CN109919636B - Credit grade determining method, system and related components - Google Patents
Credit grade determining method, system and related components Download PDFInfo
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Abstract
The application discloses a credit rating determining method, which comprises the steps of receiving a query instruction of a credit rating and determining a user identification code of a target user corresponding to the query instruction; querying historical contract performance data corresponding to the user identification code in the blockchain network; and comparing the historical contract performance data with the expected contract performance data, and determining the credit rating of the user according to the comparison result. The method can improve the accuracy of credit rating evaluation and reduce the operation risk. The application also discloses a credit rating determining system, a computer readable storage medium and a blockchain node device, which have the beneficial effects.
Description
Technical Field
The present disclosure relates to the field of blockchain technologies, and in particular, to a method and a system for determining a credit level, a computer readable storage medium, and a blockchain node device.
Background
With the development of socioeconomic performance, the phenomenon of contracting between companies is becoming more common, for example, after a company develops a new partner by sales promotion, it is necessary to contract with the company and then ship the product. However, the current general mode of sales is to pay after shipping or pay-as-you-go, the total amount of sales is very small and can be cleared in time, and a situation of dragging one drag and then another drag is often encountered.
The related sales risk control method is generally determined empirically based on previous cooperation or by evaluating the credit of the sales object by a third party to decide whether to reach a sales agreement. However, whether to continue signing a sales contract is judged based on early cooperation experience or through evaluation of the credit condition of the sales object by a third party, so that the method has larger uncertainty, and the evaluation feasibility of the credit condition of the sales object by the third party is doubtful, so that the program is complex, the evidence obtaining is difficult, and the final decision of a company is influenced.
Therefore, how to improve the accuracy of the credit rating assessment and reduce the operation risk is a technical problem that needs to be solved by those skilled in the art.
Disclosure of Invention
The invention aims to provide a credit level determining method, a credit level determining system, a computer-readable storage medium and a blockchain node device, which can improve the accuracy of credit level assessment and reduce operation risks.
In order to solve the above technical problems, the present application provides a credit rating determining method applied to a block link point device, the credit rating determining method includes:
receiving a query instruction of credit level, and determining a user identification code of a target user corresponding to the query instruction;
querying historical contract performance data corresponding to the user identification code in the blockchain network;
and comparing the historical contract performance data with the expected contract performance data, and determining the credit rating of the user according to the comparison result.
Optionally, before querying the historical contract fulfillment data corresponding to the user identification code in the blockchain network, the method further includes:
and uploading historical contract performance data corresponding to the sales contract of the target user to the blockchain network.
Optionally, the historical contract performance data includes any one or a combination of any of a refund period, a refund amount, and refund terms.
Optionally, the method further comprises:
and acquiring the business information of the target user, and adjusting the credit rating of the user according to the business information.
Optionally, before comparing the historical contract performance data with the expected contract performance data, further comprising:
acquiring user credit information corresponding to the user identification code;
judging whether the user credit investigation information accords with the expected credit investigation condition;
if not, the credit rating determination flow is terminated by using the first intelligent contract, and credit risk warning information is generated.
Optionally, the method further comprises:
judging whether the credit rating of the user meets the credit rating requirement;
if not, generating credit risk prompt information by using the second intelligent contract.
Optionally, the method further comprises:
after signing a sales contract with the target user, determining a sales refund risk level of the target user according to the current credit information, refund state information and operation information of the target user; the refund state information is obtained by comparing refund information with refund clauses, and the refund information comprises a refund period and a refund amount.
The application also provides a credit rating system applied to the block link point device, the credit rating system comprises:
the user determining module is used for receiving the inquiry command of the credit grade and determining the user identification code of the target user corresponding to the inquiry command;
the fulfillment data query module is used for querying historical contract fulfillment data corresponding to the user identification code in the blockchain network;
and the grade determining module is used for comparing the historical contract performance data with the expected contract performance data and determining the credit grade of the user according to the comparison result.
