CN114638614A - Enterprise credit line determination method and device based on multi-dimensional government affair data - Google Patents
Enterprise credit line determination method and device based on multi-dimensional government affair data Download PDFInfo
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Abstract
The disclosure relates to a method and a device for determining enterprise credit line based on multidimensional government affair data, and relates to the technical field of big data analysis. The method comprises the following steps: screening enterprises according to at least one dimension of government affair data and corresponding admission conditions, and determining whether the enterprises meet the admission conditions, wherein the government affair data at least comprises the following components: tax amount data, social security payment data, tax declaration sales data, industry and commerce annual declaration sales data, enterprise owner house property data and accumulation payment data of the enterprise; responding to the fact that the enterprise meets the admission condition, and determining a target enterprise and government affair limit data corresponding to the target enterprise; and determining the credit line data of the target enterprise according to the government affair line data and the outstanding loan line data of the target enterprise. By adopting the method, the problem of asymmetric information can be solved, the credit line of the small and micro enterprise can be accurately evaluated, and the credit risk can be reduced.
Description
Technical Field
The disclosure relates to the technical field of big data analysis, in particular to a method and a device for determining an enterprise credit line based on multidimensional government affair data.
Background
With the development of socio-economic, developing hewlett packard finance is an inevitable choice for financial institutions. The development focus of Hewlett-packard finance is usually the problem of financing of small micro-enterprises. And the information asymmetry is one of the main reasons for restricting the financing of the small micro-enterprise. The information asymmetry is generally caused by the large whole quantity of small micro-enterprises, small individual scale, insufficient self-management capacity, relatively poor credit conditions and the like, and the lack of the specified and insufficient financial information or even the loss of the financial information.
The existing small and micro enterprise loan pre-credit-granting model mainly calculates the credit-granting amount of the enterprise loan according to the financial assets, security, credit conditions and other data of enterprises and business owners, the reference data mainly refers to the financial conditions of the enterprises, such as receivable data, tax data, agency wage data and the like, the reference data is suitable for large enterprises which operate stably for a long time, and for small and micro enterprises, the problem of information asymmetry usually exists, so that the existing small and micro enterprise loan pre-credit-granting model cannot accurately evaluate the credit-granting amount of the small and micro enterprises.
Disclosure of Invention
Therefore, in order to solve the above technical problem, it is necessary to provide a method and an apparatus for determining the credit line of an enterprise based on multidimensional government affair data, which can solve the problem of asymmetric information and accurately evaluate the credit line of a small-sized enterprise.
In a first aspect, the disclosure provides a method for determining an enterprise credit line based on multidimensional government affair data. The method comprises the following steps:
screening enterprises according to government affair data of at least one dimension and corresponding admission conditions, and determining whether the enterprises meet the admission conditions;
responding to the fact that the enterprise meets the admission condition, and determining a target enterprise and government affair limit data corresponding to the target enterprise;
determining credit line data of the target enterprise according to the government affair line data and the outstanding loan line data of the target enterprise
In one embodiment, the screening an enterprise according to at least one dimension of government affair data and corresponding admission conditions to determine whether the enterprise meets the admission conditions includes:
acquiring government affair data of at least one dimension of the enterprise;
determining that the enterprise meets the admission condition under the condition that the government affair data of the enterprise meet the admission condition;
otherwise, determining that the enterprise does not meet the admission condition.
In one embodiment, the government data includes at least: tax payment data, social insurance payment data, tax declaration sales data, industry and commerce annual sales data, enterprise owner house property data and accumulation payment data of enterprises.
In one embodiment, the method further comprises: and in response to the business failing to meet the admission conditions, denying the loan application of the business.
In one embodiment, the determining, in response to the enterprise satisfying the admission condition, a target enterprise and government credit data corresponding to the target enterprise includes:
determining the target enterprise according to the enterprises meeting the admission conditions;
and determining the government affair amount data corresponding to the target enterprise according to the government affair data of the target enterprise.
In one embodiment, the determining credit line data of the target enterprise according to the government affair line data and the outstanding loan line data of the target enterprise includes:
determining the most valuable government affair line data in the government affair line data;
and subtracting the outstanding loan amount data of the target enterprise from the government amount data with the maximum value to obtain the credit line data of the target enterprise.
