic data into the influence factor model to obtain the loan influence factor data of the user, further comprising:

confirming that the credit limit of the user loan is allowed to pass based on the credit granting database; wherein the quota is a non-zero quota.

10. The method of claim 1, further comprising, prior to generating and outputting the user's loan product based on the loan interest rate:

and confirming that the loan approval of the user passes based on the exclusion policy, credit investigation and credit granting database.

11. The method of claim 1, wherein generating and outputting the user's loan products based on the loan interest rate comprises:

and outputting and displaying the repayment type, the bill date, the repayment date and the interest amount corresponding to each repayment date as a repayment plan of the loan product of the user.

12. An apparatus for creating a loan product, comprising:

the receiving module is used for receiving a loan request of a user;

the influence factor determining module is used for inquiring the economic data of the user from a credit granting database according to the user identification in the loan request, calling a model library and extracting an influence factor model so as to input the economic data into the influence factor model and obtain loan influence factor data of the user;

13. The apparatus of claim 12, wherein the interest rate calculating module invokes a matching engine to calculate the interest rate of the loan of the user based on the loan factor data and the loan requirement information in the loan request, comprising:

14. An electronic device for creating a loan product, comprising:

one or more processors;

a storage device for storing one or more programs,

when executed by the one or more processors, cause the one or more processors to implement the method of any one of claims 1-11.

15. A computer-readable medium, on which a computer program is stored, which, when being executed by a processor, carries out the method according to any one of claims 1-11.