CN109271415B - Data processing method and device for credit investigation database - Google Patents
Data processing method and device for credit investigation database Download PDFInfo
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Abstract
The embodiment of the application relates to the field of finance, in particular to a data processing method and device for a credit investigation database, wherein the method comprises the following steps: the server acquires a query request; the query request carries user information; the server acquires an effective query record of the user information from the credit investigation database according to the user information, wherein the effective query record records a query request of a user corresponding to the user information as a query object in historical monitoring time; and if the server determines that the query request associated with the query request exists in the effective query records, the server takes the query request as an invalid query record.
Description
Technical Field
The application relates to the field of finance, in particular to a data processing method and device of a credit investigation database.
Background
The multi-head loan refers to the behavior of a single user to provide loan demands to 2 or more financial institutions. Lending to multiple parties necessarily entails a higher risk due to the limited repayment capabilities of the individual users. Generally, when a single user has a plurality of loans, the user has a great difficulty in the fund demand, and the repayment capability is doubted.
To avoid multi-loan, the current approach is to introduce a credit database. When each financial institution checks the credit of the user, credit investigation needs to be carried out on the user in a credit investigation database, if the user is found to have a plurality of inquiry records in a short time, the possibility of multi-head loan of the user is considered to exist, and therefore checking of the user is strengthened.
However, in the credit auditing method, many users are not multi-head loans in the enhanced auditing stage, so that the prior art has large misjudgment of the multi-head loans.
Disclosure of Invention
The embodiment of the application provides a data processing method and device of a credit investigation database, which are used for solving the problem of inaccurate borrowing records in the prior art.
The embodiment of the application provides a data processing method of a credit investigation database, which comprises the following steps:
the server acquires a query request; the query request carries user information;
the server acquires an effective query record of the user information from the credit investigation database according to the user information, wherein the effective query record records a query request of a user corresponding to the user information as a query object in historical monitoring time;
and if the server determines that the query request associated with the query request exists in the effective query records, the server takes the query request as an invalid query record.
One possible implementation manner, where the server determines that there is a query request associated with the query request in the valid query record, includes:
the server determining a first query originator of the query request;
and if the server determines that the second query initiator in the effective query records has an association relation with the first query initiator, determining that the query request associated with the query request exists in the effective query records.
One possible implementation manner of determining that the second query originator in the valid query record has an association relationship with the first query originator includes:
the server searches a third inquiry initiator associated with the first inquiry initiator in a lender association list in the credit investigation database;
and if the server determines that the query initiator in the effective query record is the first query initiator or the query initiator in the effective query record is the third query initiator, determining that the second query initiator in the effective query record has an association relationship with the first query initiator.
In one possible implementation, the method further includes:
and if the server determines that the query request associated with the query request does not exist in the effective query records, the server stores the query request as an effective query record to the credit investigation database.
The embodiment of the application provides a data processing device of a credit investigation database, and the device comprises:
an acquisition unit configured to acquire an inquiry request; the query request carries user information;
the processing unit is used for acquiring an effective query record of the user information from the credit investigation database according to the user information, wherein the effective query record records a query request of a user corresponding to the user information as a query object in historical monitoring time; and if the query request associated with the query request exists in the effective query records, the server takes the query request as an ineffective query record.
In a possible implementation manner, the processing unit is specifically configured to:
determining a first query originator of the query request; and if the second query initiator in the effective query records is determined to have an association relation with the first query initiator, determining that the query requests associated with the query requests exist in the effective query records.
In a possible implementation manner, the processing unit is specifically configured to:
searching a third query originator associated with the first query originator in a lender association list in the credit investigation database; and if the query initiator in the effective query record is determined to be the first query initiator, or the query initiator in the effective query record is determined to be the third query initiator, determining that the second query initiator in the effective query record has an association relation with the first query initiator.
In one possible implementation, the processing unit is further configured to:
and if the query request associated with the query request does not exist in the effective query records, storing the query request as an effective query record to the credit investigation database.
Embodiments of the present application provide a computer-readable storage medium storing computer-executable instructions for causing a computer to perform any one of the methods provided by embodiments of the present application.
An embodiment of the present application provides a computing device, including:
a memory for storing program instructions;
and the processor is used for calling the program instructions stored in the memory and executing the method provided by any one of the embodiments of the application according to the obtained program.