In a second aspect, the disclosure also provides a device for determining the credit line of the enterprise based on the multidimensional government affair data. The device comprises:
and the condition determining module is used for screening the enterprises according to the government affair data of at least one dimension and the corresponding admission conditions and determining whether the enterprises meet the admission conditions.
And the target determining module is used for determining the target enterprise and the government affair amount data corresponding to the target enterprise in response to the fact that the enterprise meets the admission condition.
And the line determining module is used for determining the credit line data of the target enterprise according to the government affair line data and the outstanding loan line data of the target enterprise.
In one embodiment of the apparatus, the condition determining module includes: the system comprises a government affair data acquisition module, a satisfaction condition determining module and an unsatisfied condition determining module;
the government affair data acquisition module is used for acquiring government affair data of at least one dimension of the enterprise;
the satisfaction condition determining module is used for determining that the enterprise meets the admission condition under the condition that the government affair data of the enterprise meet the admission condition;
the unsatisfied condition determining module is used for determining that the enterprise does not satisfy any admission condition under the condition that the government affair data of the enterprise does not satisfy any admission condition.
In one embodiment of the device, the government data includes at least: tax amount data, social insurance payment data, tax declaration sales data, industry and commerce annual declaration sales data, enterprise owner house property data and accumulation payment data of the enterprise.
In one embodiment of the apparatus, the apparatus further comprises: and the application refusing module is used for refusing the loan application of the enterprise in response to the fact that the enterprise does not meet the admission condition.
In one embodiment of the apparatus, the goal determining module includes: the system comprises a target enterprise determining module and a limit data determining module;
the target enterprise determining module is used for determining the target enterprise according to the enterprises meeting the admission conditions;
and the quota data determining module is used for determining government quota data corresponding to the target enterprise according to the government data of the target enterprise.
In one embodiment of the apparatus, the quota determining module includes: the system comprises a government affair amount data determining module and a credit line data determining module;
the government affair line data determining module is used for determining the government affair line data with the largest value in the government affair line data;
and the credit line data determining module is used for subtracting the unfinished credit line data of the target enterprise from the government line data with the maximum value to obtain the credit line data of the target enterprise.
In a third aspect, the present disclosure also provides a computer device. The computer device comprises a memory having a computer program stored therein and a processor implementing the steps of the method when executing the computer program.
In a fourth aspect, the present disclosure also provides a computer-readable storage medium. The computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the above-mentioned method.
In a fifth aspect, the present disclosure also provides a computer program product. The computer program product comprises a computer program which, when being executed by a processor, carries out the steps of the above-mentioned method.
In the above embodiments, the enterprises are screened by adopting government affairs and admission conditions of multiple dimensions. The small micro-enterprise can be identified more accurately and judged whether to have loan qualification. And under the condition of loan qualification, determining the credit line data of the target enterprise according to the government affair line data and the outstanding loan line data of the target enterprise. Can carry out accurate discernment, layering and location to each target enterprise through the government affairs data of difference, and then develop differentiated marketing and examination and approval, and the accurate management and the early warning of risk behind the loan, and government affairs data are the data of multiple type through government integration usually, it has the publicization, the characteristics of transparence, so can not have the asymmetric problem of information, and then this scheme uses the government affairs data as the government affairs amount data of the little enterprise of the accurate determination of reference data ability, and then the definite amount of credit of carrying out the business of awarding to little enterprise. And because the small and micro enterprises may have outstanding loan lines before the loan, the credit line data of the target enterprise is finally determined according to the government affair line data and the outstanding loan line data of the target enterprise, the outstanding loan line data can be deleted, the final credit line is reduced, and the loan risk is further reduced.
Drawings
In order to more clearly illustrate the embodiments of the present disclosure or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present disclosure, and other drawings can be obtained by those skilled in the art without creative efforts.
FIG. 1 is a schematic diagram of an application environment of a method for determining an enterprise credit line based on multidimensional government data in one embodiment;
FIG. 2 is a flowchart illustrating a method for determining an enterprise credit line based on multidimensional government data in one embodiment;
FIG. 3 is a schematic block diagram of a loan approval method for a small micro enterprise in accordance with one embodiment;
FIG. 4 is a flowchart illustrating the step of S20 according to an embodiment;
FIG. 5 is a flowchart illustrating the step of S30 according to an embodiment;
FIG. 6 is a flowchart illustrating the step S40 according to an embodiment;
FIG. 7 is a block diagram schematically illustrating the structure of an apparatus for determining an amount of credit based on multidimensional government data according to an embodiment;
FIG. 8 is a diagram showing an internal configuration of a computer device according to an embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present disclosure more clearly understood, the present disclosure is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the disclosure and are not intended to limit the disclosure.
