CN114092223A - Quota determining method, device, equipment and storage medium - Google Patents

Abstract

The embodiment of the invention relates to the field of general finance, in particular to a method, a device, equipment and a storage medium for determining a quota. The method is applied to the server and can comprise the following steps: when a limit application is received, acquiring a target small micro enterprise identifier carried by the limit application; screening at least one target set from a database according to the target small and micro enterprise identification; and determining a target limit corresponding to the target small micro-enterprise according to the at least one target set. By the technical scheme, small and micro enterprises in the database can be screened according to the quota application, and the target quota corresponding to the small and micro enterprises is determined.

Description

A quota determination method, device, equipment and storage medium

technical field

Embodiments of the present invention relate to the field of inclusive finance, and in particular, to a method, apparatus, device, and storage medium for determining a quota.

Background technique

Small and micro enterprises are easily affected by changes in the external economic environment and lack of personal investment management experience. The traditional product and service model based on product research and development in the financial industry and oriented towards large and medium-sized enterprises cannot effectively evaluate the actual value of small and micro enterprises. The poor operation and default rate of micro-enterprises are increasing year by year, which brings huge challenges to the development of inclusive finance.

In this context, it is urgent to find a model suitable for the value evaluation of small and micro enterprises, and to reflect the value concept with data, based on the big data analysis and data modeling of individuals and their small and micro enterprises, objective evaluation, and complete the value of small and micro enterprises Calculation is a new model.

SUMMARY OF THE INVENTION

Embodiments of the present invention provide a method, device, device, and storage medium for determining a quota, so as to screen small and micro enterprises in a database according to quota application, and determine a target quota corresponding to the small and micro enterprises.

In a first aspect, an embodiment of the present invention provides a method for determining a quota, including:

When receiving a quota application, obtain the target small and micro enterprise logo carried in the quota application;

Filter out at least one target set from the database according to the target small and micro enterprise identifier;

The target quota corresponding to the target small and micro enterprise is determined according to the at least one target set.

In a second aspect, an embodiment of the present invention further provides an apparatus for determining a quota, the apparatus comprising:

The acquiring module is used to acquire the target small and micro enterprise identifier carried in the quota application when the quota application is received;

a screening module, configured to screen out at least one target set from the database according to the target small and micro enterprise identifier;

A determination module, configured to determine the target quota corresponding to the target small and micro enterprise according to the at least one target set.

In a third aspect, an embodiment of the present invention further provides an electronic device, including a memory, a processor, and a computer program stored in the memory and running on the processor, the processor implementing the program as described in the present invention when the processor executes the program The quota determination method described in any one of the embodiments.

In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium on which a computer program is stored, and when the program is executed by a processor, implements the quota determination method according to any one of the embodiments of the present invention.

In the embodiment of the present invention, the small and micro enterprises in the database are screened according to the quota application, and the target quota corresponding to the small and micro enterprises is determined.

Description of drawings

In order to illustrate the technical solutions of the embodiments of the present invention more clearly, the following briefly introduces the accompanying drawings used in the embodiments. It should be understood that the following drawings only show some embodiments of the present invention, and therefore do not It should be regarded as a limitation of the scope, and for those of ordinary skill in the art, other related drawings can also be obtained according to these drawings without any creative effort.

1 is a flowchart of a method for determining a quota provided by Embodiment 1 of the present invention;

2 is a flowchart of data value assessment in database preprocessing provided by Embodiment 1 of the present invention;

3 is a flow chart of establishing a quota calculation model in a quota determination method provided in Embodiment 1 of the present invention;

4 is a flowchart of generating a user quota in a quota determination method provided in Embodiment 1 of the present invention;

Fig. 5 is the working flow chart of the HP financial quota calculation platform of a quota determination method provided in Embodiment 1 of the present invention;

6 is a schematic structural diagram of a quota determination device provided in Embodiment 2 of the present invention;

7 is a schematic structural diagram of an electronic device according to Embodiment 3 of the present invention;

FIG. 8 is a schematic structural diagram of a computer-readable storage medium including a computer program according to Embodiment 4 of the present invention.

Detailed ways

The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention, but not to limit the present invention. In addition, it should be noted that, for the convenience of description, the drawings only show some but not all structures related to the present invention. Furthermore, the embodiments of the invention and the features of the embodiments may be combined with each other without conflict.

