CN112990907A - Method and device for small credit granting based on bulk commodities and electronic equipment - Google Patents
Method and device for small credit granting based on bulk commodities and electronic equipment Download PDFInfo
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Abstract
The utility model provides a method of small amount credit based on bulk commodity carries out, carry out small amount credit evaluation to bulk commodity data that bulk commodity held the user through bulk commodity transaction platform, for user configuration credit amount and repayment plan according to the assessment result, use the bulk commodity that the user held in bulk commodity transaction platform to provide small amount credit for applying for user's operation for the endorsement of credit, can shorten the flow when carrying out the loan under lower risk, improve the efficiency of borrowing, then through monitoring the state of applying for user's bulk commodity data, based on the more repayment plan of state of bulk commodity data makes whole borrowing, repayment process be in monitoring range, can in time adapt to the fluctuation of bulk commodity.
Description
Technical Field
The application relates to the field of internet finance, in particular to a method and a device for petty credit granting based on bulk commodities and electronic equipment.
Background
With the development of internet finance, it gradually enters the personal life field to offer a certain amount of borrowing for a user based on the credit level of the user, which provides the borrowing by taking the credit of the user as an endorsement, however, with the occurrence of cheating, it indicates that there is still a great risk in issuing the borrowing for the user by taking the credit as the endorsement.
In the field of bulk commodity transaction, a bulk commodity online transaction platform is provided with registered users and bulk commodities held by the registered users, so that a low-risk credit endorsement is formed, when a bulk commodity holder needs to perform financing, the bulk commodity online transaction platform performs financing and fund obtaining in a tray mode, namely, a merchant acquires a commodity right and provides a certain fund to an original holder of the bulk commodity, and the holder carries out redemption in a mode of withdrawing the money and the goods at the later stage.
However, in practice, the bulk commodity holder does not need a large amount of money each time, that is, the bulk commodity holder may only need to borrow a small amount of money when the bulk commodity holder wishes to borrow a tray, and the existing bulk commodity online transaction platform does not meet the small amount of money borrowing requirement of the bulk commodity holder.
Disclosure of Invention
The embodiment of the specification provides a method, a device and electronic equipment for small credit granting based on bulk commodities, and aims to solve the problem that in the prior art, the borrowing efficiency of bulk commodity holders in a bulk commodity transaction platform is low.
The application provides a method for small credit granting based on bulk commodities, which comprises the following steps:
carrying out petty credit granting evaluation on the application user based on the bulk commodity data of the application user;
configuring a credit line and a repayment plan for the application user according to the evaluation result;
providing a small credit for the operation of the application user by taking a bulk commodity held by the application user in a bulk commodity trading platform as a credit endorsement, wherein the small credit is smaller than the market price of the bulk commodity;
monitoring the state of the bulk commodity data of the application user, and updating a repayment plan based on the state of the bulk commodity data.
Optionally, the monitoring a state of the bulk goods data of the application user, and updating the repayment plan based on the state of the bulk goods data includes:
monitoring the state of the bulk commodity data of the applying user in a repayment period of the repayment plan, if the bulk commodity data changes, adjusting the repayment plan based on the change of the bulk commodity data, and providing the adjusted repayment plan for the applying user.
Optionally, the monitoring the status of the bulk goods data of the application user includes:
monitoring a price of an associated item associated with the block of items;
predicting the state of the bulk commodity data based on the association degree of the associated commodity and the bulk commodity and the price of the associated commodity.
Optionally, the method further comprises:
collecting price fluctuations of a plurality of commodities in a first period and price fluctuations of the bulk commodity in a second period as training samples, wherein the first period is earlier than the second period;
setting labels for the training samples according to consistency of price lag;
training a bulk commodity price prediction model by using the training samples and the labels;
the predicting the state of the bulk commodity data based on the association degree of the associated commodity with the bulk commodity and the price of the associated commodity comprises:
and predicting the price of the bulk commodity by using the built bulk commodity price prediction model.
Optionally, the predicting the price of the bulk commodity by using the built bulk commodity price prediction model includes:
predicting a price of the block of merchandise over a future time period;
the configuring credit line and repayment plan for the application user according to the evaluation result comprises the following steps:
and configuring a credit line and a repayment plan for the application user according to the qualified price and the future time period.
Optionally, the associated merchandise includes complements and substitutes.
Optionally, the method further comprises:
the state of the bulk commodity data is warned, comprising:
and if the change of the data of the bulk commodity exceeds a preset range, warning the transaction platform of the bulk commodity, so that the transaction platform of the bulk commodity reduces the business range of the application user for performing transaction by using the bulk commodity.
Optionally, the monitoring the status of the bulk goods data of the application user further includes:
and monitoring the transaction progress of the bulk goods of the application user, and updating a repayment plan based on the transaction progress.
Optionally, the method further comprises:
and accepting an exhibition request of a user, and updating the repayment plan based on the exhibition request.
