CN114092223A - Quota determining method, device, equipment and storage medium - Google Patents
Quota determining method, device, equipment and storage medium Download PDFInfo
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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
Technical Field
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.
Background
The small and medium-sized enterprises are susceptible to external economic environment change and insufficient personal investment management experience, the product service mode facing the large and medium-sized enterprises based on financial industry product research and development is not capable of effectively evaluating the actual value of the small and medium-sized enterprises, and the poor operation and default rate of the small and medium-sized enterprises are on the trend of increasing year by year in recent years, which brings great challenges to the development of the popular finance.
Under the background, a mode suitable for evaluating the value of the small and micro enterprises is urgently needed to be found, the data embodies the value concept, and the mode is a new mode based on the analysis and data modeling of individuals and the small and micro enterprises to which the data embodies, objective evaluation and completion of the value measurement and calculation of the small and micro enterprises.
Disclosure of Invention
The embodiment of the invention provides a method, a device, equipment and a storage medium for determining a limit, which are used for screening small micro-enterprises in a database according to limit application and determining target limits corresponding to the small micro-enterprises.
In a first aspect, an embodiment of the present invention provides a method for determining an amount, including:
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.
In a second aspect, an embodiment of the present invention further provides an amount determining device, where the device includes:
the acquisition module is used for acquiring a target small and micro enterprise identifier carried by the limit application when the limit application is received;
the screening module is used for screening at least one target set from a database according to the target small and micro enterprise identification;
and the determining module is used for determining a target limit corresponding to the target small 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 on the memory and executable on the processor, where the processor executes the computer program to implement the quota determining method according to any of the embodiments of the present invention.
In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the quota determining method according to any of the embodiments of the present invention.
According to the embodiment of the invention, 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.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
FIG. 1 is a flowchart of a method for determining an amount according to an embodiment of the present invention;
FIG. 2 is a flow chart of data value evaluation in database preprocessing according to an embodiment of the present invention;
FIG. 3 is a flowchart illustrating the establishment of a credit calculation model in the credit determination method according to an embodiment of the present invention;
FIG. 4 is a flowchart of generating user's quota in a method for determining quota provided by an embodiment of the present invention;
FIG. 5 is a flowchart illustrating a working process of the Hewlett packard financial credit measuring and calculating platform of the credit determining method according to an embodiment of the present invention;
FIG. 6 is a schematic structural diagram of a quota determining apparatus according to a second embodiment of the present invention;
fig. 7 is a schematic structural diagram of an electronic device according to a third embodiment of the present invention;
fig. 8 is a schematic structural diagram of a computer-readable storage medium containing a computer program according to a fourth embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures. In addition, the embodiments and features of the embodiments in the present invention may be combined with each other without conflict.
Before discussing exemplary embodiments in more detail, it should be noted that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although a flowchart may describe the operations (or steps) as a sequential process, many of the operations can be performed in parallel, concurrently or simultaneously. In addition, the order of the operations may be re-arranged. The process may be terminated when its operations are completed, but may have additional steps not included in the figure. The processes may correspond to methods, functions, procedures, subroutines, and the like. In addition, the embodiments and features of the embodiments in the present invention may be combined with each other without conflict.
The term "include" and variations thereof as used herein are intended to be open-ended, i.e., "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 reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures. Meanwhile, in the description of the present invention, the terms "first", "second", and the like are used only for distinguishing the description, and are not construed as indicating or implying relative importance.
When the following attribute information is stored and/or processed, it complies with relevant regulations of national laws and regulations.
Example one
Fig. 1 is a flowchart of an quota determining method provided in an embodiment of the present invention, where the embodiment is applicable to a quota determining situation, the method may be executed by a quota determining apparatus in an embodiment of the present invention, and the apparatus may be implemented in a software and/or hardware manner, as shown in fig. 1, the method specifically includes the following steps:
s101, when the quota application is received, acquiring a target small micro enterprise identifier carried by the quota application.