Optionally, the credit rating determining system further includes:
and the data uploading module is used for uploading the historical contract performance data corresponding to the sales contract of the target user to the blockchain network before inquiring the historical contract performance data corresponding to the user identification code in the blockchain network.
Optionally, the historical contract performance data includes any one or a combination of any of a refund period, a refund amount, and refund terms.
Optionally, the credit rating determining system further includes:
and acquiring the business information of the target user, and adjusting the credit rating of the user according to the business information.
Optionally, the credit rating determining system further includes:
the credit information acquisition module is used for acquiring the user credit information corresponding to the user identification code;
the credit information judgment module is used for judging whether the credit information of the user accords with the expected credit conditions; if not, the credit rating determination flow is terminated by using the first intelligent contract, and credit risk warning information is generated.
Optionally, the credit rating determining system further includes:
the credit rating judging module is used for judging whether the credit rating of the user meets the credit rating requirement; if not, generating credit risk prompt information by using the second intelligent contract.
Optionally, the credit rating determining system further includes:
the refund risk level determining module is used for determining the sales refund risk level of the target user according to the current credit information, refund state information and operation information of the target user after signing a sales contract with the target user; the refund state information is obtained by comparing refund information with refund clauses, and the refund information comprises a refund period and a refund amount.
The present application also provides a computer-readable storage medium having stored thereon a computer program which, when executed, implements the steps performed by the above-described credit rating determination method.
The application also provides a blockchain node device, which comprises a memory and a processor, wherein the memory stores a computer program, and the processor realizes the steps executed by the credit level determining method when calling the computer program in the memory.
The application provides a credit level determining method, which comprises the steps of receiving a query instruction of a credit level and determining a user identification code of a target user corresponding to the query instruction; querying historical contract performance data corresponding to the user identification code in a blockchain network; and comparing the historical contract performance data with expected contract performance data, and determining the credit rating of the user according to the comparison result.
According to the method and the device, the historical contract performance data of the target user is queried from the blockchain network based on the blockchain technology, and the data in the blockchain are non-tamper-proof, so that the true and reliable historical contract performance data can be obtained. And comparing the historical contract performance data with the expected contract performance data, and determining the deviation degree of the contract performance condition and the ideal condition of the target user according to the comparison result, thereby obtaining the user credit rating of the target user. The credit rating assessment method and the credit rating assessment device can improve accuracy of credit rating assessment and reduce operation risks. The application also provides a credit rating determining system, a computer readable storage medium and a block link point device, which have the advantages and are not described herein.
Drawings
For a clearer description of the embodiments of the present application, the drawings that are needed in the embodiments will be briefly described, it being apparent that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of a credit rating determining method according to an embodiment of the present application;
fig. 2 is a schematic structural diagram of a credit rating determining system according to an embodiment of the present application;
FIG. 3 is a block chain node device according to an embodiment of the present disclosure;
fig. 4 is a block chain node device structure diagram according to another embodiment of the present application.
Detailed Description
For the purposes of making the objects, technical solutions and advantages of the embodiments of the present application more clear, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are within the scope of the present disclosure.
With the development of socioeconomic performance, the phenomenon of contracting between companies is becoming more common, for example, after a company develops a new partner by sales promotion, it is necessary to contract with the company and then ship the product. However, the existence of a condition where the first or second party does not fulfill the obligation according to the relevant terms in the contract after the contract is made will cause a significant loss to the other party. To circumvent the above-described loss, it is generally necessary to know the credit status of the counterpart before contracting. The related solution is to determine the credit status of the user, and determine whether to continue to sign the sales contract based on previous cooperation experience or the credit of the listened-to counterpart. However, the method has high uncertainty, the feasibility of the heard information is doubtful, the program is complex, the evidence obtaining is difficult, and the final decision of the company is influenced. In view of the above drawbacks of the related solutions, the present application provides a new credit rating determination solution by the following embodiments, which can improve accuracy of credit rating evaluation and reduce operation risk.
Referring to fig. 1, fig. 1 is a flowchart of a credit rating determining method according to an embodiment of the present application.