The application also provides a device based on the bulk commodity carries out petty credit granting, includes:
the evaluation module is used for carrying out petty credit evaluation on the application user based on the bulk commodity data of the application user;
the configuration module configures credit line and repayment plan for the application user according to the evaluation result;
the dynamic support module is used for providing small credit for dynamic support operation of the application user by taking a bulk commodity held by the application user in a bulk commodity trading platform as a credit endorsement, wherein the small credit is smaller than the market price of the bulk commodity;
the configuration module monitors the state of the bulk commodity data of the application user and updates the repayment plan based on the state of the bulk commodity data.
Optionally, the monitoring a state of the bulk goods data of the application user, and updating the repayment plan based on the state of the bulk goods data includes:
monitoring the state of the bulk commodity data of the applying user in a repayment period of the repayment plan, if the bulk commodity data changes, adjusting the repayment plan based on the change of the bulk commodity data, and providing the adjusted repayment plan for the applying user.
Optionally, the monitoring the status of the bulk goods data of the application user includes:
monitoring a price of an associated item associated with the block of items;
predicting the state of the bulk commodity data based on the association degree of the associated commodity and the bulk commodity and the price of the associated commodity.
Optionally, the configuration module is further configured to:
collecting price fluctuations of a plurality of commodities in a first period and price fluctuations of the bulk commodity in a second period as training samples, wherein the first period is earlier than the second period;
setting labels for the training samples according to consistency of price lag;
training a bulk commodity price prediction model by using the training samples and the labels;
the predicting the state of the bulk commodity data based on the association degree of the associated commodity with the bulk commodity and the price of the associated commodity comprises:
and predicting the price of the bulk commodity by using the built bulk commodity price prediction model.
Optionally, the predicting the price of the bulk commodity by using the built bulk commodity price prediction model includes:
predicting a price of the block of merchandise over a future time period;
the configuring credit line and repayment plan for the application user according to the evaluation result comprises the following steps:
and configuring a credit line and a repayment plan for the application user according to the qualified price and the future time period.
Optionally, the associated merchandise includes complements and substitutes.
Optionally, the configuration module is further configured to:
the state of the bulk commodity data is warned, comprising:
and if the change of the data of the bulk commodity exceeds a preset range, warning the transaction platform of the bulk commodity, so that the transaction platform of the bulk commodity reduces the business range of the application user for performing transaction by using the bulk commodity.
Optionally, the monitoring the status of the bulk goods data of the application user further includes:
and monitoring the transaction progress of the bulk goods of the application user, and updating a repayment plan based on the transaction progress.
Optionally, the configuration module is further configured to:
and accepting an exhibition request of a user, and updating the repayment plan based on the exhibition request.
The present application further provides an electronic device, wherein the electronic device includes:
a processor; and the number of the first and second groups,
a memory storing computer-executable instructions that, when executed, cause the processor to perform any of the methods described above.
The present application also provides a computer readable storage medium, wherein the computer readable storage medium stores one or more programs which, when executed by a processor, implement any of the methods described above.
According to various technical schemes, small credit granting evaluation is carried out on large commodity data of a large commodity holding user through a large commodity transaction platform, a credit amount and a repayment plan are configured for the user according to an evaluation result, small credit is provided for the payment operation of the application user by taking the large commodity held by the user in the large commodity transaction platform as a credit endorsement, the process can be shortened while the loan is carried out at a lower risk, the loan efficiency is improved, then the repayment plan is updated based on the state of the large commodity data by monitoring the state of the large commodity data of the application user, the whole loan and repayment process is in a monitoring range, and the fluctuation of the large commodity can be adapted in time.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:
FIG. 1 is a schematic structural diagram of a system for petty credit granting based on bulk goods according to the present disclosure;
FIG. 2 is a schematic diagram illustrating a method for petty credit based on a bulk good according to an embodiment of the present disclosure;
FIG. 3 is a schematic diagram illustrating an apparatus for petty credit based on a bulk good according to an embodiment of the present disclosure;
fig. 4 is a schematic structural diagram of an electronic device provided in an embodiment of the present disclosure;
fig. 5 is a schematic diagram of a computer-readable medium provided in an embodiment of the present specification.
Detailed Description
Exemplary embodiments of the present invention will now be described more fully with reference to the accompanying drawings. The exemplary embodiments, however, may be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these exemplary embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of the invention to those skilled in the art. The same reference numerals denote the same or similar elements, components, or parts in the drawings, and thus their repetitive description will be omitted.
Features, structures, characteristics or other details described in a particular embodiment do not preclude the fact that the features, structures, characteristics or other details may be combined in a suitable manner in one or more other embodiments in accordance with the technical idea of the invention.
In describing particular embodiments, the present invention has been described with reference to features, structures, characteristics or other details that are within the purview of one skilled in the art to provide a thorough understanding of the embodiments. One skilled in the relevant art will recognize, however, that the invention may be practiced without one or more of the specific features, structures, characteristics, or other details.