It should be noted that the terms "first," "second," and the like in the description and claims herein and in the above-described drawings are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments herein described are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, apparatus, article, or device that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or device.
It should be noted that, in the description of the present disclosure, the small micro-corporation loan generally refers to a loan issued by a credit agency or a financial institution on the small micro-corporation as a target.
Credit generally refers to a way to aggregate various data for loan line calculations.
As described in the background, with the overall rise and rapid development of Chinese economy, a huge development opportunity is created for financial institutions. The financial market innovation is deepened, the interest rate market is changed, the finance is off the medium, the internet finance is started, and the like, so that the market and the profit space of each finance are greatly compressed, and the development of the popular finance becomes the inevitable choice of commercial banks. The intelligent fast loan service of the small and micro enterprises refers to recyclable RMB loan service which is issued by the small and micro enterprises or individual industrial and commercial businesses through online self-service handling (pure credit) and is analyzed and evaluated by using a big data technology based on enterprise and personal information integrated by governments. For the special product, if a traditional single evaluation system of 'fund flow' is used, small and micro enterprises participating in the platform fast loan are difficult to evaluate in an all-around manner, which is very unfavorable for the enterprises to obtain precious financial resources. Therefore, it is very necessary to develop a characteristic and comprehensive assessment system for small and micro enterprises. At present, common loan credit granting sources of small and micro enterprises mainly comprise enterprise sales, accounts receivable of the enterprises, tax data, work and fund conditions and the like, but multidimensional government data of the enterprises are not synthesized as calculation indexes of loan credit granting of the enterprises.
It should be noted that the loan in this embodiment is generally referred to as intelligent fast loan.
Therefore, to solve the above problems and the problems in the background art, the embodiments of the present disclosure provide a method for determining an enterprise credit line based on multidimensional government affair data, which can be applied to the application environment shown in fig. 1. Wherein the terminal 102 communicates with the server 104 via a network. The data storage system may store data that the server 104 needs to process. The data storage system may be integrated on the server 104, or may be located on the cloud or other network server. The terminal 102 obtains at least one dimension of government affair data and corresponding admission conditions stored in the server 104 or data storage system. The terminal 102 screens the enterprise according to the admission condition to determine whether the enterprise meets the admission condition. In response to the enterprise satisfying the admission condition, the terminal 102 may determine the target enterprise and the corresponding government credit data according to the enterprise satisfying the admission condition. The terminal 102 obtains the outstanding loan amount data corresponding to the target enterprise in the server 104 or the data storage system. The terminal 102 determines credit line data of the target enterprise according to the government affair line data and the outstanding loan line data of the target enterprise. The terminal 102 may be, but is not limited to, various personal computers, notebook computers, smart phones, and tablet computers. The server 104 may be implemented as a stand-alone server or as a server cluster comprised of multiple servers. It should be noted that the method may also be implemented by the terminal 102 or the server 104 alone.
In one embodiment, as shown in fig. 2, a method for determining an enterprise credit line based on multidimensional government affair data is provided, which is described by taking the method as an example applied to the terminal 102 in fig. 1, and includes the following steps:
s20, screening the enterprises according to the government affair data of at least one dimension and the corresponding admission conditions, and determining whether the enterprises meet the admission conditions.
The government affair data can be various types of data integrated by governments, and can be data from multiple departments such as a reform committee, a state and earth bureau, a financial institution, a tax bureau, a social security bureau, a mobile phone operator and the like. The admission condition is generally a condition for screening the enterprise through government affair data, whether the government affair data of the enterprise meets the condition is judged, and if the government affair data of the enterprise meets the condition, the enterprise can be proved to be loaned.
Specifically, one-dimensional or multi-dimensional government affair data (generally, multi-dimensional government affair data) stored in a system of a reform commission, a state and earth agency, a financial institution, a tax authority, a social security agency, or the like is acquired. And screening the enterprises needing to be loaned according to the government affair data and the corresponding admission conditions, and determining whether the enterprises needing to be loaned meet the admission conditions. The enterprise may typically be a small micro-enterprise. It should be noted that, a person skilled in the art may generally set the admission condition according to actual needs, and the specific admission condition is not limited in this embodiment.
