A data reporting method and device, and a storage medium

Abstract

Embodiments of the present application disclose a data reporting method and device, and a storage medium, including: obtaining credit source data corresponding to a credit service; grouping the credit source data to obtain grouped data; obtaining target grouped data from the grouped data when a credit reporting time is reached; determining reporting data from the target grouped data; generating a credit report according to the reporting data; and reporting the credit report to a credit device.

Description

Technical Field

[0001] This application relates to the field of data reporting technology, and in particular to a data reporting method, apparatus, and storage medium. Background Technology

[0002] Credit data reporting for credit business mainly involves calculating the corresponding credit report based on the credit business data, then sending the credit report to the People's Bank of China Credit Reference Center and merging it with data submitted by other financial institutions to form the final credit report, which is then provided to various financial institutions.

[0003] In existing technologies, Extract-Transform-Load (ETL) is used to process credit business data corresponding to credit business to obtain corresponding credit reporting messages. However, due to the complexity of the ETL process for reporting credit business data, the process of obtaining credit reporting messages is time-consuming, thereby reducing the speed of credit reporting. Summary of the Invention

[0004] To address the aforementioned technical problems, embodiments of this application aim to provide a data reporting method, apparatus, and storage medium that can improve the accuracy of determining the probability of target loss warning.

[0005] The technical solution of this application is implemented as follows:

[0006] This application provides a data reporting method, the data reporting method including:

[0007] Obtain credit source data corresponding to credit business; and group the credit source data to obtain grouped data;

[0008] When the credit reporting time arrives, the target group data is obtained from the group data;

[0009] Determine the data to be reported from the target group data;

[0010] Based on the reported data, a credit reporting message is generated; and the credit reporting message is reported to the credit reporting device.

[0011] This application provides a data reporting device, the device comprising:

[0012] The acquisition unit is used to acquire credit source data corresponding to credit business; and to acquire target group data from the group data when the credit reporting time arrives.

[0013] A grouping unit is used to group the credit source data to obtain grouped data;

[0014] The determining unit is used to determine the reporting data from the target group data;

[0015] The generation unit is used to generate credit reports based on the submitted data;

[0016] The reporting unit is used to report the credit reporting message to the credit reporting device.

[0017] This application provides a data reporting device, the device comprising:

[0018] The system includes a memory, a processor, and a communication bus. The memory communicates with the processor via the communication bus. The memory stores a data reporting program that can be executed by the processor. When the data reporting program is executed, the processor performs the data reporting method described above.

[0019] This application provides a storage medium storing a computer program for use in a data reporting device. The computer program, when executed by a processor, implements the data reporting method described above.

[0020] This application provides a data reporting method, apparatus, and storage medium. The data reporting method includes: acquiring credit source data corresponding to a credit business; grouping the credit source data to obtain grouped data; when the credit reporting time arrives, acquiring target grouped data from the grouped data; determining the reporting data from the target grouped data; generating a credit report based on the reporting data; and reporting the credit report to the credit reporting device. By employing the above method, the data reporting apparatus simplifies the steps of generating a credit report based on credit source data corresponding to a credit business by grouping the credit source data to obtain grouped data; acquiring target grouped data from the grouped data when the credit reporting time arrives; determining the reporting data from the target grouped data; and generating a credit report based on the reporting data. This shortens the time required to obtain the credit report and thus improves the speed of credit report reporting. Attached Figure Description

[0021] Figure 1 A schematic diagram of a credit data reporting source and target in the prior art provided in this application embodiment;

[0022] Figure 2 This application provides a schematic diagram of a data reporting process in the prior art.

