CN118134618A - Credit risk assessment method and device, electronic equipment and storage medium - Google Patents
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Abstract
The application provides a credit risk assessment method, a credit risk assessment device, electronic equipment and a storage medium, wherein the credit risk assessment method comprises the following steps: when a user to be evaluated performs order creation, acquiring a preset risk level of the user to be evaluated; determining whether the preset risk level of the user to be evaluated is a target risk level; if yes, acquiring historical transaction information of the user to be evaluated, and determining the current credit balance of the user to be evaluated according to the transaction amount and the historical transaction information of the current order of the user to be evaluated; generating first credit risk assessment information of the user to be assessed according to the current credit balance of the user to be assessed; wherein the first credit risk assessment information is used for determining a subsequent processing mode of the current order. By the technical scheme provided by the application, the accuracy and efficiency of the credit risk assessment result of the user to be assessed can be improved.
Description
Technical Field
The present application relates to the field of data processing technologies, and in particular, to a credit risk assessment method, apparatus, electronic device, and storage medium.
Background
Credit is a common sales business in an enterprise, and is a business in which sellers and buyers conduct purchase and sales transactions using business credits, and buyers pay on a prescribed date according to an agreement after taking or receiving goods. In essence, credit-based sales, so that if the credit system is not perfect, bad accounts of large accounts receivable can occur, which seriously reduces the fund turnover rate and profit margin of the enterprise, and even leads to breakage of the enterprise fund chain. The key to dealing with this problem is how to manage the necessary credit for the customer, and to adopt an effective credit control strategy to balance the business risk between the expansion of sales and the recovery of receipts as much as possible. At present, the credit risk of the loan user is usually evaluated according to personal information, value data, credit investigation data and the like of the loan user, various information of the loan user is generally evaluated in the prior art, or the credit risk of the loan user is evaluated through manually counting historical transaction data of the loan user and the unit, but the method causes excessive consumption of evaluation resources, low evaluation efficiency and inaccurate evaluation result.
Disclosure of Invention
Accordingly, the present application is directed to a credit risk assessment method, apparatus, electronic device and storage medium, which determine a user to be assessed who needs risk monitoring by presetting a risk level of the user, and determine first credit risk assessment information of the user to be assessed by a current order and historical transaction information of the user to be assessed, so as to improve accuracy and efficiency of a credit risk assessment result of the user to be assessed.
The embodiment of the application provides a credit risk assessment method, which comprises the following steps:
When a user to be evaluated performs order creation, acquiring a preset risk level of the user to be evaluated;
Determining whether the preset risk level of the user to be evaluated is a target risk level;
if yes, acquiring historical transaction information of the user to be evaluated, and determining the current credit balance of the user to be evaluated according to the transaction amount and the historical transaction information of the current order of the user to be evaluated;
Generating first credit risk assessment information of the user to be assessed according to the current credit balance of the user to be assessed; wherein the first credit risk assessment information is used for determining a subsequent processing mode of the current order.
Optionally, the historical transaction information includes: credit limit, credit risk total, and historical credit balance.
Optionally, the determining the current credit balance of the user to be evaluated according to the transaction amount of the current order of the user to be evaluated and the historical transaction information includes:
And determining a difference value obtained by subtracting the historical credit balance in the historical transaction information from the transaction amount of the current order as the current credit balance of the user to be evaluated.
Optionally, the evaluation method further includes:
And generating second credit risk assessment information of the user to be assessed according to the comparison result of the transaction amount of the current order of the user to be assessed and the preset order limit.
Optionally, the evaluation method further includes:
Acquiring all outstanding orders and first order total amount of all orders in a certain historical period of the user to be evaluated, and determining overdue time and order amount of each outstanding order;
determining a second order total of the outstanding orders exceeding the preset time according to the overdue time of each outstanding order;
And generating third credit risk assessment information of the user to be assessed according to the ratio of the second order total sum to the first order total sum and a preset proportion.
Optionally, after generating the first credit risk assessment information of the user to be assessed, the assessment method includes:
And when the current credit balance is recorded as a negative value in the first credit risk assessment information, freezing the current order or prohibiting the current order from being saved.