S30, responding to the fact that the enterprise meets the admission condition, and determining a target enterprise and government affair amount data corresponding to the target enterprise.
The government affair amount data can be data with a certain amount of money determined according to the government affair data. The target business may be generally considered a small micro-business that qualifies for a loan.
Specifically, in the case that the government affair data of the enterprise meets the admission condition, the target enterprise is determined, and the government affair amount data is determined through the government affair data of the target enterprise.
And S40, determining the credit line data of the target enterprise according to the government affair line data and the outstanding loan line data of the target enterprise.
The outstanding loan amount data may be a small and quick loan amount of a small and outstanding amount of a loan that the company has not settled in the bank.
Specifically, the credit line data of the target enterprise is obtained by integrating the government affair line data and calculating according to the integrated government affair line data and the outstanding loan line data of the target enterprise.
S50, responding to the business not meeting the admission condition, and refusing the loan application of the business.
Specifically, when the enterprise does not meet the admission condition, the enterprise can be proved not to have the loan application qualification, the loan application of the enterprise can be refused, and the government line data does not need to be calculated correspondingly.
In some exemplary embodiments, as shown in fig. 3, when a business applies for a small micro business loan, it may first be determined whether the business is a small micro business that satisfies the intelligent fast loan admission condition according to at least one dimension of government affair data and corresponding admission conditions. Wherein, the small and micro enterprises and the enterprise owners have the joint guarantee responsibility.
If not, the loan application of the enterprise is rejected. If so, determining government affair line data according to the government affair data of the small and micro enterprises through the real-time approval component, and carrying out line pre-credit for the enterprises according to the family net property condition of the enterprise owner and the outstanding credit line data of the small and micro enterprises to obtain credit line data of the enterprises. Then checking internal control lists and credit investigation information (including personal credit investigation and enterprise credit investigation) of small and micro enterprises and enterprise owners. And if the internal control list passes, checking credit investigation information. If the internal control list check is not passed, the loan is refused, and if the credit investigation information check is not passed, the loan is refused. If the credit investigation information passes the check, the loan application is approved on the basis of an approval rule base (including advanced approval, wisdom fast loan approval and other approval), and if the credit investigation information does not pass the check, the loan is rejected. If the loan application is accepted, whether the loan application is accepted or not is determined according to the grading result of the final grading card, if the loan application is accepted according to the grading card, the loan is released, and if the loan application is not accepted according to the grading card, the loan is refused, so that monitoring and early warning are performed.
In the method for determining the credit line of the enterprise based on the multi-dimensional government affair data, the enterprise is screened by adopting the government affairs with multiple dimensions and the admission conditions. The small micro-enterprise can be identified more accurately and judged whether to have loan qualification. And under the condition of loan qualification, determining the credit line data of the target enterprise according to the government affair line data and the outstanding loan line data of the target enterprise. Can carry out accurate discernment, layering and location to each target enterprise through the government affairs data of difference, and then develop differentiated marketing and examination and approval to and the accurate management and the early warning of risk after lending, and government affairs data is the data of multiple type through government integration usually, and it has the characteristics of publicization, transparence, so can not have the asymmetric problem of information, and then this scheme uses the credit line of the little enterprise of evaluation that government affairs data can be accurate as reference data, reduces the loan risk.
In one embodiment, as shown in fig. 4, the screening an enterprise according to at least one dimension of government data and corresponding admission conditions to determine whether the enterprise meets the admission conditions includes:
s22, acquiring government affair data of at least one dimension of the enterprise.
Specifically, the government data may include at least: tax amount data, social insurance payment data, tax declaration sales data, industry and commerce annual declaration sales data, enterprise owner house property data and accumulation payment data of the enterprise. And acquiring the government affair data of the at least one dimension.
The business owner may be the owner of the enterprise, the investor of the exclusive enterprise and the partner enterprise. Under the condition that ownership and operation rights of the enterprises are not separated, enterprise owners can decide operators of the enterprises by themselves.
And S24, judging whether the government affair data of the enterprise meet the admission condition.
And S26, determining that the enterprise meets the admission condition under the condition that the government affair data of the enterprise meet the admission condition.
Specifically, each government affair data corresponds to one admission condition. The obtained government affair data of the enterprise needs to meet each admission condition, and the enterprise can be determined to meet the admission condition.
