CN113269629A - Credit limit determining method, electronic equipment and related product - Google Patents
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Abstract
The embodiment of the application discloses a credit line determining method, electronic equipment and related products, wherein the method comprises the following steps: acquiring first enterprise information of an enterprise to be evaluated; preprocessing the first enterprise information to obtain second enterprise information; performing admission risk assessment on the enterprise to be assessed according to the second enterprise information; when the enterprise to be evaluated passes the access risk evaluation, performing operation risk and credit risk cross evaluation on the enterprise to be evaluated; when the enterprise to be evaluated is subjected to cross evaluation of operation risk and credit risk, determining a target credit line of the enterprise to be evaluated; and displaying the target credit line. By adopting the method and the device, the credit line determining efficiency can be improved.
Description
Technical Field
The application relates to the technical field of data processing, in particular to a credit limit determination method, electronic equipment and related products.
Background
With the rapid development of the economic society, the number of small and medium-sized micro manufacturing enterprises is also rapidly increased; meanwhile, when small and medium-sized micro-manufacturing enterprises operate, the production equipment of the enterprises needs to apply for loan from financial institutions. For financial institutions, in order to ensure their economic safety, comprehensive judgment needs to be performed on the overall operation conditions and equipment value conditions of small and medium-sized micro-enterprises to determine whether to credit the small and medium-sized micro-enterprises.
In the prior art, the assessment of the equipment financing risk of small and medium-sized micro-manufacturing enterprises is generally judged by deep investigation and analysis under a manual line; after receiving the equipment financing requirements of small and medium-sized micro-manufacturing enterprises, financial institutions need to arrange different personnel to visit the enterprises in a field investigation mode according to the internal flow and different flow schedules, and during the period, the financing enterprises still need to continuously provide or manufacture various financing materials according to the requirements of the financial institutions, provide financing enterprise risk assessment reports and explain the related financing risks of the enterprises, so that the problem of how to quickly determine the credit line of the enterprises needs to be solved urgently.
Disclosure of Invention
The embodiment of the application provides a credit line determining method, electronic equipment and related products, and the credit line determining efficiency can be improved.
In a first aspect, an embodiment of the present application provides a method for determining a credit line, where the method includes:
acquiring first enterprise information of an enterprise to be evaluated;
preprocessing the first enterprise information to obtain second enterprise information;
performing admission risk assessment on the enterprise to be assessed according to the second enterprise information;
when the enterprise to be evaluated passes the access risk evaluation, performing operation risk and credit risk cross evaluation on the enterprise to be evaluated;
when the enterprise to be evaluated is subjected to cross evaluation of operation risk and credit risk, determining a target credit line of the enterprise to be evaluated;
and displaying the target credit line.
In a second aspect, an embodiment of the present application provides a credit line determining device, where the device includes: an acquisition unit, a preprocessing unit, a first evaluation unit, a second evaluation unit, a determination unit and a presentation unit, wherein,
the acquisition unit is used for acquiring first enterprise information of an enterprise to be evaluated;
the preprocessing unit is used for preprocessing the first enterprise information to obtain second enterprise information;
the first evaluation unit is used for performing access risk evaluation on the enterprise to be evaluated according to the second enterprise information;
the second evaluation unit is used for performing cross evaluation on the operation risk and the credit risk of the enterprise to be evaluated when the enterprise to be evaluated passes the access risk evaluation;
the determining unit is used for determining the target credit line of the enterprise to be evaluated when the enterprise to be evaluated is subjected to cross evaluation of operation risk and credit risk;
and the display unit is used for displaying the target credit line.
In a third aspect, an embodiment of the present application provides an electronic device, including a processor, a memory, a communication interface, and one or more programs, where the one or more programs are stored in the memory and configured to be executed by the processor, and the program includes instructions for executing the steps in the first aspect of the embodiment of the present application.
In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, where the computer-readable storage medium stores a computer program for electronic data exchange, where the computer program enables a computer to perform some or all of the steps described in the first aspect of the embodiment of the present application.
In a fifth aspect, embodiments of the present application provide a computer program product, where the computer program product includes a non-transitory computer-readable storage medium storing a computer program, where the computer program is operable to cause a computer to perform some or all of the steps as described in the first aspect of the embodiments of the present application. The computer program product may be a software installation package.
The embodiment of the application has the following beneficial effects:
it can be seen that, according to the credit line determining method, the electronic device and the related product described in the embodiment of the application, the first enterprise information of the enterprise to be evaluated is acquired, the first enterprise information is preprocessed to obtain the second enterprise information, the access risk assessment is performed on the enterprise to be evaluated according to the second enterprise information, when the enterprise to be evaluated passes the access risk assessment, the operation risk and the credit risk cross assessment are performed on the enterprise to be evaluated, when the enterprise to be evaluated passes the operation risk and the credit risk cross assessment, the target credit line of the enterprise to be evaluated is determined, and the target credit line is displayed.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic flow chart of a method for determining a credit line provided in an embodiment of the present application;
FIG. 2 is a schematic flow chart of another method for determining credit line provided in the embodiment of the present application;
fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present application;
fig. 4 is a block diagram illustrating functional units of a credit limit determination device according to an embodiment of the present application.
Detailed Description
The terms "first," "second," and the like in the description and claims of the present application and in the above-described drawings are used for distinguishing between different objects and not for describing a particular order. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may include other steps or elements not listed or inherent to such process, method, article, or apparatus in one possible example.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.