In the embodiment of the application, the validity of the query record in the credit investigation database is judged by establishing the incidence relation of the query initiator. Furthermore, the inquiry records which are repeatedly inquired in a short time can be judged as the same inquiry record in the credit investigation database, and the problem of data pollution caused by inquiring the credit investigation database in a short time by a related company is further avoided.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.
Fig. 1A is a schematic view of an application scenario of a credit investigation database according to an embodiment of the present application;
fig. 1B is a schematic view of an application scenario of a credit investigation database according to an embodiment of the present application;
FIG. 1C is a diagram illustrating a query record according to an embodiment of the present disclosure;
fig. 2 is a schematic flowchart illustrating a data processing method of a credit investigation database according to an embodiment of the present application;
fig. 3 is a schematic flowchart illustrating a data processing method of a credit investigation database according to an embodiment of the present application;
fig. 4 is a schematic structural diagram of a data processing apparatus of a credit investigation database according to an embodiment of the present application.
Detailed Description
The object of the embodiment of the present application may be any object having certain information, such as a person, a business, and the like. The group of multi-head loan is usually about 25 years old, just graduates, has not high income, but has strong consumption desire. Meanwhile, as people just step into the society, the consumption idea is advanced, the credit consciousness is not strong, people in the age group have vigorous demands for funds, and most of the people are caused by insufficient economic strength. Due to the fact that suitable financial products and services are not obtained in financial institutions such as banks for a long time, numerous small credit companies, network credit platforms and the like have been produced with aroused credit policy relaxation and crowd consumption consciousness, and cash credit products are provided for the part of crowds. At present, the phenomenon of multi-head loan has a tendency of flooding. Relevant research shows that the proportion of users with multiple borrowing behaviors in the small cash credit population is more than 50%.
The group of cash loan products is very easy to generate multi-head loan behaviors. The average number of multi-head loans is the highest for people in the age range of 25 years, and the average number is 25-30 years. In general, the average number of multi-head loans in the population of 20-35 years of age is significantly higher than the level of all the population. The credit overdue risk of a multi-head loan user is 3-4 times that of a common client, and the probability of default is increased by 20% when a loan applicant applies for one institution more than once. These users often borrow new credits and return old credits, or add new larger amount of money, and the interest accruing to the principal results in the continued accumulation of debts. When the repayment capacity is exceeded, only overdue can be selected.
In order to reduce multi-head borrowing, respective credit investigation platforms are established in the current cash credit approval, and because the credit investigation platforms do not count in the central credit investigation, the borrowing of users is not directly influenced, and a part of users are not considered and forbidden in the overdue process. And a large amount of overdue causes violent hastening actions of some irregular loan platforms and the like.
Meanwhile, by utilizing the phenomenon that the information of each platform is not intercommunicated and is organized and financial fraud is carried out in advance, numerous fraud risks such as false or falsely-used information application, institutions, group cheating loan and the like are generated, and great challenges are brought to the credit review and air control of each platform.
Therefore, the problems caused by the multi-head loan, especially the fraud, are not ignored, which not only causes financial risks, but also derives some social problems.
For a multi-head loan user, the credit risk and the fraud risk faced by the network loan platform can bring huge loss. To control risk, we need to examine not only the past history of such customers with multiple loans, but also the industry that these people have been exposed to when they have loans.
At present, many network lending institutions share the credit assessment data of borrowers, and corresponding technologies exist for identifying whether a user is suspected of overdue or long-term loan before and after applying for loan. For the clients who are overdue for multiple loans or frequently depend on dismantling the east wall to fill the west wall, the institution determines whether to deposit money or not through information screening.
Most target groups of cash loan are long-tailed groups which are not covered by the traditional loan institution and lack complete information gathering data in the central row, so platforms engaged in cash loan business cooperate with each other to realize sharing of loan application data. In addition, the cash loan platform must leave a large amount of information about the identity of the loan applicant when a third-party credit investigation institution queries each loan application record. This information is filtered by the query anomaly detection algorithm to form a reliable multi-head loan database.
