CN116151964A

CN116151964A - Data processing method, apparatus, device, medium, and program product

Info

Publication number: CN116151964A
Application number: CN202310295224.9A
Authority: CN
Inventors: 张文星
Original assignee: China Construction Bank Corp; CCB Finetech Co Ltd
Current assignee: China Construction Bank Corp; CCB Finetech Co Ltd
Priority date: 2023-03-23
Filing date: 2023-03-23
Publication date: 2023-05-23

Abstract

The application discloses a data processing method, a device, equipment, a medium and a program product, and relates to the technical field of financial information service, wherein the method comprises the following steps: acquiring a credit product and at least one borrowing object lending the credit product, and at least one dimensional information corresponding to the borrowing product, wherein the borrowing object lends the credit product with a complete borrowing period; obtaining the score of each lending object in each dimension information; for each piece of dimension information, dividing the dimension information into at least one dimension level according to the score; dividing each lending object into at least one object level according to at least one dimension level corresponding to each dimension information; and determining the target interest rate corresponding to each object grade according to each object grade. To achieve the effect of accurately determining the interest rate of credit products according to the needs of different customers.

Description

Data processing method, apparatus, device, medium, and program product

Technical Field

The present invention relates to the technical field of financial information services, and in particular, to a data processing method, apparatus, device, medium, and program product.

Background

Financial institutions have issued many credit products and how to determine the interest rate of the credit products so that the financial institutions acquire larger revenue is a hotspot problem in current research.

In the prior art, when determining the interest rate of credit products, unified interest rate pricing is carried out according to prior experience of experts or a white list mode, and the determined interest rate is inaccurate.

Disclosure of Invention

An object of the embodiments of the present application is to provide a data processing method, apparatus, device, medium and program product, so as to achieve the effect of precisely determining the interest rate of a credit product according to the requirements of different lending objects.

The technical scheme of the application is as follows:

in a first aspect, a data processing method is provided, the method comprising:

acquiring a credit product and at least one borrowing object lending the credit product, and at least one dimensional information corresponding to the borrowing product, wherein the borrowing object lends the credit product with a complete borrowing period;

obtaining the score of each lending object in each dimension information;

for each piece of dimension information, dividing the dimension information into at least one dimension level according to the score;

dividing each lending object into at least one object level according to at least one dimension level corresponding to each dimension information;

and determining the target interest rate corresponding to each object grade according to each object grade.

In a second aspect, there is provided a data processing apparatus comprising:

the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring a credit product, at least one lending object lending the credit product and at least one dimensional information corresponding to the lending product, wherein the lending object lends the credit product with a complete lending period;

the acquisition module is further used for acquiring the score of each lending object in each dimension information;

the dividing module is used for dividing the dimension information into at least one dimension level according to the scores for each dimension information;

the dividing module is further configured to divide each lending object into at least one object level according to at least one dimension level corresponding to each dimension information;

and the determining module is used for determining the target interest rate corresponding to each object grade.

In a third aspect, an embodiment of the present application provides an electronic device, where the electronic device includes a processor, a memory, and a program or an instruction stored on the memory and executable on the processor, where the program or the instruction implements the steps of the data processing method according to any one of the embodiments of the present application when executed by the processor.

In a fourth aspect, embodiments of the present application provide a readable storage medium having stored thereon a program or instructions which, when executed by a processor, implement the steps of a data processing method according to any of the embodiments of the present application.

In a fifth aspect, embodiments of the present application provide a computer program product, the instructions in which, when executed by a processor of an electronic device, enable the electronic device to perform the steps of the data processing method according to any one of the embodiments of the present application.

The technical scheme provided by the embodiment of the application at least brings the following beneficial effects:

in the method, the obtained score of each dimension information of each lending object corresponding to the lending product can be used for dividing each dimension information into at least one dimension level, then each lending object can be divided into at least one object level according to at least one dimension level corresponding to each dimension information, and the target interest rate corresponding to the object level can be determined according to each object level, so that each lending object of the lending product can be layered according to the score of each dimension information to obtain the object level corresponding to each lending object, and then the corresponding target interest rate of each object level is different according to each object level, namely, the interest rate of each object level is different, so that different target interest rates can be obtained according to the requirements of different lending objects, the accuracy of the interest rate of the lending product is improved without being determined according to priori unification of specialists.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the application and together with the description, serve to explain the principles of the application and do not constitute an undue limitation on the application.