In order to make the technical solutions of the present application better understood, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The electronic device according to the embodiment of the present application may include, but is not limited to: a smart phone, a tablet computer, a smart robot, a vehicle-mounted device, a wearable device, a computing device or other processing device connected to a wireless modem, as well as various forms of User Equipment (UE), a Mobile Station (MS), a terminal device (terminal device), and the like, which are not limited herein, the electronic device may also be a server.
Referring to fig. 1, fig. 1 is a schematic flow chart of a method for determining a credit line provided in an embodiment of the present application, and as shown in the figure, the method for determining a credit line is applied to an electronic device, and the method for determining a credit line includes:
101. first enterprise information of an enterprise to be evaluated is obtained.
In this embodiment, the first enterprise information may include enterprise tax-related management data, business and judicial data, equipment data, human credit data, and the like, which are not limited herein. The enterprise tax-related business data may include at least one of: enterprise turnover, enterprise tax payment, number of enterprises, enterprise tax type, enterprise invoice, etc., without limitation. The business jurisdictional data may be at least one of: the name of the business, the geographic location of the business, the tax size, the registered funds of the business, the size of the business, the scope of the business, the risk of the business, etc., are not limited herein. The device data may be at least one of: the type of the device, the model of the device, the device identification code, the manufacturer of the device, the device number, the duration of the device, the production efficiency of the device, etc., which are not limited herein. The pedestrian credit data may be at least one of: enterprise credit investigation, enterprise infringement, enterprise illegal operation, enterprise liability, etc., without limitation. In a specific implementation, the first enterprise information of the enterprise to be evaluated may be uploaded by the enterprise to be evaluated or acquired through a third-party application.
102. And preprocessing the first enterprise information to obtain second enterprise information.
In a specific implementation, the pretreatment may be at least one of: data cleaning, data deduplication, data sampling, processing and the like, which are not limited herein, and the processing may be converting enterprise information into keywords or feature vectors. Furthermore, the electronic device can preprocess the first enterprise information to obtain the second enterprise information, and further obtain enterprise information required by risk assessment.
103. And performing admission risk assessment on the enterprise to be assessed according to the second enterprise information.
In specific implementation, the admission risk assessment is equivalent to preliminary screening, namely, the electronic equipment can perform admission risk assessment on the enterprise to be assessed according to the second enterprise information, and then, if the second enterprise information passes the admission risk assessment, the electronic equipment can execute the next step, otherwise, the electronic equipment can prompt the user that the admission risk assessment fails.
Optionally, in step 103, performing admission risk assessment on the enterprise to be assessed according to the second enterprise information, which may include the following steps:
31. acquiring tax-related sample data of the enterprise to be evaluated;
32. performing feature extraction on the tax-related sample data to obtain a target feature set;
33. and performing admission risk assessment on the enterprise to be assessed according to the target feature set and the second enterprise information.
In a specific implementation, the tax-related sample data may be at least one of: the method includes the steps that invoices, tax lists, quarterly or annual financial statements of companies and the like are not limited, electronic equipment can obtain tax-related sample data of an enterprise to be evaluated, and further feature extraction can be performed on the tax-related sample data to obtain a target feature set, the target feature set can include at least one feature, and the features can be at least one of the following: number, name, taxpayer identification number, address, telephone, issuer and account number, invoice code, invoice number, invoice date, invoice type, project name, unit price, amount, tax rate, tax amount, specification type, etc., without limitation. The characteristics reflect the core index variables of the invoice to a certain extent.
In the embodiment of the application, various invoicing core index variables can be formed again based on the test result and the risk expert experience, and are used for effectively identifying the transaction risk of an enterprise, and the invoice indexes mainly measure the aspects of the operation condition and the invoicing behavior of the borrowing enterprise by taking the invoice as an example, and can include but are not limited to: the billing amount of the enterprise, the income stability, the zero billing record, the coincidence degree of the upstream and the downstream, the red flushing voiding behavior and the like are not limited herein. The concrete indexes are as follows:
(1) according to the invoice issuing time of the invoice sold, the method can be used for judging the operation duration of the enterprise and eliminating the enterprise with the problem of poor stability;
(2) according to the total amount of invoicing of the invoice on the purchase and sale item, the method can be used for eliminating a large number of enterprises with empty shells and no purchase on the purchase item in a short period, or a large number of enterprises with bad operation and no goods sold due to inflexible purchase and turnover;
(3) the invoicing amount is increased in a same proportion according to the invoice of the sales invoice, and the operation increase condition can be considered; the invoicing amount of the entry invoice is increased in the same proportion, and the operation and maintenance condition is considered;
(4) the invoicing amount is increased according to the invoice billing cycle of the purchase and sale item, and the risk of short-term operation fluctuation can be identified;
(5) according to the short-term zero-invoice-making behavior of the invoice with the incoming and outgoing item, fraud risks are prevented; the zero billing behavior for medium and long periods prevents the operation risk;
(6) preventing fraud risk of false invoicing according to the top-amount invoicing proportion;
(7) and identifying abnormal enterprise fraud risk according to the proportion of the red flushing invoice to the invalid invoice.
Furthermore, the electronic device may perform access risk assessment on the enterprise to be assessed according to the target feature set and the second enterprise information, for example, the features corresponding to the target feature set and the second enterprise information may be compared, and if the comparison is successful, the enterprise information is true, and it may be determined that the access risk assessment is passed.