The malignant multi-head loan behavior means that the borrower borrows new or old or has a large number of multi-head loans in the same period. The identification of the loan application interval and loan term may be combined with the identification of the loan repayment activity. If the loan application interval is obviously smaller than the loan term, the loan application has a larger risk of new loan and old loan.
At present, a financial institution may send a credit inquiry to a third-party wind control platform for a credit, or companies or parts in the financial institution may respectively verify the credit, so that different institutions may repeatedly inquire the loan records of a borrower, which may cause a course of a credit, and may inquire in a credit investigation database many times, which enlarges the loan times of the borrower, thereby causing the inquiry records in the credit investigation database to fail to correctly evaluate the loan risk of the borrower.
At present, in the aspect of multi-head loan data, the form of journal is adopted, namely, a record is recorded as long as a query is made for any reason.
As shown in fig. 1A, before approving the loan, the financial institution a queries whether the user has a query record of other companies on the third-party wind control platform (in this embodiment, the query record may be a credit investigation database) and determines whether the borrower is suspected of having multiple loans according to the query record. However, there may be an association between the financial institution a and the financial institutions B and C.
For example, as shown in fig. 1B, the financial institution a includes different departments M and R under one company. In a specific scenario, the M department is a market department, the R department is a wind control department, and the market department can inquire whether the user 1 has an inquiry record on a third-party wind control platform when determining that the user 1 is a potential client of the loan of the company; upon determining that the user 1 meets the marketing scope of the marketing department, marketing information may be transmitted to the user 1.
After receiving the marketing message, the user 1 registers the user information in the company and applies for a loan amount. Financial institution B is now the institution that the company has used to process the approval of the loan value unit, which receives the request of user 1 for the loan value unit, and may also want a third-party hosted platform to query user 1 for the query record on the platform to determine the loan value unit to be allocated to user 1.
After the user 1 obtains the loan amount, a loan request may be made to the company. At this time, the financial institution B may also delegate the application to a sub-institution C of the financial institution B for various reasons, and when the sub-institution C approves the loan request, the sub-institution C queries the third-party wind-control platform for the query record of the user 1 on the platform.
At this time, the user 1 has not completed the application for the loan for 1 time, but the company has queried the third-party wind control platform 4 times, if the third-party wind control platform does not know that the financial institution a includes M department and R department, and does not know the association relationship between the financial institution B and the sub-institution C and the association relationship between the financial institution a and the financial institution B, the 4 query records of the user 1 actually correspond to the application for the loan for 1 time in a short time, and there is a great error in determining whether the user 1 has a risk of a multi-head loan through the query records.
Taking the credit investigation report of the people's bank as an example, as shown in fig. 1C, on the same day as 7/2/2017, different departments of the tendering bank inquire 3 times, but actually record the same loan data. This approach is suitable for technical error checking, but can produce data contamination.
In another scenario, if the financial institution B and the financial institution C are companies in a parent-child relationship, the parent-child company calls: in the marketing process or the process of registering the user to the company, the financial institution B and the financial institution C may need to query the third-party wind control platform for the query record of the user on the third-party wind control platform in different marketing processes, which results in that the parent company queries once on the platform, distributes to the subsidiary companies and searches again for the subsidiary companies. After the parent company or sibling company obtains the user's registration information, it may be assigned to financial institution A, which may be used to approve the loan amount for the user. Then in the process of examining and approving the loan amount, the financial institution A also inquires the information of the user from the third-party wind control platform.
At this time, after the user 1 obtains the loan amount, a loan application may be made by the parent company, at this time, the parent company may directly perform a loan approval, may distribute the loan application to a subsidiary company for processing, and may entrust to a brother company, and in these processes, there may be a plurality of times of query records on the third-party wind control platform due to the same loan application.
In another scenario, due to the fact that wind control evaluation, market research and the like are performed, repeated calling in a short period may occur in some financial institution systems, and query records of a third-party wind control platform cause the third-party wind control platform to record multiple query records, but the query records are all caused by one loan application or generated when a user does not initiate a loan application.
In the above various scenarios, multiple records may occur, that is, the credit process is only one time, but the records are recorded multiple times on the third-party wind control platform, so that the query record cannot be directly used for evaluating whether the borrower has the possibility of multi-head loan, the query record amplifies the loan times of the borrower, the data cannot be correctly evaluated on the borrower, and the data is polluted.