Optionally, when the credit data is abnormal, the evaluation method further includes:
For each user needing risk monitoring, acquiring historical transaction data of the user from a pre-constructed database;
determining an outstanding order credit value for the user according to sales orders in the historical transaction data of the user;
Determining an outstanding delivery credit value for the user based on the delivery slip in the historical transaction data for the user;
determining an outstanding invoice credit value of the user according to sales invoices in historical transaction data of the user;
determining a pre-payment balance of the user according to the receipt and payment data in the historical transaction data of the user;
updating credit data of the user based on the outstanding order credit value, outstanding delivery credit value, outstanding invoice credit value, and pre-charge balance of the user.
The embodiment of the application also provides a credit risk assessment device, which comprises:
the acquisition module is used for acquiring a preset risk level of the user to be evaluated when the user to be evaluated performs order creation;
The first determining module is used for determining whether the preset risk level of the user to be evaluated is a target risk level;
The second determining module is used for acquiring the historical transaction information of the user to be evaluated when the user to be evaluated is yes, and determining the current credit balance of the user to be evaluated according to the transaction amount of the current order of the user to be evaluated and the historical transaction information;
The first generation module is used for generating first credit risk assessment information of the user to be assessed according to the current credit balance of the user to be assessed; wherein the first credit risk assessment information is used for determining a subsequent processing mode of the current order.
Optionally, the historical transaction information includes: credit limit, credit risk total, and historical credit balance.
Optionally, when the second determining module is configured to determine the current credit balance of the user to be evaluated according to the transaction amount and the historical transaction information of the current order of the user to be evaluated, the second determining module is configured to:
And determining a difference value obtained by subtracting the historical credit balance in the historical transaction information from the transaction amount of the current order as the current credit balance of the user to be evaluated.
Optionally, the evaluation device further includes a second generating module, where the second generating module is configured to:
And generating second credit risk assessment information of the user to be assessed according to the comparison result of the transaction amount of the current order of the user to be assessed and the preset order limit.
Optionally, the evaluation device further includes a third generating module, where the third generating module is configured to:
Acquiring all outstanding orders and first order total amount of all orders in a certain historical period of the user to be evaluated, and determining overdue time and order amount of each outstanding order;
determining a second order total of the outstanding orders exceeding the preset time according to the overdue time of each outstanding order;
And generating third credit risk assessment information of the user to be assessed according to the ratio of the second order total sum to the first order total sum and a preset proportion.
Optionally, the evaluation device further includes a processing module, where the processing module is configured to:
And when the current credit balance is recorded as a negative value in the first credit risk assessment information, freezing the current order or prohibiting the current order from being saved.
Optionally, the evaluation device further includes an update module, where the update module is configured to:
For each user needing risk monitoring, acquiring historical transaction data of the user from a pre-constructed database;
determining an outstanding order credit value for the user according to sales orders in the historical transaction data of the user;
Determining an outstanding delivery credit value for the user based on the delivery slip in the historical transaction data for the user;
determining an outstanding invoice credit value of the user according to sales invoices in historical transaction data of the user;
determining a pre-payment balance of the user according to the receipt and payment data in the historical transaction data of the user;
updating credit data of the user based on the outstanding order credit value, outstanding delivery credit value, outstanding invoice credit value, and pre-charge balance of the user.
The embodiment of the application also provides electronic equipment, which comprises: a processor, a memory and a bus, the memory storing machine-readable instructions executable by the processor, the processor and the memory in communication via the bus when the electronic device is running, the machine-readable instructions when executed by the processor performing the steps of the evaluation method as described above.
The embodiments of the present application also provide a computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the evaluation method as described above.
The embodiment of the application provides a credit risk assessment method, a credit risk assessment device, electronic equipment and a storage medium, wherein the credit risk assessment method comprises the following steps: when a user to be evaluated performs order creation, acquiring a preset risk level of the user to be evaluated; determining whether the preset risk level of the user to be evaluated is a target risk level; if yes, acquiring historical transaction information of the user to be evaluated, and determining the current credit balance of the user to be evaluated according to the transaction amount and the historical transaction information of the current order of the user to be evaluated; generating first credit risk assessment information of the user to be assessed according to the current credit balance of the user to be assessed; wherein the first credit risk assessment information is used for determining a subsequent processing mode of the current order.