Optionally, in the step 33, performing admission risk assessment on the enterprise to be assessed according to the target feature set and the second enterprise information may include the following steps:
331. performing feature extraction on the second enterprise information to obtain a reference feature set;
332. comparing the target characteristic set with the reference characteristic set to obtain a target comparison value;
333. when the target comparison value is larger than a preset threshold value, performing risk assessment according to the target characteristic set to obtain a first risk assessment value;
334. performing risk assessment according to the reference feature set to obtain a second risk assessment value;
335. determining a target weight value pair corresponding to the target comparison value according to a mapping relation between a preset ratio and the weight value pair;
336. performing weighted operation according to the first risk assessment value, the second risk assessment value and the target weight value to obtain a target risk assessment value;
337. and when the target risk assessment value is larger than a preset risk assessment value, confirming that the enterprise to be assessed passes the access risk assessment.
The preset threshold and the preset risk assessment value can be set by the user or defaulted by the system. The mapping relationship between the preset ratio and the weight pair may be stored in the electronic device in advance.
Specifically, the electronic device may perform feature extraction on the second enterprise information to obtain a reference feature set, where the reference feature set may include at least one feature, and the feature may be at least one of: number, name, taxpayer identification number, address, telephone, issuer and account number, invoice code, invoice number, invoice date, invoice type, project name, unit price, amount, tax rate, tax amount, specification type, etc., without limitation.
Further, the electronic device may compare the target feature set with the reference feature set to obtain a target comparison value, and when the target comparison value is greater than a preset threshold, may perform the next operation, otherwise, may determine that the access risk assessment does not pass. When the access risk assessment passes, the electronic device may perform risk assessment according to the target feature set to obtain a first risk assessment value, specifically, the target feature set may be classified to obtain at least one category, each category corresponds to one category tag, a mapping relationship between the category tag and a weight may be stored in the electronic device in advance, further, a weight corresponding to each category tag of the at least one category may be determined according to the mapping relationship to obtain at least one weight, the electronic device may further input the target feature set to a preset neural network model to obtain at least one operation result, each operation result corresponds to one category tag, and then, the at least one operation result and the at least one weight are subjected to weighted operation to obtain the first risk assessment value. The preset neural network model can be preset or default to a system, and the preset neural network model can be at least one of the following: convolutional neural network models, impulse neural network models, fully-connected neural network models, recurrent neural network models, and the like, without limitation. Of course, the electronic device may also perform data cleaning on the target feature set, and then input the feature set after the data cleaning to the preset neural network model. The preset neural network model can be used for selecting proper indexes through the system and constructing an enterprise transaction risk credit evaluation model. The category labels may correspond to respective degrees of risk (risk classes).
In a specific implementation, the operation result may be a probability value, and each operation result may correspond to one category label.
In a specific implementation, before step 101, the following steps may be further included: acquiring sample data; extracting the characteristics of the sample data to obtain multiple types of characteristics, wherein each type of characteristic corresponds to a class label; and training the neural network model through the multi-class characteristics to obtain a trained neural network model, and taking the trained neural network model as the preset neural network model.
In specific implementation, the electronic device may obtain sample data, the sample data may include multiple invoices by taking the sample data as sample invoice data as an example, and further, the features of the sample invoice data may be extracted to obtain multiple types of features, each type of feature corresponds to one type of tag, and then the neural network model is trained based on the multiple types of features to obtain a trained neural network model, and the trained neural network model is used as a preset neural network model, so that the trained neural network model may be obtained, and the model capability of the neural network model is facilitated to be improved.
Further, similarly, the electronic device performs risk assessment according to the reference feature set to obtain a second risk assessment value, different comparison values may correspond to different weight pairs, and further, the electronic device may determine a target weight pair corresponding to the target comparison value according to a mapping relationship between a preset ratio and the weight pair, where the weight pair may include two weights, and a sum of the two weights is 1.
Furthermore, the target weight pair may include a target first weight and a target second weight, and the electronic device may perform a weighted operation according to the first risk assessment value, the second risk assessment value, and the target weight pair to obtain a target risk assessment value, where the specific calculation method is as follows:
a target risk assessment value is first target weight value + first target second weight value
Further, when the target risk assessment value is greater than the preset risk assessment value, the electronic device may confirm that the enterprise to be assessed passes the access risk assessment.
104. And when the enterprise to be evaluated passes the access risk evaluation, performing operation risk and credit risk cross evaluation on the enterprise to be evaluated.
In the specific implementation, the admission risk assessment is equivalent to a preliminary risk assessment, and when the enterprise to be assessed passes the admission risk assessment, the electronic device can perform cross assessment on the operation risk and the credit risk of the enterprise to be assessed, as follows.
Optionally, in the step 104, performing cross-assessment on the operation risk and the credit risk of the enterprise to be assessed may include the following steps:
41. acquiring tax-related sample data of the enterprise to be evaluated;
42. and performing cross evaluation on the operation risk and the credit risk according to the tax-related sample data.