In this embodiment, the credit line application can be understood as an application of credit line initiated by the user on the platform to the tenant. The user refers to a small enterprise (the small enterprise is a general name of a small enterprise, a micro enterprise, a family workshop type enterprise and an individual industrial and commercial business), the tenant refers to a financial institution, and the platform refers to a general business data value evaluation platform, so as to support the tenant and the user to provide data access, data value evaluation and quota calculation services.
It should be noted that the target small-micro enterprise identifier may be understood as enterprise information of the small-micro enterprise carried by the quota application initiated by the user, and may be, for example, enterprise name, unified social credit code, legal identity information, and the like of the small-micro enterprise.
S102, screening at least one target set from the database according to the target small and micro enterprise identification.
In this embodiment, the database may be understood as a database formed by data information included in a plurality of existing small micro-enterprises. The small micro-enterprises in the database can be classified and stored according to the enterprise identifications, and the small micro-enterprises meeting the requirements can be screened from the database according to the small micro-enterprise identifications.
Specifically, the target set refers to a set formed by at least one small micro enterprise screened from the database and meeting the identification of the target small micro enterprise.
All data in the database are classified into three categories: business owners, small micro-enterprises, and external environments. Further, enterprise owners, small and micro enterprises and the external environment are divided into a plurality of sets, and the sets comprise education and training, basic information, registration, enterprise management, macro economy, maps and the like. Wherein each set corresponds to specific data and data association attributes. For example, a "property/vehicle property" set in the enterprise master category corresponds to data "real property estimate value and vehicle estimate value", and data-related attributes of the data "real property estimate value and vehicle estimate value" are "identity card, house registration number and vehicle license plate".
S103, determining a target limit corresponding to the target small micro-enterprise according to at least one target set.
The target limit refers to an application limit of the small micro-enterprise which meets the target small micro-enterprise identification in a target set corresponding to the target small micro-enterprise.
According to the technical scheme, small micro-enterprises in the database can be screened according to the limit application, and the target limit corresponding to the small micro-enterprises is determined.
Optionally, determining a target quota corresponding to the target small micro-enterprise according to at least one target set includes:
and acquiring attribute information corresponding to each target set.
Specifically, the attribute information refers to information in the data-associated attribute column. For example, the attribute information corresponding to the set "school subject and school calendar" is "identification card, name".
And determining a conversion rule corresponding to each target set according to the attribute information.
In the present embodiment, the conversion rule may be understood as a rule that converts a set into a specific calculation method. For example, the conversion rule corresponding to a property may be a property area (in square meters) x 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.
And determining the evaluation value corresponding to each target set according to each target set and the conversion rule corresponding to each target set.
It should be noted that, the evaluation of value refers to defining value data, risk data, area and industry data according to the service classification of the database, and directly evaluating the value of data according to the data of different classifications, and the value type includes positive or negative.
In an exemplary practical operation process, data classification, data value evaluation and data association analysis need to be completed on the basis of data analysis in data value conversion. The data classification corresponds to the data dependence analysis result of the database, the identification tag is defined by a data main key, and the evaluation rule and the value type are determined by a data analyst. The tenant marks are divided into platform-level shared data and data specific to each tenant, and the tenant customizes the value evaluation result of each data on the basis of the platform-level data to participate in the data of each tenant.
The data value conversion model is shown in table 1.
TABLE 1
Tables 2-7 are examples of 5 data value conversions.
The results of the data value conversion of the 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 the property data are shown in table 4.
TABLE 4
The results of data value conversion of the vehicle product data are shown in table 5.
TABLE 5
The results of data value conversion of the behavior data are shown in table 6.
TABLE 6
The data value conversion results of the basic information of the industry and commerce are shown in table 7.
TABLE 7
And determining a target limit corresponding to the target small micro-enterprise according to the evaluation value corresponding to each target set, the weight corresponding to each target set and the risk regulation coefficient.
In this embodiment, in order to meet the requirements of the next comprehensive quota measurement, each type of data must include personal and enterprise identification tags and weight information set according to a unified standard.
Specifically, the risk adjustment coefficient may be set manually, or may be a specific 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 micro enterprise identifier carried in the quota application, the method further includes:
first data corresponding to at least two small micro-enterprises are obtained.
It should be understood that the first data may be personal, business or environmental information corresponding to a small micro-business. For example, it may be educational information for the owner of the business, the business behavior of the business, or a macro-place of the environment.