In this way, the user to be assessed which needs to be subjected to risk monitoring is determined through the preset risk level of the user, and the first credit risk assessment information of the user to be assessed is determined through the current order and the historical transaction information of the user to be assessed, so that the accuracy and the efficiency of the credit risk assessment result of the user to be assessed are improved.
In order to make the above objects, features and advantages of the present application more comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments will be briefly described below, it being understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and other related drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a credit risk assessment method according to an embodiment of the present application;
FIG. 2 is a flow chart for determining credit balances provided by the present application;
FIG. 3 is a schematic diagram of a credit risk assessment apparatus according to an embodiment of the present application;
FIG. 4 is a second schematic diagram of a credit risk assessment apparatus according to an embodiment of the present application;
Fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. The components of the embodiments of the present application generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the application, as presented in the figures, is not intended to limit the scope of the application, as claimed, but is merely representative of selected embodiments of the application. Based on the embodiments of the present application, every other embodiment obtained by a person skilled in the art without making any inventive effort falls within the scope of protection of the present application.
Credit is a common sales business in an enterprise, and is a business in which sellers and buyers conduct purchase and sales transactions using business credits, and buyers pay on a prescribed date according to an agreement after taking or receiving goods. In essence, credit-based sales, so that if the credit system is not perfect, bad accounts of large accounts receivable can occur, which seriously reduces the fund turnover rate and profit margin of the enterprise, and even leads to breakage of the enterprise fund chain. The key to dealing with this problem is how to manage the necessary credit for the customer, and to adopt an effective credit control strategy to balance the business risk between the expansion of sales and the recovery of receipts as much as possible. At present, the credit risk of the loan user is usually evaluated according to personal information, value data, credit investigation data and the like of the loan user, various information of the loan user is generally evaluated in the prior art, or the credit risk of the loan user is evaluated through manually counting historical transaction data of the loan user and the unit, but the method causes excessive consumption of evaluation resources, low evaluation efficiency and inaccurate evaluation result.
Based on the above, the embodiment of the application provides a credit risk assessment method, a device, electronic equipment and a storage medium, which are used for determining a user to be assessed which needs risk monitoring through presetting a risk level of the user, and determining first credit risk assessment information of the user to be assessed through a current order and historical transaction information of the user to be assessed, so that accuracy and efficiency of a credit risk assessment result of the user to be assessed are improved.
Referring to fig. 1, fig. 1 is a flowchart of a credit risk assessment method according to an embodiment of the application. As shown in fig. 1, an evaluation method provided by an embodiment of the present application includes:
S101, when a user to be evaluated performs order creation, acquiring a preset risk level of the user to be evaluated.
Here, a risk level is preset for each user in advance, so that different risk assessment policies can be performed for different users according to the preset risk levels of the different users.
By way of example, the preset risk level may include three levels, high, medium, and low, such as determining the preset risk level of the internal customer as low risk and the preset risk level of the external customer as high risk or medium risk. Wherein, the specific setting of high risk or medium risk can be set autonomously according to the company operation condition of the external clients. The internal clients specifically refer to clients of different companies under one group.
S102, determining whether the preset risk level of the user to be evaluated is a target risk level.
Here, whether the target risk level is determined according to the preset risk level of the user to be evaluated. For example, assuming that the target risk levels are medium risk and high risk, when the preset risk level of the user to be evaluated is determined to be low risk, the preset risk level of the user to be evaluated is determined not to be the target risk level, and when the preset risk level of the user to be evaluated is determined to be medium risk or high risk, the preset risk level of the user to be evaluated is determined to be the target risk level.
For clients with low risk of the preset risk level, credit risk assessment can be omitted so as to ensure normal transaction.
And S103, when yes, acquiring historical transaction information of the user to be evaluated, and determining the current credit balance of the user to be evaluated according to the transaction amount and the historical transaction information of the current order of the user to be evaluated.
Here, the historical transaction information of the user to be evaluated includes: credit limit, credit risk total, and historical credit balance.