[0023] Figure 3 A flowchart of a data reporting method provided in an embodiment of this application;

[0024] Figure 4 An exemplary engine illustration diagram provided for embodiments of this application;

[0025] Figure 5A schematic diagram of an exemplary data reporting structure provided in this application embodiment. Figure 1 ;

[0026] Figure 6 A flowchart illustrating an exemplary data reporting method provided in this application embodiment;

[0027] Figure 7 A schematic diagram of an exemplary data reporting structure provided in this application embodiment. Figure 2 ;

[0028] Figure 8 A schematic diagram of an exemplary data reporting structure provided in this application embodiment. Figure 3 ;

[0029] Figure 9 A schematic diagram of an exemplary data reporting structure provided in this application embodiment. Figure 4 ;

[0030] Figure 10 A schematic diagram of the composition structure of a data reporting device provided in this application embodiment. Figure 1 ;

[0031] Figure 11 A schematic diagram of the composition structure of a data reporting device provided in this application embodiment. Figure 2 . Detailed Implementation

[0032] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit this application.

[0033] Credit reporting for lending businesses, such as Figure 1 As shown, ETL processing logic is used to process business data (credit information, loan agreement information, repayment plan, repayment transaction, guarantee information, and basic information) to obtain message data (loan account, credit agreement, collateral contract, and basic information). Specifically, as... Figure 2 As shown, the ETL processing logic uses the first calculation layer, the second calculation layer, ..., the calculation layer and the integration layer to process the business data (credit information, loan information, repayment plan, repayment transaction, guarantee information and basic information) in sequence to obtain message data (loan account, credit agreement, collateral contract and basic information).

[0034] The existing credit reporting methods for credit business use a large number of stored procedures or SQL scripts to complete a series of program calculations in complex computing units. This requires stacking many repetitive calculation units, which makes the calculation logic complex, causes slow operation, readability issues, and redundant calculations, among other problems.

[0035] The existing credit reporting methods for credit business can also reduce the complexity of the program by breaking down the complex calculation program into multiple units for separate calculation. However, this also leads to the need for multiple joint queries on the same set of source tables, resulting in a significant increase in computing resources and a doubling of storage resources.

[0036] In existing credit reporting methods, individual resources are split into multiple parts, and their inter-relationships need to be managed through other programs. There are no strong dependencies between intermediate tables, which brings unpredictable troubles to subsequent operation and maintenance.

[0037] Current credit reporting methods for lending operations, due to their multi-layered structure, exhibit a critical path. The overall computation time depends on the time taken for this critical path; other paths must wait for the critical path to complete before participating in the next layer's computation. Further splitting the process to address this issue would require even more computational resources and storage space.

[0038] The existing credit reporting methods for credit business are based on a horizontally layered calculation logic, requiring layer-by-layer calculations from the source table to the result table, resulting in long testing cycles and poor timeliness.

[0039] The problems existing in the prior art can be solved by the method described in Example 1.

[0040] Example 1

[0041] This application provides a data reporting method, which is applied to a data reporting device. Figure 3 A flowchart of a data reporting method provided in this application embodiment is shown below. Figure 3 As shown, data reporting methods may include:

[0042] S101. Obtain the credit source data corresponding to the credit business; and group the credit source data to obtain grouped data.

[0043] The data reporting method provided in this application embodiment is applicable to scenarios where credit source data is determined to correspond to credit reporting messages.

[0044] In the embodiments of this application, the data reporting device can be implemented in various forms. For example, the data reporting device described in this application may include devices such as mobile phones, cameras, tablet computers, laptops, handheld computers, personal digital assistants (PDAs), portable media players (PMPs), navigation devices, wearable devices, smart bracelets, pedometers, etc., as well as devices such as digital TVs, desktop computers, servers, etc.

[0045] In this embodiment, the data reporting device can periodically acquire credit source data corresponding to the credit business; the data reporting device can also acquire the credit source data corresponding to the credit business upon receiving a credit source data acquisition instruction; the data reporting device can also acquire the credit source data corresponding to the credit business in other ways; the specific method by which the data reporting device acquires the credit source data corresponding to the credit business can be determined according to the actual situation, and this embodiment does not limit it.

