A method and system for processing overdue data

Abstract

A method and system for processing overdue data. Step S1: Set up a total database and multiple sub-databases; Step S2: Generate multiple first queues in the total database and write the overdue data into the corresponding first queues; Step S3: Conduct verification of the overdue data; Step S4: Obtain the extraction quantity of each upper layer of the first queue in real time; Step S5: Calculate the extraction difference between the extraction quantities of the upper layers of two first queues. If the extraction difference reaches the locking threshold, locate the queue with the smaller extraction quantity among the two first queues and make it no longer be extracted; Through the present invention, automatic verification of overdue data can be achieved; The present invention sets up a total database and sub-databases and establishes first queues, enabling the overdue data in the first queues to be automatically compared and verified with the data in the sub-databases, so that before using the overdue data, the system completes the verification of the overdue data in advance, reducing the work pressure of the salespersons.

Description

Technical Field

[0001] The present invention belongs to the technical field of data processing, and particularly relates to a method and system for processing overdue data. Background Art

[0002] Non-performing assets include non-performing loans, which refer to loans issued by banks that cannot recover the principal and interest according to the pre-agreed term and interest rate. Credit scoring is the score given by banks to customers before lending. The higher the credit score of a customer, the greater the probability of repayment. After a user has an overdue event, the bank will send a notice to the user according to the pre-determined credit score to remind the customer to make repayment as soon as possible.

[0003] With the development of Internet technology, various different types of loan methods have emerged currently. Each loan method is managed by a different risk control department. Since overdue data has financial attributes, after the overdue data is uploaded to the database, it needs to be repeatedly verified at intervals to ensure the accuracy of the overdue data. The current verification method is mainly that each risk control department extracts overdue data from the database and conducts manual verification one by one. Due to the limited resource utilization rate of the database, if multiple risk control departments extract overdue data from the database simultaneously, it will affect the running speed of the database, thereby affecting the verification and processing efficiency of the overdue data. Summary of the Invention

[0004] The present invention provides a method and system for processing overdue data to solve the technical problem of low work efficiency in manually processing overdue data in the background art.

[0005] To achieve the above object, a technical solution of a method for processing overdue data according to the present invention includes:

[0006] Step S1: Set up a master database and multiple sub-databases, where the master database contains the overdue data of all the sub-databases;

[0007] Step S2: Generate multiple first queues in the master database. The overdue data in each first queue corresponds to the overdue data in the corresponding sub-database. Extract the credit scores in the overdue data and write the overdue data into each first queue according to the size of the credit scores;

[0008] Step S3: When verifying the overdue data, first select the overdue data with the highest credit score from the overdue data at the topmost position of each first queue, and verify the data with the overdue data in the sub-database that also contains the overdue data. After the verification is completed, remove the verified overdue data from the first queue, and then select the overdue data with the highest credit score from the overdue data at the topmost position of each first queue again for verification. Repeat this step until all the overdue data in all the first queues is removed;

[0009] Step S4: Obtain the upper extraction quantity of each first queue in real time, where the upper extraction quantity is the number of overdue data extracted from the first queue from top to bottom;

[0010] Step S5: Set a locking threshold, calculate the extraction difference between the upper extraction quantities of the two first queues. If there is an extraction difference that reaches the locking threshold, locate the queue with the smaller upper extraction quantity among the two first queues that reach the locking threshold, lock it, and prevent the overdue data at its topmost position from being extracted until the extraction difference is less than the locking threshold again.

[0011] Furthermore, in step S3, removing the verified overdue data from the first queue includes the following steps:

[0012] Step S31: Determine whether the overdue data passes the verification. If so, move the overdue data to the bottommost of the first queue; if not, execute step S32;

[0013] Step S32: Determine the identification information included in the overdue data that fails to pass the verification. The identification information includes a first identifier and a second identifier. If the overdue data does not contain any identification information, write the first identifier into the overdue data and insert the overdue data back to the first position in the selected first queue. If the overdue data contains the first identifier, write the second identifier into the overdue data and insert the overdue data back to the second position in the selected first queue. If the overdue data contains both the first identifier and the second identifier, move the overdue data to the second queue.