For example, referring to FIG. 2, FIG. 2 is a flow chart for determining credit balances provided by the present application. As shown in fig. 2, the credit limit, also referred to as the total credit risk, is the used credit limit, which is the sum of the receivables and the current outstanding sales value minus the amount after pre-collection. For example, the sum should be received: 0 yuan, sales value: 0 yuan; receiving customer payment, i.e. special to and from liabilities: 20,000 yuan, i.e. credit risk sum = receivable sum + sales value-special to-and-fro liability (pre-payment) = -20000 yuan.
The credit balance is determined from a credit limit and a credit risk total, in particular credit balance = credit limit-credit risk total. As shown in fig. 2, the credit limit is set to 0 yuan, credit risk total: 20,000 yuan, the credit balance before the sales order is generated is 20000 yuan.
The sales value is determined from the outstanding order credit value, the outstanding delivery credit value, the outstanding invoice credit value, specifically sales value = outstanding order credit value + outstanding delivery credit value + outstanding invoice credit value. As shown in fig. 2, the outstanding order credit value = sales order value for all outstanding deliveries (sales order number 10 tons, unit price 1,000 yuan, amount 10,000 yuan), the outstanding delivery credit value = delivery order value for all outstanding invoices (delivery number 8 tons, unit price 1,000 yuan, amount 8,000 yuan), at which point the outstanding order credit value remains 2,000 yuan; outstanding invoice credit value = all outstanding invoice values (invoice number 8 tons, unit price 1,000 yuan, amount 8,000 yuan), at which point the outstanding order credit value still remains 2,000 yuan, outstanding delivery credit value 0 yuan.
Continuing to refer to FIG. 2, after the sales invoice is posted to finance, the credit value of the outstanding invoice is updated to the receivables, and the amount is 8,000 yuan; after clearing and pre-collecting accounts, clearing accounts receivable, and keeping the customer pre-collecting accounts for the remaining 12,000 yuan; so final credit balance = pre-charge-outstanding order credit value = 12000-2000 = 10000 yuan.
In one embodiment of the present application, the determining the current credit balance of the user to be evaluated according to the transaction amount and the historical transaction information of the current order of the user to be evaluated includes: and determining a difference value obtained by subtracting the historical credit balance in the historical transaction information from the transaction amount of the current order as the current credit balance of the user to be evaluated.
Thus, the current credit balance of the user to be evaluated after creating the order can be determined according to the transaction amount and the historical credit balance of the current order of the user to be evaluated.
S104, generating first credit risk assessment information of the user to be assessed according to the current credit balance of the user to be assessed.
Here, the first credit risk assessment information is used to determine a subsequent processing style of the current order.
For example, when the current credit balance is recorded as a negative value in the first credit risk assessment information, the current order is frozen or the current order is forbidden to be saved.
Here, specifically, whether the current order is frozen or the current order is forbidden to be saved may be determined according to the preset risk level of the user to be evaluated. Freezing a current order of the user to be evaluated, for example, when the preset risk level of the user to be evaluated is risk and the current credit balance is recorded as a negative value in the first credit risk evaluation information; and when the preset risk level of the user to be evaluated is high risk, and the current credit balance is recorded as a negative value in the first credit risk evaluation information, prohibiting the current order of the user to be evaluated from being saved.
It should be noted that, when the credit risk assessment is performed on the user to be assessed according to the assessment method in steps S101 to S104, the assessment may be performed in real time, or an validity period may be set, and the assessment may be performed only in the validity period.
In one embodiment of the present application, the evaluation method further includes: and generating second credit risk assessment information of the user to be assessed according to the comparison result of the transaction amount of the current order of the user to be assessed and the preset order limit.
Here, the second credit risk assessment information may also be used to determine a subsequent manner of processing of the current order. For example, assuming that the second credit risk assessment information records that the current order transaction amount of the user to be assessed exceeds a preset order limit, the current order is frozen or the current order is prohibited from being saved.
In another embodiment of the present application, the evaluation method further includes: acquiring all outstanding orders and first order total amount of all orders in a certain historical period of the user to be evaluated, and determining overdue time and order amount of each outstanding order; determining a second order total of the outstanding orders exceeding the preset time according to the overdue time of each outstanding order; and generating third credit risk assessment information of the user to be assessed according to the ratio of the second order total sum to the first order total sum and a preset proportion.
Here, the third credit risk assessment information may also be used to determine a subsequent processing manner of the current order, that is, to freeze the current order or prohibit the current order from being saved.