[0046] It should be noted that if the data reporting device acquires credit source data corresponding to the credit business at regular intervals, the timing time can be 8:00 AM every day; the timing time can also be 10:00 AM every day; the timing time can also be other times; the specific timing time can be determined according to the actual situation, and this application embodiment does not limit it.

[0047] In this embodiment, the data reporting device can obtain credit source data corresponding to the credit business from the credit business system; the data reporting device can also obtain credit source data corresponding to the credit business from the database; the data reporting device can also obtain credit source data corresponding to the credit business based on user input information; the data reporting device can also obtain credit source data corresponding to the credit business in other ways; the specific way the data reporting device obtains credit source data corresponding to the credit business can be determined according to the actual situation, and this embodiment does not limit it.

[0048] In this embodiment of the application, the credit source data can be the source data corresponding to one credit transaction; it can be the source data corresponding to two credit transactions; or it can be the source data corresponding to multiple credit transactions. The specific credit source data can be determined according to the actual situation, and this embodiment of the application does not limit it.

[0049] It should be noted that if the credit source data is source data corresponding to multiple credit transactions, then the multiple credit transactions can be credit data corresponding to one customer; the multiple credit transactions can also be credit data corresponding to two customers; the multiple credit transactions can also be credit data corresponding to multiple customers; the specifics can be determined according to the actual situation, and this application embodiment does not limit this.

[0050] In this embodiment of the application, the process by which the data reporting device acquires credit source data corresponding to the credit business includes: the data reporting device acquiring credit granting data, loan receipt data, repayment plan data, repayment transaction data, guarantee data, and customer data corresponding to the credit business; the data reporting device using the credit granting data, loan receipt data, repayment plan data, repayment transaction data table, guarantee data, and customer data as credit source data.

[0051] In this embodiment of the application, the process of the data reporting device grouping credit source data to obtain grouped data includes: filtering first source data of revolving credit loans with unified repayment management from the credit source data, and grouping the first source data with the credit agreement number as the grouping field to obtain grouped data; or, the data reporting device filtering second source data of revolving credit loans with non-unified repayment management from the credit source data, and grouping the second source data with the loan receipt number as the grouping field to obtain grouped data; or, the data reporting device filtering third source data of non-revolving credit loans issued in a one-time manner from the credit source data, and grouping the third source data with the loan receipt number as the grouping field to obtain grouped data; or, the data reporting device filtering fourth source data of non-revolving credit loans issued in a non-one-time manner from the credit source data, and grouping the fourth source data with the credit agreement number as the grouping field to obtain grouped data.

[0052] It should be noted that the first source data includes credit data, loan agreement data, repayment plan data, repayment transaction data, guarantee data, and customer data; the second source data includes credit data, loan agreement data, repayment plan data, repayment transaction data, guarantee data, and customer data; the third source data includes credit data, loan agreement data, repayment plan data, repayment transaction data, guarantee data, and customer data; and the fourth source data includes credit data, loan agreement data, repayment plan data, repayment transaction data, guarantee data, and customer data.

[0053] In the embodiments of this application, the number of grouped data can be one group; the number of grouped data can be two groups; the number of grouped data can be multiple groups; the specific number of grouped data can be determined according to the actual situation, and the embodiments of this application do not limit this.

[0054] In this embodiment, the process of the data reporting device grouping the first source data using the credit agreement number as the grouping field to obtain grouped data includes: the data reporting device searching for data with the same credit agreement number field in the first source data, and grouping the data with the same credit agreement number field as a group of grouped data, thereby obtaining the grouped data. That is, one group of grouped data corresponds to one credit agreement number; multiple groups of grouped data correspond to multiple credit agreement numbers.

[0055] In this embodiment, the process of the data reporting device grouping the second source data using the loan receipt number as the grouping field to obtain grouped data includes: the data reporting device searching for data with the same loan receipt number field in the second source data, and grouping the data with the same loan receipt number field as a group of grouped data, thereby obtaining grouped data. That is, one group of grouped data corresponds to one loan receipt number; multiple groups of grouped data correspond to multiple loan receipt numbers.