The specific steps may include:
s101: receiving a query instruction of credit level, and determining a user identification code of a target user corresponding to the query instruction;
the execution body of the embodiment may be a block chain node device, and before this step, there may be an operation that an operator sends a query instruction to the block chain node device through a user terminal. The query instruction mentioned in this step is an instruction for querying the credit rating of a specific user, and the specific content of the query instruction may be: the credit rating status of user B is queried. The application scenario for receiving the query instruction may be that before the user a is about to contract with the user B, the user a needs to query the credit status of the user B in advance in order to ensure that the user B can fulfill the terms in the contract, that is, the user a sends the query instruction for querying the credit level of the user B to the blockchain node device through the user terminal. Specifically, this stepAnd determining the user identification code of the target user by analyzing the query instruction.
S102: querying historical contract performance data corresponding to the user identification code in the blockchain network;
wherein historical contract performance data for a plurality of users may be pre-stored in the blockchain network, the historical contract performance data may include any one or a combination of any of a refund period, a refund amount, and refund terms. As a preferred embodiment, historical contract performance data may also be extracted from the sales contracts of the target users prior to this step and uploaded to the blockchain network. Specifically, the sales contract successfully signed by the target user for the past time can be uploaded to the blockchain network through the blockchain node device, and the sales object, the contract fulfillment time, the refund clause and the like in the sales contract are packaged into a data block (namely, are stored in a structured manner) to be used as a reference basis for judging the subsequent sales risk.
S103: and comparing the historical contract performance data with the expected contract performance data, and determining the credit rating of the user according to the comparison result.
Wherein the step is based on having obtained historical contract performance data, the historical contract performance data may be compared with expected contract performance data. The expected contract performance data is preset ideal contract performance data, can be flexibly adjusted according to actual application scenes, and can be a standard refund period, a standard refund amount and standard refund clauses obtained by extracting a standard sales contract.
Specifically, the specific process of data comparing the historical contract performance data with the expected contract performance data may be: and determining the actual time difference between the actual withdrawal time and the withdrawal time specified by the contract and the actual amount difference between the actual withdrawal amount and the withdrawal amount specified by the contract according to the withdrawal period, the withdrawal amount and the withdrawal terms in the historical contract performance data. The standard time difference and standard amount difference are determined based on the standard rebate period, the standard rebate amount, and the standard rebate terms in the expected contract performance data. And taking the first deviation amount of the actual time difference and the standard time difference and the second deviation amount of the actual amount difference and the standard amount difference as comparison results. For example, company a may enter a company B identification code (company name, organization code, etc.) on the blockchain to search for a sales profile (specific sales products, quantity, amount, etc. may be obscured or encrypted based on privacy requirements) related to company B in the public part and compare its refund period, refund amount with refund terms, and if the refund period exceeds the psychological expectation of company a or the refund amount is problematic, the credit rating of company B is lowered and a credit alert is sent to company a.
In this embodiment, there may be a correspondence between the first deviation amount and the second deviation amount and the user credit level, for example, the user credit level of the target user may be determined to be one level when the first deviation amount and the second deviation amount are both 0, the user credit level of the target user may be determined to be two levels when the first deviation amount is 7 days but the second deviation amount is 0, and the user credit level of the target user may be determined to be three levels when the first deviation amount is 7 days and the second deviation amount is ten thousand yuan. And the credit grades of the users are ranked in order of the first grade, the second grade and the third grade according to the sales risk from low to high. The "7 days" mentioned in the above example is that the actual return date is 7 days later than the prescribed return date, and the "ten thousand yuan" mentioned in the above example is that the actual return amount is less than the prescribed return amount by ten thousand yuan. Of course, the corresponding relationship between the comparison result and the credit rating of the user can be flexibly set according to the relevant regulations of the company, which is not particularly limited herein.