For example, referring to table 1, table 1 shows all outstanding orders of the user to be evaluated within a certain history period.
Table 1:
| Order number | Amount of money | Current date | Invoice date | Estimated date of collection (reference day) | Expiration of the delay period |
| Order 1 | 100 | 2022.09.09 | 2022.09.08 | 2022.09.08 | 1 |
| Order 2 | 100 | 2022.09.09 | 2022.09.07 | 2022.09.07 | 2 |
| Order 3 | 200 | 2022.09.09 | 2022.09.06 | 2022.09.06 | 3 |
As shown in table 1, assuming that the preset proportion is 74%, that is, the proportion of the order 3 (the amount 300) to all the outstanding orders (the amount 400) is 75% in the outstanding order 2 whose expiration delay days exceed 1 day, and the proportion exceeds 74% set in the configuration, the current order of the user to be evaluated is frozen or the current order preservation is prohibited. However, if the preset ratio is assumed to be 75%, that is, the ratio of the total amount of the second order to the total amount of the first order is equal to the preset ratio, the system will not report errors, and the order can be successfully created.
In another embodiment provided by the present application, when abnormality occurs in credit data, the evaluation method further includes: for each user needing risk monitoring, acquiring historical transaction data of the user from a pre-constructed database; determining an outstanding order credit value for the user according to sales orders in the historical transaction data of the user; determining an outstanding delivery credit value for the user based on the delivery slip in the historical transaction data for the user; determining an outstanding invoice credit value of the user according to sales invoices in historical transaction data of the user; determining a pre-payment balance of the user according to the receipt and payment data in the historical transaction data of the user; updating credit data of the user based on the outstanding order credit value, outstanding delivery credit value, outstanding invoice credit value, and pre-charge balance of the user.
The method comprises the steps of updating credit data, wherein when the credit data of any user is found to be abnormal, the credit data can be updated according to historical transaction data of the user so as to avoid influencing the creation of a follow-up order.
Here, in determining the outstanding order credit value for the user, a determination may be made based on the sales order delivery processing status in the sales order in the user's historical transaction data; when determining the outstanding delivery credit value of the user, determining according to the invoice status of the delivery bill in the historical transaction data of the user; in determining the sales invoice for the user, the determination may be based on the invoice posting status in the sales invoice in the user's historical transaction data.
It should be noted that, when determining the subsequent processing manner of the current order of the user to be evaluated, the determination may be performed in combination with at least one of the first credit risk assessment information, the second credit risk assessment information, and the third credit risk assessment information.
The embodiment of the application provides a credit risk assessment method, which comprises the following steps: when a user to be evaluated performs order creation, acquiring a preset risk level of the user to be evaluated; determining whether the preset risk level of the user to be evaluated is a target risk level; if yes, acquiring historical transaction information of the user to be evaluated, and determining the current credit balance of the user to be evaluated according to the transaction amount and the historical transaction information of the current order of the user to be evaluated; generating first credit risk assessment information of the user to be assessed according to the current credit balance of the user to be assessed; wherein the first credit risk assessment information is used for determining a subsequent processing mode of the current order.
In this way, the user to be assessed which needs to be subjected to risk monitoring is determined through the preset risk level of the user, and the first credit risk assessment information of the user to be assessed is determined through the current order and the historical transaction information of the user to be assessed, so that the accuracy and the efficiency of the credit risk assessment result of the user to be assessed are improved.
Referring to fig. 3 and 4, fig. 3 is a schematic structural diagram of a credit risk assessment device according to an embodiment of the present application, and fig. 4 is a schematic structural diagram of a credit risk assessment device according to an embodiment of the present application. As shown in fig. 3, the evaluation apparatus 300 includes:
an obtaining module 310, configured to obtain a preset risk level of a user to be evaluated when the user to be evaluated performs order creation;
A first determining module 320, configured to determine whether a preset risk level of the user to be evaluated is a target risk level;
A second determining module 330, configured to obtain historical transaction information of the user to be evaluated, and determine a current credit balance of the user to be evaluated according to the transaction amount and the historical transaction information of the current order of the user to be evaluated when the user to be evaluated is yes;
A first generation module 340, configured to generate first credit risk assessment information of the user to be assessed according to the current credit balance of the user to be assessed; wherein the first credit risk assessment information is used for determining a subsequent processing mode of the current order.