[0056] In this embodiment, the process of the data reporting device grouping the third source data using the loan receipt number as the grouping field to obtain grouped data includes: the data reporting device searching for data with the same loan receipt number field in the third source data, and grouping the data with the same loan receipt number field as a group of grouped data, thereby obtaining grouped data. That is, one group of grouped data corresponds to one loan receipt number; multiple groups of grouped data correspond to multiple loan receipt numbers.

[0057] In this embodiment, the process of the data reporting device grouping the fourth source data using the credit agreement number as the grouping field to obtain grouped data includes: the data reporting device searching for data with the same credit agreement number field in the fourth source data, and grouping the data with the same credit agreement number field as a group of grouped data, thereby obtaining the grouped data. That is, one group of grouped data corresponds to one credit agreement number; multiple groups of grouped data correspond to multiple credit agreement numbers.

[0058] In this embodiment of the application, the credit source data includes first source data and / or second source data and / or third source data and / or fourth source data.

[0059] In this embodiment of the application, the process of the data reporting device grouping credit source data to obtain grouped data includes: the data reporting device compressing the credit source data to obtain compressed data; and the data reporting device grouping the compressed data to obtain grouped data.

[0060] In this embodiment, the data reporting device groups compressed data to obtain grouped data in the following ways: First, the data reporting device filters the compressed data for first-source data of revolving credit loans with unified repayment management, and groups the first-source data using the credit agreement number as the grouping field to obtain grouped data; second, the data reporting device filters the compressed data for second-source data of revolving credit loans with non-unified repayment management, and groups the second-source data using the loan receipt number as the grouping field to obtain grouped data; third, the data reporting device filters the compressed data for third-source data of non-revolving credit loans issued in a one-time manner, and groups the third-source data using the loan receipt number as the grouping field to obtain grouped data; fourth, the data reporting device filters the compressed data for fourth-source data of non-revolving credit loans issued in a non-one-time manner, and groups the fourth-source data using the credit agreement number as the grouping field to obtain grouped data.

[0061] In this embodiment, the data reporting device compresses the credit source data to obtain compressed data. This compression can occur in several ways: the data reporting device compresses the credit source data to obtain compressed data with one field; it can also compress the credit source data to obtain compressed data with two fields; or it can compress the credit source data to obtain compressed data of other sizes. The specific method by which the data reporting device compresses the credit source data to obtain compressed data can be determined based on actual circumstances, and this embodiment does not limit this approach.

[0062] In this embodiment, the process of the data reporting device compressing credit source data to obtain compressed data includes: the data reporting device grouping credit data according to customer number and credit agreement number to obtain grouped credit data; and compressing the grouped credit data to obtain compressed credit data; the data reporting device grouping loan receipt data according to customer number, credit agreement number, and loan receipt number to obtain grouped loan receipt data; and compressing the grouped loan receipt data to obtain compressed loan receipt data; the data reporting device grouping repayment plan data according to loan receipt number to obtain grouped repayment plan data; and compressing the grouped repayment plan data to obtain compressed repayment plan data; the data reporting device then... The data transmission device groups repayment transaction data according to the loan agreement number to obtain grouped repayment transaction data; then compresses the grouped repayment transaction data to obtain compressed repayment transaction data. The data transmission device groups guarantee data according to the credit agreement number to obtain grouped guarantee data; then compresses the grouped guarantee data to obtain compressed guarantee data. The data transmission device groups customer data according to customer number to obtain grouped customer data; then compresses the grouped customer data to obtain compressed customer data. The data transmission device uses the compressed credit data, compressed loan agreement data, compressed repayment plan, compressed guarantee data, compressed customer data, and compressed repayment transactions as compressed data.