The flow charts shown in the drawings are merely illustrative and do not necessarily include all of the contents and operations/steps, nor do they necessarily have to be performed in the order described. For example, some operations/steps may be decomposed, and some operations/steps may be combined or partially combined, so that the actual execution sequence may be changed according to the actual situation.
The block diagrams shown in the figures are functional entities only and do not necessarily correspond to physically separate entities. I.e. these functional entities may be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor means and/or microcontroller means.
The term "and/or" and/or "includes all combinations of any one or more of the associated listed items.
Fig. 1 is a schematic structural diagram of a system for petty credit granting based on a large commodity provided in this specification, where the system may include:
the database 11 stores the data related to the credit and financing application, the financing amount management, the financing repayment and the like of the bulk commodity online transaction platform in the process of developing the supply chain financing service.
The trading platform 12 is a bulk commodity online trading platform, registered users are arranged in the trading platform, the users trade through the trading platform, the trading platform obtains data generated by user behaviors, bulk commodity data held by the users are obtained, and the bulk commodity data are stored in a database so as to be convenient for subsequent online trading.
The credit system 13 has a credit account management device, and performs various types of service interaction and data interaction through an authentication interface, a payment structure, a repayment interface and an exhibition interface with the transaction platform 12, so as to perform small credit based on bulk goods held by a user.
The authentication interface can be used for receiving a supply chain financing service application initiated by a customer on a bulk commodity online transaction platform and granting credit to the qualified customer; the payment interface can receive a financing purchase application initiated by a credit client on a bulk commodity online transaction platform, verify whether the client can carry out financing purchase through credit, authorize the credit meeting the requirements, update the credit line, generate a repayment plan by means of a credit repayment calculation model, store the credit use related data and the repayment plan into a database, and return a processing result to a front-end system; the repayment interface receives a redemption application initiated by a customer on the bulk commodity online transaction platform, calculates the corresponding credit repayment amount according to the credit using related data, performs repayment, updates the credit line of the corresponding credit account, regenerates a repayment plan by using a credit repayment calculation model, and records the performance condition and the new repayment plan into the database; and the exhibition period interface receives a request of customer redemption or contract exhibition on a bulk commodity online transaction platform, calculates the default risk of the customer, updates the repayment plan and feeds back the risk warning information to the front-end system.
The system converts links such as customer qualification examination, purchase payment, redemption, contract exhibition period and the like in financing business on a bulk commodity e-commerce online transaction platform into operations such as authentication, payment, repayment, exhibition period and the like on the basis of a big data and risk management model.
The bulk goods can be bulk spot goods, and if the user holding the bulk spot goods needs to change cash (cash), the user needs to be served by the transaction platform, so that the probability that the user holding the bulk spot goods overdues the loan granted with the small amount or does not repay the loan is low.
In a specific application scenario, the credit granting method may include: receiving credit financing and payment, repayment and exhibition applications initiated by a user on a bulk commodity transaction platform, responding to a request through evaluation, and opening a credit account for the user meeting the credit financing requirements to complete credit granting; when the user uses the credit fund payment, the credit account management device evaluates whether the user meets the credit fund payment condition, if so, the credit account management device provides payment service, updates the credit line of the credit account, records the related information of the use of the credit into a database, calculates the repayment date and the repayment amount and generates a repayment plan; in the repayment process, the credit account management device monitors user risks, updates the repayment plan to adapt to environmental changes, and feeds back risk warning information in real time. And if the monitored user risk is not abnormal, the credit account management device can receive an exhibition request of the front-end user through the exhibition interface and generate an exhibition repayment plan.
The credit system 13 may further have a data extraction device for sharing data with the bulk commodity online transaction platform, acquiring various data for user risk control, and storing the data in a database, wherein the credit account management device is used according to the requirements of various models.
A convenient and efficient risk management system is established for the bulk commodity online transaction platform by setting a credit system, so that the small loan requirement ubiquitous in the bulk commodity spot field can be met.
The system performs small credit granting evaluation on the bulk commodity data of a bulk commodity holding user in a bulk commodity transaction platform, configures a credit limit and a repayment plan for the user according to an evaluation result, provides small credit for the mobile payment operation of the application user by taking the bulk commodity held by the application user in the bulk commodity transaction platform as a credit endorsement, can borrow at a lower risk and shorten the flow, improves the small credit borrowing efficiency of the user, updates the repayment plan based on the state of the bulk commodity data by monitoring the state of the bulk commodity data, enables the whole borrowing and repayment process to be in a monitoring range, and can adapt to the fluctuation of the bulk commodity in time.
Fig. 2 is a schematic diagram illustrating a method for petty credit based on a bulk commodity according to an embodiment of the present disclosure, where the method may include:
s201: and carrying out small credit granting evaluation on the application user based on the bulk commodity data of the application user.
In the embodiment of the present specification, the application user is a user holding a large quantity of commodities in a large quantity of commodities online trading platform, in order to meet the small quantity borrowing requirement, a small quantity borrowing service may be added to the large quantity of commodities online trading platform, and a system providing such a service may be referred to as a credit system in fig. 1.