The embodiment queries the historical contract performance data of the target user from the blockchain network based on the blockchain technology, and the data in the blockchain is non-tamper-proof, so that the actual and reliable historical contract performance data can be obtained. And comparing the historical contract performance data with the expected contract performance data, and determining the deviation degree of the contract performance condition and the ideal condition of the target user according to the comparison result, thereby obtaining the user credit rating of the target user. The embodiment can improve the accuracy of credit rating evaluation and reduce the operation risk.
As a possible implementation manner, after determining the user credit rating of the target user, it may also be determined whether the user credit rating meets the credit rating requirement; if not, generating credit risk prompt information by using the second intelligent contract.
After the credit rating of the user is obtained, the feasible implementation mode judges whether the credit rating of the target user meets the preset standard, if not, the credit rating of the target user is lower, a certain risk exists in signing a sales contract with the target user, and the target user is not recommended to sign the sales contract. Specifically, in the above possible embodiments, the signaling level requirements may be: the user credit rating of the target user is required to be primary or secondary, and therefore, when the user credit rating is tertiary, the second intelligent contract is triggered to generate credit risk prompt information.
As a further supplement to the embodiment corresponding to fig. 1, the above embodiment may also obtain the operation information of the target user, and adjust the credit level of the user according to the operation information.
The business information may include news information and/or sales status information of the target user, among others. News information about a target user (e.g., sales object) may be monitored during credit rating evaluation, and risk prompt information may be generated by adjusting the user's credit rating when the target user is determined to be mismanaged based on the news information. When a major operation problem occurs to a target user, the intelligent contract can be directly triggered to carry out risk prompt so as to reduce the risk of sales refund. Specifically, the acquired news information and sales status information may be uploaded to a blockchain network for storage. It can be appreciated that determining that the target user is out of the best way or has good credit performance for a long time according to the management information can properly improve the credit rating of the user.
As a further complement to the corresponding embodiment of fig. 1, the above-described embodiment may have the following steps prior to data comparing the historical contract performance data with the expected contract performance data:
step 1: acquiring user credit information corresponding to the user identification code;
step 2: judging whether the user credit investigation information accords with the expected credit investigation condition; if yes, continuing to execute the credit rating determining flow; if not, entering a step 3;
step 3: and terminating the credit rating determination flow by using the first intelligent contract, and generating credit risk warning information.
Specifically, the credit information of the target user can be used as a risk assessment parameter of a sales object to perform a pre-rating before the sales contract is signed, so that the sales object with problems in credit can be eliminated. Meanwhile, credit information of the sales object can be dynamically monitored in the contract performance process, and the change of the credit information, the comparison result of the refund information and the refund clause and the business news of the sales object are used as input parameters of risk rating so as to control the sales refund risk. Specifically, the operation of evaluating the sales return risk level may include determining the sales return risk level of the target user according to the current credit information, the return status information, and the operation information of the target user after the sales contract is made with the target user. The refund state information is obtained by comparing refund information with refund clauses, and the refund information comprises a refund period and a refund amount.
Referring to fig. 2, fig. 2 is a schematic structural diagram of a credit rating determining system according to an embodiment of the present application; the system may include:
the user determining module 201 is configured to receive a query instruction of a credit level, and determine a user identification code of a target user corresponding to the query instruction;
a fulfillment data query module 202 for querying historical contract fulfillment data in the blockchain network corresponding to the user identification code;
the level determining module 203 is configured to compare the historical contract performance data with the expected contract performance data, and determine a credit level of the user according to the comparison result.
The embodiment queries the historical contract performance data of the target user from the blockchain network based on the blockchain technology, and the data in the blockchain is non-tamper-proof, so that the actual and reliable historical contract performance data can be obtained. And comparing the historical contract performance data with the expected contract performance data, and determining the deviation degree of the contract performance condition and the ideal condition of the target user according to the comparison result, thereby obtaining the user credit rating of the target user. The embodiment can improve the accuracy of credit rating evaluation and reduce the operation risk.
Optionally, the credit rating determining system further includes:
and the data uploading module is used for uploading the sales contract of the target user as historical contract performance data to the blockchain network before inquiring the historical contract performance data corresponding to the user identification code in the blockchain network, and carrying out structural storage on the sales object, the contract performance time and the money returning clause in the sales contract.