[0063] In the embodiments of this application, the number of group credit granting data can be one group; the number of group credit granting data can also be two groups; the number of group credit granting data can also be multiple groups; the specific number of group credit granting data can be determined according to the actual situation, and the embodiments of this application do not limit it.

[0064] It should be noted that the credit agreement number, customer number, and group credit data are in one-to-one correspondence; specifically, one credit agreement number corresponds to one customer number and one group of group credit data.

[0065] In this embodiment of the application, the number of grouped loan receipt data can be one group; the number of grouped loan receipt data can also be two groups; the number of grouped loan receipt data can also be multiple groups; the specific number of grouped loan receipt data can be determined according to the actual situation, and this embodiment of the application does not limit it.

[0066] It should be noted that the credit agreement number, customer number, loan receipt number, and grouped loan receipt data are in one-to-one correspondence; specifically, one credit agreement number corresponds to one customer number, one loan receipt number, and one group of grouped loan receipt data.

[0067] In this embodiment of the application, the number of group repayment plan data can be one group; the number of group repayment plan data can also be two groups; the number of group repayment plan data can also be multiple groups; the specific number of group repayment plan data can be determined according to the actual situation, and this embodiment of the application does not limit it.

[0068] It should be noted that there is a one-to-one correspondence between the IOU number and the group repayment plan data; specifically, one IOU number corresponds to one group repayment plan data.

[0069] In this embodiment of the application, the group repayment transaction data can be one group; the number of group repayment transaction data can also be two groups; the number of group repayment transaction data can also be multiple groups; the specific number of group repayment transaction data can be determined according to the actual situation, and this embodiment of the application does not limit it.

[0070] It should be noted that there is a one-to-one correspondence between the IOU number and the group repayment transaction data; specifically, one IOU number corresponds to one group repayment transaction data.

[0071] In this embodiment of the application, the number of grouped guarantee data can be one group; the number of grouped guarantee data can also be two groups; the number of grouped guarantee data can also be multiple groups; the specific number of grouped guarantee data can be determined according to the actual situation, and this embodiment of the application does not limit it.

[0072] It should be noted that there is a one-to-one correspondence between the credit agreement number and the group guarantee data; specifically, one credit agreement number corresponds to one group guarantee data.

[0073] In this embodiment of the application, the number of customer data groups can be one group; the number of customer data groups can be two groups; the number of customer data groups can be multiple groups; the specific number of customer data groups can be determined according to the actual situation, and this embodiment of the application does not limit this.

[0074] It should be noted that there is a one-to-one correspondence between customer IDs and group customer data; specifically, one customer ID corresponds to one group of group customer data.

[0075] S102. When the credit reporting time arrives, retrieve the target group data from the group data.

[0076] In this embodiment of the application, the data reporting device acquires credit source data corresponding to the credit business; and groups the credit source data to obtain grouped data. After obtaining the grouped data, the data reporting device acquires the target grouped data from the grouped data when the credit reporting time arrives.

[0077] In this embodiment, the credit reporting time can be the time configured in the data reporting device; the credit reporting time can also be the time transmitted from other devices to the data reporting device; the credit reporting time can also be the time obtained by the user input value in the data reporting device; the specific method by which the data reporting device obtains the credit reporting time can be determined according to the actual situation, and this embodiment does not limit it.

[0078] For example, the credit reporting time can be the 1st of each month; the credit reporting time can also be the 10th of each month; the credit reporting time can also be other times; the specific credit reporting time can be determined according to the actual situation, and this application embodiment does not limit it.

[0079] In the embodiments of this application, the number of target group data can be one set; the number of target group data can also be two sets; the number of target group data can also be multiple sets; the specific number of target group data can be determined according to the actual situation, and the embodiments of this application do not limit it.

[0080] It should be noted that the target group data is data that matches the credit reporting time. That is, the data required for reporting during the credit reporting period.