Optionally, the historical transaction information includes: credit limit, credit risk total, and historical credit 5 credit balance.
Optionally, when the second determining module 330 is configured to determine the current credit balance of the user to be evaluated according to the transaction amount of the current order of the user to be evaluated and the historical transaction information, the second determining module 330 is configured to:
And determining a difference value obtained by subtracting 0 from the historical credit balance in the historical transaction information and the transaction amount of the current order as the current credit balance of the user to be evaluated.
Optionally, as shown in fig. 4, the evaluation apparatus 300 further includes a second generating module 350, where the second generating module 350 is configured to:
And generating second credit risk assessment information of the user to be assessed according to the comparison result of the transaction amount of the current order of the user to be assessed and the preset order limit.
5 Optionally, the evaluation apparatus 300 further includes a third generating module 360, and the third generating module 360 is configured to:
Acquiring all outstanding orders and first order total amount of all orders in a certain historical period of the user to be evaluated, and determining overdue time and order amount of each outstanding order;
determining a second 0 order total of the outstanding orders exceeding the preset time according to the overdue time of each outstanding order;
And generating third credit risk assessment information of the user to be assessed according to the ratio of the second order total sum to the first order total sum and a preset proportion.
Optionally, the evaluation device 300 further comprises a processing module 370, the processing module 370 being configured to:
And when the current credit balance is recorded as a negative value in the first credit risk assessment information, freezing the current order or prohibiting the current order from being saved.
Optionally, the evaluation device 300 further includes an update module 380, where the update module 380 is configured to:
For each user needing risk monitoring, acquiring historical transaction data of the user from a pre-constructed database;
determining an outstanding order credit value for the user according to sales orders in the historical transaction data of the user;
Determining an outstanding delivery credit value for the user based on the delivery slip in the historical transaction data for the user;
determining an outstanding invoice credit value of the user according to sales invoices in historical transaction data of the user;
determining a pre-payment balance of the user according to the receipt and payment data in the historical transaction data of the user;
updating credit data of the user based on the outstanding order credit value, outstanding delivery credit value, outstanding invoice credit value, and pre-charge balance of the user.
Referring to fig. 5, fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the application. As shown in fig. 5, the electronic device 500 includes a processor 510, a memory 520, and a bus 530.
The memory 520 stores machine-readable instructions executable by the processor 510, and when the electronic device 500 is running, the processor 510 communicates with the memory 520 through the bus 530, and when the machine-readable instructions are executed by the processor 510, the steps in the method embodiments shown in fig. 1 and fig. 2 can be executed, and the specific implementation can be referred to the method embodiments and will not be described herein.
The embodiment of the present application further provides a computer readable storage medium, where a computer program is stored, and when the computer program is executed by a processor, the steps in the method embodiments shown in fig. 1 and fig. 2 may be executed, and a specific implementation manner may refer to the method embodiment and will not be described herein.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, and are not repeated herein.
In the several embodiments provided by the present application, it should be understood that the disclosed systems, devices, and methods may be implemented in other manners. The above-described apparatus embodiments are merely illustrative, for example, the division of the units is merely a logical function division, and there may be other manners of division in actual implementation, and for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some communication interface, device or unit indirect coupling or communication connection, which may be in electrical, mechanical or other form.
The units described as separate units may or may not be physically separate, and units shown 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 may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a non-volatile computer readable storage medium executable by a processor. Based on this understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
Finally, it should be noted that: the above examples are only specific embodiments of the present application, and are not intended to limit the scope of the present application, but it should be understood by those skilled in the art that the present application is not limited thereto, and that the present application is described in detail with reference to the foregoing examples: any person skilled in the art may modify or easily conceive of the technical solution described in the foregoing embodiments, or perform equivalent substitution of some of the technical features, while remaining within the technical scope of the present disclosure; such modifications, changes or substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present application, and are intended to be included in the scope of the present application. Therefore, the protection scope of the application is subject to the protection scope of the claims.