And classifying the first data according to the enterprise owner node, the enterprise node and the external environment node to obtain at least three first sets.
It should be noted that the enterprise owner node reflects a plurality of milestone stages that the enterprise owner must go through in the process of growing with the small and micro enterprise, the enterprise node is defined according to the general process of production and operation of the small and micro enterprise, and the external environment node is defined according to the environment theme where the small and micro enterprise is located.
In this embodiment, the first set may be understood as a set obtained by classifying the first data corresponding to the small micro enterprise according to the enterprise owner node, the enterprise node, and the external environment node. The first data are classified according to three nodes, and each classified node at least corresponds to one set, so that at least three first sets exist.
In the actual operation process, production and operation activities of small and micro enterprises are influenced by three major business topics including individuals, enterprises and environments, and the individual topics cover basic identification, education, consumption, medical treatment, behaviors, property, risks and the like of enterprise owners; the enterprise theme comprises enterprise identification, management behavior, property, enterprise behavior, enterprise association, risk and the like; the environment theme provides macro-local and industrial economic analysis and the like, and the businesses form a complete closed loop for the operation of small micro-enterprises. The specific data corresponding to the small micro-enterprise can be shown in table 8.
TABLE 8
And analyzing the data in each first set to obtain enterprise identification information corresponding to the data in each first set.
It can be known that the enterprise identification information refers to information having an identification function, such as the name of an enterprise, a unified social credit code, and a legal identity card.
And storing the data in each first set in association with the enterprise identification information corresponding to the data.
Specifically, the association storage may be understood as establishing a relationship between the data in each first set and the enterprise identification information corresponding to the data and storing the relationship. A relationship is created between the two such that when data in the first set is searched, the data can be directly associated with the enterprise identification information corresponding to the data.
Optionally, analyzing the data in each first set to obtain the enterprise identification information corresponding to the data in each first set includes:
and if the first set is a non-value analysis set, analyzing the data in the first set to obtain enterprise identification information corresponding to the data in each first set.
The non-value analysis set refers to a set that does not require value analysis. For example, the non-value analysis set may be a set of basic information of the business owner (the basic information of the business owner may be, for example, the name, the identification number, and the family information of the business owner) and a set of registration of the small-sized business (the registration information of the small-sized business may be, for example, information of the registration year, the registration place, and the like).
And if the first sets are value analysis sets, analyzing the data in the first sets to obtain enterprise identification information corresponding to the data in each first set, and acquiring conversion rules corresponding to the first sets.
The value analysis set refers to a set for which value analysis is required. For example, the value analysis set may be a set of house property and car property of a business owner, a set of business value of a small micro business, and the like.
Optionally, if the first set is a value analysis set, analyzing the data in the first set to obtain enterprise identification information corresponding to the data in each first set, and obtaining a conversion rule corresponding to the first set, where the method includes:
and if the first set is a value analysis set, analyzing the data in the first set to obtain enterprise identification information corresponding to the data in each first set.
Attribute information of the first set is obtained.
And determining a conversion rule corresponding to the first set according to the attribute information of the first set.
Optionally, if the first set is a non-value analysis set, analyzing the data in the first set to obtain the enterprise identification information corresponding to the data in each first set includes:
and if the data in the first set is the basic information of the enterprise owner and/or the enterprise registration information, determining that the first set is a non-value analysis set, and analyzing the data in the first set to obtain enterprise identification information corresponding to the data in each first set.
The basic information of the enterprise owner refers to an identity card, a mobile phone number and family information of the enterprise owner. The enterprise registration information refers to the industrial and commercial registration information of the small micro-enterprise.
Fig. 2 is a flowchart of data value evaluation in database preprocessing provided in an embodiment of the present invention, where in step S101, before obtaining a target small-sized enterprise identifier carried in a quota application, data value evaluation preprocessing is performed on the database in S102, as shown in fig. 2, the method specifically includes the following operations:
acquiring first data corresponding to at least two small micro-enterprises from a database; classifying the first data according to enterprise main nodes, enterprise nodes and external environment nodes to obtain at least three first sets; it is determined whether each first set relates to a value analysis.