In some exemplary embodiments, if the government data is tax amount data of the enterprise, the corresponding admission condition may be:
(1) the enterprise is established and actually operates for more than 2 years (including) except for M-level customers, and the individual industrial and commercial enterprises are established for more than 1 year (including); wherein, the M-level customers can be customers with no income and score of more than 70 points in the new enterprise year. It should be noted that, those skilled in the art can set the class M client or other clients not to apply the admission condition according to practical situations, and this is only used for illustration in this embodiment.
(2) The latest tax payment credit rating result of the enterprise is A, B, M (except for clients of individual industrial and commercial enterprises), wherein A, B, M may generally refer to the enterprise tax payment credit rating, and is generally the rating of the tax authority or tax bureau on the tax payment credit of the taxpayer in a certain period according to the tax payment obligation situation of the taxpayer. The grade a is usually 90 points or more of the annual evaluation index score. The grade B is generally above 70 and below 90 points. Grade C is generally less than 70 points above the score of 40. Grade D is typically determined by scoring less than 40 points or by direct rating.
(3) The enterprise is honest to pay tax (except for M-level customers) in the last 24 months, and the total tax payment amount is more than 5000 Yuan (inclusive) in the last 12 months, wherein the total tax payment amount refers to the sum (inclusive of tax deduction, tax exemption and tax payment amount) of tax items such as added value tax paid by the enterprise in national tax, local tax departments, income tax of the enterprise and the like.
(4) The enterprise has tax payment records with tax payment amount more than 0 at least once in the last half year.
If the government affair data is social security payment data of the enterprise, the corresponding admission conditions may be:
(1) the social security payment records of enterprises or employees are recorded within 12 months before the enterprises apply for the loan for at least 10 months.
(2) Within 3 months before the enterprises apply for loans, social security payment records of enterprises or enterprise employees are recorded.
If the government affair data is tax declaration sales data of the enterprise, the corresponding admission conditions may be:
(1) enterprises can be established for more than 2 years (including), and individual industrial and commercial enterprises can be established for more than 1 year (including).
(2) The tax declaration (value added tax) sales income is not 0 for at least 4 months before the enterprise applies for the loan, or the income amount of the tax due to the last year (income tax) is more than 0.
(3) The tax declaration (value added tax) sales income of at least 1 month before the enterprise applies for the loan is not 0, or the sum of the income amount due to tax payment is more than 0 3 months before the application for the loan.
If the government affair data is the annual sales data of the enterprises and the house property data of the enterprises, the corresponding admission conditions can be as follows:
(1) the enterprise has records of annual business annual sales of nearly two years.
(2) The annual industrial and commercial annual profit of the enterprise is not negative.
(3) The business or business owner has a residence and is in an uncompromised state.
If the government affair data are accumulated data of the public accumulation fund, the corresponding admission conditions can be as follows:
(1) enterprises pay the accumulation fund for more than 2 years (inclusive).
(2) At least 6 months before the enterprise applies for the loan, the fee payment records of the public accumulation fund are all recorded.
It should be noted that the tax payment data, social security payment data, tax declaration sales data, annual business declaration sales data, enterprise owner property data, public deposit payment data, and corresponding admission conditions of the enterprise are merely examples, and in the actual application process, a person skilled in the art may add, modify, or delete the admission conditions, and the specific admission conditions are not limited in this embodiment.
S28, otherwise, determining that the enterprise does not meet the admission condition.
Specifically, if the government affair data of the enterprise does not satisfy the admission condition corresponding to any government affair data, the enterprise is determined not to satisfy the admission condition, and the enterprise is proved not to have loan qualification.
In this embodiment, the enterprises are screened through government affair data and admission conditions of various dimensions, and the small and micro enterprises with loan qualification can be accurately identified, so that the loan risk can be reduced.
In one embodiment, as shown in fig. 5, the determining, in response to the enterprise satisfying the admission condition, government quota data corresponding to a target enterprise and the target enterprise includes:
s32, determining the target enterprise according to the enterprises meeting the admission conditions;
and S34, determining the government affair amount data corresponding to the target enterprise according to the government affair data of the target enterprise.
Specifically, when an enterprise meets the admission condition, the enterprise meeting the condition may be a target enterprise. And further, government affair data of at least one dimension of the target enterprise can be obtained. And determining the government affair line data corresponding to each dimension according to the government affair data of each dimension.