FIG. 1 is one of the flow diagrams of a method for pricing interest rates of products provided in an embodiment of a first aspect of the present application;

FIG. 2 is a second flow chart of a method for pricing interest rates of products according to embodiments of the first aspect of the present application;

FIG. 3 is a third flow chart of a method for pricing interest rates of products according to embodiments of the first aspect of the present application;

FIG. 4 is a flow chart diagram of a method for pricing interest rates of products according to an embodiment of the first aspect of the present application;

FIG. 5 is a flow diagram of a method for pricing interest rates of products according to embodiments of the first aspect of the present application;

FIG. 6 is a schematic structural view of a device for pricing interest rates of products according to an embodiment of the second aspect of the present application;

fig. 7 is a schematic structural diagram of an electronic device according to an embodiment of a third aspect of the present application.

Detailed Description

In order to enable those skilled in the art to better understand the technical solutions of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are intended to be illustrative of the application and are not intended to be limiting. It will be apparent to one skilled in the art that the present application may be practiced without some of these specific details. The following description of the embodiments is merely intended to provide a better understanding of the present application by showing examples of the present application.

It should be noted that, in the technical scheme of the application, the acquisition, storage, use, processing and the like of the data all conform to the relevant regulations of national laws and regulations.

It should be noted that the terms "first," "second," and the like in the description and claims of the present application and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that embodiments of the present application described herein may be implemented in sequences other than those illustrated or otherwise described herein. The implementations described in the following exemplary examples are not representative of all implementations consistent with the present application. Rather, they are merely examples consistent with some aspects of the present application as detailed in the accompanying claims.

As described in the background art, in order to solve the problem of inaccuracy in the prior art, the embodiments of the present application provide a data processing method, apparatus, device, medium and program product, by classifying each dimension information into at least one dimension level according to the obtained score of each dimension information of each lending object corresponding to the lending product, then classifying each lending object into at least one object level according to at least one dimension level corresponding to each dimension information, and determining a target interest rate corresponding to the object level for each object level, so that each lending object of the lending product can be layered according to the score of each dimension information to obtain an object level corresponding to each lending object, and then, for each object level, the interest rate of each object level is different, so that different target interest rates can be obtained according to different prior requirements of different lending objects, without determining the target interest rate corresponding to each object level, thereby improving the accuracy of the lending product.

The data processing method provided by the embodiment of the application is described in detail below through specific embodiments and application scenes thereof with reference to the accompanying drawings.

Figure 1 is a flow chart of a data processing method according to an embodiment of the present application,

as shown in fig. 1, the data processing method provided in the embodiment of the present application may include steps 110 to 150.

Step 110, obtaining at least one lending object of a credit product and a lending credit product, and at least one dimension information corresponding to the lending product.

Wherein the credit product may be a credit product having a complete credit period over a historical period of time. A specific full credit period, that is to say with a full loan appearance, may be that the credit products here are all credit products that have expired.

The lending object may be an object that lends the credit product. It should be noted that, the client of the loan credit product may be a person or an enterprise, which is not limited herein. The dimension information may be dimension information related to interest rate determination of the credit product, such as risk dimension information, asset size dimension information, and funding hunger dimension information.

And 120, obtaining the score of each lending object in each dimension information.

In some embodiments of the present application, referring to fig. 2, where the dimension information includes risk dimension information, step 120 may specifically include steps 1201 and 1202:

step 1201, obtaining image information of a lending object of a lending credit product; wherein, the portrait information at least includes: credit information of the lending object, credit card information of the lending object and loan overdue information of the lending object;

step 1202, taking credit information of the lending object and credit card information of the lending object as sample data, and taking loan overdue information of the lending object as tag data, so as to obtain a score of risk dimension information of the lending object of the lending credit product.

The risk dimension information is used for reflecting the risk that the lending object is overdue after the credit product is loaned to the lending object.