As shown in fig. 2, an embodiment of the present application provides a data processing method for a credit investigation database, where the method includes:
step 201: the server acquires a query request; the query request carries user information;
step 202: the server acquires an effective query record of the user information from the credit investigation database according to the user information, wherein the effective query record records a query request of a user corresponding to the user information as a query object in historical monitoring time;
step 203: and if the server determines that the query request associated with the query request exists in the effective query records, the server takes the query request as an invalid query record.
It should be noted that the credit investigation database may be a credit investigation database in a third-party wind control platform, or may be a credit investigation database autonomously established by a certain company, which is not limited herein.
In the embodiment of the present invention, the server may be a server of a credit investigation database, or may be a server that can call data in a real bank database, which is not limited herein.
In step 201, the query request acquired by the server may be a query request initiated by a company initiating a loan application by a borrower to a credit investigation database, or a query request sent by the company to the credit investigation database for marketing purposes before the borrower has not registered a loan item of the company, or a query request sent by the company to the credit investigation database when the borrower applies for a loan amount sent by the company, which is not limited herein.
The user information carried in the query request may include identity information of the borrower, for example, information such as an identity card and a name of the borrower, or other information that can prove the identity; the system can also comprise borrowing information of a borrower, such as the amount of the borrowed money, the repayment deadline, the interest rate and other information; the system can also comprise information such as property certification of the borrower and the like; other credit investigation certificates may also be included, which are not limited herein.
In a possible implementation manner, the query request may also carry a purpose of the query request, for example, the query request is used for performing loan approval for a loan application of the user, or is used for establishing a loan amount for the user, or is used for sending marketing information for the user, evaluating loan capability, and the like.
In step 202, after the server receives the query request, the method may include the following steps:
step one, according to the user information of the user, the effective query records of the user information obtained in the credit investigation database can be found out from the credit investigation database by all the query records matched with the identity information of the user.
For example, the search may be directly performed according to the identity information of the user, and of course, the search may also be performed according to other information, which is not limited herein.
And step two, determining the query record in the historical monitoring time in the query record matched with the identity information of the user.
The historical monitoring time may be determined as needed, for example, all records of the user, the query record of the user in the last 1 week, or the query record of the user in 1 day.
In a specific implementation process, a plurality of historical monitoring times may also be set, for example, a first historical monitoring time and a second historical monitoring time may be set. The first historical monitoring time is less than the second historical monitoring time. When the query record queried by using the first historical monitoring time does not meet the query requirement, the query can be performed again according to the second historical monitoring time. The query requirement may be determined according to a business requirement, and is not limited herein.
For example, if it is determined that the user has fewer query records within 1 day, the query records of the last week may be queried.
And step three, determining effective query records according to the query records in the historical monitoring time searched in the credit investigation database.
In a possible implementation manner, the valid query record may be a query record marked as valid in the credit investigation database.
In a specific implementation manner, if it is determined that the query request associated with the query request does not exist in the valid query records, the server stores the query request as a valid query record to the credit investigation database.
In step 203, the method for marking a query record in the credit investigation database by the specific server may include:
step one, a server generates a query record according to a query request;
step two, the server determines a first query initiator of the query request;
the first query initiator may be a query initiator that initiates the query request determined in the query request, or may be determined according to an API interface of the query request, which is not limited herein. The API interface through which the server determines the query request may be used to tag the first querier.
Step three, if the server determines that the second query initiator in the effective query record has an association relation with the first query initiator, determining that a query request associated with the query request exists in the effective query record;
and step four, the server takes the query request as an invalid query record.
In step three, the server may determine, according to a preset association relationship between the query initiators, whether the second query initiator in the valid query record has an association relationship with the first query initiator.
In the specific implementation process, the method can comprise the following steps:
step one, a server searches a third inquiry initiator associated with the first inquiry initiator in a payer association list in the credit investigation database;
step two, if the server determines that the query initiator in the effective query record is the first query initiator, or the query initiator in the effective query record is the third query initiator, determining that the second query initiator in the effective query record has an association relationship with the first query initiator.