If the first set does not relate to value analysis, the first set is a non-value analysis set, data in the first set is analyzed, data primary keys (namely enterprise identification information corresponding to the data in the set) are analyzed, association rules with other data are analyzed, and modeling of other data is completed. For example, if the enterprise identification information obtained after analyzing the data primary key of the data a in the first set is company a, the data a and the company a are stored in a correlated manner; and analyzing the data primary key of the data B in the first set to obtain enterprise identification information of a company B, and storing the data B and the company B in a correlation manner.
If the first set relates to value analysis, the first set is a value analysis set, data in the first set is analyzed, data primary keys are analyzed, enterprise identification information corresponding to the data in the set is obtained, meanwhile, attribute information of the first set is obtained, conversion rules corresponding to the first set are determined according to the attribute information of the first set, the conversion rules are analyzed, and finally, a data value conversion result is generated. For example, if the enterprise identification information obtained by analyzing the data primary key of the data a in the first set is company a, the data a and the company a are stored in association, and meanwhile, the attribute information of the first set is acquired and can be a property assessment, a conversion rule corresponding to the property assessment is determined, and the conversion rule can be, for example, a property area (unit is square meter) × unit price per square meter, and finally, a conversion result corresponding to the first set after data value conversion is generated.
Optionally, determining a target amount corresponding to the target small micro-enterprise according to the evaluation value corresponding to each target set, the weight corresponding to each target set, and the risk adjustment coefficient, includes:
and calculating the target amount based on the following formula:
wherein,
1>j>0，Vnfor the corresponding evaluation value of the target set, WnAnd K is the weight corresponding to the target set, K is the number of the target set, and j is a risk adjustment coefficient.
It should be noted that n is a set currently being calculated, weights corresponding to the target set are set according to a unified standard, and 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.
In the actual operation process, the platform provides a measuring and calculating model configuration function for tenants, selects a value data set on line, sets the weight of the value data, and evaluates the value V corresponding to a target set by an identification tag and data association methodnCan be accurately located to individuals and business individuals.
FIG. 3 is a flowchart illustrating the process of establishing the quota calculating model in the quota determining method according to an embodiment of the present invention, which is applicable to the calculation of the target quota in the quota determining method according to the embodiment of the present invention, the method can be executed by the quota determining apparatus according to an embodiment of the present invention, the apparatus can be implemented by software and/or hardware, as shown in FIG. 3, the establishing of the quota calculating model specifically includes the following operations:
first, a value data set (i.e., the evaluation value V corresponding to the target set) is selectedn). Next, value weights (i.e., weights W corresponding to the target set) are configuredn) The system comprises a data set association rule (namely enterprise identification information which is correspondingly and associatively stored in the target set) and a risk adjustment coefficient (namely the risk adjustment coefficient j). Finally, the model is verified.
Optionally, when receiving the quota application, acquiring the target small micro enterprise identifier carried by the quota application includes:
and acquiring identity information input by a user.
For example, the identity information may be personal information such as a name and an identification number of the user, which can prove the identity of the user.
And performing identity verification according to the identity information.
The identity verification refers to verifying and checking identity information input by a user, and verifying whether the identity information input by the user is correct, for example, whether the name and the identification number of the user are matched.
And if the identity verification passes, acquiring the target small and micro enterprise identification carried by the limit application when the limit application is received.
In the actual operation process, before the platform applies for the quota, the user signs a data use authorization protocol, after the identity of the user is verified, the platform calculates a quota measuring and calculating model configured by each tenant, and pushes the business opportunity to the tenant.
Fig. 4 is a flowchart of generating a user's quota in a method for determining a quota according to an embodiment of the present invention, which is applicable to a situation where a user's quota is generated in the method for determining a quota according to the embodiment of the present invention, where the method may be executed by a quota determining apparatus according to an embodiment of the present invention, and the apparatus may be implemented in a software and/or hardware manner, as shown in fig. 4, the generating of the user's quota specifically includes the following operations:
the method comprises the steps of obtaining identity information input by a user, carrying out identity verification according to the identity information, if the identity verification is passed, operating a limit measuring and calculating model configured by a tenant by a platform, selecting the tenant of the financial enterprise meeting conditions, generating and displaying the limit of the tenant, and pushing business opportunities to the user.