Optionally, the historical contract performance data includes any one or a combination of any of a refund period, a refund amount, and refund terms.
Optionally, the credit rating determining system further includes:
and acquiring the business information of the target user, and adjusting the credit rating of the user according to the business information.
Optionally, the credit rating determining system further includes:
the credit information acquisition module is used for acquiring the user credit information corresponding to the user identification code;
the credit information judgment module is used for judging whether the credit information of the user accords with the expected credit conditions; if not, the credit rating determination flow is terminated by using the first intelligent contract, and credit risk warning information is generated.
Optionally, the credit rating determining system further includes:
the credit rating judging module is used for judging whether the credit rating of the user meets the credit rating requirement; if not, generating credit risk prompt information by using the second intelligent contract.
Optionally, the credit rating determining system further includes:
the refund risk level determining module is used for determining the sales refund risk level of the target user according to the current credit information, refund state information and operation information of the target user after signing a sales contract with the target user; the refund state information is obtained by comparing refund information with refund clauses, and the refund information comprises a refund period and a refund amount.
Since the embodiments of the system portion and the embodiments of the method portion correspond to each other, the embodiments of the system portion refer to the description of the embodiments of the method portion, which is not repeated herein.
The present application also provides a computer-readable storage medium having stored thereon a computer program which, when executed, implements the steps provided by the above embodiments. The storage medium may include: 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. The storage medium has stored thereon a computer program which, when executed by a processor, performs the steps of: receiving a query instruction of credit level, and determining a user identification code of a target user corresponding to the query instruction; querying historical contract performance data corresponding to the user identification code in the blockchain network; and comparing the historical contract performance data with the expected contract performance data, and determining the credit rating of the user according to the comparison result.
The embodiment queries the historical contract performance data of the target user from the blockchain network based on the blockchain technology, and the data in the blockchain is non-tamper-proof, so that the actual and reliable historical contract performance data can be obtained. And comparing the historical contract performance data with the expected contract performance data, and determining the deviation degree of the contract performance condition and the ideal condition of the target user according to the comparison result, thereby obtaining the user credit rating of the target user. The embodiment can improve the accuracy of credit rating evaluation and reduce the operation risk.
Preferably, the computer subroutine stored in the computer readable storage medium is executed by the processor, and the following steps may be specifically implemented: uploading the sales contract of the target user as historical contract performance data to the blockchain network, and structurally storing the sales object, contract performance time and refund clauses in the sales contract.
Preferably, the computer subroutine stored in the computer readable storage medium is executed by the processor, and the following steps may be specifically implemented: and acquiring the business information of the target user, and adjusting the credit rating of the user according to the business information.
Preferably, the computer subroutine stored in the computer readable storage medium is executed by the processor, and the following steps may be specifically implemented: before data comparison is carried out on historical contract performance data and expected contract performance data, user credit information corresponding to the user identification code is obtained; judging whether the user credit investigation information accords with the expected credit investigation condition; if not, the credit rating determination flow is terminated by using the first intelligent contract, and credit risk warning information is generated.
Preferably, the computer subroutine stored in the computer readable storage medium is executed by the processor, and the following steps may be specifically implemented: judging whether the credit rating of the user meets the credit rating requirement; if not, generating credit risk prompt information by using the second intelligent contract.
Preferably, the computer subroutine stored in the computer readable storage medium is executed by the processor, and the following steps may be specifically implemented: after signing a sales contract with the target user, determining a sales refund risk level of the target user according to the current credit information, refund state information and operation information of the target user; the refund state information is obtained by comparing refund information with refund clauses, and the refund information comprises a refund period and a refund amount.
The embodiment is based on the block chain technology, and can ensure the authenticity of the data according to the non-falsifiability of the block chain data. In this embodiment, with the centralized data, the user can register the relevant sales records of the user at any time, and can perform credit rating for both involved contracts according to the sales records, and before a new sales contract is signed, the credits of both parties can be evaluated and corresponding advice information can be given, so that the credit evidence collection process is simplified, the working efficiency is improved, and the sales risk is reduced.