[0014] Furthermore, in step S31, the first position where the overdue data is inserted into the first queue is determined based on the following steps:

[0015] Obtain the number of remaining overdue data that needs to be inserted back into the first queue, and insert the overdue data into the first queue so that the number of rows between the row where the overdue data is located and the topmost overdue data in the current first queue is n 1 , n 1 Obtained through the first formula, and the first formula is: where δ 1 is the number of overdue data in the first queue, m 1 is the first preset value, and int() is the rounding function.

[0016] Furthermore, in step S32, the second position where the overdue data is inserted into the first queue is determined based on the following steps:

[0017] Obtain the number of remaining overdue data that needs to be inserted back into the first queue, and make the number of rows between the row where the overdue data is located and the topmost overdue data in the current first queue be n 2, n 2 Obtained by a second formula, the second formula being: where m 2 is a second preset value.

[0018] Furthermore, the overdue data in the second queue is verified manually.

[0019] The present invention also provides an overdue data processing system for implementing the above-mentioned overdue data processing method, the system comprising:

[0020] A scraping module for scraping overdue data;

[0021] A creating module for creating a first queue;

[0022] A filling module for filling the overdue data into the first queue;

[0023] A moving module for moving the position of the overdue data;

[0024] A calculating module for obtaining in real time the upper extraction quantity of each first queue and calculating a locking threshold based on the upper extraction quantity;

[0025] A locking module for locking the overdue data in the first queue so that it cannot be extracted.

[0026] Compared with the prior art, the beneficial effects of the present invention are at least as follows:

[0027] 1. The present invention sets up a total database and a sub-database and establishes a first queue, enabling the overdue data in the first queue to be automatically compared and verified with the data in the sub-database. Thus, before using the overdue data, the system pre-completes the verification of the overdue data in advance, reducing the work pressure of the salesperson. Secondly, since the data verification is initiated by the system, the verification speed of the system is not only faster than manual verification, but also the number of overdue data to be verified can be preset in advance, so that the access quantity of the database will not exceed the threshold, thereby reducing the access pressure on the database.

[0028] 2. Based on sorting the credit scores in the overdue data and filling them into the first queue, and then extracting and verifying them in sequence based on the sorting order, the overdue data with higher credit scores can be preferentially verified. Since the overdue data with higher credit scores will be preferentially used, this way can avoid the situation where the overdue data has not been verified when it is needed. By setting a locking threshold, the system will not always extract the same queue and ignore other queues, ensuring the balance of extraction. Through the present invention, not only can the automatic verification of overdue data be realized, reducing the access pressure on the database, but also by setting a locking threshold, the balance of verifying the overdue data of each risk control department is ensured. Description of the Drawings

[0029] Figure 1 It is a flowchart of the steps of a method for processing overdue data according to the present invention;

[0030] Figure 2 It is a schematic diagram of locking the first queue according to the present invention. Detailed Embodiment

[0031] In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0032] It can be understood that the terms "first", "second", etc. used in the present application may be used herein to describe various elements, but unless otherwise specified, these elements are not limited by these terms. These terms are only used to distinguish the first element from another element. For example, without departing from the scope of the present application, the first xx script may be referred to as the second xx script, and similarly, the second xx script may be referred to as the first xx script.

[0033] Such as Figure 1 , a method for processing overdue data, including:

[0034] Step S1: Set up a total database and a plurality of sub-databases. The total database contains the overdue data of all sub-databases;

[0035] By setting up the total database and sub-databases, the data in the total database comes from the sub-databases, and the sub-databases are maintained by the corresponding risk control departments. When the credit department uses the overdue data, it only needs to call the data from the total database. Compared with the traditional situation of only setting up one database, this setting method not only makes the database easy to maintain, but also disperses the access pressure of the database.

[0036] Step S2: Generate a plurality of first queues in the total database. The overdue data in each first queue corresponds to the overdue data in the corresponding sub-database. Extract the credit scores in the overdue data and write the overdue data into each first queue according to the size of the credit scores;

[0037] Step S3: When performing overdue data verification, first select the overdue data with the highest credit score from the overdue data at the topmost position of each first queue, and perform data verification with the overdue data in the sub-database that also contains this overdue data. After the verification is completed, remove the verified overdue data from the first queue, and then select the overdue data with the highest credit score from the overdue data at the topmost position of each first queue again for verification. Repeat this step until all the overdue data in the first queues are removed;

[0038] Specifically, in step S2, first write the overdue data with a larger credit score into the first queue, and then write the overdue data with a smaller credit score. Since the overdue data is extracted from the top of the first queue in step S3, the overdue data with a higher credit score will be verified first. Since customers with a higher credit score have a greater probability of repayment, notifying users with a higher credit score first can improve work efficiency. Moreover, verifying the overdue data with a higher credit score first can avoid the situation where the overdue data has not been verified when it is needed.