Optionally, after determining a target quota corresponding to the target small enterprise according to at least one target set, the method further includes:
and displaying the target amount.
After receiving the request for applying for quota, the quota is issued according to the target quota.
The credit line applying request can be applied by the user on the platform, and the credit line applying can be performed by the platform on the user.
As an exemplary description of the embodiment, fig. 5 is a working flow diagram of a hewlett packard financial credit measurement and calculation platform of a credit determination method according to an embodiment of the present invention, where the hewlett packard service data value evaluation platform selects a data source with market public credibility, and deploys the credit measurement and calculation service under a multi-party agreement framework of a user, a platform, a financial enterprise, and a data provider. As shown in fig. 5, the working process of the hewlett packard financial quota measuring and calculating platform specifically includes:
a signing stage: the user registers and initiates authorization, the financial enterprise and the data supplier sign a contract with the platform, and the quota measuring and calculating platform generates an authorization book.
Parameter and data preparation stage: the user fills in questionnaire (because the data type used by the quota calculation model in the embodiment of the invention is many, the quota calculation needs to be authorized by the user before the quota calculation according to the personal information protection requirement in the civil court, and the user authorization information can be adjusted and updated), the data supplier prepares data, transmits the data to the financial enterprise through the data interface of the platform, and the financial enterprise analyzes the value data according to the data and creates the quota calculation model.
And (3) line calculation stage: after the user fills in the questionnaire, the user initiates an amount application, the financial enterprise calculates the amount according to the amount application initiated by the user, the enterprise verifies the amount after the amount calculation (off-line), and the amount is manually adjusted according to the operation standard in the enterprise.
An amount confirmation stage: after the financial enterprise calculates, verifies and adjusts the limit, the limit information is fed back to the user, and the user checks the limit.
The quota issuing stage: the user applies for the quota issuing after confirming the quota, the financial enterprise issues the quota, and the quota measuring and calculating platform collects the feedback of the condition after credit.
The technical scheme of the embodiment of the invention is based on big data technology, fuses various data of users and enterprises, fuses the business closed-loop analysis method and the data credit conversion model for the first time, provides credit measurement service with market public credibility for small and micro enterprises, and creates a new mechanism for financing of the small and micro enterprises.
Example two
FIG. 6 is a schematic structural diagram of an amount determination device according to a second embodiment of the present invention. The embodiment may be applicable to the case of determining the credit, the device may be implemented in a software and/or hardware manner, and the device may be integrated in any device that provides a credit determining function, as shown in fig. 6, where the credit determining device specifically includes: an acquisition module 210, a screening module 220, and a determination module 230.
Further, the determining module 230 may further include:
the first acquisition unit is used for acquiring attribute information corresponding to each target set;
the first determining unit is used for determining a conversion rule corresponding to each target set according to the attribute information;
the second determining unit is used for determining the evaluation value corresponding to each target set according to each target set and the conversion rule corresponding to each target set;
and the third determining unit is used for determining the target amount corresponding to the target small micro-enterprise according to the evaluation value corresponding to each target set, the weight corresponding to each target set and the risk regulation coefficient.
Further, before the obtaining module 210 obtains the target small micro enterprise identifier carried in the quota application, the method further includes:
the first data acquisition module is used for acquiring first data corresponding to at least two small micro-enterprises;
the classification module is used for classifying the first data according to the enterprise owner node, the enterprise node and the external environment node to obtain at least three first sets;
the analysis module is used for analyzing the data in each first set to obtain enterprise identification information corresponding to the data in each first set;
and the storage module is used for storing the data in each first set and the enterprise identification information corresponding to the data in an associated manner.
Further, the analysis module may further include:
the first analysis unit is used for analyzing 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 non-value analysis set;
and the second analysis unit is used for analyzing the data in the first sets to obtain enterprise identification information corresponding to the data in each first set and obtain the conversion rules corresponding to the first sets if the first sets are value analysis sets.