The bulk commodity online transaction platform can record the account opening data and the authentication information of the user, including a business certificate, a tax registration certificate, an organization certificate, an invoicing data, legal information, an authorization entrustment book and a payment mode, and judges whether the user has complete transaction qualification or not according to the integrity of the information.
Therefore, when a user holding a large commodity in the large commodity online transaction platform initiates an application, the system can receive the request and perform small credit assessment on the application user based on the large commodity data of the application user.
Therefore, the performing of the petty credit assessment on the application user based on the bulk commodity data of the application user may include:
receiving an application initiated by a user holding a bulk commodity in a bulk commodity online transaction platform;
and carrying out small credit granting evaluation on the application user based on the bulk commodity data of the application user. The risk is lower by granting credit to the user for the bulk goods held by the user on the platform.
In this embodiment of the present specification, the performing of the petty credit assessment on the application user may include:
and evaluating the credit line of the application user.
In an embodiment implemented in this specification, the method may further include: and carrying out pre-authorization evaluation on the user, and creating a credit account for the user passing the evaluation. The precondition that pre-authorization can be performed is as follows: the credit account with the approved status, the credit remaining available amount >0 and the contract (such as the contract of gold resource, the non-guaranteed contract and the on-line payment contract) meeting the pre-authorization requirement.
Specifically, the pre-authorization evaluation condition may be: whether it is a business to authenticate members, whether the authentication data is complete (such as business license, tax registration certificate, etc.), whether the transaction frequency exceeds a threshold (such as more than 10 transactions in a half year), and default.
In the embodiment of the present specification, the reference amount may be Ra ═ Min (q1 r1, Tm × d × s × f, Fm, Am), where q1 is unbundled traffic, r1 is performance capability r1 ∈ (0, 1), Tm is traffic in one traffic cycle, d is customer reputation, s is customer risk coefficient, f is dynamic adjustment factor, and Am is credit available amount.
In the embodiment of the specification, when the user requests to perform action, checking whether the credit account information of the user and the contract information of purchasing spot resources allow the use of the credit, wherein the preset condition of the authorization is as follows: the credit available limit Am is greater than 0, the credit use amount Req is greater than the minimum credit use limit MinM; an authorization condition expression: Am-Req > 0.
Wherein the credit is available
(q1 represents outstanding traffic, p1 represents the proportion of outstanding credit traffic, Ra represents the credit amount, tmi represents the used credit amount, and rmi represents the paid credit amount).
The authorized amount calculation formula is as follows: the authorized amount rm is the credit available amount Am.
After payment of the payment (move) using the credit line, the available balance of the credit account is updated, i.e., Am-rm.
In the embodiment of the specification, service fees and default funds are also counted, and functions of calculating credit service fees and default funds are provided, wherein the credit repayment amount T is the credit amount rm + the service fees C + the default funds Pm. If the actual using days N of the credit is less than or equal to the using period N of the credit, the service fee is given
If the actual number of days N > the service life N of the credit
rm is paidAnd ri is the service rate. And the default gold Pm is tm p2, wherein tm is the used credit amount, and p2 is the default gold fine proportion).
In the embodiment of the description, the credit limit of the user is calculated in real time by combining the transaction qualification, the unfinished business volume, the deal history record and the performance integrity of the user in the spot transaction platform, and the user applying for the small credit is assessed.
In this embodiment of the present specification, the performing a petty credit assessment on the application user may further include: and evaluating the repayment period of the application user.
Thus, the credit limit and the corresponding repayment plan can be generated for the application user according to the evaluation result.
S202: and configuring a credit line and a repayment plan for the application user according to the evaluation result.
In an embodiment of the present specification, the method may further include:
collecting price fluctuations of a plurality of commodities in a first period and price fluctuations of the bulk commodity in a second period as training samples, wherein the first period is earlier than the second period;
setting labels for the training samples according to consistency of price lag;
training a bulk commodity price prediction model by using the training samples and the labels;
the configuring of the credit line and the repayment plan for the application user according to the evaluation result may include:
forecasting price fluctuation of the bulk commodity in a future period by using the constructed bulk commodity price forecasting model;
configuring credit limit for the application user;
and generating a repayment plan based on the date corresponding to the price fluctuation meeting the preset condition.
The credit payment calculation model in the system shown in fig. 1 may include a bulk price prediction model.
Of course, the bulk goods price prediction model constructed in the embodiment of the present specification may also update the repayment plan by the user.
In the embodiment of the specification, because the small credit granting evaluation is performed based on the bulk commodity data of the user applying for, the probability that the evaluation result is credit granting is high, the situation that no credit is granted rarely occurs, and the user satisfaction is high.
In an embodiment of the present specification, after generating the payment plan, the method may further include:
and accepting an exhibition request of a user, and updating the repayment plan based on the exhibition request.