Before discussing the exemplary embodiments in greater detail, it should be mentioned that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although a flowchart depicts various operations (or steps) as a sequential process, many of the operations may be performed in parallel, concurrently, or concurrently. Additionally, the order of operations can be rearranged. The process may be terminated when its operation is complete, but may also have additional steps not included in the figures. The processes may correspond to methods, functions, procedures, subroutines, subroutines, and the like. Furthermore, the embodiments of the invention and the features of the embodiments may be combined with each other without conflict.

The term "including" and its variants used in the present invention are open to include, ie, "including but not limited to". The term "based on" is "based at least in part on." The term "one embodiment" means "at least one embodiment."

It should be noted that like numerals and letters refer to like items in the following figures, so once an item is defined in one figure, it does not require further definition and explanation in subsequent figures. Meanwhile, in the description of the present invention, the terms "first", "second", etc. are only used to distinguish the description, and cannot be understood as indicating or implying relative importance.

The storage and/or processing of the following attribute information shall comply with the relevant provisions of national laws and regulations.

Example 1

FIG. 1 is a flowchart of a method for determining a quota provided by Embodiment 1 of the present invention. This embodiment is applicable to the situation of determining quotas. The method can be executed by the quota determining device in the embodiment of the present invention, and the device can use software And/or hardware implementation, as shown in Figure 1, the method specifically includes the following steps:

S101. When a quota application is received, obtain the target small and micro enterprise identifier carried in the quota application.

In this embodiment, the quota application can be understood as an application for a loan quota initiated by the user to the tenant on the platform. Among them, users refer to small and micro enterprises (small and micro enterprises are collectively referred to as small enterprises, micro enterprises, family workshop enterprises and individual industrial and commercial households), tenants refer to financial institutions, and platforms refer to the inclusive business data value evaluation platform , to support tenants and users to provide data access, data value assessment and quota calculation services.

It should be noted that the target small and micro enterprise identifier can be understood as the enterprise information of the small and micro enterprise carried in the quota application initiated by the user, such as the enterprise name of the small and micro enterprise, unified social credit code and legal person identity information and other information.

S102. Screen out at least one target set from the database according to the target small and micro enterprise identifier.

In this embodiment, the database can be understood as a database formed by data information contained in a plurality of existing small and micro enterprises. The small and micro enterprises in the database can be classified and stored according to the enterprise ID, and the small and micro enterprises that meet the needs can be screened from the database according to the small and micro enterprise ID.

Specifically, the target set refers to a set formed by at least one small and micro enterprise that is screened from the database and conforms to the identification of the target small and micro enterprise.

All data in the database is divided into three categories: business owners, small and micro businesses, and the external environment. Further, business owners, small and micro enterprises, and the external environment are divided into multiple sets, including education and training, basic information, registration, business operations, macroeconomics, and maps. Among them, each set corresponds to specific data and data-related attributes. For example, the "real estate and vehicle property" collection in the business owner classification corresponds to the data "real estate valuation, vehicle valuation", and the data associated attributes of the data "real estate valuation, vehicle valuation" are "ID card, house registration number, vehicle license plate".

S103. Determine a target quota corresponding to the target small and micro enterprise according to at least one target set.

Among them, the target quota refers to the application quota of the small and micro enterprises that meet the identification of the target small and micro enterprises in the target set corresponding to the target small and micro enterprises.

The technical solution of this embodiment can screen the small and micro enterprises in the database according to the quota application, and determine the target quota corresponding to the small and micro enterprises.

Optionally, determining the target quota corresponding to the target small and micro enterprise according to at least one target set includes:

Get the attribute information corresponding to each target set.

Specifically, the attribute information refers to the information in the data association attribute column. For example, the attribute information corresponding to the set "student status and education background" is "ID card, name".

The conversion rule corresponding to each target set is determined according to the attribute information.

In this embodiment, the conversion rule can be understood as a rule for converting a set into a specific calculation method. For example, the conversion rule corresponding to the real estate may be the area of the real estate (unit is square meters) × the unit price per square meter. Specifically, in the actual operation process, each tenant using the platform can set an independent data value conversion model according to the data.

The evaluation value corresponding to each target set is determined according to each target set and the conversion rule corresponding to each target set.

It should be noted that evaluating the value refers to identifying the value data, risk data, regional and industry data according to the business classification of the database, and directly evaluating the data value according to the data of different classifications. The value type includes positive or negative.

Exemplarily, in the actual operation process, data value conversion needs to complete data classification, data value evaluation, and data association analysis on the basis of data analysis. The data classification corresponds to the data dependency analysis result of the database, the identification label comes from the data primary key definition, and the evaluation rules and value types are determined by the data analyst. Tenant signs are divided into platform-level shared data and tenant-specific data. Tenants can customize the value evaluation results of each data on the basis of platform-level data and participate in the data of each tenant.