[0039] By setting multiple first queues, the overdue data is split into multiple groups, and each first queue corresponds to a sub-database managed by a risk control department. When there are problems with data verification, the risk control department responsible for managing and maintaining this overdue data can be quickly located according to the queue where the overdue data is located, thus improving the data processing efficiency.

[0040] Step S4: Obtain the upper-layer extraction quantity of each first queue in real time. The upper-layer extraction quantity is the number of overdue data extracted from the first queue from top to bottom;

[0041] Step S5: Set a locking threshold, calculate the extraction difference between the upper-layer extraction quantities of two first queues. If there is an extraction difference that reaches the locking threshold, locate the queue with the smaller upper-layer extraction quantity among the two first queues that reach the locking threshold, and lock it so that the overdue data at its topmost position is no longer extracted until the extraction difference is less than the locking threshold again.

[0042] If the credit score of the overdue data in a certain first queue is much larger than that of the overdue data in other queues, then the system will keep extracting the overdue data in this queue for verification and ignore other queues, which will affect the work of the corresponding risk control department; for example Figure 2Among them, there are three first queues, namely a, b, and c. The system always extracts the upper-layer overdue data of the first queue b from top to bottom, instead of extracting the first queue a and the first queue c. Therefore, by setting step S4 and step S5, this situation can be avoided. For example, the locking threshold is set to 3. When 3 upper-layer overdue data of the first queue b are extracted and the other two first queues have not been extracted yet, the first queue b is locked, so that the system can no longer select the first queue b for extraction, thus ensuring the balance of extraction and avoiding the situation that the overdue data in a certain risk control department cannot be verified for a long time.

[0043] The present invention sets up a total database and a sub-database, and establishes a first queue, so that the overdue data in the first queue is automatically compared and verified with the data in the sub-database. Thus, before using the overdue data, the system completes the verification of the overdue data in advance, reducing the work pressure of the salesman; secondly, since the data verification is initiated by the system, the verification speed of the system is not only faster than manual verification, but also the number of verified overdue data can be set in advance, so that the access quantity of the database will not exceed the threshold, thereby reducing the access pressure of the database.

[0044] Based on sorting the credit scores in the overdue data and filling them into the first queue, and then sequentially extracting and verifying based on the sorting order, the overdue data with higher credit scores can be preferentially verified. Since the overdue data with higher credit scores will be preferentially used, this way can avoid the situation that the overdue data has not been verified when it is needed; by setting the locking threshold, the system will not always extract the same queue and ignore other queues, ensuring the balance of extraction; through the present invention, not only can the automatic verification of overdue data be realized, reducing the access pressure of the database, but also by setting the locking threshold, the balance of verifying the overdue data of each risk control department is ensured.

[0045] Although the above technical solution enables the automatic verification of overdue data, however, when the verification of the overdue data is completed and the verification result is not passed, it needs to be verified again. If the overdue data that fails the verification is directly extracted and verified manually, it will lead to a certain waste of human resources, because the failure of the overdue data verification is not due to an error in the overdue data itself, but may be caused by the failure to update the overdue data in the total database or the sub-database in time; if the overdue data that fails the verification is retained and verified again after a period of time, the overdue data that fails the verification will occupy the reading resources of the total database, thereby reducing the verification efficiency of the total database for the overdue data.