Thus, the repayment plan can better reflect the time requirement of the user.
S203: and providing small credit for the operation of the application user by taking the bulk commodity held by the application user in the bulk commodity trading platform as a credit endorsement, wherein the small credit is smaller than the market price of the bulk commodity.
After the credit is given to the user, the user can act, and the credit amount is smaller than the market price of the bulk commodity, so that the small credit is given by taking the bulk commodity as the credit endorsement, the risk is lower, and the borrowing process can be shortened.
In an embodiment of the present specification, the method may further include: and evaluating whether the credit account information of the user and the contract information of purchasing spot resources allow to use the credit or not according to a preset dynamic decision rule, and specifically evaluating the credit line according to the transaction condition and the performance condition of the user on a bulk spot online transaction platform.
The input indexes of the branch decision rule may include: contract attribute values, account status attribute values, and member transaction account attribute values. Wherein, the contract attribute value may be: one of the credit is approved or the balance of the available credit limit of the credit is passed; the account state attribute value can be one of a contract of gold resource, a non-guarantee bond contract and an on-line payment contract; the member transaction account attribute value may be one of a record of no default or a transaction account blocked.
S204: monitoring the state of the bulk commodity data of the application user, and updating a repayment plan based on the state of the bulk commodity data.
The small credit is granted and evaluated according to the large commodity data of a large commodity holding user in a large commodity transaction platform, a credit limit and a repayment plan are configured for the user according to an evaluation result, the large commodity held by the application user in the large commodity transaction platform is used as a credit endorsement to provide small credit for the payment operation of the application user, the process can be shortened while the money is borrowed at a lower risk, the small credit borrowing efficiency of the user is improved, then the repayment plan is updated according to the state of the large commodity data by monitoring the state of the large commodity data of the application user, the whole borrowing and repayment process is in a monitoring range, and the fluctuation of the large commodity can be adapted in time.
Because the bulk commodities in the bulk commodity trading platform fluctuate with the market environment or the trading of the bulk commodities has new progress with time, the data of the bulk commodities can be monitored and the repayment plan can be adjusted in time.
In an embodiment of the present specification, the monitoring the status of the bulk goods data of the application user, and updating the repayment plan based on the status of the bulk goods data may include:
monitoring the state of the bulk commodity data of the applying user in a repayment period of the repayment plan, if the bulk commodity data changes, adjusting the repayment plan based on the change of the bulk commodity data, and providing the adjusted repayment plan for the applying user.
In a practical application scenario, if it is predicted that the price of the bulk commodity will go low through the monitored bulk commodity data, the user may be required to pay in advance.
In another practical scenario, if the user sells a large commodity and holds cash, the user may also be required to pay in advance.
In the embodiment of the specification, after the monitoring of the state of the bulk goods data of the application user, the fluctuation of the bulk goods in the payment period can be predicted, the payment plan is updated based on the fluctuation, and the payment period is advanced to the tolerable fluctuation date.
Specifically, the monitoring of the state of the bulk commodity data of the application user may include:
monitoring a price of an associated item associated with the block of items;
predicting the state of the bulk commodity data based on the association degree of the associated commodity and the bulk commodity and the price of the associated commodity.
In an embodiment of the present specification, the method may further include:
collecting price fluctuations of a plurality of commodities in a first period and price fluctuations of the bulk commodity in a second period as training samples, wherein the first period is earlier than the second period;
setting labels for the training samples according to consistency of price lag;
training a bulk commodity price prediction model by using the training samples and the labels;
the predicting the state of the bulk commodity data based on the association degree of the associated commodity with the bulk commodity and the price of the associated commodity may include:
and predicting the price of the bulk commodity by using the built bulk commodity price prediction model.
In an embodiment of the present specification, the predicting the price of the block commodity by using the constructed block commodity price prediction model may include:
predicting a price of the block of merchandise over a future time period;
the configuring of the credit line and the repayment plan for the application user according to the evaluation result may include:
and configuring a credit line and a repayment plan for the application user according to the qualified price and the future time period.
In embodiments of the present description, the associated merchandise may include complements and substitutes.
In the embodiment of the present specification, the method may further include:
the warning of the state of the bulk commodity data may include:
and if the change of the data of the bulk commodity exceeds a preset range, warning the transaction platform of the bulk commodity, so that the transaction platform of the bulk commodity reduces the business range of the application user for performing transaction by using the bulk commodity.
Wherein alerting the bulk commodity trading platform may comprise:
and dynamically calculating the risk of the customer according to the execution progress of the transaction in the bulk spot commodity online transaction platform and the contract state, generating risk warning information after the potential risk is identified, returning the risk warning information to the front-end platform, and informing a risk manager.
The narrowing of the business scope of the application user for carrying out transaction by using bulk commodities may be: limiting the application function of the invoice of the sale item of the application user before the application user does not clear credit; and freezing the credit account and the transaction account which are overdue and not paid back.