Further, the second analysis unit may further include:
the analysis subunit is configured to, 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;
an obtaining subunit, configured to obtain attribute information of the first set;
and the determining subunit is used for determining the conversion rule corresponding to the first set according to the attribute information of the first set.
Further, the first analysis unit is specifically configured to:
and if the data in the first set is the basic information of the enterprise owner and/or the enterprise registration information, determining that the first set is a non-value analysis set, and analyzing the data in the first set to obtain enterprise identification information corresponding to the data in each first set.
Further, the third determining unit is specifically configured to:
calculating a target quota based on the following formula:
wherein,
1>j>0，Vnfor the corresponding evaluation value of the target set, WnAnd K is the weight corresponding to the target set, K is the number of the target sets, and j is a risk adjustment coefficient.
Further, the obtaining module 210 may further include:
the second acquisition unit is used for acquiring the identity information input by the user;
the verification unit is used for verifying the identity according to the identity information;
and the third acquisition unit is used for acquiring the target small and micro enterprise identification carried by the quota application when the quota application is received if the identity verification passes.
Further, after the determining module 230 determines the target quota corresponding to the target small enterprise according to the at least one target set, the method further includes:
the display module is used for displaying the target amount;
and the issuing module is used for issuing the quota according to the target quota after receiving the quota applying request.
The product can execute the method provided by any embodiment of the invention, and has corresponding functional modules and beneficial effects of the execution method.
According to 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.
EXAMPLE III
Fig. 7 is a schematic structural diagram of an electronic device according to a third embodiment of the present invention. FIG. 7 illustrates 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 bring any limitation to the functions and the scope of use of the embodiment of the present invention. Device 312 is a computing device for typical credit determination functions.
As shown in fig. 7, electronic device 312 is in the form of a general purpose computing device. The components of the electronic device 312 may include, but are not limited to: one or more processors 316, a storage device 328, and a bus 318 that couples the various system components including the storage device 328 and the processors 316.
The processor 316 executes various functional applications and data processing by running programs stored in the storage 328, for example, implementing the credit determination method provided by the above-described embodiment of the present invention.
Example four
Fig. 8 is a schematic structural diagram of a computer-readable storage medium containing a computer program in a fourth embodiment of the present invention. The embodiment of the invention provides a computer-readable storage medium 61, on which a computer program 610 is stored, where the computer-readable storage medium 61 is connected with one or more processors 316, and when the program is executed by the one or more processors, the program implements the quota determining method provided by all embodiments of the invention of this application:
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.
Any combination of one or more computer-readable media may be employed. The computer readable medium may be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
In some embodiments, the clients, servers may communicate using any currently known or future developed network Protocol, such as HTTP (Hyper Text Transfer Protocol), and may interconnect with any form or medium of digital data communication (e.g., a communications network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), the Internet (e.g., the Internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future developed network.
The computer readable medium may be embodied in the electronic device; or may exist separately without being assembled into the electronic device.
Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + +, or the like, as well as conventional procedural programming languages, such as the "C" programming language or similar programming languages. 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. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
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, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units described in the embodiments of the present disclosure may be implemented by software or hardware. Where the name of an element does not in some cases constitute a limitation on the element itself.
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 a chip (SOCs), Complex Programmable Logic Devices (CPLDs), and the like.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
It is to be noted that the foregoing description is only exemplary of the invention and that the principles of the technology may be employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
Claims (15)
1. An amount determining method, comprising:
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.
2. The method of claim 1, wherein determining the target quota corresponding to the target micro-enterprise based on the at least one target set comprises:
acquiring attribute information corresponding to each target set;
determining a conversion rule corresponding to each target set according to the attribute information;
determining the evaluation value corresponding to each target set according to each target set and the conversion rule corresponding to each target set;
and determining a target limit corresponding to the target small micro-enterprise according to the evaluation value corresponding to each target set, the weight corresponding to each target set and the risk regulation coefficient.
3. The method of claim 1, further comprising, before obtaining the target micro-enterprise identity carried in the quota application:
acquiring first data corresponding to at least two small micro-enterprises;
classifying the first data according to enterprise main nodes, enterprise nodes and external environment nodes 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;
and storing the data in each first set in association with the enterprise identification information corresponding to the data.