In a specific implementation, the tax-related sample data is specifically referred to the above description, and is not described herein again. The operational risk is the possibility that the future operational cash flow of an enterprise changes due to the change of production and operation or the change of market environment, thereby affecting the market value of the enterprise. The change degree of the enterprise price value depends on the influence degree of the variable factors on the future sales volume, price and cost of the enterprise, and further, the electronic equipment can predict the operation risk of the enterprise to be evaluated through the tax-related sample data, for example, the sales volume, price and cost of the company product are extracted from the tax-related sample data in different periods, and further, a corresponding curve is drawn, and the operation risk is determined through the curve.
Additionally, credit risk refers to the risk of a counterparty not fulfilling an expired debt. The credit risk is also called default risk, which means the possibility that a borrower, a security issuer or a transaction counterpart will lose money due to unwilling or inability to fulfill contract conditions for various reasons, thereby causing loss to banks, investors or transaction partners. Due to the difference of settlement modes, credit risks involved in the on-site derivative transaction and the off-site derivative transaction are different, and the electronic equipment can extract the relevant parameters of the credit risks from tax-related sample data so as to realize credit risk assessment.
And then, cross evaluation can be carried out through the operation risk and the credit risk, because the operation risk and the credit risk are realized based on tax-related sample data, the cross entropy between the operation risk and the credit risk can be determined, the evaluation result of the cross evaluation of the operation risk and the credit risk is determined according to the cross entropy, or a first weight value pair corresponding to the cross entropy between the operation risk and the credit risk is determined according to the mapping relation between the preset cross entropy and the weight value pair, and then the operation is carried out on the operation risk, the credit risk and the first weight value pair, so that the evaluation result is obtained.
105. And when the enterprise to be evaluated is subjected to cross evaluation of the operation risk and the credit risk, determining the target credit line of the enterprise to be evaluated.
In the specific implementation, the electronic device may obtain the evaluation result when the enterprise to be evaluated performs the cross evaluation of the operation risk and the credit risk, and determine the target credit line of the enterprise to be evaluated according to the evaluation result. Certainly, when the enterprise to be evaluated does not pass the cross evaluation of the operation risk and the credit risk, the target credit line can be set as a default value. Or, when the enterprise to be evaluated does not pass the cross evaluation of the operation risk and the credit risk, the enterprise can be considered to not pass the audit.
Optionally, in the step 105, determining the target credit line of the enterprise to be evaluated may include the following steps:
a51, acquiring equipment list information of the enterprise to be evaluated, wherein the equipment list information comprises at least one piece of equipment, and each piece of equipment corresponds to an equipment purchase price, an equipment residual value rate, a second-hand market trading price corresponding to the equipment and an equipment capacity factor;
a52, determining the fixed asset value of the enterprise to be evaluated according to the equipment list information;
a53, acquiring target operation parameter information of the enterprise to be evaluated, wherein the target operation parameter information comprises enterprise tax income, tax payment amount, tax rate condition, enterprise growth condition and operation capacity;
a54, determining the liquidity fund limit of the enterprise to be evaluated according to the target operation parameter information;
a55, determining the target credit line according to the fixed asset value and the mobile fund line.
In specific implementation, the electronic device may obtain device list information of an enterprise to be evaluated, where the device list information includes at least one device, and each device corresponds to a device purchase price, a device residual value rate, a second-hand market trading price corresponding to the device, and a device productivity factor, where the device productivity factor may be an empirical value, the device residual value rate may be an empirical value, and the second-hand market trading price may be a market research price.
Furthermore, the electronic device may determine the fixed asset value of the enterprise to be assessed according to the device inventory information, then obtain the target operation parameter information of the enterprise to be assessed, where the target operation parameter information includes tax income, tax payment amount, tax rate, enterprise growth condition and operation capacity of the enterprise, determine the mobile fund amount of the enterprise to be assessed according to the target operation parameter information, and then determine the target credit line according to the fixed asset value and the mobile fund amount, for example, may perform a weighting operation on the fixed asset value and the mobile fund amount to obtain the target credit line.
For example, the financing amount evaluation of the financing enterprise can be combined with the mobile capital demand of the enterprise and the equipment evaluation value to comprehensively measure the financing amount of the enterprise.
Specifically, as for the equipment evaluation value, the 5-year financial straight-line depreciation method (fixed asset value: equipment purchase price (1-equipment residual rate)/5 used years), the trading price of the second-hand market, and the current industry capacity condition are combined for evaluation, that is, the equipment final assessment value is (equipment depreciation price + second-hand trading price)/2-year equipment capacity factor.
In addition, for example, the demand of the liquidity fund can be comprehensively evaluated by combining factors such as tax income, tax total, tax rate condition, growth condition, operation capacity and the like of the enterprise, and a liquidity fund limit is given to the client. Namely, the mobile capital quota of the enterprise (average tax income in last 2 years + total tax payment in last 2 years + industry tax rate) operation evaluation coefficient, enterprise growth coefficient, enterprise operation capacity coefficient and quota risk coefficient.
Optionally, in the step 105, determining the target credit line of the enterprise to be evaluated may include the following steps:
b51, obtaining a target evaluation result of the cross evaluation of the operation risk and the credit risk;
b52, determining target optimization parameters corresponding to the target evaluation results according to the preset mapping relation between the evaluation results and the optimization parameters;
b53, acquiring the target tax payment limit of the enterprise to be evaluated in the last year;
b54, determining a reference credit line corresponding to the target tax payment line according to a preset mapping relation between the tax payment line and the credit line;
and B55, optimizing the reference credit line through the target optimization parameters to obtain the target credit line.