The present application further provides a blockchain node device, referring to fig. 3, fig. 3 is a block chain node device structure diagram provided in an embodiment of the present application, including:
a memory 100 for storing a computer program;
the processor 200, when executing the computer program, may implement the steps provided in the above embodiments.
Specifically, the memory 100 includes a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and computer readable instructions, and the internal memory provides an environment for the operating system and the execution of the computer readable instructions in the non-volatile storage medium. The processor 200 provides computing and control capabilities for the block link point device, and when executing the computer program stored in the memory 100, may implement the following steps: receiving a query instruction of credit level, and determining a user identification code of a target user corresponding to the query instruction; querying historical contract performance data corresponding to the user identification code in the blockchain network; and comparing the historical contract performance data with the expected contract performance data, and determining the credit rating of the user according to the comparison result.
The embodiment queries the historical contract performance data of the target user from the blockchain network based on the blockchain technology, and the data in the blockchain is non-tamper-proof, so that the actual and reliable historical contract performance data can be obtained. And comparing the historical contract performance data with the expected contract performance data, and determining the deviation degree of the contract performance condition and the ideal condition of the target user according to the comparison result, thereby obtaining the user credit rating of the target user. The embodiment can improve the accuracy of credit rating evaluation and reduce the operation risk.
Preferably, when the processor 200 executes the computer subroutine stored in the memory 100, the following steps may be implemented: uploading the sales contract of the target user as historical contract performance data to the blockchain network, and structurally storing the sales object, contract performance time and refund clauses in the sales contract.
Preferably, when the processor 200 executes the computer subroutine stored in the memory 100, the following steps may be implemented: and acquiring the business information of the target user, and adjusting the credit rating of the user according to the business information.
Preferably, when the processor 200 executes the computer subroutine stored in the memory 100, the following steps may be implemented: before data comparison is carried out on historical contract performance data and expected contract performance data, user credit information corresponding to the user identification code is obtained; judging whether the user credit investigation information accords with the expected credit investigation condition; if not, the credit rating determination flow is terminated by using the first intelligent contract, and credit risk warning information is generated.
Preferably, when the processor 200 executes the computer subroutine stored in the memory 100, the following steps may be implemented: judging whether the credit rating of the user meets the credit rating requirement; if not, generating credit risk prompt information by using the second intelligent contract.
Preferably, when the processor 200 executes the computer subroutine stored in the memory 100, the following steps may be implemented: after signing a sales contract with the target user, determining a sales refund risk level of the target user according to the current credit information, refund state information and operation information of the target user; the refund state information is obtained by comparing refund information with refund clauses, and the refund information comprises a refund period and a refund amount.
On the basis of the foregoing embodiment, as a preferred implementation manner, referring to fig. 4, fig. 4 is a block chain node device structure diagram of another block chain node device provided in the embodiment of the present application, where the block chain node device further includes:
an input interface 300, coupled to the processor 200, for obtaining externally imported computer programs, parameters and instructions, which are stored in the memory 100 under control of the processor 200. The input interface 300 may be coupled to an input device for receiving parameters or instructions manually entered by a user. The input device can be a touch layer covered on a display screen, can also be a key, a track ball or a touch pad arranged on a terminal shell, and can also be a keyboard, a touch pad or a mouse, etc.
And a display unit 400 connected to the processor 200 for displaying data transmitted from the processor 200. The display unit 400 may be a display screen on a PC, a liquid crystal display screen, or an electronic ink display screen.
The network port 500 is connected to the processor 200 and is used for communication connection with external terminal devices. The communication technology adopted by the communication connection can be a wired communication technology or a wireless communication technology, such as a mobile high definition link technology (MHL), a Universal Serial Bus (USB), a High Definition Multimedia Interface (HDMI), a wireless fidelity technology (WiFi), a Bluetooth communication technology with low power consumption, a communication technology based on IEEE802.11s, and the like.