The data value conversion model is shown in Table 1.

Table 1

Table 2-7 is an example of five data value conversion results.

The results of data value conversion of tax data are shown in Table 2.

Table 2

The results of data value conversion of litigation data are shown in Table 3.

table 3

The results of data value conversion of real estate data are shown in Table 4.

Table 4

The results of data value conversion of vehicle production data are shown in Table 5.

table 5

The results of data value conversion of behavioral data are shown in Table 6.

Table 6

The results of data value conversion of basic business information are shown in Table 7.

Table 7

The target quota corresponding to the target small and micro enterprises is determined according to the evaluation value corresponding to each target set, the weight corresponding to each target set and the risk adjustment coefficient.

In this embodiment, in order to meet the requirements of the comprehensive quota calculation in the next step, various types of data must include individual and enterprise identification labels, and weight information set according to a unified standard.

Specifically, the risk adjustment coefficient may be set manually, or may be a specific numerical value commonly used in the prior art to adjust the risk degree, which is not limited in this embodiment.

Optionally, before obtaining the target small and micro enterprise logo carried in the quota application, it also includes:

Obtain the first data corresponding to at least two small and micro enterprises.

It should be explained that the first data may be personal, enterprise or environmental information corresponding to the small and micro enterprises. For example, it can be the educational information of the business owner, the business behavior of the business, or the macro location of the environment.

Classify the first data according to the main enterprise node, the enterprise node and the external environment node to obtain at least three first sets.

It should be noted that the main node of the enterprise reflects the multiple milestone stages that the business owner must go through in the process of growing with small and micro enterprises. The enterprise node is defined according to the general process of production and operation of small and micro enterprises, and the external environment node is defined according to the requirements of the small and micro enterprises. Defined by the environmental theme at the location.

In this embodiment, the first set may be understood as a set obtained by classifying the first data corresponding to the small and micro enterprises according to the main enterprise node, the enterprise node and the external environment node. The first data is classified according to three nodes, and after classification, each node corresponds to at least one set, so there are at least three first sets.

Exemplarily, in the actual operation process, during the existence of small and micro enterprises, their production and operation activities are affected by three major business themes: individuals, enterprises and the environment. Personal themes cover basic identification of business owners, education, consumption, medical care, behavior, property and risks; corporate topics include corporate identification, business behavior, property, corporate behavior, corporate associations and risks; environmental topics provide macro-local and industry economic analysis, etc. These businesses form a complete closed loop for the operation of small and micro enterprises. The specific data corresponding to small and micro enterprises can be shown in Table 8.

Table 8

The data in each first set is analyzed to obtain enterprise identification information corresponding to the data in each first set.

It can be known that the enterprise identification information refers to the identification information such as the name of the enterprise, the unified social credit code and the legal person ID card.

The data in each first set is stored in association with the enterprise identification information corresponding to the data.

Specifically, associative storage can be understood as establishing and storing the relationship between the data in each first set and the enterprise identification information corresponding to the data. A connection is generated between the two, so that when searching for the data in the first set, the enterprise identification information corresponding to the data can be directly associated.

Optionally, analyze the data in each first set, and obtain enterprise identification information corresponding to the data in each first set, including:

If the first set is a non-value analysis set, the data in the first set is analyzed to obtain enterprise identification information corresponding to the data in each first set.

It should be noted that the non-value analysis set refers to the set that does not require value analysis. For example, the non-value analysis set can be the basic information set of the business owner (for example, the basic information of the business owner can be the business owner's name, ID number and family information) and the registration set of small and micro enterprises (the registration information of small and micro enterprises such as It can be a collection of information such as registration year and registration place).

If the first set is a value analysis set, the data in the first set is analyzed to obtain enterprise identification information corresponding to the data in each first set, and the conversion rules corresponding to the first set are obtained.

It should be noted that the value analysis set refers to the set for which value analysis needs to be performed. For example, the value analysis set may be a set of real estate and automobile production of business owners, a set of enterprise value of small and micro enterprises, and the like.

Optionally, if the first set is a value analysis set, analyze the data in the first set, obtain enterprise identification information corresponding to the data in each first set, and obtain the conversion rules corresponding to the first set, including: :

If the first set is a value analysis set, the data in the first set is analyzed to obtain enterprise identification information corresponding to the data in each first set.

Get the attribute information of the first set.

The conversion rule corresponding to the first set is determined according to the attribute information of the first set.