In some exemplary embodiments, the government credit data corresponding to the tax payment data of the enterprise can be determined according to the average tax payment and the last tax payment credit rating result of the enterprise in the last 24 months. For example, different tax payment coefficients or weighting coefficients can be set according to different levels for the latest tax payment credit rating evaluation result, and the government affair amount data corresponding to the tax payment amount data can be calculated according to the average tax payment amount of the enterprise in the last 24 months and the tax payment coefficients or weighting coefficients.
The government affair amount data corresponding to the social security payment data of the enterprise can be determined according to the social security payment condition of the enterprise in about 24 months. For example, social security payment base number and payment number data of the enterprise in the last 24 months are obtained and determined according to the payment base number, the payment number and the payment number. The payment base number can be multiplied by the number of the payers and then multiplied by the corresponding preset coefficient to obtain the payment. Or the payment value can be directly multiplied by a preset coefficient to determine.
The government affair amount data corresponding to the tax declaration sales data of the enterprise can be determined according to the tax declaration sales of the previous year. For example, it may be determined by multiplying the sales of the last year by a preset coefficient. And the sales amount can be directly determined by declaring sales in the tax payment of the last year.
The annual sales data of the enterprises and the government affair amount data corresponding to the house property data of the enterprise can be determined according to the annual sales data of the enterprises and the house property information of the enterprise. For example, it can be determined directly from the business owner's property information (property value). Or directly multiplying the annual sales of the previous year of the industry and the commerce by a preset coefficient. The method can also be determined by integrating the average value of the house property information (house property value) of the enterprise annual sales owner and multiplying the average value by a preset coefficient.
The government affair amount data corresponding to the accumulation fund payment data of the enterprise can be determined according to the house accumulation fund payment condition of the enterprise in the last 12 months. For example, the paying base number and the paying number data of the house accumulation fund of the enterprise in the last 12 months are obtained and determined according to the paying base number, the paying number and the paying number value. The payment base number can be multiplied by the number of the payers and then multiplied by the corresponding preset coefficient to obtain the payment. Or the payment value can be directly multiplied by a preset coefficient to determine.
It should be noted that the method for determining the government affair amount data is only an example, and those skilled in the art may modify the method for determining the government affair amount data according to actual situations in the actual application process, and in this embodiment, the method for determining the government affair amount data is not limited.
In this embodiment, the corresponding government affair amount data is determined according to the government affair data with different dimensions, so that the government affair amount of the target enterprise (a small enterprise with loan qualification) can be accurately determined, and after the credit line data is calculated for the target enterprise, risks are reduced when the target enterprise is loaned.
In one embodiment, as shown in fig. 6, the determining the credit line data of the target enterprise according to the government affair line data and the outstanding loan line data of the target enterprise includes:
and S42, determining the most valuable government affair amount data in the government affair amount data.
And S44, subtracting the outstanding loan amount data of the target enterprise from the government amount data with the maximum value to obtain the credit line data of the target enterprise.
Specifically, when the government affair line data corresponding to the government affair data of at least one dimension is obtained, the largest government affair line data needs to be selected from the government affair line data, so that the loan amount of the target enterprise is maximized. Considering the situation that a target enterprise may have an outstanding loan amount, in order to reduce the loan risk, the outstanding loan amount data of the target enterprise needs to be subtracted from the government amount data with the largest value to obtain credit amount data of the target enterprise.
In this embodiment, the credit line of the target enterprise can be accurately improved by determining the government line data with the largest value, and because the government line data is determined by the government data, the credit line of the target enterprise can be accurately determined, the credit granting risk can be reduced, and the credit granting risk can be further reduced by subtracting the outstanding credit line data of the target enterprise from the government line data with the largest value.
It should be understood that, although the steps in the flowcharts related to the embodiments as described above are sequentially displayed as indicated by arrows, the steps are not necessarily performed sequentially as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least a part of the steps in the flowcharts related to the embodiments described above may include multiple steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, and the execution order of the steps or stages is not necessarily sequential, but may be rotated or alternated with other steps or at least a part of the steps or stages in other steps.