[0081] In this embodiment of the application, the process by which the data reporting device obtains target group data from the group data when the credit reporting time arrives includes: determining the data indicator corresponding to the credit reporting time when the credit reporting time arrives; and the data reporting device obtaining the target group data matching the data indicator from the group data.

[0082] It should be noted that data indicators may include account opening date, loan type, loan amount, loan balance, overdue amount, overdue principal, number of overdue periods, account status, repayment status, repayment method, repayment frequency, etc.

[0083] S103. Determine the data to be reported from the target group data.

[0084] In this embodiment of the application, when the credit reporting time is reached, the data reporting device obtains the target group data from the group data, and then determines the reporting data from the target group data.

[0085] In this embodiment of the application, the process of the data reporting device determining the reporting data from the target group data includes: the data reporting device determining the reporting method corresponding to the target group data; the data reporting device determining the data value corresponding to the data indicator according to the reporting method and the target group data; the data reporting device combining the data value according to the reporting format of the preset data segment to obtain the combined data; and the data reporting device using the combined data as the reporting data.

[0086] It should be noted that the preset data segments include customer data segments, loan account data segments, credit agreement data segments, and mortgage (pledge) contract data segments.

[0087] In the embodiments of this application, the reporting methods include consolidated reporting of revolving credit limits, single reporting of revolving credit limits, consolidated reporting of non-revolving credit limits, and single reporting of non-revolving credit limits.

[0088] S104. Generate a credit reporting message based on the reported data; and report the credit reporting message to the credit reporting device.

[0089] In this embodiment of the application, after the data reporting device determines the reporting data from the target group data, the data reporting device generates a credit reporting message based on the reporting data and reports the credit reporting message to the credit reporting device.

[0090] In this embodiment of the application, the data in the credit reporting message includes customer data, loan account data records, credit agreement data records, and mortgage (pledge) contract data records, etc.

[0091] Understandably, this application uses a vertical calculation process to group credit source data according to a series of rules, and then processes each group through a pre-defined program. First, it determines whether the reporting time point is met, reducing unnecessary calculations and saving computing resources. For grouped data that meets the conditions, the intermediate calculation results are cached in memory, and the corresponding indicator values ​​are extracted during the final integration to synthesize the results required by the business rules. Source data association queries are completed in one go, reducing the waste of computing resources caused by the reuse of source tables. Horizontal processing is transformed into vertical processing, calculating the required intermediate and final results in one go, solving the problems of excessive layering or critical paths. Intermediate results are cached in memory for reuse, reducing the need for repeated calculations for various business results and lowering the requirements for computing and storage resources. High-level development languages ​​(such as Python, Java, Scala, etc.) are used to complete the program coding, enhancing structure and improving readability. It also effectively utilizes the abstraction and decoupling capabilities of high-level languages, ensuring strong structure and traceable dependencies while making it very easy to modify a unit without affecting other units. Auxiliary unit testing and combination testing methods are used to quickly verify the accuracy of the code.

[0092] For example, such as Figure 4As shown: The data reporting device acquires credit source data (credit grant data, loan agreement data, repayment plan data, repayment transaction data, guarantee data, and customer data) corresponding to credit business; and groups the credit source data to obtain grouped data; when the credit reporting time arrives, it determines the data indicators (primary indicators and N-level indicators, which are newly added calculation engines, and the calculation results of primary and N-level indicators are cached in memory); it obtains target grouped data matching the data indicators from the grouped data; it determines the reporting data (loan account processing, credit agreement processing, collateral contract processing, and basic information processing) from the target grouped data; based on the reporting data, it generates a credit reporting message (message data, which includes loan accounts, credit agreements, collateral contracts, and basic information); and it reports the credit reporting message to the credit reporting device.

[0093] It should be noted that the primary indicators include: minimum loan date, maximum maturity date, total balance, maximum expected number of days, amount due this month, amount actually repaid this month, and amount of collateral. The secondary indicators include: minimum loan date, maximum maturity date, total balance, maximum expected number of days, amount due this month, amount actually repaid this month, and amount of collateral.