Optionally, if the first set is a non-value analysis set, the data in the first set is analyzed, and the enterprise identification information corresponding to the data in each first set is obtained, including:

If the data in the first set is the basic information of the business owner and/or the company registration information, the first set is determined to be a non-value analysis set, and the data in the first set is analyzed to obtain the data in each first set. The enterprise identification information corresponding to the data.

Among them, the basic information of the business owner refers to the business owner's ID card, mobile phone number, and family information. Enterprise registration information refers to the industrial and commercial registration information of small and micro enterprises.

FIG. 2 is a flowchart of data value evaluation in database preprocessing provided by Embodiment 1 of the present invention. In step S101, before obtaining the target small and micro enterprise identifier carried in the quota application, the database in S102 is preprocessed for data value evaluation, as shown in FIG. As shown in Figure 2, the method specifically includes the following operations:

Obtain the first data corresponding to at least two small and micro enterprises from the database; classify the first data according to the main node of the enterprise, the enterprise node and the external environment node to obtain at least three first sets; judge each first set Whether value analysis is involved.

If the first set does not involve value analysis, the first set is a non-value analysis set, the data in the first set is analyzed, the data primary key (ie the enterprise identification information corresponding to the data in the set) is analyzed, and other Data association rules, complete other data modeling. For example, if the enterprise identification information obtained after analyzing the data primary key of data A in the first set is company A, the data A and company A are stored in association; the enterprise identification information obtained after analyzing the data primary key of data B in the first set If the information is company B, data B and company B are stored in association.

If the first set involves value analysis, the first set is a value analysis set, and the data in the first set is analyzed, the primary key of the data is analyzed, and the enterprise identification information corresponding to the data in the set is obtained. For the attribute information of the first set, the conversion rule corresponding to the first set is determined according to the attribute information of the first set, the conversion rule is analyzed, and finally, a data value conversion result is generated. For example, if the enterprise identification information obtained after analyzing the data primary key of data A in the first set is company A, then the data A and company A are stored in association, and at the same time, obtaining the attribute information of the first set can be used for real estate evaluation , the conversion rule corresponding to the real estate evaluation is determined. The conversion rule may be, for example, the area of the real estate (unit: square meters) × the unit price per square meter, and finally, the corresponding conversion result after the data value conversion of the first set is generated.

Optionally, the target quota corresponding to the target small and micro enterprises is determined according to the evaluation value corresponding to each target set, the weight corresponding to each target set, and the risk adjustment coefficient, including:

The target amount is calculated based on the following formula:

1>j>0，V_n为目标集合对应的评估价值，W_n为目标集合对应的权重，K为目标集合的数量，j为风险调节系数。in,

1>j>0, V _n is the evaluation value corresponding to the target set, W _n is the weight corresponding to the target set, K is the number of target sets, and j is the risk adjustment coefficient.

It should be noted that n is the set currently being calculated, the weight corresponding to the target set is set according to a unified standard, and the risk adjustment coefficient can be set manually, or it can be a specific method commonly used in the prior art to adjust the risk degree. , which is not limited in this embodiment.

In the actual operation process, the platform provides tenants with the function of configuring measurement models, selects value data sets online, and sets value data weights. Through identification tags and data association methods, the assessed value _Vn corresponding to the target set can be precisely located to individuals and enterprises. .

3 is a flow chart of establishing a quota calculation model in a quota determination method provided in Embodiment 1 of the present invention, which is applicable to the calculation of target quotas in the quota determination method of this embodiment. Determine the device to execute, and the device can be implemented in software and/or hardware. As shown in Figure 3, the establishment of the quota measurement model specifically includes the following operations:

First, a value data set (ie, the evaluation value V _n corresponding to the above target set) is selected. Next, configure the value weight (ie the weight W _n corresponding to the target set), the data set association rule (ie the enterprise identification information stored in association with the target set) and the risk adjustment coefficient (ie the risk adjustment coefficient j). Finally, validate the model.

Optionally, when a quota application is received, the target small and micro enterprise identifiers carried in the quota application include:

Get the identity information entered by the user.

Exemplarily, the identity information may be personal information that can prove the identity of the user, such as the user's name and ID number.

Perform identity verification based on identity information.

The identity verification refers to auditing and checking the identity information input by the user to verify whether the identity information input by the user is correct, such as whether the user's name and ID number match.

If the identity verification is passed, when the quota application is received, the target small and micro enterprise identifier carried in the quota application is obtained.

In the actual operation process, users sign a data use authorization agreement before applying for a quota on the platform. After passing the user identity verification, the platform calculates the quota calculation model configured by each tenant, and pushes business opportunities to the tenants.