In an embodiment of this specification, the monitoring the state of the bulk goods data of the application user may further include:
and monitoring the transaction progress of the bulk goods of the application user, and updating a repayment plan based on the transaction progress.
In an embodiment of the present specification, the method further comprises:
if receiving the redemption operation of the large-volume spot commodity online transaction platform of the application user, recording the repayment amount of the credit by a repayment management unit, and finishing the repayment operation; in the staged redemption business, the remaining repayment amount of the credit can be further updated, the repayment plan is regenerated, and the credit line and the available line of the credit account are synchronized.
The client may need to postpone the repayment of the credit in the financing purchase service due to actual operation conditions, and therefore, the method further comprises the following steps:
and if receiving the exhibition operation of the large-volume spot commodity online transaction platform of the application user, calculating the performance risk of the client, updating the risk coefficient of the client, and regenerating a repayment plan through a repayment management unit.
Wherein, the exhibition operation can be initiated on a large-volume spot commodity online transaction platform.
Fig. 3 is a schematic structural diagram of an apparatus for performing petty credit based on a bulk good according to an embodiment of the present disclosure, where the apparatus may include:
the evaluation module 301 is used for carrying out petty credit evaluation on the application user based on the bulk commodity data of the application user;
a configuration module 302, configured a credit line and a repayment plan for the application user according to the evaluation result;
the dynamic supporting module 303 is configured to provide a small credit for dynamic supporting operation of the application user by using a bulk commodity held by the application user in a bulk commodity transaction platform as a credit endorsement, where the small credit is smaller than the market price of the bulk commodity;
the configuration module 302 monitors the status of the bulk goods data of the application user, and updates the repayment plan based on the status of the bulk goods data.
Optionally, the monitoring the status of the bulk goods data of the application user, and updating the repayment plan based on the status of the bulk goods data may include:
monitoring the state of the bulk commodity data of the applying user in a repayment period of the repayment plan, if the bulk commodity data changes, adjusting the repayment plan based on the change of the bulk commodity data, and providing the adjusted repayment plan for the applying user.
Optionally, the monitoring the status of the bulk goods data of the application user may include:
monitoring a price of an associated item associated with the block of items;
predicting the state of the bulk commodity data based on the association degree of the associated commodity and the bulk commodity and the price of the associated commodity.
Optionally, the configuration module 302 may be further configured to:
collecting price fluctuations of a plurality of commodities in a first period and price fluctuations of the bulk commodity in a second period as training samples, wherein the first period is earlier than the second period;
setting labels for the training samples according to consistency of price lag;
training a bulk commodity price prediction model by using the training samples and the labels;
the predicting the state of the bulk commodity data based on the association degree of the associated commodity with the bulk commodity and the price of the associated commodity may include:
and predicting the price of the bulk commodity by using the built bulk commodity price prediction model.
Optionally, the predicting the price of the bulk commodity by using the built bulk commodity price prediction model may include:
predicting a price of the block of merchandise over a future time period;
the configuring of the credit line and the repayment plan for the application user according to the evaluation result may include:
and configuring a credit line and a repayment plan for the application user according to the qualified price and the future time period.
Optionally, the associated merchandise may include complements and substitutes.
Optionally, the configuration module 302 may be further configured to:
the warning of the state of the bulk commodity data may include:
and if the change of the data of the bulk commodity exceeds a preset range, warning the transaction platform of the bulk commodity, so that the transaction platform of the bulk commodity reduces the business range of the application user for performing transaction by using the bulk commodity.
Optionally, the monitoring the status of the bulk goods data of the application user may further include:
and monitoring the transaction progress of the bulk goods of the application user, and updating a repayment plan based on the transaction progress.
Optionally, the configuration module 302 may be further configured to:
and accepting an exhibition request of a user, and updating the repayment plan based on the exhibition request.
The device carries out small credit granting evaluation on the bulk commodity data of a bulk commodity holding user in a bulk commodity transaction platform, configures a credit limit and a repayment plan for the user according to an evaluation result, uses the bulk commodity held by an application user in the bulk commodity transaction platform as a credit endorsement to provide small credit for the mobile support operation of the application user, can borrow at lower risk and shorten the flow, improves the small credit borrowing efficiency of the user, and then updates the repayment plan by monitoring the state of the bulk commodity data of the application user, so that the whole borrowing and repayment process is in a monitoring range and can be adapted to the fluctuation of the bulk commodity in time.
It should be noted that the apparatus shown in fig. 3 may perform specific steps in the embodiment shown in fig. 1, and is not specifically described herein.
Based on the same inventive concept, the embodiment of the specification further provides the electronic equipment.
In the following, embodiments of the electronic device of the present invention are described, which may be regarded as specific physical implementations for the above-described embodiments of the method and apparatus of the present invention. Details described in the embodiments of the electronic device of the invention should be considered supplementary to the embodiments of the method or apparatus described above; for details which are not disclosed in embodiments of the electronic device of the invention, reference may be made to the above-described embodiments of the method or the apparatus.