In a specific implementation, the electronic device may pre-store a mapping relationship between a preset tax payment amount and a credit line and a mapping relationship between a preset evaluation result and an optimization parameter.
Specifically, the electronic device may obtain a target evaluation result of the cross evaluation of the operation risk and the credit risk, determine a target optimization parameter corresponding to the target evaluation result according to a preset mapping relationship between the evaluation result and the optimization parameter, and according to a value range of the optimization parameter being 0-1, obtain a target tax payment amount of the enterprise to be evaluated in the previous year, determine a reference credit line corresponding to the target tax payment amount according to a preset mapping relationship between the tax payment amount and the credit line, and optimize the reference credit line through the target optimization parameter to obtain the target credit line, wherein specifically, the target credit line is the target optimization parameter.
106. And displaying the target credit line.
In the specific implementation, the electronic device may show the target credit line, specifically, the electronic device may obtain target identity information of the target user, and after the target identity information is verified, the target credit line may be shown, where the target identity information may be at least one of the following information: face images, iris images, fingerprint images, vein images, voice print information, character strings, and the like, which are not limited herein.
The embodiment of the application can be applied to risk assessment of financing of equipment of small and medium-sized micro-manufacturing enterprises by financial institutions, and can realize the following functions:
(1) by collecting data such as tax-related operation data, invoice data and the like of financing enterprises, the operation condition of the enterprises can be more accurately and efficiently represented;
(2) providing a more efficient and convenient pre-loan risk management method for financial institutions in enterprise equipment financing;
(3) through scientific statistical analysis, more accurate enterprise operation condition evaluation, equipment value evaluation, financing capacity evaluation, operation continuous capacity evaluation and the like are provided for equipment financing loan operation, and the bad account rate of the loan in the equipment financing process is reduced.
Based on the above embodiments of the present application, it can be seen that:
firstly, the data of application approval can be obtained on line in a passive mode basically, so that the approval efficiency of the existing equipment financing can be improved, and various operational risks in the conventional manual approval can be avoided;
secondly, the current advanced machine learning algorithm can be introduced to construct an enterprise operation risk scoring card and a credit risk scoring card, so that the operation risk and the credit risk of the enterprise can be more comprehensively and accurately evaluated, and the data image of the enterprise operation condition can be more comprehensively and objectively drawn;
and thirdly, the credit line of the enterprise is comprehensively evaluated according to the operation condition, the profit condition and the equipment condition of the enterprise, so that the actual condition of the enterprise can be better matched, and the credit line is more reasonable and within the bearing range.
It can be seen that, according to the credit line determining method described in the embodiment of the application, the first enterprise information of the enterprise to be evaluated is acquired, the first enterprise information is preprocessed to obtain the second enterprise information, the access risk assessment is performed on the enterprise to be evaluated according to the second enterprise information, when the enterprise to be evaluated passes the access risk assessment, the operation risk and the credit risk cross assessment are performed on the enterprise to be evaluated, when the enterprise to be evaluated passes the operation risk and the credit risk cross assessment, the target credit line of the enterprise to be evaluated is determined, and the target credit line is displayed.
Referring to fig. 2, in keeping with the embodiment shown in fig. 1, fig. 2 is a schematic flow chart of another method for determining a credit line provided in the embodiment of the present application, and the method is applied to an electronic device, and the method for determining a credit line includes:
201. first enterprise information of an enterprise to be evaluated is obtained.
202. And preprocessing the first enterprise information to obtain second enterprise information.
203. And performing admission risk assessment on the enterprise to be assessed according to the second enterprise information.
204. And when the enterprise to be evaluated passes the access risk evaluation, performing operation risk and credit risk cross evaluation on the enterprise to be evaluated.
205. And when the enterprise to be evaluated is subjected to cross evaluation of the operation risk and the credit risk, determining the target credit line of the enterprise to be evaluated.
206. And acquiring target identity information of a target user.
207. And after the target identity information is verified, displaying the target credit line.
The detailed description of the steps 201 to 207 may refer to the corresponding steps of the credit line determination method described in fig. 1, and will not be described herein again.
It can be seen that, the method for determining credit line described in the embodiment of the present application obtains the first enterprise information of the enterprise to be evaluated, pre-processes the first enterprise information to obtain the second enterprise information, performs the access risk evaluation on the enterprise to be evaluated according to the second enterprise information, performs the cross evaluation of the operation risk and the credit risk on the enterprise to be evaluated when the enterprise to be evaluated passes the access risk evaluation, determines the target credit line of the enterprise to be evaluated when the enterprise to be evaluated passes the cross evaluation of the operation risk and the credit risk, obtains the target identity information of the target user, and displays the target credit line after the target identity information is verified, on one hand, the risk condition of the enterprise to be evaluated can be determined through the access risk evaluation and the cross evaluation of the operation risk and the credit risk, on the other hand, the credit line can be determined quickly, so that, the credit limit determination efficiency is improved.
Referring to fig. 3, fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present application, and as shown in the drawing, the electronic device includes a processor, a memory, a communication interface, and one or more programs, where the one or more programs are stored in the memory and configured to be executed by the processor, and in an embodiment of the present application, the programs include instructions for performing the following steps:
acquiring first enterprise information of an enterprise to be evaluated;
preprocessing the first enterprise information to obtain second enterprise information;
performing admission risk assessment on the enterprise to be assessed according to the second enterprise information;
when the enterprise to be evaluated passes the access risk evaluation, performing operation risk and credit risk cross evaluation on the enterprise to be evaluated;
when the enterprise to be evaluated is subjected to cross evaluation of operation risk and credit risk, determining a target credit line of the enterprise to be evaluated;
and displaying the target credit line.