[0046] Therefore, in step S3, removing the verified overdue data from the first queue includes the following steps:

[0047] Step S31: Determine whether the overdue data passes the verification. If so, move the overdue data to the bottom of the first queue; if not, execute Step S32;

[0048] Step S32: Determine the identification information included in the overdue data that fails the verification. The identification information includes a first identifier and a second identifier. If the overdue data does not contain any identification information, write the first identifier into the overdue data and insert the overdue data back to the first position in the selected first queue. If the overdue data contains the first identifier, write the second identifier into the overdue data and insert the overdue data back to the second position in the selected first queue. If the overdue data contains both the first identifier and the second identifier, move the overdue data to the second queue;

[0049] Through Step S31, the overdue data that passes the verification returns to the bottom of the first queue, so that it will not be verified for a long time; through Step S32, by setting identification information in the overdue data that fails the verification, the number of times the overdue data fails the verification is judged. If the overdue data contains the first identifier, it means that the overdue data has failed the verification once and needs to be verified again. If the overdue data contains both the first identifier and the second identifier, it means that there are two failures in verification. At this time, the overdue data should be moved from the first queue to the second queue. And regardless of whether the overdue data contains the first identifier and the second identifier, the verified overdue data will return to the first queue or the second queue. In addition, the total database will not extract the overdue data in the second queue for verification, so it will not occupy the reading resources; and by setting the second queue, the overdue data that fails the verification is concentrated in the second queue, which is convenient to distinguish from other overdue data.

[0050] In Step S31, determine the first position where the overdue data is inserted into the first queue based on the following steps:

[0051] Obtain the number of remaining overdue data that needs to be inserted back into the first queue, and insert the overdue data into the first queue so that the number of rows between the row where the overdue data is located and the topmost overdue data in the current first queue is n 1 ,n 1 Obtained through the first formula. The first formula is: where, δ 1 is the number of overdue data in the first queue, m 1 is the first preset value, and int() is the rounding function.

[0052] In Step S32, determine the second position where the overdue data is inserted into the first queue based on the following steps:

[0053] Obtain the number of remaining overdue data that need to be inserted back into the first queue, so that the number of rows between the row where the overdue data is located and the topmost overdue data in the current first queue is n 2 , n 2 Obtained through the second formula, and the second formula is: where m 2 is the second preset value.

[0054] Based on the above steps, determine the insertion position of the overdue data in the first queue through the first formula and the second formula, ensuring the verification interval of the overdue data; specifically, set m 1 in the first formula to 10. When the overdue data containing the first identifier needs to be inserted into the first queue, if the number of remaining overdue data in the first queue to be inserted is 50, then calculate n 1 through the first formula, and the value of n is 5. Then, after inserting the overdue data containing the first identifier into the first queue, there are 5 rows between the overdue data and the overdue data at the topmost position of the first queue, that is, the data is closer to the edge position of the first queue, making the value of n 1 not too large, and finally realizing that the extraction time interval of the overdue data will not be too long, so as to verify the overdue data again in a short time; similarly, set m 2 in the second formula to 2. When the overdue data containing the second identifier needs to be inserted into the first queue, if the number of remaining overdue data in the first queue to be inserted is 50, then calculate n 2 through the second formula, and the value of n is 25, that is, the position of the overdue data is closer to the middle position of the first queue, making the extraction time of the overdue data containing the second identifier have a longer time interval compared to the previous time. If it still cannot pass the verification after a long time interval, it indicates that the reason for the failure of the overdue data verification is not due to untimely database update, and manual verification is required.

[0055] In this embodiment, the overdue data located in the second queue is verified manually.

[0056] On the other hand, the present invention also provides a collection management system based on user portraits, which is used to implement the above-mentioned method for processing overdue data. The system includes:

[0057] A capture module for capturing overdue data;

[0058] A creation module for creating a first queue;

[0059] An input module for inputting overdue data into the first queue;

[0060] A movement module for moving the position of the overdue data;

[0061] A calculation module that obtains the upper-layer extraction quantity of each first queue in real time and calculates a locking threshold based on the upper-layer extraction quantity;

[0062] A locking module for locking the overdue data in the first queue so that it cannot be extracted.

[0063] It should be understood that although the steps in the flowcharts of the embodiments of the present invention are shown in sequence according to the arrows, these steps do not necessarily have to be executed in the order indicated by the arrows. Unless there is a clear description in this article, there is no strict order limit for the execution of these steps, and these steps can be executed in other orders. Moreover, at least a part of the steps in each embodiment may include multiple sub-steps or multiple stages. These sub-steps or stages do not necessarily have to be executed at the same moment, but can be executed at different moments. The execution order of these sub-steps or stages does not necessarily have to be sequential, but can be executed alternately or in turn with at least a part of other steps or sub-steps or stages of other steps.