4. The method of claim 3, wherein analyzing the data in each first set to obtain the enterprise identification information corresponding to the data in each first set comprises:
if the first set is a non-value analysis set, analyzing the data in the first set to obtain enterprise identification information corresponding to the data in each first set;
and if the first set is a value analysis set, analyzing the data in the first set to obtain enterprise identification information corresponding to the data in each first set, and acquiring a conversion rule corresponding to the first set.
5. The method of claim 4, wherein if the first set is a value analysis set, analyzing the data in the first set to obtain enterprise identification information corresponding to the data in each first set, and obtaining the conversion rule corresponding to the first set includes:
if the first set is a value analysis set, analyzing the data in the first set to obtain enterprise identification information corresponding to the data in each first set;
acquiring attribute information of the first set;
and determining a conversion rule corresponding to the first set according to the attribute information of the first set.
6. The method of claim 4, wherein if the first set is a non-value analysis set, analyzing the data in the first set to obtain the enterprise identification information corresponding to the data in each first set comprises:
and if the data in the first set is the basic information of the enterprise owner and/or the enterprise registration information, determining that the first set is a non-value analysis set, and analyzing the data in the first set to obtain enterprise identification information corresponding to the data in each first set.
7. The method of claim 2, wherein determining the target amount corresponding to the target small enterprise according to the evaluation value corresponding to each target set, the weight corresponding to each target set and the risk adjustment coefficient comprises:
calculating a target quota based on the following formula:
wherein,
Vnfor the corresponding evaluation value of the target set, WnThe weight corresponding to the target set, K the number of the target set, and j the riskAnd (4) section coefficient.
8. The method of claim 1, wherein when receiving the credit application, acquiring the target micro-enterprise identifier carried by the credit application comprises:
acquiring identity information input by a user;
performing identity verification according to the identity information;
and if the identity verification passes, acquiring the target small enterprise identification carried by the limit application when the limit application is received.
9. The method of claim 1, further comprising, after determining a target quota corresponding to the target micro-enterprise based on the at least one target set:
displaying the target amount;
and after receiving the request for applying for the quota, performing quota issuing according to the target quota.
10. An amount determining apparatus, comprising:
the acquisition module is used for acquiring a target small micro enterprise identifier carried by the limit application when the limit application is received;
the screening module is used for screening at least one target set from a database according to the target small and micro enterprise identification;
and the determining module is used for determining a target limit corresponding to the target small micro-enterprise according to the at least one target set.
11. The apparatus of claim 10, wherein the determining module further comprises:
the first acquisition unit is used for acquiring attribute information corresponding to each target set;
the first determining unit is used for determining a conversion rule corresponding to each target set according to the attribute information;
the second determining unit is used for determining the evaluation value corresponding to each target set according to each target set and the conversion rule corresponding to each target set;
and the third determining unit is used for determining the target amount corresponding to the target small micro-enterprise according to the evaluation value corresponding to each target set, the weight corresponding to each target set and the risk regulation coefficient.
12. The apparatus of claim 10, wherein the obtaining module further comprises:
the second acquisition unit is used for acquiring the identity information input by the user;
the verification unit is used for verifying the identity according to the identity information;
and the third acquisition unit is used for acquiring the target small and micro enterprise identification carried by the quota application when the quota application is received if the identity verification passes.
13. The apparatus according to claim 11, wherein the third determining unit is specifically configured to:
calculating a target quota based on the following formula:
wherein,
Vnfor the corresponding evaluation value of the target set, WnAnd K is the weight corresponding to the target set, K is the number of the target set, and j is a risk adjustment coefficient.
14. An electronic device, comprising:
one or more processors;
a 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 containing a computer program, on which the computer program is stored, characterized in that the program, when executed by one or more processors, implements the method of any one of claims 1-9.
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| CN116402571A (en) * | 2023-03-14 | 2023-07-07 | 上海峰沄网络科技有限公司 | Budget data processing method, device, equipment and storage medium |
| CN116402571B (en) * | 2023-03-14 | 2024-04-26 | 上海峰沄网络科技有限公司 | Budget data processing method, device, equipment and storage medium |
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