It can be seen that, the credit line electronic device described in the embodiment of the present application obtains first enterprise information of an enterprise to be evaluated, pre-processes the first enterprise information to obtain second enterprise information, performs access risk evaluation on the enterprise to be evaluated according to the second enterprise information, performs cross evaluation on an operation risk and a credit risk of the enterprise to be evaluated when the enterprise to be evaluated passes the access risk evaluation, determines a target credit line of the enterprise to be evaluated when the enterprise to be evaluated passes the cross evaluation on the operation risk and the credit risk, and displays the target credit line.
Optionally, in the aspect of performing admission risk assessment on the enterprise to be assessed according to the second enterprise information, the program includes instructions for executing the following steps:
acquiring tax-related sample data of the enterprise to be evaluated;
performing feature extraction on the tax-related sample data to obtain a target feature set;
and performing admission risk assessment on the enterprise to be assessed according to the target feature set and the second enterprise information.
Optionally, in the aspect of performing admission risk assessment on the enterprise to be assessed according to the target feature set and the second enterprise information, the program includes instructions for performing the following steps:
performing feature extraction on the second enterprise information to obtain a reference feature set;
comparing the target characteristic set with the reference characteristic set to obtain a target comparison value;
when the target comparison value is larger than a preset threshold value, performing risk assessment according to the target characteristic set to obtain a first risk assessment value;
performing risk assessment according to the reference feature set to obtain a second risk assessment value;
determining a target weight value pair corresponding to the target comparison value according to a mapping relation between a preset ratio and the weight value pair;
performing weighted operation according to the first risk assessment value, the second risk assessment value and the target weight value to obtain a target risk assessment value;
and when the target risk assessment value is larger than a preset risk assessment value, confirming that the enterprise to be assessed passes the access risk assessment.
Optionally, in the aspect of performing the operation risk and credit risk cross evaluation on the enterprise to be evaluated, the program includes instructions for performing the following steps:
acquiring tax-related sample data of the enterprise to be evaluated;
and performing cross evaluation on the operation risk and the credit risk according to the tax-related sample data.
Optionally, in the aspect of determining the target credit line of the enterprise to be assessed, the program includes instructions for executing the following steps:
acquiring equipment list information of the enterprise to be evaluated, wherein the equipment list information comprises at least one piece of equipment, and each piece of equipment corresponds to an equipment purchase price, an equipment residual value rate, a second-hand market trading price corresponding to the equipment and an equipment capacity factor;
determining the fixed asset value of the enterprise to be evaluated according to the equipment list information;
acquiring target operation parameter information of the enterprise to be evaluated, wherein the target operation parameter information comprises enterprise tax income, tax payment amount, tax rate condition, enterprise growth condition and operation capacity;
determining the mobile fund amount of the enterprise to be evaluated according to the target operation parameter information;
and determining the target credit line according to the fixed asset value and the mobile fund line.
The above description has introduced the solution of the embodiment of the present application mainly from the perspective of the method-side implementation process. It is understood that in order to implement the above functions, it includes corresponding hardware structures and/or software modules for performing the respective functions. Those of skill in the art will readily appreciate that the present application is capable of hardware or a combination of hardware and computer software implementing the various illustrative elements and algorithm steps described in connection with the embodiments provided herein. Whether a function is performed as hardware or computer software drives hardware depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
In the embodiment of the present application, the functional units may be divided according to the above method example, for example, each functional unit may be divided corresponding to each function, or two or more functions may be integrated into one processing unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit. It should be noted that the division of the unit in the embodiment of the present application is schematic, and is only a logic function division, and there may be another division manner in actual implementation.
Fig. 4 is a block diagram showing functional units of the credit line determination device 400 according to the embodiment of the present application, and the credit line determination device 400 may include: an acquisition unit 401, a pre-processing unit 402, a first evaluation unit 403, a second evaluation unit 404, a determination unit 405 and a presentation unit 406, wherein,
the acquiring unit 401 is configured to acquire first enterprise information of an enterprise to be evaluated;
the preprocessing unit 402 is configured to preprocess the first enterprise information to obtain second enterprise information;
the first evaluation unit 403 is configured to perform admission risk evaluation on the enterprise to be evaluated according to the second enterprise information;
the second evaluation unit 404 is configured to perform cross-evaluation on the operation risk and the credit risk of the enterprise to be evaluated when the enterprise to be evaluated passes the admission risk evaluation;
the determining unit 405 is configured to determine a target credit line of the enterprise to be assessed when the enterprise to be assessed is cross-assessed through the operation risk and the credit risk;
the display unit 406 is configured to display the target credit line.
It can be seen that, the credit line determining apparatus described in the embodiment of the present application obtains first enterprise information of an enterprise to be evaluated, pre-processes the first enterprise information to obtain second enterprise information, performs access risk assessment on the enterprise to be evaluated according to the second enterprise information, performs cross-assessment of operation risk and credit risk on the enterprise to be evaluated when the enterprise to be evaluated passes the access risk assessment, and determines a target credit line of the enterprise to be evaluated and displays the target credit line when the enterprise to be evaluated passes the cross-assessment of operation risk and credit risk.