The image information of the lending object may be, in particular, information describing some basic information of the lending object. For example, the image information of the lending object may further include basic information of the lending object, such as a unit name, an age, and the like of the lending object.

In some embodiments of the present application, risk dimension information may be learned in a supervised manner based on pictorial information of all lending objects lending the credit product, resulting in a score for the risk dimension information. In one example, a micro-credit express product a of one year of application from 9/month 1/year 2020 to 8/month 31/year is acquired, and 100 lending objects of the micro-credit express product a are loaned. The credit information of the 100 lending objects and the credit card information of the lending objects are taken as sample data, the loan overdue information of the 100 lending objects is taken as label data, and the degree of overdue not loan of the 100 lending objects is comprehensively analyzed, specifically, the degree of overdue not loan of the 100 lending objects is represented by scores, namely the scores of the risk dimension information of the 100 clients are obtained.

In the embodiment of the application, the score of the risk dimension information of the lending object of the lending credit product is calculated by acquiring the image information of the lending object of the lending credit product, taking credit information of the lending object and credit card information of the lending object in the image information as sample data and taking loan overdue information of the lending object as tag data, so that the score of the risk dimension information of all the lending objects of the lending credit product can be accurately calculated.

In some embodiments of the present application, referring to fig. 3, in a case where the dimension information includes funding hunger and thirst dimension information, the portrait information may further include: asset information of the lending object. Step 120 may specifically further include step 1203:

step 1203, calculating a score of the fund hunger and thirst dimension information of the lending object of the lending credit product according to the asset information of the lending object and the credit card information of the lending object.

Wherein the fund hunger and thirst dimension information is used for reflecting the urgent need degree of the lending object for money.

In some embodiments of the present application, whether the lending object lending the loan product is in urgent need of money, i.e., in urgent need of money, may be comprehensively analyzed according to the property information of the lending object and the credit card information of the lending object, and in particular, the score may be used to characterize the in urgent need of money by the lending object lending the loan product.

In embodiments of the present application, the scoring of the fund hunger and thirst dimension information of the lending object of the loan credit product may be accurately calculated based on the property information of the lending object and the credit card information of the lending object.

In some embodiments of the present application, where the at least one dimension information includes an asset size, the asset size of each lending object may be determined based on the asset information of all lending objects lending the credit product, and the asset size of each lending object may be scored based on its specific size to obtain a score for the asset size dimension information.

Step 130, for each piece of dimension information, dividing the dimension information into at least one dimension level according to the score.

In some embodiments of the present application, for any one dimension information, the dimension information may be classified according to the score of each lending object in the dimension information, so as to obtain multiple dimension levels.

It should be noted that, the steps of classifying each dimension information are not limited herein, and the specific number of the classified steps can be set according to the user's requirement.

Continuing with the above example, taking the risk dimension information as an example, if scores of risk dimension information of 100 lending objects of the lending small micro credit product a have been obtained, the risk dimension information may be divided into different dimension levels according to the 100 scores, for example, may be divided into 3 dimension levels, specifically, may be divided into one dimension level with a score of 60 points or less, one dimension level with a score of 60-80 points, and one dimension level with a score of 80 points or more.

And 140, dividing each lending object into at least one object level according to at least one dimension level corresponding to each dimension information.

The object level may be each level obtained by classifying each lending object.

With continued reference to the above example, taking three dimensional information including risk dimensional information, asset scale dimensional information and fund hunger and thirst dimensional information as an example, if each dimensional information is divided into three dimensional levels, the three dimensional levels of the three dimensional information may be integrated to form a grid matrix of 3 x 3 as shown in table 1 below, and each lending object may be placed in one of the grids according to the scoring condition of each dimensional information.

In some embodiments of the present application, table 1 may be partitioned with respect to table 1, which may be a priori by an expert, for example, three dimensional rankings of three dimensional information in table 1 may be partitioned into 7 different rankings of L-3 through L3. Since each lending object occupies a grid correspondingly, it is equivalent to classifying each lending object to obtain at least one object class. TABLE 1

And 150, determining a target interest rate corresponding to the object grade according to each object grade.