FIG. 4 is a flowchart of generating a user quota in a quota determination method provided in Embodiment 1 of the present invention, which is applicable to the situation in which a user quota is generated in the quota determination method of this embodiment, and the method can be determined by the quota in this embodiment of the present invention. The device can be implemented by means of software and/or hardware. As shown in FIG. 4 , generating a user quota specifically includes the following operations:

Obtain the identity information entered by the user, and perform identity verification based on the identity information. If the identity verification is passed, the platform calculates the quota calculation model configured by the tenant, selects qualified financial enterprise tenants, generates and displays the tenant quota, and pushes business opportunities to users.

Optionally, after determining the target quota corresponding to the target small and micro enterprise according to at least one target set, the method further includes:

Displays the target amount.

After receiving the application quota issuance request, the quota is issued according to the target quota.

Wherein, the request for applying for quota issuance may be applied by the user on the platform, and the quota issuance may be issued by the platform to the user.

As an exemplary description of this embodiment, FIG. 5 is a working flow chart of the HP financial quota calculation platform of a quota determination method provided in Embodiment 1 of the present invention. The inclusive business data value evaluation platform selects data sources with market credibility , Under the framework of multi-party agreements between users, platforms, financial enterprises, and data suppliers, the quota measurement business is carried out. As shown in Figure 5, the workflow of the HP Financial Quota Calculation Platform specifically includes:

Signing stage: users register and initiate authorization, financial enterprises and data providers sign contracts with the platform, and the quota calculation platform generates an authorization letter.

Parameter and data preparation stage: the user fills in a questionnaire (because the quota calculation model in the embodiment of the present invention uses many data types, according to the personal information protection requirements in the Civil Code, the user authorization must be obtained before the quota calculation, and the user authorization information can be adjusted and updated. ), the data supplier prepares the data and transmits the data to the financial enterprise through the data interface of the platform. The financial enterprise analyzes the value data and creates a quota calculation model according to the data.

Quota calculation stage: After the user fills in the questionnaire, the user initiates a quota application, and the financial enterprise calculates the quota according to the quota application initiated by the user. Make artificial adjustments.

Quota confirmation stage: After the financial enterprise calculates, verifies and adjusts the quota, it feeds back the quota information to the user, and the user can check the quota.

Quota issuance stage: After the user confirms the quota, he applies for quota issuance, the financial enterprise issues the quota, and the quota calculation platform collects the feedback on the post-loan situation.

The technical solution of the embodiment of the present invention is based on big data technology, integrates various data of users and enterprises, and integrates the business closed-loop analysis method and the data quota conversion model for the first time. Micro-enterprise financing has innovated new mechanisms.

Embodiment 2

FIG. 6 is a schematic structural diagram of an apparatus for determining a quota according to Embodiment 2 of the present invention. This embodiment can be applied to the situation of quota determination, the device can be implemented in software and/or hardware, and the device can be integrated into any device that provides the function of quota determination, as shown in FIG. 6 , the quota determination device Specifically, it includes: an acquisition module 210 , a screening module 220 and a determination module 230 .

Further, the determining module 230 may further include:

a first obtaining unit, used to obtain attribute information corresponding to each target set;

a first determining unit, configured to determine a conversion rule corresponding to each target set according to the attribute information;

a second determining unit, configured to determine the evaluation value corresponding to each target set according to the conversion rules corresponding to each target set and each target set;

The third determining unit is configured to determine the target quota corresponding to the target small and micro enterprises according to the evaluation value corresponding to each target set, the weight corresponding to each target set, and the risk adjustment coefficient.

Further, before the acquiring module 210 acquires the target small and micro enterprise identifier carried in the quota application, it also includes:

a first data acquisition module, configured to acquire the first data corresponding to at least two small and micro enterprises;

a classification module, configured to classify the first data according to the main enterprise node, the enterprise node and the external environment node to obtain at least three first sets;

an analysis module, configured to analyze the data in each first set to obtain enterprise identification information corresponding to the data in each first set;

The storage module is used for storing the data in each first set in association with the enterprise identification information corresponding to the data.

Further, the analysis module may also include:

a first analysis unit, configured to analyze the data in the first set if the first set is a non-value analysis set, and obtain enterprise identification information corresponding to the data in each first set;

The second analysis unit is configured to analyze the data in the first set if the first set is a value analysis set, obtain enterprise identification information corresponding to the data in each first set, and obtain the first set Set the corresponding transformation rules.