Optionally, in terms of performing admission risk assessment on the enterprise to be assessed according to the second enterprise information, the first assessment unit 403 is specifically configured to:
acquiring tax-related sample data of the enterprise to be evaluated;
performing feature extraction on the tax-related sample data to obtain a target feature set;
and performing admission risk assessment on the enterprise to be assessed according to the target feature set and the second enterprise information.
Optionally, in the aspect of performing admission risk assessment on the enterprise to be assessed according to the target feature set and the second enterprise information, the first assessment unit 403 is specifically configured to:
performing feature extraction on the second enterprise information to obtain a reference feature set;
comparing the target characteristic set with the reference characteristic set to obtain a target comparison value;
when the target comparison value is larger than a preset threshold value, performing risk assessment according to the target characteristic set to obtain a first risk assessment value;
performing risk assessment according to the reference feature set to obtain a second risk assessment value;
determining a target weight value pair corresponding to the target comparison value according to a mapping relation between a preset ratio and the weight value pair;
performing weighted operation according to the first risk assessment value, the second risk assessment value and the target weight value to obtain a target risk assessment value;
and when the target risk assessment value is larger than a preset risk assessment value, confirming that the enterprise to be assessed passes the access risk assessment.
Optionally, in the aspect of performing the operation risk and credit risk cross evaluation on the enterprise to be evaluated, the second evaluation unit 404 is specifically configured to:
acquiring tax-related sample data of the enterprise to be evaluated;
and performing cross evaluation on the operation risk and the credit risk according to the tax-related sample data.
Optionally, in the aspect of determining the target credit line of the enterprise to be evaluated, the determining unit 405 is specifically configured to:
acquiring equipment list information of the enterprise to be evaluated, wherein the equipment list information comprises at least one piece of equipment, and each piece of equipment corresponds to an equipment purchase price, an equipment residual value rate, a second-hand market trading price corresponding to the equipment and an equipment capacity factor;
determining the fixed asset value of the enterprise to be evaluated according to the equipment list information;
acquiring target operation parameter information of the enterprise to be evaluated, wherein the target operation parameter information comprises enterprise tax income, tax payment amount, tax rate condition, enterprise growth condition and operation capacity;
determining the mobile fund amount of the enterprise to be evaluated according to the target operation parameter information;
determining the target credit limit according to the fixed asset value and the mobile fund limit
It can be understood that the functions of each program module of the credit line determination device in this embodiment may be specifically implemented according to the method in the foregoing method embodiment, and the specific implementation process may refer to the related description of the foregoing method embodiment, which is not described herein again.
Embodiments of the present application also provide a computer storage medium, where the computer storage medium stores a computer program for electronic data exchange, the computer program enabling a computer to execute part or all of the steps of any one of the methods described in the above method embodiments, and the computer includes an electronic device.
Embodiments of the present application also provide a computer program product comprising a non-transitory computer readable storage medium storing a computer program operable to cause a computer to perform some or all of the steps of any of the methods as described in the above method embodiments. The computer program product may be a software installation package, the computer comprising an electronic device.
It should be noted that, for simplicity of description, the above-mentioned method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present application is not limited by the order of acts described, as some steps may occur in other orders or concurrently depending on the application. Further, those skilled in the art should also appreciate that the embodiments described in the specification are preferred embodiments and that the acts and modules referred to are not necessarily required in this application.
In the foregoing embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus may be implemented in other manners. For example, the above-described embodiments of the apparatus are merely illustrative, and for example, the above-described division of the units is only one type of division of logical functions, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of some interfaces, devices or units, and may be an electric or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit may be stored in a computer readable memory if it is implemented in the form of a software functional unit and sold or used as a stand-alone product. Based on such understanding, the technical solution of the present application may be substantially implemented or a part of or all or part of the technical solution contributing to the prior art may be embodied in the form of a software product stored in a memory, and including several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the above-mentioned method of the embodiments of the present application. And the aforementioned memory comprises: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.
Those skilled in the art will appreciate that all or part of the steps in the methods of the above embodiments may be implemented by associated hardware instructed by a program, which may be stored in a computer-readable memory, which may include: flash Memory disks, Read-Only memories (ROMs), Random Access Memories (RAMs), magnetic or optical disks, and the like.
The foregoing detailed description of the embodiments of the present application has been presented to illustrate the principles and implementations of the present application, and the above description of the embodiments is only provided to help understand the method and the core concept of the present application; meanwhile, for a person skilled in the art, according to the idea of the present application, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present application.
Claims (10)
1. A credit line determining method is characterized by comprising the following steps:
acquiring first enterprise information of an enterprise to be evaluated;
preprocessing the first enterprise information to obtain second enterprise information;
performing admission risk assessment on the enterprise to be assessed according to the second enterprise information;
when the enterprise to be evaluated passes the access risk evaluation, performing operation risk and credit risk cross evaluation on the enterprise to be evaluated;
when the enterprise to be evaluated is subjected to cross evaluation of operation risk and credit risk, determining a target credit line of the enterprise to be evaluated;
and displaying the target credit line.
2. The method of claim 1, wherein performing admission risk assessment on the enterprise to be assessed according to the second enterprise information comprises:
acquiring tax-related sample data of the enterprise to be evaluated;
performing feature extraction on the tax-related sample data to obtain a target feature set;
and performing admission risk assessment on the enterprise to be assessed according to the target feature set and the second enterprise information.