Wherein the target interest rate may be a final interest rate for each subject class.

In some embodiments of the present application, the target interest rate for each object level may be different.

In some embodiments of the present application, referring to fig. 4, in order to further increase the accuracy of the target interest rate, step 150 may specifically include steps 1501-1504:

step 1501, determining an initial interest rate corresponding to the object level for each object level.

The initial interest rate may be an initial interest rate of the subject grade, for example, an interest rate that is established by an expert according to prior experience.

In some embodiments of the present application, the initial interest rates of the various object levels in embodiments of the present application may be uniform, since the interest rates of the credit products are all uniformly formulated by the expert based on prior experience, i.e., the same credit product is debited for different lending objects, and the interest rates are the same. Step 1502, obtaining a first benefit corresponding to the initial interest rate.

Wherein the first benefit may be a related benefit when lending a credit product at an initial interest rate. For example, the total profit of the bank, the credit amount, etc. may be made while the credit product is being loaned at the initial interest rate.

Step 1503, adjusting the initial interest rate, and calculating a second benefit of the credit product when lending according to the adjusted interest rate.

The second benefit may be a relevant benefit when the credit product is borrowed according to the interest rate adjusted for the initial interest rate, for example, a total profit, a credit amount, etc. of the bank when the credit product is borrowed according to the interest rate adjusted for the initial interest rate.

Step 1504, determining a target interest rate corresponding to the object level based on the first benefit and the second benefit.

In some embodiments of the present application, for a certain object level, the revenue is calculated for the initial interest rate loan credit product, then the initial interest rate is adjusted, and the revenue is calculated for the adjusted interest rate loan credit product, so that the adjustment is continuously and circularly performed to obtain a first revenue and a plurality of second benefits. And then, according to the first benefit and the second benefit, determining the target interest rate corresponding to the object grade.

With continued reference to the above example, for the L0 object level in table 1, the initial interest rate of the small micro credit product a is 1, the initial interest rate may be calculated according to the interest rate, if the small micro credit product a is borrowed according to the interest rate, the total profit of the bank is adjusted, for example, to 1.2, the initial interest rate is calculated according to the interest rate of 1.2, the total profit of the bank is calculated, the initial interest rate is continuously adjusted within a certain value range, the total profit of the bank after each adjustment is calculated, and the final interest rate of the object level is obtained according to the calculated total profit corresponding to each interest rate. In the embodiment of the application, the initial interest rate corresponding to each object level is obtained, the first benefit of the credit product when the credit product is borrowed according to the initial interest rate is calculated based on the initial interest rate, then the initial interest rate is adjusted, the second benefit of the credit product when the credit product is borrowed according to the adjusted interest rate is calculated, then the target interest rate corresponding to each object level can be accurately determined based on the first benefit and the second benefit, and the calculated target interest rate comprehensively considers the benefits of banks on the basis that the multi-attraction borrowing object borrowing the credit product is considered.

In some embodiments of the present application, in order to further accurately determine the target interest rate, step 1504 may specifically include:

and determining the interest rate corresponding to the maximum value in the first benefit and the second benefit as the target interest rate corresponding to the object level.

In some embodiments of the present application, the interest rate corresponding to the maximum value in the first benefit and the second benefits may be determined as the target interest rate corresponding to the object level.

With continued reference to the above example, for the L0 object level in table 1, if the total profit of the bank at the time of lending the credit product according to the initial interest rate 1 is 1 million, the total profit of the bank at the time of lending the credit product according to the interest rate 1.2 is 1.5 million, the total profit of the bank at the time of lending the credit product according to the interest rate 0.8 is 1.1 million, the total profit of the bank at the time of lending the credit product according to the interest rate 1.3 is 0.8 million, and according to the comparison, the total profit of the bank at the time of interest rate 1.2 is highest, the interest rate 1.2 corresponding to the highest profit can be regarded as the target interest rate corresponding to the L0 object level.