Further, the second analysis unit may also include:

an analysis subunit, configured to analyze the data in the first set if the first set is a value analysis set, and obtain enterprise identification information corresponding to the data in each first set;

obtaining a subunit for obtaining the attribute information of the first set;

A determination subunit, configured to determine the conversion rule corresponding to the first set according to the attribute information of the first set.

Further, the first analysis unit is specifically used for:

If the data in the first set is business owner basic information and/or enterprise registration information, determine that the first set is a non-value analysis set, analyze the data in the first set, and obtain each Enterprise identification information corresponding to the data in a set.

Further, the third determining unit is specifically used for:

The target amount is calculated based on the following formula:

1>j>0，V_n为目标集合对应的评估价值，W_n为目标集合对应的权重，K为目标集合的数量，j为风险调节系数。in,

1>j>0, V _n is the evaluation value corresponding to the target set, W _n is the weight corresponding to the target set, K is the number of target sets, and j is the risk adjustment coefficient.

Further, the obtaining module 210 may also include:

a second acquiring unit, configured to acquire the identity information input by the user;

a verification unit, configured to perform identity verification according to the identity information;

The third acquiring unit is configured to acquire the target small and micro enterprise identifier carried in the quota application when the quota application is received if the identity verification is passed.

Further, after the determining module 230 determines the target quota corresponding to the target small and micro enterprises according to the at least one target set, the method further includes:

a display module for displaying the target amount;

The issuing module is configured to issue the quota according to the target quota after receiving the application quota distribution request.

The above product can execute the method provided by any embodiment of the present invention, and has corresponding functional modules and beneficial effects for executing the method.

The technical solution of this embodiment can screen the small and micro enterprises in the database according to the quota application, and determine the target quota corresponding to the small and micro enterprises.

Embodiment 3

FIG. 7 is a schematic structural diagram of an electronic device according to Embodiment 3 of the present invention. Figure 7 shows a block diagram of an electronic device 312 suitable for use in implementing embodiments of the present invention. The electronic device 312 shown in FIG. 7 is only an example, and should not impose any limitation on the function and scope of use of the embodiment of the present invention. Device 312 is a typical credit determination function computing device.

As shown in FIG. 7, electronic device 312 takes the form of a general-purpose computing device. Components of electronic device 312 may include, but are not limited to, one or more processors 316, storage 328, and a bus 318 that connects various system components including storage 328 and processor 316.

The bus 318 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, a graphics acceleration port, a processor, or a local bus using any of a variety of bus structures. For example, these architectures include, but are not limited to, Industry Standard Architecture (ISA) bus, Micro Channel Architecture (MCA) bus, enhanced ISA bus, Video Electronics Standards Association (Video Electronics Standards Association) , VESA) local bus and peripheral component interconnect (Peripheral Component Interconnect, PCI) bus.

Electronic device 312 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by electronic device 312, including both volatile and nonvolatile media, removable and non-removable media.

Storage 328 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 330 and/or cache memory 332 . Electronic device 312 may further include other removable/non-removable, volatile/non-volatile computer system storage media. For example only, storage system 334 may be used to read and write to non-removable, non-volatile magnetic media (not shown in FIG. 7, commonly referred to as a "hard drive"). Although not shown in FIG. 7, a magnetic disk drive for reading and writing to removable non-volatile magnetic disks (eg "floppy disks") and removable non-volatile optical disks (eg Compact Disc-Read only) may be provided. Read Only Memory, CD-ROM), Digital Video Disc (Digital Video Disc-Read Only Memory, DVD-ROM) or other optical media) read and write optical disc drives. In these cases, each drive may be connected to bus 318 through one or more data media interfaces. Storage 328 may include at least one program product having a set (eg, at least one) of program modules configured to perform the functions of various embodiments of the present invention.

A program 336 having a set (at least one) of program modules 326, which may be stored, for example, in a storage device 328, such program modules 326 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, which An implementation of a network environment may be included in each or some combination of the examples. Program modules 326 generally perform the functions and/or methods of the described embodiments of the present invention.

The electronic device 312 may also communicate with one or more external devices 314 (eg, a keyboard, pointing device, camera, display 324, etc.), may also communicate with one or more devices that enable a user to interact with the electronic device 312, and/or Or with any device (eg, network card, modem, etc.) that enables the electronic device 312 to communicate with one or more other computing devices. Such communication may take place through input/output (I/O) interface 322 . Also, the electronic device 312 may communicate with one or more networks (eg, Local Area Network (LAN), Wide Area Network, WAN) and/or a public network such as the Internet through a network adapter 320 . As shown, network adapter 320 communicates with other modules of electronic device 312 via bus 318 . It should be understood that, although not shown, other hardware and/or software modules may be used in conjunction with electronic device 312, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, Redundant Arrays of Independent Disks, RAID) systems, tape drives, and data backup storage systems.