3. The method of claim 2, wherein performing admission risk assessment on the enterprise to be assessed according to the target feature set and the second enterprise information comprises:
performing feature extraction on the second enterprise information to obtain a reference feature set;
comparing the target characteristic set with the reference characteristic set to obtain a target comparison value;
when the target comparison value is larger than a preset threshold value, performing risk assessment according to the target characteristic set to obtain a first risk assessment value;
performing risk assessment according to the reference feature set to obtain a second risk assessment value;
determining a target weight value pair corresponding to the target comparison value according to a mapping relation between a preset ratio and the weight value pair;
performing weighted operation according to the first risk assessment value, the second risk assessment value and the target weight value to obtain a target risk assessment value;
and when the target risk assessment value is larger than a preset risk assessment value, confirming that the enterprise to be assessed passes the access risk assessment.
4. The method according to any one of claims 1 to 3, wherein the cross-assessing of business risk and credit risk for the enterprise to be assessed comprises:
acquiring tax-related sample data of the enterprise to be evaluated;
and performing cross evaluation on the operation risk and the credit risk according to the tax-related sample data.
5. The method according to any one of claims 1 to 4, wherein the determining the target credit line of the enterprise to be evaluated comprises:
acquiring equipment list information of the enterprise to be evaluated, wherein the equipment list information comprises at least one piece of equipment, and each piece of equipment corresponds to an equipment purchase price, an equipment residual value rate, a second-hand market trading price corresponding to the equipment and an equipment capacity factor;
determining the fixed asset value of the enterprise to be evaluated according to the equipment list information;
acquiring target operation parameter information of the enterprise to be evaluated, wherein the target operation parameter information comprises enterprise tax income, tax payment amount, tax rate condition, enterprise growth condition and operation capacity;
determining the mobile fund amount of the enterprise to be evaluated according to the target operation parameter information;
and determining the target credit line according to the fixed asset value and the mobile fund line.
6. An apparatus for determining an amount of credit, the apparatus comprising: an acquisition unit, a preprocessing unit, a first evaluation unit, a second evaluation unit, a determination unit and a presentation unit, wherein,
the acquisition unit is used for acquiring first enterprise information of an enterprise to be evaluated;
the preprocessing unit is used for preprocessing the first enterprise information to obtain second enterprise information;
the first evaluation unit is used for performing access risk evaluation on the enterprise to be evaluated according to the second enterprise information;
the second evaluation unit is used for performing cross evaluation on the operation risk and the credit risk of the enterprise to be evaluated when the enterprise to be evaluated passes the access risk evaluation;
the determining unit is used for determining the target credit line of the enterprise to be evaluated when the enterprise to be evaluated is subjected to cross evaluation of operation risk and credit risk;
and the display unit is used for displaying the target credit line.
7. The apparatus according to claim 6, wherein in the admission risk assessment of the enterprise to be assessed according to the second enterprise information, the first assessment unit is specifically configured to:
acquiring tax-related sample data of the enterprise to be evaluated;
performing feature extraction on the tax-related sample data to obtain a target feature set;
and performing admission risk assessment on the enterprise to be assessed according to the target feature set and the second enterprise information.
8. The apparatus according to claim 7, wherein in the admission risk assessment of the enterprise to be assessed according to the target feature set and the second enterprise information, the first assessment unit is specifically configured to:
performing feature extraction on the second enterprise information to obtain a reference feature set;
comparing the target characteristic set with the reference characteristic set to obtain a target comparison value;
when the target comparison value is larger than a preset threshold value, performing risk assessment according to the target characteristic set to obtain a first risk assessment value;
performing risk assessment according to the reference feature set to obtain a second risk assessment value;
determining a target weight value pair corresponding to the target comparison value according to a mapping relation between a preset ratio and the weight value pair;
performing weighted operation according to the first risk assessment value, the second risk assessment value and the target weight value to obtain a target risk assessment value;
and when the target risk assessment value is larger than a preset risk assessment value, confirming that the enterprise to be assessed passes the access risk assessment.
9. An electronic device comprising a processor, a memory for storing one or more programs and configured for execution by the processor, the programs comprising instructions for performing the steps in the method of any of claims 1-5.
10. A computer-readable storage medium, characterized in that a computer program for electronic data exchange is stored, wherein the computer program causes a computer to perform the method according to any one of claims 1-5.
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| CN202110499782.8A CN113269629A (en) | 2021-05-08 | 2021-05-08 | Credit limit determining method, electronic equipment and related product |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114219208A (en) * | 2021-11-10 | 2022-03-22 | 中国建设银行股份有限公司 | Credit granting processing method and device for small and micro enterprises and electronic equipment |
| CN115082225A (en) * | 2022-07-21 | 2022-09-20 | 天津金城银行股份有限公司 | Enterprise financing risk assessment method and device |
-
2021
- 2021-05-08 CN CN202110499782.8A patent/CN113269629A/en active Pending
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114219208A (en) * | 2021-11-10 | 2022-03-22 | 中国建设银行股份有限公司 | Credit granting processing method and device for small and micro enterprises and electronic equipment |
| CN115082225A (en) * | 2022-07-21 | 2022-09-20 | 天津金城银行股份有限公司 | Enterprise financing risk assessment method and device |
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