According to the calculation mode, the target interest rate corresponding to each object level can be calculated. The specific calculated target interest rate corresponding to each object level may be as shown in table 2:

TABLE 2

The average interest rate in table 2 refers to the initial interest rate of each subject class, and the initial interest rate of each subject class is the same since the initial interest rate of each subject class is uniformly formulated according to the prior experience of the expert.

In the embodiment of the application, the interest rate corresponding to the maximum value in the first benefit and the second benefit is determined as the target interest rate corresponding to the object level, so that the benefit of the bank can be ensured when the target interest rate is manufactured.

In some embodiments of the present application, after the interest rate of a certain credit product is determined in the above manner, the interest rate may be applied to the lending object that subsequently lends the credit product, e.g., after the interest rate of the small micro-credit product a is determined, the interest rate unique to the lending object that subsequently lends the small micro-credit product a may be formulated based on the interest rate. The specific implementation manner can be as follows:

in some embodiments of the present application, referring to fig. 5, after step 150, the data processing method referred to above may further include step 160-step:

step 160, receiving a loan request for a loan credit product sent by the target lending object.

The target lending object may be a lending object to lend the credit product.

The loan request may be a request to borrow the credit product.

Step 170, determining a target score of the target lending object in each dimension information based on the loan request.

The target score may be a score of the target lending object in each dimension information.

And 180, determining a target object grade corresponding to the target lending object according to the scores of the target lending object in the dimensional information.

The target object level may be a interest rate level corresponding to the target lending object.

And 190, taking the target interest rate corresponding to the target object grade as the interest rate of the target lending object lending credit product.

In some embodiments of the present application, after a loan request for a target loan object to loan a credit product is obtained, a score of the target loan object on at least one dimension information may be determined based on image information, property information, etc. of the target loan object according to the credit request, a target object level corresponding to the target loan object may be determined according to the score, and then a target interest rate corresponding to the target object level may be determined as the interest rate of the target loan object to loan the credit product.

In the embodiment of the present application, the score of the target lending object in at least one dimension information may be determined according to the loan request of the lending credit product sent by the received target lending object, then the target object level corresponding to the target lending object is determined according to the score of the target lending object in at least one dimension information, and then the target interest rate corresponding to the target object level is taken as the interest rate of the lending credit product of the target lending object, so that a corresponding interest rate may be formulated for each lending object.

It should be noted that, in the data processing method provided in the embodiment of the present application, the execution body may be a data processing apparatus, or a control module in the data processing apparatus for executing the data processing method.

The present application also provides a data processing apparatus based on the same inventive concept as the above-described data processing method. The data processing apparatus provided in the embodiment of the present application is described in detail below with reference to fig. 6.

Fig. 6 is a schematic diagram showing a structure of a data processing apparatus according to an exemplary embodiment.

As shown in fig. 6, the data processing apparatus 600 may include:

an obtaining module 610, configured to obtain a credit product and at least one lending object lending the credit product, and at least one dimensional information corresponding to the lending product, where the lending object lends the credit product with a complete lending period;

the obtaining module 610 is further configured to obtain a score of each lending object in each dimension information;

a dividing module 620, configured to divide, for each piece of dimension information, the dimension information into at least one dimension level according to the score;

the dividing module 620 is further configured to divide each lending object into at least one object level according to at least one dimension level corresponding to each dimension information;

a determining module 630, configured to determine, for each object level, a target interest rate corresponding to the object level.

In some embodiments of the present application, the determining module 630 may specifically include:

a first determining unit, configured to determine, for each object level, an initial interest rate corresponding to the object level;

the acquisition unit is used for acquiring the first benefit corresponding to the initial interest rate;

the adjustment unit is used for adjusting the initial interest rate and calculating second benefits of the credit product when the credit product is borrowed according to the adjusted interest rate;

and the second determining unit is used for determining the target interest rate corresponding to the object grade based on the first benefit and the second benefit.

In some embodiments of the present application, the second determining unit may be specifically configured to

And determining the interest rate corresponding to the maximum value in the first benefit and the second benefit as the target interest rate corresponding to the object grade.