In a specific implementation process, the association relationship may include association relationships of different departments, parent and child companies, brother companies, and the like under the same company, and may also include association relationships of multiple layers of parent and child companies, and the association relationships may be stored in an association list of the depositor, and a specific setting method thereof may be determined as needed, and is not limited herein. For example, the relationship between parent and child companies may be stored in the following manner. As shown in table 1:
| subsidiary company | Parent company |
| Company A | Company A |
| Company B | C Corp Ltd |
| C Corp Ltd | Company E |
| Company E | Company F |
| Company F | Company G |
| Company G | Company G |
TABLE 1
Table 1 may be used to query the primary and secondary mapping tables of the primary company according to the secondary company, if a company does not have the primary company, the primary company may be himself, for example, if a record is queried that the secondary company is company a and the primary company is company a, it is determined that company a does not have the primary company; if a record is found that the subsidiary company is the company B and the parent company is the company C, determining that the parent company of the company B is the company C; and continuing to inquire the parent company of the company C, if one record is that the child company is the company C and the parent company is the company C, determining that the company C does not have the parent company, and stopping the inquiry.
In another setting mode, the position where the association does not exist can be set as a null value; for example, if a record is found that the subsidiary is company a and the parent is empty, it is determined that company a does not have the parent. There may be no record in the table, for example, if company a cannot be found in the subsidiary column in the subsidiary-subsidiary mapping table, it is determined that company a does not have a parent.
Based on the same inventive concept, a parent-subsidiary mapping table for querying subsidiary companies according to parent companies can be established, which is not described herein again. Other association relations can also be correspondingly established according to the primary and secondary company mapping table, and can also be established according to actual requirements, which is not described herein again.
In step four, in a possible implementation manner, the server takes the query request as an invalid query record, and may add a column to the generated query record to mark whether the query record is valid.
If the query request is determined to be an invalid record, marking the column corresponding to the query record as invalid; if the query request is determined to be a valid record, the column corresponding to the query record may be marked as valid.
Of course, whether the record is valid may also be determined in other ways.
In a possible implementation manner, the valid query records may be a query record table respectively established for the valid query records and the invalid query records by the server in the credit investigation database.
In step four, one possible implementation manner includes:
and if the server determines that the query request is an invalid query record, recording the query request in an invalid query record table.
And if the server determines that the query request is an effective query record, recording the query request in an effective query record table.
Thus, in this embodiment, when the server invokes a valid query log within the historical monitoring time, it can query in the valid query log table without looking at the invalid query log table.
In an embodiment of the present application, the query record may include the following information, as shown in table 2:
TABLE 2
Of course, the query record may also include other information, such as the purpose of the query record. According to the purpose of the query record and the historical monitoring time, whether the query request is used for approving one-batch debit application or not or the query request irrelevant to approving one-batch debit application can be determined, the classification mode can be specifically set according to needs, and limitation is not made herein. The method is beneficial to the data completion of the credit investigation database, expands the application range of the credit investigation database, improves the accuracy of credit investigation and reduces the wind control difficulty.
As shown in fig. 3, an embodiment of the present application provides a specific flow of a method for processing a credit investigation database, including:
step 301: the server receives the query request;
step 302: the server acquires an effective query record of the user information from the credit investigation database according to the user information;
the user information can be an identity card and a name; the effective query record records a query request which takes a user corresponding to the user information as a query object in historical monitoring time; for example, the historical monitoring time is 24 hours.
Step 303: comparing the first query initiator in the query request with the query initiators in the valid query records one by one, and if the query records of the same query initiator are determined, executing step 307; otherwise, go to step 304;
step 304: the server searches a third inquiry initiator associated with the first inquiry initiator in a lender association list in the credit investigation database;
for example, the third query originator is the parent company of the first query originator; the primary company of the company can be found in the primary and secondary company mapping table by the company of the first query initiator until no primary company exists above the primary company.
Step 305: comparing the effective query records with the query requests one by one according to a third query initiator determined by the association relationship, and executing step 307 if the same query initiator is determined to exist; otherwise, go to step 306;
for example, the company in the query request may be compared to the query originator's parent company in the valid query records, the parent company of the first query request in the query request (the third query originator) to the query originator's parent company in the valid query records. And if the comparison of one query record is the same, ending the comparison.
Step 306: recording the query request as a valid query record;
step 307: and recording the query request as an invalid query record.