In the description, each embodiment is described in a progressive manner, and each embodiment is mainly described by the differences from other embodiments, so that the same similar parts among the embodiments are mutually referred. For the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant points refer to the description of the method section. It should be noted that it would be obvious to those skilled in the art that various improvements and modifications can be made to the present application without departing from the principles of the present application, and such improvements and modifications fall within the scope of the claims of the present application.
It should also be noted that in this specification, relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
Claims (7)
1. A method for determining a credit rating, applied to a block link point device, comprising:
receiving a query instruction of credit level, and determining a user identification code of a target user corresponding to the query instruction;
querying historical contract performance data corresponding to the user identification code in a blockchain network;
comparing the historical contract performance data with expected contract performance data, and determining the credit rating of the user according to the comparison result;
acquiring the operation information of the target user, and adjusting the credit rating of the user according to the operation information; wherein the business information comprises news information and/or sales status information of the target user;
wherein the historical contract performance data includes a refund period, a refund amount, and refund terms, and the expected contract performance data includes a standard refund period, a standard refund amount, and a standard refund terms;
wherein prior to data comparing the historical contract performance data with expected contract performance data, further comprising:
acquiring user credit information corresponding to the user identification code;
judging whether the user credit investigation information accords with an expected credit investigation condition or not;
if not, the credit rating determination flow is terminated by using the first intelligent contract, and credit risk warning information is generated.
2. The credit rating determining method according to claim 1, further comprising, prior to the querying the blockchain network for historical contract fulfillment data corresponding to the user identification code:
and uploading historical contract performance data corresponding to the sales contract of the target user to the blockchain network.
3. The credit rating determining method according to claim 1 or 2, further comprising:
judging whether the credit rating of the user meets the credit rating requirement or not;
if not, generating credit risk prompt information by using the second intelligent contract.
4. The credit rating determining method according to claim 3, further comprising:
after signing a sales contract with the target user, determining a sales refund risk level of the target user according to the current credit information, refund state information and operation information of the target user; the refund state information is obtained by comparing refund information with refund clauses, and the refund information comprises a refund period and a refund amount.
5. A credit rating determining apparatus, applied to a block link point device, comprising:
the user determining module is used for receiving a query instruction of the credit grade and determining a user identification code of a target user corresponding to the query instruction;
the fulfillment data query module is used for querying historical contract fulfillment data corresponding to the user identification code in the blockchain network;
the grade determining module is used for comparing the historical contract performance data with the expected contract performance data and determining the credit grade of the user according to the comparison result; the system is also used for acquiring the operation information of the target user and adjusting the credit rating of the user according to the operation information; wherein the business information comprises news information and/or sales status information of the target user;
the credit information acquisition module is used for acquiring user credit information corresponding to the user identification code before comparing the historical contract performance data with the expected contract performance data;
the credit information judgment module is used for judging whether the credit information of the user accords with the expected credit conditions; if not, terminating the credit rating determination flow by using the first intelligent contract, and generating credit risk warning information;
wherein the historical contract performance data includes a refund period, a refund amount, and refund terms, and the expected contract performance data includes a standard refund period, a standard refund amount, and a standard refund terms.
6. A block link point apparatus, comprising:
a memory for storing a computer program;
a processor for implementing the steps of the credit rating determination method as claimed in any one of claims 1 to 4 when executing said computer program.
7. A computer readable storage medium, characterized in that the computer readable storage medium has stored thereon a computer program which, when executed by a processor, implements the steps of the credit rating determination method according to any of claims 1 to 4.
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| CN110570296A (en) * | 2019-07-31 | 2019-12-13 | 阿里巴巴集团控股有限公司 | Risk assessment method and device in credit project |
| CN111639874A (en) * | 2020-06-05 | 2020-09-08 | 中国银行股份有限公司 | Rating method and related equipment |
| CN113271230B (en) * | 2021-07-21 | 2021-09-28 | 湖南三湘银行股份有限公司 | Data interaction system based on priority level |
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