In some embodiments of the present application, the data processing apparatus referred to above may further include:

the receiving module is used for receiving a loan request for lending the credit product sent by the target credit object;

the determining module is further used for determining a target score of the target credit object in each dimension information based on the loan request; determining a target object grade corresponding to the target credit object according to the target score; and taking the target interest rate corresponding to the target object grade as the interest rate of the credit product of the target credit object loan.

In some embodiments of the present application, the dimension information includes risk dimension information, and the obtaining module 610 may specifically be configured to:

obtaining pictorial information of a lending object lending the credit product; wherein the portrait information at least includes: credit information of the lending object, credit card information of the lending object and loan overdue information of the lending object;

and taking credit information of the borrowing object and credit card information of the borrowing object as sample data, and taking loan overdue information of the borrowing object as tag data to obtain scores of risk dimension information of the borrowing object of the borrowing product.

In some embodiments of the present application, the dimension information further includes funding hunger and thirst dimension information, and the portrait information further includes: asset information of the lending object; the acquisition module 610 may also be specifically configured to:

and calculating the score of the fund hunger and thirst dimension information of the lending object lending the credit product according to the asset information of the lending object and the credit card information of the lending object.

The data processing device provided in the embodiment of the present application may be used to execute the data processing method provided in the above embodiments of the method, and its implementation principle and technical effects are similar, and for the sake of brevity, it is not repeated here.

Based on the same inventive concept, the embodiment of the application also provides electronic equipment.

Fig. 7 is a schematic structural diagram of an electronic device according to an embodiment of the present application. As shown in fig. 7, the electronic device may include a processor 701 and a memory 702 storing computer programs or instructions.

In particular, the processor 701 may comprise a Central Processing Unit (CPU), or an application specific integrated circuit (Application Specific Integrated Circuit, ASIC), or may be configured as one or more integrated circuits implementing embodiments of the present invention.

Memory 702 may include mass storage for data or instructions. By way of example, and not limitation, memory 702 may comprise a Hard Disk Drive (HDD), floppy Disk Drive, flash memory, optical Disk, magneto-optical Disk, magnetic tape, or universal serial bus (Universal Serial Bus, USB) Drive, or a combination of two or more of the foregoing. The memory 702 may include removable or non-removable (or fixed) media, where appropriate. Memory 702 may be internal or external to the integrated gateway disaster recovery device, where appropriate. In a particular embodiment, the memory 702 is a non-volatile solid state memory. The Memory may include read-only Memory (Read Only Memory image, ROM), random-Access Memory (RAM), magnetic disk storage media devices, optical storage media devices, flash Memory devices, electrical, optical, or other physical/tangible Memory storage devices. Thus, in general, the memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software comprising computer-executable instructions and when the software is executed (e.g., by one or more processors) it is operable to perform the operations described in the data processing methods provided by the embodiments described above.

The processor 701 implements any of the data processing methods of the above embodiments by reading and executing computer program instructions stored in the memory 702.

In one example, the electronic device may also include a communication interface 703 and a bus 710. As shown in fig. 7, the processor 701, the memory 702, and the communication interface 703 are connected by a bus 710 and perform communication with each other.

The communication interface 703 is mainly used for implementing communication among the modules, devices, units and/or devices in the embodiment of the present invention.

Bus 710 includes hardware, software, or both that couple components of the electronic device to one another. By way of example, and not limitation, the buses may include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a HyperTransport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an infiniband interconnect, a Low Pin Count (LPC) bus, a memory bus, a micro channel architecture (MCa) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a video electronics standards association local (VLB) bus, or other suitable bus, or a combination of two or more of the above. Bus 710 may include one or more buses, where appropriate. Although embodiments of the invention have been described and illustrated with respect to a particular bus, the invention contemplates any suitable bus or interconnect.

The electronic device may execute the data processing method in the embodiment of the present invention, thereby implementing the data processing method described in the above embodiment.

In addition, in combination with the data processing method in the above embodiment, the embodiment of the present invention may be implemented by providing a readable storage medium. The readable storage medium has program instructions stored thereon; the program instructions, when executed by a processor, implement any of the data processing methods of the above embodiments.

In addition, in combination with the data processing method in the above embodiment, the embodiment of the present invention may provide a computer program product, where instructions in the computer program product when executed by a processor of an electronic device cause the electronic device to execute any one of the data processing methods in the above embodiment.