It should be noted that step 303 may be performed after step 304 or step 305, and is not limited herein.
In the embodiment of the application, the incidence relation of the query initiator is established, and the data of the credit investigation database in the historical monitoring time is used as an effective query record, so that the data pollution caused by the fact that the incidence company repeatedly queries in a short time and records in the credit investigation database for many times is avoided. Therefore, the inquiry records which are repeatedly inquired in a short period can be judged as the same effective inquiry record in the credit investigation database, and the problem of misjudgment of multi-head loan is further avoided.
Based on the same inventive concept, as shown in fig. 4, an embodiment of the present application provides a data processing apparatus for a credit investigation database, where the apparatus includes:
an obtaining unit 401, configured to obtain a query request; the query request carries user information;
a processing unit 402, configured to obtain, according to the user information, an effective query record of the user information in the credit investigation database, where the effective query record records a query request that a user corresponding to the user information serves as a query object within historical monitoring time; and if the query request associated with the query request exists in the effective query records, the server takes the query request as an ineffective query record.
In a possible implementation manner, the processing unit 402 is specifically configured to:
determining a first query originator of the query request; and if the second query initiator in the effective query records is determined to have an association relation with the first query initiator, determining that the query requests associated with the query requests exist in the effective query records.
In a possible implementation manner, the processing unit 402 is specifically configured to:
searching a third query originator associated with the first query originator in a lender association list in the credit investigation database; and if the query initiator in the effective query record is determined to be the first query initiator, or the query initiator in the effective query record is determined to be the third query initiator, determining that the second query initiator in the effective query record has an association relation with the first query initiator.
In one possible implementation, the processing unit 402 is further configured to:
and if the query request associated with the query request does not exist in the effective query records, storing the query request as an effective query record to the credit investigation database.
Embodiments of the present application provide a computer-readable storage medium storing computer-executable instructions for causing a computer to perform any one of the methods provided by embodiments of the present application.
An embodiment of the present application provides a computing device, including:
a memory for storing program instructions;
and the processor is used for calling the program instructions stored in the memory and executing the method provided by any one of the embodiments of the application according to the obtained program.
The present application is described above with reference to block diagrams and/or flowchart illustrations of methods, apparatus (systems) and/or computer program products according to embodiments of the application. It will be understood that one block of the block diagrams and/or flowchart illustrations, and combinations of blocks in the block diagrams and/or flowchart illustrations, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, and/or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer and/or other programmable data processing apparatus, create means for implementing the functions/acts specified in the block diagrams and/or flowchart block or blocks.
Accordingly, the subject application may also be embodied in hardware and/or in software (including firmware, resident software, micro-code, etc.). Furthermore, the present application may take the form of a computer program product on a computer-usable or computer-readable storage medium having computer-usable or computer-readable program code embodied in the medium for use by or in connection with an instruction execution system. In the context of this application, a computer-usable or computer-readable medium may be any medium that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present application without departing from the spirit and scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is intended to include such modifications and variations as well.
Claims (10)
1. A data processing method of a credit investigation database is characterized by comprising the following steps:
the server acquires a query request; the query request carries user information;
the server acquires an effective query record of the user information from the credit investigation database according to the user information, wherein the effective query record records a query request of a user corresponding to the user information as a query object in historical monitoring time;
and if the server determines that the query request associated with the query request exists in the effective query records, the server takes the query request as an invalid query record.
2. The method of claim 1, wherein the server determining that a query request associated with the query request exists in the valid query record comprises:
the server determining a first query originator of the query request;
and if the server determines that the second query initiator in the effective query records has an association relation with the first query initiator, determining that the query request associated with the query request exists in the effective query records.
3. The method of claim 2, wherein determining that a second query originator in the valid query record has an association with the first query originator comprises:
the server searches a third inquiry initiator associated with the first inquiry initiator in a lender association list in the credit investigation database;
and if the server determines that the query initiator in the effective query record is the first query initiator or the query initiator in the effective query record is the third query initiator, determining that the second query initiator in the effective query record has an association relationship with the first query initiator.
4. The method of claim 1 or 2, wherein the method further comprises:
and if the server determines that the query request associated with the query request does not exist in the effective query records, the server stores the query request as an effective query record to the credit investigation database.