The processor 316 executes various functional applications and data processing by running the program stored in the storage device 328, for example, to implement the method for determining the amount provided by the above embodiments of the present invention.

Embodiment 4

FIG. 8 is a schematic structural diagram of a computer-readable storage medium containing a computer program according to Embodiment 4 of the present invention. An embodiment of the present invention provides a computer-readable storage medium 61 on which a computer program 610 is stored. The computer-readable storage medium 61 is connected to one or more processors 316, and when the program is executed by one or more processors Realize the quota determination method provided by all the invention embodiments of this application:

When receiving a quota application, obtain the target small and micro enterprise logo carried in the quota application;

Filter out at least one target set from the database according to the target small and micro enterprise identifier;

The target quota corresponding to the target small and micro enterprise is determined according to the at least one target set.

Any combination of one or more computer-readable media may be employed. The computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium or any combination of the two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus or device, or a combination of any of the above. More specific examples (a non-exhaustive list) of computer readable storage media include: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read only memory (ROM), Erasable programmable read only memory (EPROM or flash memory), optical fiber, portable compact disk read only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the above. In this document, a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

A computer-readable signal medium may include a propagated data signal in baseband or as part of a carrier wave, with computer-readable program code embodied thereon. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the foregoing. A computer-readable signal medium can also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device .

Program code embodied on a computer readable medium may be transmitted using any suitable medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

In some embodiments, the client and server can use any currently known or future developed network protocol such as HTTP (Hyper Text Transfer Protocol) to communicate, and can communicate with digital data in any form or medium Communication (eg, a communication network) interconnects. Examples of communication networks include local area networks ("LAN"), wide area networks ("WAN"), the Internet (eg, the Internet), and peer-to-peer networks (eg, ad hoc peer-to-peer networks), as well as any currently known or future development network of.

The above-mentioned computer-readable medium may be included in the above-mentioned electronic device; or may exist alone without being assembled into the electronic device.

Computer program code for carrying out operations of the present invention may be written in one or more programming languages, including object-oriented programming languages such as Java, Smalltalk, C++, and also conventional procedures, or a combination thereof programming language - such as "C" or a similar programming language. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer, or entirely on the remote computer or server. Where a remote computer is involved, the remote computer may be connected to the user's computer through any kind of network including a local area network (LAN) or wide area network (WAN), or may be connected to an external computer (eg, using an Internet service provider to connect over the Internet) .

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 disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code that contains one or more logical functions for implementing the specified functions executable instructions. It should also be noted that, in some alternative implementations, the functions noted in the blocks 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 is also noted that each block of the block diagrams and/or flowchart illustrations, and combinations of blocks in the block diagrams and/or flowchart illustrations, can be implemented in dedicated hardware-based systems that perform the specified functions or operations , or can be implemented in a combination of dedicated hardware and computer instructions.

The units involved in the embodiments of the present disclosure may be implemented in a software manner, and may also be implemented in a hardware manner. Among them, the name of the unit does not constitute a limitation of the unit itself under certain circumstances.

The functions described herein above may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: Field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), Systems on Chips (SOCs), Complex Programmable Logical Devices (CPLDs) and more.

In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in connection with the instruction execution system, apparatus or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. Machine-readable media may include, but are not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media would include one or more wire-based electrical connections, portable computer disks, hard disks, random access memory (RAM), read only memory (ROM), erasable programmable read only memory (EPROM or flash memory), fiber optics, compact disk read only memory (CD-ROM), optical storage, magnetic storage, or any suitable combination of the foregoing.

Note that the above are only preferred embodiments of the present invention and applied technical principles. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the protection scope of the present invention. Therefore, although the present invention has been described in detail through the above embodiments, the present invention is not limited to the above embodiments, and can also include more other equivalent embodiments without departing from the concept of the present invention. The scope is determined by the scope of the appended claims.