It should be understood that the invention is not limited to the particular arrangements and instrumentality described above and shown in the drawings. For the sake of brevity, a detailed description of known methods is omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method processes of the present invention are not limited to the specific steps described and shown, and those skilled in the art can make various changes, modifications and additions, or change the order between steps, after appreciating the spirit of the present invention.

The functional blocks shown in the above-described structural block diagrams may be implemented in hardware, software, firmware, or a combination thereof. When implemented in hardware, it may be, for example, an electronic circuit, an Application Specific Integrated Circuit (ASIC), suitable firmware, a plug-in, a function card, or the like. When implemented in software, the elements of the invention are the programs or code segments used to perform the required tasks. The program or code segments may be stored in a machine readable medium or transmitted over transmission media or communication links by a data signal carried in a carrier wave. A "machine-readable medium" may include any medium that can store or transfer information. Examples of machine-readable media include electronic circuitry, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, radio Frequency (RF) links, and the like. The code segments may be downloaded via computer networks such as the internet, intranets, etc.

It should also be noted that the exemplary embodiments mentioned in this disclosure describe some methods or systems based on a series of steps or devices. However, the present invention is not limited to the order of the above-described steps, that is, the steps may be performed in the order mentioned in the embodiments, or may be performed in a different order from the order in the embodiments, or several steps may be performed simultaneously.

Aspects of the present application are described above with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions/acts specified in the flowchart and/or block diagram block or blocks. Such a processor may be, but is not limited to being, a general purpose processor, a special purpose processor, an application specific processor, or a field programmable logic circuit. It will also be understood that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware which performs the specified functions or acts, or combinations of special purpose hardware and computer instructions.

In the foregoing, only the specific embodiments of the present invention are described, and it will be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes of the systems, modules and units described above may refer to the corresponding processes in the foregoing method embodiments, which are not repeated herein. It should be understood that the scope of the present invention is not limited thereto, and any equivalent modifications or substitutions can be easily made by those skilled in the art within the technical scope of the present invention, and they should be included in the scope of the present invention.

Claims

1. A method of data processing, the method comprising:

obtaining the score of each lending object in each dimension information;

2. The method of claim 1, wherein the determining, for each object level, a target interest rate corresponding to the object level comprises:

for each object level, determining an initial interest rate corresponding to the object level;

acquiring a first benefit corresponding to the initial interest rate;

adjusting the initial interest rate, and calculating a second benefit of the credit product when the credit product is borrowed according to the adjusted interest rate;

and determining a target interest rate corresponding to the object grade based on the first benefit and the second benefit.

3. The method of claim 2, wherein the determining the target interest rate corresponding to the object level based on the first benefit and the second benefit comprises:

4. The method of claim 1, wherein after said determining, for each object level, a target interest rate corresponding to said object level, the method further comprises:

receiving a loan request for lending the credit product sent by the target credit object;

determining a target score of the target credit object in each dimension information based on the loan request;

determining a target object grade corresponding to the target credit object according to the target score;

and taking the target interest rate corresponding to the target object grade as the interest rate of the credit product of the target credit object loan.

5. The method of claim 1, wherein the dimension information includes risk dimension information, and wherein the obtaining a score for each of the lending objects in each dimension information comprises:

6. The method of claim 5, wherein the dimension information further comprises funding hunger dimension information, the portrayal information further comprising: asset information of the lending object; the step of obtaining the score of each lending object in each dimension information comprises the following steps:

7. A data processing apparatus, the apparatus comprising:

8. An electronic device comprising a processor, a memory and a program or instruction stored on said memory and executable on said processor, said program or instruction when executed by said processor implementing the steps of the data processing method according to any of claims 1-6.

9. A readable storage medium, characterized in that the readable storage medium has stored thereon a program or instructions which, when executed by a processor, implement the steps of the data processing method according to any of claims 1-6.

10. A computer program product, characterized in that instructions in the computer program product, when executed by a processor of an electronic device, cause the electronic device to perform the steps of the data processing method according to any of claims 1-6.