Fig. 4 is a schematic structural diagram of an electronic device provided in an embodiment of the present specification. An electronic device 400 according to this embodiment of the invention is described below with reference to fig. 4. The electronic device 400 shown in fig. 4 is only an example and should not bring any limitation to the function and the scope of use of the embodiments of the present invention.
As shown in fig. 4, electronic device 400 is embodied in the form of a general purpose computing device. The components of electronic device 400 may include, but are not limited to: at least one processing unit 410, at least one memory unit 420, a bus 430 that connects the various system components (including the memory unit 420 and the processing unit 410), a display unit 440, and the like.
Wherein the storage unit stores program code executable by the processing unit 410 to cause the processing unit 410 to perform steps according to various exemplary embodiments of the present invention described in the above-mentioned processing method section of the present specification. For example, the processing unit 410 may perform the steps as shown in fig. 1.
The storage unit 420 may include readable media in the form of volatile storage units, such as a random access memory unit (RAM)4201 and/or a cache memory unit 4202, and may further include a read only memory unit (ROM) 4203.
The storage unit 420 may also include a program/utility 4204 having a set (at least one) of program modules 4205, such program modules 4205 including, but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which, or some combination thereof, may comprise an implementation of a network environment.
The electronic device 400 may also communicate with one or more external devices 500 (e.g., keyboard, pointing device, bluetooth device, etc.), with one or more devices that enable a user to interact with the electronic device 400, and/or with any devices (e.g., router, modem, etc.) that enable the electronic device 400 to communicate with one or more other computing devices. Such communication may occur via input/output (I/O) interfaces 450. Also, the electronic device 400 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network, such as the internet) via the network adapter 460. The network adapter 460 may communicate with other modules of the electronic device 400 via the bus 430. It should be appreciated that although not shown in FIG. 4, other hardware and/or software modules may be used in conjunction with electronic device 400, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.
Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments of the present invention described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solution according to the embodiment of the present invention can be embodied in the form of a software product, which can be stored in a computer-readable storage medium (which can be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to make a computing device (which can be a personal computer, a server, or a network device, etc.) execute the above-mentioned method according to the present invention. The computer program, when executed by a data processing apparatus, enables the computer readable medium to implement the above-described method of the invention, namely: such as the method shown in fig. 2.
Fig. 5 is a schematic diagram of a computer-readable medium provided in an embodiment of the present specification.
A computer program implementing the method illustrated in fig. 2 may be stored on one or more computer readable media. The computer readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
The computer readable storage medium may include a propagated data signal with readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A readable storage medium may also be any readable medium that is not a readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a readable storage medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., through the internet using an internet service provider).
In summary, the invention may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. Those skilled in the art will appreciate that some or all of the functionality of some or all of the components in embodiments in accordance with the invention may be implemented in practice using a general purpose data processing device such as a microprocessor or a Digital Signal Processor (DSP). The present invention may also be embodied as apparatus or device programs (e.g., computer programs and computer program products) for performing a portion or all of the methods described herein. Such programs implementing the present invention may be stored on computer-readable media or may be in the form of one or more signals. Such a signal may be downloaded from an internet website or provided on a carrier signal or in any other form.
While the foregoing embodiments have described the objects, aspects and advantages of the present invention in further detail, it should be understood that the present invention is not inherently related to any particular computer, virtual machine or electronic device, and various general-purpose machines may be used to implement the present invention. The invention is not to be considered as limited to the specific embodiments thereof, but is to be understood as being modified in all respects, all changes and equivalents that come within the spirit and scope of the invention.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments.
The above description is only an example of the present application and is not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.
Claims (20)
1. A method for petty credit based on a large commodity, comprising:
carrying out petty credit granting evaluation on the application user based on the bulk commodity data of the application user;
configuring a credit line and a repayment plan for the application user according to the evaluation result;
providing a small credit for the operation of the application user by taking a bulk commodity held by the application user in a bulk commodity trading platform as a credit endorsement, wherein the small credit is smaller than the market price of the bulk commodity;
monitoring the state of the bulk commodity data of the application user, and updating a repayment plan based on the state of the bulk commodity data.
2. The method of claim 1, wherein the monitoring of the status of the block of merchandise data of the requesting user, and updating the payment plan based on the status of the block of merchandise data comprises:
monitoring the state of the bulk commodity data of the applying user in a repayment period of the repayment plan, if the bulk commodity data changes, adjusting the repayment plan based on the change of the bulk commodity data, and providing the adjusted repayment plan for the applying user.
3. The method of claim 2, wherein the monitoring of the status of the block merchandise data of the requesting user comprises:
monitoring a price of an associated item associated with the block of items;
predicting the state of the bulk commodity data based on the association degree of the associated commodity and the bulk commodity and the price of the associated commodity.