[0064] Those of ordinary skill in the art can understand that all or part of the processes of implementing the methods in the above embodiments can be completed by instructing relevant hardware through a computer program. The above program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, storage, database, or other medium used in the embodiments provided in the present application can include non-volatile and / or volatile memories. Non-volatile memories can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memories can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and Rambus dynamic RAM (RDRAM), etc.

[0065] The technical features of the above embodiments can be combined arbitrarily. For the sake of concise description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification.

[0066] The above-mentioned embodiments only represent several implementation manners of the present invention. The description is relatively specific and detailed, but it should not be construed as a limitation on the scope of the patent of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present invention, several modifications and improvements can still be made, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the appended claims.

[0067] The above is only the preferred embodiment of the present invention, and it is not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for processing overdue data, characterized in that: The steps include: Step S1: Setting a main database and multiple sub-databases, wherein the main database contains overdue data of all the sub-databases; Step S2: generating a plurality of first queues in the general database, wherein the overdue data in each first queue corresponds to the overdue data in the corresponding sub-database, extracting the credit score in the overdue data, and writing the overdue data into the corresponding first queue in order from top to bottom and from small to large credit scores according to the credit score size; Step S3: When verifying the overdue data, firstly, the overdue data with the highest credit score is selected from the overdue data at the top of each first queue, and the data is verified with the overdue data in the sub-database that also contains the overdue data. After the verification is completed, the verified overdue data is removed from the first queue, and then the overdue data with the highest credit score is selected from the overdue data at the top of each first queue for verification again. This step is repeated until all the overdue data in the first queues are removed; Step S4: acquiring the upper layer extraction quantity of each first queue in real time, where the upper layer extraction quantity is the number of overdue data extracted from the first queue from top to bottom; Step S5: Set a locking threshold, calculate the extraction difference between the upper layer extraction quantities of the two first queues, and if the extraction difference reaches the locking threshold, locate the queue with the smaller upper layer extraction quantity among the two first queues that reach the locking threshold, and lock it so that the overdue data at the top layer position will no longer be extracted until the extraction difference is less than the locking threshold again.

2. A method for processing overdue data according to claim 1, characterized in that: In step S3, removing the overdue data that has completed verification from the first queue includes the following steps: Step S31: Determine whether the overdue data has passed the verification. If so, move the overdue data to the bottom of the first queue. If not, execute step S32. Step S32: Determine the identification information contained in the overdue data that has not passed the verification, and the identification information includes a first identification and a second identification. If the overdue data does not contain any identification information, write the first identification in the overdue data, and insert the overdue data back to the first position in the selected first queue. If the overdue data contains the first identification, write the second identification in the overdue data, and insert the overdue data back to the second position in the selected first queue. If the overdue data contains both the first identification and the second identification, move the overdue data to the second queue.

3. A method for processing overdue data according to claim 2, characterized in that In step S31, the first position for inserting the overdue data in the first queue is determined based on the following steps: The remaining number of overdue data to be inserted back into the first queue is obtained, and the overdue data is inserted into the first queue so that the number of rows between the row where the overdue data is located and the top overdue data in the current first queue is n1, and n1 is obtained by the first formula, which is: Among them, δ1 is the amount of overdue data in the first queue, m1 is the first preset value, and int() is the rounding function.

4. The overdue data processing method according to claim 2, characterized in that: In step S32, the second position for inserting the overdue data into the first queue is determined based on the following steps: The remaining number of overdue data that needs to be inserted back into the first queue is obtained so that the number of rows between the row where the overdue data is located and the top overdue data in the current first queue is n2. n2 is obtained by the second formula, which is: Among them, m2 is the second preset value.

5. The overdue data processing method according to claim 2, characterized in that: The overdue data in the second queue is verified manually.

6. An overdue data processing system, used to implement the method according to any one of claims 1 to 5, characterized in that: include: The crawling module is used to crawl overdue data; A creation module is used to create a first queue; A filling module, used to fill overdue data into the first queue; A moving module, used to move the location of overdue data; A calculation module, which obtains the upper layer extraction quantity of each first queue in real time, and calculates a locking threshold based on the upper layer extraction quantity; The locking module is used to lock the overdue data in the first queue so that it cannot be extracted.

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