5. A data processing apparatus for credit investigation of a database, the apparatus comprising:
an acquisition unit configured to acquire an inquiry request; the query request carries user information;
the processing unit is used for acquiring an effective query record of the user information from the credit investigation database according to the user information, wherein the effective query record records a query request of a user corresponding to the user information as a query object in historical monitoring time; and if the query request associated with the query request exists in the effective query records, taking the query request as an invalid query record.
6. The apparatus as claimed in claim 5, wherein said processing unit is specifically configured to:
determining a first query originator of the query request; and if the second query initiator in the effective query records is determined to have an association relation with the first query initiator, determining that the query requests associated with the query requests exist in the effective query records.
7. The apparatus as claimed in claim 6, wherein said processing unit is specifically configured to:
searching a third query originator associated with the first query originator in a lender association list in the credit investigation database; and if the query initiator in the effective query record is determined to be the first query initiator, or the query initiator in the effective query record is determined to be the third query initiator, determining that the second query initiator in the effective query record has an association relation with the first query initiator.
8. The apparatus of claim 5 or 6, wherein the processing unit is further to:
and if the query request associated with the query request does not exist in the effective query records, storing the query request as an effective query record to the credit investigation database.
9. A computer-readable storage medium having stored thereon computer-executable instructions for causing a computer to perform the method of any one of claims 1 to 4.
10. A computing device, comprising:
a memory for storing program instructions;
a processor for calling program instructions stored in said memory to execute the method of any one of claims 1 to 4 in accordance with the obtained program.
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| CN110909382B (en) * | 2019-11-14 | 2022-11-04 | 北京字节跳动网络技术有限公司 | Data security control method and device, electronic equipment and computer readable medium |
| CN113313577A (en) * | 2021-06-15 | 2021-08-27 | 中国银行股份有限公司 | Credit data processing method, device and equipment |
| CN115048406B (en) * | 2022-08-16 | 2022-11-18 | 北京虹鳟在线科技有限公司 | Associated person data information query method based on multi-party credible graph computing technology |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106339942A (en) * | 2016-08-31 | 2017-01-18 | 国信优易数据有限公司 | Financial information processing method and system |
| CN107844575A (en) * | 2017-11-06 | 2018-03-27 | 国家计算机网络与信息安全管理中心 | A kind of personal data shared system and method for internet financial platform |
Family Cites Families (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20060287767A1 (en) * | 2005-06-20 | 2006-12-21 | Kraft Harold H | Privacy Information Reporting Systems with Refined Information Presentation Model |
| US7856385B2 (en) * | 2007-09-07 | 2010-12-21 | National Default Exchange Lp | System and method for management and processing of bankruptcy claims and payments |
| JP5895523B2 (en) * | 2011-12-28 | 2016-03-30 | 富士通株式会社 | Information processing apparatus and data management method |
| CN102930365B (en) * | 2012-09-24 | 2016-09-21 | 中国电力科学研究院 | A kind of relay protection statistical analysis and the check method of operational management data |
| CN103699645A (en) * | 2013-12-26 | 2014-04-02 | 中国人民银行征信中心 | System and method for identifying association relations among enterprises |
| US10353895B2 (en) * | 2015-11-24 | 2019-07-16 | Sap Se | Atomic visibility switch for transactional cache invalidation |
| CN106611372B (en) * | 2016-12-27 | 2021-01-08 | 深圳微众信用科技股份有限公司 | Credit investigation data query method and system |
-
2018
- 2018-08-14 CN CN201810923920.9A patent/CN109271415B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106339942A (en) * | 2016-08-31 | 2017-01-18 | 国信优易数据有限公司 | Financial information processing method and system |
| CN107844575A (en) * | 2017-11-06 | 2018-03-27 | 国家计算机网络与信息安全管理中心 | A kind of personal data shared system and method for internet financial platform |
Non-Patent Citations (2)
| Title |
|---|
| Factors Affecting Online Purchase Behavior: Implications to Improve the Existing Credit Rating System;Hui Peng 等;《2009 International Conference on Management and Service Science》;20091020;全文 * |
| 云技术在我国社会信用体系建设中应用的思考;汪继宁;《征信》;20170303;第34卷(第12期);全文 * |
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