Based on the same inventive concept, the embodiment of the disclosure also provides an enterprise credit line determining device based on the multidimensional government affair data, which is used for realizing the enterprise credit line determining method based on the multidimensional government affair data. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the method, so the specific limitations and the specific implementation modes in one or more embodiments of the device for determining the credit line of the enterprise based on the multidimensional government affair data provided below can be referred to the limitations and the specific implementation modes of the method for determining the credit line of the enterprise based on the multidimensional government affair data, and details are not repeated herein.
In one embodiment, as shown in fig. 7, there is provided an enterprise credit line determining apparatus 700 based on multidimensional government data, including: a condition determination module 702, a target determination module 704, and a quota determination module 706, wherein:
a condition determining module 702, configured to screen an enterprise according to at least one dimension of government affair data and corresponding admission conditions, and determine whether the enterprise meets the admission conditions.
And the target determining module 704 determines the target enterprise and the government affair amount data corresponding to the target enterprise in response to the enterprise meeting the admission condition.
And the line determining module 706 is used for determining the credit line data of the target enterprise according to the government affair line data and the outstanding loan line data of the target enterprise.
In one embodiment of the apparatus, the condition determining module 702 includes: the system comprises a government affair data acquisition module, a satisfaction condition determining module and an unsatisfied condition determining module;
the government affair data acquisition module is used for acquiring government affair data of at least one dimensionality of the enterprise;
the satisfaction condition determining module is used for determining that the enterprise meets the admission condition under the condition that the government affair data of the enterprise meet the admission condition;
the unsatisfied condition determining module is used for determining that the enterprise does not satisfy any admission condition under the condition that the government affair data of the enterprise does not satisfy any admission condition.
In one embodiment of the apparatus, the government data includes at least: tax amount data, social insurance payment data, tax declaration sales data, industry and commerce annual declaration sales data, enterprise owner house property data and accumulation payment data of the enterprise.
In one embodiment of the apparatus, the apparatus further comprises: and the application refusing module is used for refusing the loan application of the enterprise in response to the enterprise not meeting the admission condition.
In one embodiment of the apparatus, the targeting module 704 includes: the system comprises a target enterprise determining module and a limit data determining module;
the target enterprise determining module is used for determining the target enterprise according to the enterprises meeting the admission conditions;
and the quota data determining module is used for determining government quota data corresponding to the target enterprise according to the government data of the target enterprise.
In an embodiment of the apparatus, the quota determining module 706 comprises: a government affair line data determining module and a credit line data determining module;
the government affair line data determining module is used for determining the government affair line data with the largest value in the government affair line data;
and the credit line data determining module is used for subtracting the unfinished credit line data of the target enterprise from the government line data with the maximum value to obtain the credit line data of the target enterprise.
All or part of the modules in the enterprise credit line determination device based on the multidimensional government affair data can be realized by software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as shown in fig. 8. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database of the computer equipment is used for storing government affair data and government affair amount data. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to realize a method for determining the credit line of the enterprise based on multidimensional government affair data.
Those skilled in the art will appreciate that the architecture shown in fig. 8 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, a computer device is provided, comprising a memory and a processor, the memory having stored therein a computer program, the processor implementing the steps of the above-described method embodiments when executing the computer program.
In an embodiment, a computer-readable storage medium is provided, on which a computer program is stored, which computer program, when being executed by a processor, carries out the steps of the above-mentioned method embodiments.
In an embodiment, a computer program product is provided, comprising a computer program which, when executed by a processor, carries out the steps in the method embodiments described above.
It should be noted that the government affair data referred to in the present disclosure are information and data authorized by the user or sufficiently authorized by each party.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above may be implemented by hardware instructions of a computer program, which may be stored in a non-volatile computer-readable storage medium, and when executed, may include the processes of the embodiments of the methods described above. Any reference to memory, databases, or other media used in the embodiments provided by the present disclosure may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high-density embedded nonvolatile Memory, resistive Random Access Memory (ReRAM), Magnetic Random Access Memory (MRAM), Ferroelectric Random Access Memory (FRAM), Phase Change Memory (PCM), graphene Memory, and the like. Volatile Memory can include Random Access Memory (RAM), external cache Memory, and the like. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM), among others. The databases involved in embodiments provided by the present disclosure may include at least one of relational and non-relational databases. The non-relational database may include, but is not limited to, a block chain based distributed database, and the like. The processors referred to in the embodiments provided in this disclosure may be general purpose processors, central processing units, graphics processors, digital signal processors, programmable logic, quantum computing based data processing logic, etc., without limitation.