Claims (15)

1. a quota determination method, is characterized in that, comprises: When receiving a quota application, obtain the target small and micro enterprise logo carried in the quota application; Filter out at least one target set from the database according to the target small and micro enterprise identifier; The target quota corresponding to the target small and micro enterprise is determined according to the at least one target set. 2. The method according to claim 1, wherein determining the target quota corresponding to the target small and micro enterprise according to the at least one target set comprises: Get the attribute information corresponding to each target set; Determine the conversion rule corresponding to each target set according to the attribute information; Determine the evaluation value corresponding to each target set according to each target set and the conversion rule corresponding to each target set; The target quota corresponding to the target small and micro enterprises is determined according to the evaluation value corresponding to each target set, the weight corresponding to each target set and the risk adjustment coefficient. 3. The method according to claim 1, characterized in that, before obtaining the target small and micro enterprise identification carried by the quota application, further comprising: Obtain the first data corresponding to at least two small and micro enterprises; Classify the first data according to the main enterprise node, the enterprise node and the external environment node to obtain at least three first sets; Analyzing the data in each first set to obtain enterprise identification information corresponding to the data in each first set; The data in each first set is stored in association with the enterprise identification information corresponding to the data. 4. The method according to claim 3, wherein the data in each first set is analyzed to obtain enterprise identification information corresponding to the data in each first set comprising: If the first set is a non-value analysis set, analyze the data in the first set to obtain enterprise identification information corresponding to the data in each first set; If the first set is a value analysis set, the data in the first set is analyzed to obtain enterprise identification information corresponding to the data in each first set, and the conversion rules corresponding to the first set are obtained. 5 . The method according to claim 4 , wherein if the first set is a value analysis set, then the data in the first set is analyzed to obtain an enterprise identifier corresponding to the data in each first set. 6 . information, and obtain the conversion rules corresponding to the first set, including: If the first set is a value analysis set, analyze the data in the first set to obtain enterprise identification information corresponding to the data in each first set; obtain attribute information of the first set; The conversion rule corresponding to the first set is determined according to the attribute information of the first set. 6. The method according to claim 4, wherein, if the first set is a non-value analysis set, then the data in the first set is analyzed to obtain the corresponding data in each first set. Corporate identity information includes: If the data in the first set is business owner basic information and/or enterprise registration information, determine that the first set is a non-value analysis set, analyze the data in the first set, and obtain each Enterprise identification information corresponding to the data in a set. 7. The method according to claim 2, wherein the target quota corresponding to the target small and micro enterprises is determined according to the evaluation value corresponding to each target set, the corresponding weight of each target set and the risk adjustment coefficient, comprising: The target amount is calculated based on the following formula:

in,

V _n is the evaluation value corresponding to the target set, W _n is the weight corresponding to the target set, K is the number of target sets, and j is the risk adjustment coefficient. 8. The method according to claim 1, wherein when receiving the quota application, obtaining the target small and micro enterprise identifier carried in the quota application comprises: Obtain the identity information entered by the user; Perform identity verification according to the identity information; If the identity verification is passed, when the quota application is received, the target small and micro enterprise identifier carried in the quota application is obtained. 9 . The method according to claim 1 , wherein after determining the target quota corresponding to the target small and micro enterprise according to the at least one target set, the method further comprises: 10 . display the target amount; After receiving the application quota issuance request, the quota is issued according to the target quota. 10. A quota determination device, characterized in that it comprises: The acquiring module is used to acquire the target small and micro enterprise identifier carried in the quota application when the quota application is received; a screening module, configured to screen out at least one target set from the database according to the target small and micro enterprise identifier; A determination module, configured to determine the target quota corresponding to the target small and micro enterprise according to the at least one target set. 11. The apparatus according to claim 10, wherein the determining module further comprises: a first obtaining unit, used to obtain attribute information corresponding to each target set; a first determining unit, configured to determine a conversion rule corresponding to each target set according to the attribute information; a second determining unit, configured to determine the evaluation value corresponding to each target set according to the conversion rules corresponding to each target set and each target set; The third determining unit is configured to determine the target quota corresponding to the target small and micro enterprises according to the evaluation value corresponding to each target set, the weight corresponding to each target set, and the risk adjustment coefficient. 12. The apparatus according to claim 10, wherein the acquiring module further comprises: a second acquiring unit, configured to acquire the identity information input by the user; a verification unit, configured to perform identity verification according to the identity information; The third acquiring unit is configured to acquire the target small and micro enterprise identifier carried in the quota application when the quota application is received if the identity verification is passed. 13. The apparatus according to claim 11, wherein the third determining unit is specifically configured to: The target amount is calculated based on the following formula:

in,

V _n is the evaluation value corresponding to the target set, W _n is the weight corresponding to the target set, K is the number of target sets, and j is the risk adjustment coefficient. 14. An electronic device, comprising: one or more processors; memory for storing one or more programs; The one or more programs, when executed by the one or more processors, cause the processors to implement the method of any of claims 1-9. 15. A computer-readable storage medium comprising a computer program, on which the computer program is stored, characterized in that, when the program is executed by one or more processors, the method according to any one of claims 1-9 is implemented .

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