Claims (10)
1. A method of credit risk assessment, the method comprising:
When a user to be evaluated performs order creation, acquiring a preset risk level of the user to be evaluated;
Determining whether the preset risk level of the user to be evaluated is a target risk level;
if yes, acquiring historical transaction information of the user to be evaluated, and determining the current credit balance of the user to be evaluated according to the transaction amount and the historical transaction information of the current order of the user to be evaluated;
Generating first credit risk assessment information of the user to be assessed according to the current credit balance of the user to be assessed; wherein the first credit risk assessment information is used for determining a subsequent processing mode of the current order.
2. The assessment method according to claim 1, wherein the historical transaction information comprises: credit limit, credit risk total, and historical credit balance.
3. The method of claim 2, wherein said determining the current credit balance of the user under evaluation based on the transaction amount of the current order of the user under evaluation and historical transaction information comprises:
And determining a difference value obtained by subtracting the historical credit balance in the historical transaction information from the transaction amount of the current order as the current credit balance of the user to be evaluated.
4. The evaluation method according to claim 1, characterized in that the evaluation method further comprises:
And generating second credit risk assessment information of the user to be assessed according to the comparison result of the transaction amount of the current order of the user to be assessed and the preset order limit.
5. The evaluation method according to claim 1, characterized in that the evaluation method further comprises:
Acquiring all outstanding orders and first order total amount of all orders in a certain historical period of the user to be evaluated, and determining overdue time and order amount of each outstanding order;
determining a second order total of the outstanding orders exceeding the preset time according to the overdue time of each outstanding order;
And generating third credit risk assessment information of the user to be assessed according to the ratio of the second order total sum to the first order total sum and a preset proportion.
6. The assessment method according to claim 1, wherein after generating the first credit risk assessment information of the user under assessment, the assessment method comprises:
And when the current credit balance is recorded as a negative value in the first credit risk assessment information, freezing the current order or prohibiting the current order from being saved.
7. The evaluation method according to claim 1, wherein when abnormality occurs in the credit data, the evaluation method further comprises:
For each user needing risk monitoring, acquiring historical transaction data of the user from a pre-constructed database;
determining an outstanding order credit value for the user according to sales orders in the historical transaction data of the user;
Determining an outstanding delivery credit value for the user based on the delivery slip in the historical transaction data for the user;
determining an outstanding invoice credit value of the user according to sales invoices in historical transaction data of the user;
determining a pre-payment balance of the user according to the receipt and payment data in the historical transaction data of the user;
updating credit data of the user based on the outstanding order credit value, outstanding delivery credit value, outstanding invoice credit value, and pre-charge balance of the user.
8. An assessment device for credit risk, characterized in that the assessment device comprises:
the acquisition module is used for acquiring a preset risk level of the user to be evaluated when the user to be evaluated performs order creation;
The first determining module is used for determining whether the preset risk level of the user to be evaluated is a target risk level;
The second determining module is used for acquiring the historical transaction information of the user to be evaluated when the user to be evaluated is yes, and determining the current credit balance of the user to be evaluated according to the transaction amount of the current order of the user to be evaluated and the historical transaction information;
The first generation module is used for generating first credit risk assessment information of the user to be assessed according to the current credit balance of the user to be assessed; wherein the first credit risk assessment information is used for determining a subsequent processing mode of the current order.
9. An electronic device, comprising: a processor, a memory and a bus, said memory storing machine readable instructions executable by said processor, said processor and said memory communicating via said bus when the electronic device is running, said machine readable instructions when executed by said processor performing the steps of the evaluation method according to any one of claims 1 to 7.
10. A computer-readable storage medium, characterized in that it has stored thereon a computer program which, when executed by a processor, performs the steps of the evaluation method according to any one of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211541218.9A CN118134618A (en) | 2022-12-02 | 2022-12-02 | Credit risk assessment method and device, electronic equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211541218.9A CN118134618A (en) | 2022-12-02 | 2022-12-02 | Credit risk assessment method and device, electronic equipment and storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN118134618A true CN118134618A (en) | 2024-06-04 |
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ID=91241110
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211541218.9A Pending CN118134618A (en) | 2022-12-02 | 2022-12-02 | Credit risk assessment method and device, electronic equipment and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN118134618A (en) |
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2022
- 2022-12-02 CN CN202211541218.9A patent/CN118134618A/en active Pending
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