4. The method of claim 3, further comprising:
collecting price fluctuations of a plurality of commodities in a first period and price fluctuations of the bulk commodity in a second period as training samples, wherein the first period is earlier than the second period;
setting labels for the training samples according to consistency of price lag;
training a bulk commodity price prediction model by using the training samples and the labels;
the predicting the state of the bulk commodity data based on the association degree of the associated commodity with the bulk commodity and the price of the associated commodity comprises:
and predicting the price of the bulk commodity by using the built bulk commodity price prediction model.
5. The method of claim 4, wherein the predicting the price of the block good using the constructed block good price prediction model comprises:
predicting a price of the block of merchandise over a future time period;
the configuring credit line and repayment plan for the application user according to the evaluation result comprises the following steps:
and configuring a credit line and a repayment plan for the application user according to the qualified price and the future time period.
6. The method of claim 3, wherein the associated merchandise includes complements and substitutes.
7. The method of claim 2, further comprising:
the state of the bulk commodity data is warned, comprising:
and if the change of the data of the bulk commodity exceeds a preset range, warning the transaction platform of the bulk commodity, so that the transaction platform of the bulk commodity reduces the business range of the application user for performing transaction by using the bulk commodity.
8. The method of claim 2, wherein monitoring the status of the block of merchandise data of the requesting user further comprises:
and monitoring the transaction progress of the bulk goods of the application user, and updating a repayment plan based on the transaction progress.
9. The method of claim 1, further comprising:
and accepting an exhibition request of a user, and updating the repayment plan based on the exhibition request.
10. A device for petty credit based on a large commodity, comprising:
the evaluation module is used for carrying out petty credit evaluation on the application user based on the bulk commodity data of the application user;
the configuration module configures credit line and repayment plan for the application user according to the evaluation result;
the dynamic support module is used for providing small credit for dynamic support operation of the application user by taking a bulk commodity held by the application user in a bulk commodity trading platform as a credit endorsement, wherein the small credit is smaller than the market price of the bulk commodity;
the configuration module monitors the state of the bulk commodity data of the application user and updates the repayment plan based on the state of the bulk commodity data.
11. The apparatus of claim 10, wherein the monitoring of the status of the block of merchandise data of the requesting user, the updating of the payment plan based on the status of the block of merchandise data, comprises:
monitoring the state of the bulk commodity data of the applying user in a repayment period of the repayment plan, if the bulk commodity data changes, adjusting the repayment plan based on the change of the bulk commodity data, and providing the adjusted repayment plan for the applying user.
12. The apparatus of claim 11, wherein the monitoring of the status of the block merchandise data of the requesting user comprises:
monitoring a price of an associated item associated with the block of items;
predicting the state of the bulk commodity data based on the association degree of the associated commodity and the bulk commodity and the price of the associated commodity.
13. The apparatus of claim 12, wherein the configuration module is further configured to:
collecting price fluctuations of a plurality of commodities in a first period and price fluctuations of the bulk commodity in a second period as training samples, wherein the first period is earlier than the second period;
setting labels for the training samples according to consistency of price lag;
training a bulk commodity price prediction model by using the training samples and the labels;
the predicting the state of the bulk commodity data based on the association degree of the associated commodity with the bulk commodity and the price of the associated commodity comprises:
and predicting the price of the bulk commodity by using the built bulk commodity price prediction model.
14. The apparatus of claim 13, wherein the predicting the price of the block good using the constructed block good price prediction model comprises:
predicting a price of the block of merchandise over a future time period;
the configuring credit line and repayment plan for the application user according to the evaluation result comprises the following steps:
and configuring a credit line and a repayment plan for the application user according to the qualified price and the future time period.
15. The apparatus of claim 12, wherein the associated merchandise includes complements and substitutes.
16. The apparatus of claim 11, wherein the configuration module is further configured to:
the state of the bulk commodity data is warned, comprising:
and if the change of the data of the bulk commodity exceeds a preset range, warning the transaction platform of the bulk commodity, so that the transaction platform of the bulk commodity reduces the business range of the application user for performing transaction by using the bulk commodity.
17. The apparatus of claim 11, wherein the monitoring of the status of the block data of the requesting user further comprises:
and monitoring the transaction progress of the bulk goods of the application user, and updating a repayment plan based on the transaction progress.
18. The apparatus of claim 10, wherein the configuration module is further configured to:
and accepting an exhibition request of a user, and updating the repayment plan based on the exhibition request.
19. An electronic device, wherein the electronic device comprises:
a processor; and the number of the first and second groups,
a memory storing computer-executable instructions that, when executed, cause the processor to perform the method of any of claims 1-9.
20. A computer readable storage medium, wherein the computer readable storage medium stores one or more programs which, when executed by a processor, implement the method of any of claims 1-9.
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| CN201911214074.4A CN112990907A (en) | 2019-12-02 | 2019-12-02 | Method and device for small credit granting based on bulk commodities and electronic equipment |
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| CN201911214074.4A CN112990907A (en) | 2019-12-02 | 2019-12-02 | Method and device for small credit granting based on bulk commodities and electronic equipment |
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