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present disclosure, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present disclosure. It should be noted that, for those skilled in the art, various changes and modifications can be made without departing from the concept of the present disclosure, and these changes and modifications are all within the scope of the present disclosure. Therefore, the protection scope of the present disclosure should be subject to the appended claims.
Claims (13)
1. An enterprise credit line determining method based on multidimensional government affair data is characterized by comprising the following steps:
screening enterprises according to at least one dimension of government affair data and corresponding admission conditions, and determining whether the enterprises meet the admission conditions, wherein the government affair data at least comprises the following components: tax amount data, social security payment data, tax declaration sales data, industry and commerce annual declaration sales data, enterprise owner house property data and accumulation payment data of the enterprise;
responding to the fact that the enterprise meets the admission condition, and determining a target enterprise and government affair limit data corresponding to the target enterprise;
and determining the credit line data of the target enterprise according to the government affair line data and the outstanding loan line data of the target enterprise.
2. The method of claim 1, wherein the screening of the enterprise according to the government data of at least one dimension and the corresponding admission condition to determine whether the enterprise meets the admission condition comprises:
acquiring government affair data of at least one dimension of the enterprise;
determining that the enterprise meets the admission condition under the condition that the government affair data of the enterprise meet the admission condition;
otherwise, determining that the enterprise does not meet the admission condition.
3. The method of claim 1 or 2, further comprising: and in response to the business failing to meet the admission conditions, denying the loan application of the business.
4. The method of claim 1, wherein the determining, in response to the business satisfying the admission condition, government credit data for a target business corresponding to the target business comprises:
determining the target enterprise according to the enterprises meeting the admission conditions;
and determining the government affair amount data corresponding to the target enterprise according to the government affair data of the target enterprise.
5. The method of claim 1, wherein the determining credit line data of the target enterprise based on the government line data and outstanding credit line data of the target enterprise comprises:
determining the most valuable government affair line data in the government affair line data;
and subtracting the outstanding loan amount data of the target enterprise from the government amount data with the maximum value to obtain the credit line data of the target enterprise.
6. An enterprise credit line determination device based on multidimensional government affair data, which is characterized by comprising:
a condition determining module, configured to screen an enterprise according to at least one dimension of government affair data and corresponding admission conditions, and determine whether the enterprise meets the admission conditions, where the government affair data at least includes: tax amount data, social security payment data, tax declaration sales data, industry and commerce annual declaration sales data, enterprise owner house property data and accumulation payment data of the enterprise;
the target determination module is used for determining a target enterprise and government affair amount data corresponding to the target enterprise in response to the fact that the enterprise meets the admission condition;
and the line determining module is used for determining the credit line data of the target enterprise according to the government affair line data and the outstanding loan line data of the target enterprise.
7. The apparatus of claim 6, wherein the condition determining module comprises: the system comprises a government affair data acquisition module, a satisfaction condition determining module and an unsatisfied condition determining module;
the government affair data acquisition module is used for acquiring government affair data of at least one dimension of the enterprise;
the satisfaction condition determining module is used for determining that the enterprise meets the admission condition under the condition that the government affair data of the enterprise meet the admission condition;
the unsatisfied condition determining module is used for determining that the enterprise does not satisfy any admission condition under the condition that the government affair data of the enterprise does not satisfy any admission condition.
8. The apparatus of claim 6 or 7, further comprising: and the application refusing module is used for refusing the loan application of the enterprise in response to the enterprise not meeting the admission condition.
9. The apparatus of claim 6, wherein the goal determination module comprises: a target enterprise determining module and a limit data determining module;
the target enterprise determining module is used for determining the target enterprise according to the enterprises meeting the admission conditions;
and the quota data determining module is used for determining government quota data corresponding to the target enterprise according to the government data of the target enterprise.
10. The apparatus of claim 6, wherein the credit determination module comprises: the system comprises a government affair amount data determining module and a credit line data determining module;
the government affair line data determining module is used for determining the government affair line data with the largest value in the government affair line data;
and the credit line data determining module is used for subtracting the unfinished credit line data of the target enterprise from the government line data with the maximum value to obtain the credit line data of the target enterprise.
11. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of the method of any of claims 1 to 5.
12. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 5.
13. A computer program product comprising a computer program, characterized in that the computer program realizes the steps of the method of any one of claims 1 to 5 when executed by a processor.
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