[0094] In the embodiments of this application, such as Figure 5 As shown: The data reporting device acquires credit source data (credit grant data (credit information), loan agreement data (loan agreement information), repayment plan data (repayment plan), repayment transaction data (repayment transaction), guarantee data (guarantee information), and product configuration) corresponding to credit business; and groups the credit source data to obtain grouped data (revolving credit line merged reporting with the grouping field being the credit agreement number, non-revolving credit line merged reporting with the grouping field being the credit agreement number, revolving credit line single reporting with the grouping field being the loan agreement number, and non-revolving credit line single reporting with the grouping field being the loan agreement number); when the credit reporting time arrives, the data reporting device determines the data indicators corresponding to the credit reporting time; it obtains the target grouped data matching the data indicators from the grouped data (merging and calculating the merged reporting data; calculating the single reporting data individually); it determines the reporting data from the target grouped data; and generates credit reports (loan account records, credit agreement records, and collateral contract records) based on the reporting data.

[0095] It should be noted that Group 1, where the revolving credit line is submitted in a consolidated manner and the grouping field is the credit agreement number, includes: IOU information 1…n, credit information 1…n, guarantee information 1…n, repayment plan 1…n, and repayment transaction 1…n; Group 2, where the non-revolving credit line is submitted in a consolidated manner and the grouping field is the credit agreement number, includes: IOU information 1…n, credit information 1…n, guarantee information 1…n, repayment plan 1…n, and repayment transaction 1…n; Group 3, where the revolving credit line is submitted in a single transaction and the grouping field is the IOU number, includes: IOU information 1…n, credit information 1…n, guarantee information 1…n, repayment plan 1…n, and repayment transaction 1…n; and Group 4, where the non-revolving credit line is submitted in a single transaction and the grouping field is the IOU number, includes: IOU information 1…n, credit information 1…n, guarantee information 1…n, repayment plan 1…n, and repayment transaction 1…n.

[0096] It should be noted that the indicator data includes: account opening date, loan type, loan amount, loan balance, overdue amount, overdue principal, number of overdue periods, repayment method, repayment frequency, settlement due date, amount due this month, amount actually repaid this month, last repayment date, five-tier classification, five-tier classification adjustment date, related repayment responsibilities, collateral contracts, credit effective date, credit expiry date, credit amount, co-creditors and expiry date.

[0097] For example, such as Figure 6 As shown:

[0098] S61. The data reporting device acquires credit source data corresponding to the credit business.

[0099] S62A, the data reporting device filters the first source data of revolving credit loans and unified repayment management from the credit source data, and groups the first source data with the credit agreement number as the grouping field to obtain grouped data.

[0100] S62B, the data reporting device filters the second source data of revolving credit loans with non-uniform repayment management from the credit source data, and groups the second source data by the loan number as the grouping field to obtain grouped data.

[0101] The S62C data reporting device filters out third-source data from the credit source data, which are non-revolving credit loans issued in a single transaction, and groups the third-source data by the loan receipt number as the grouping field to obtain grouped data.

[0102] S62D and the data reporting device filter out the fourth source data of non-revolving credit loans that are not issued in a one-time manner from the credit source data, and group the fourth source data by the credit agreement number to obtain grouped data.

[0103] It should be noted that after the data reporting device completes step S61, it can then proceed to step S62A; after the data reporting device completes step S61, it can then proceed to step S62B; after the data reporting device completes step S61, it can then proceed to step S62C; after the data reporting device completes step S61, it can then proceed to step S62D.

[0104] S63. When the credit reporting time arrives, the data reporting device determines the data indicators corresponding to the credit reporting time.

[0105] S64. The data reporting device obtains target group data that matches the data indicators from the group data.

[0106] S65. The data reporting device determines the reporting method corresponding to the target group data.

[0107] S66. The data reporting device determines the data value corresponding to the data indicator based on the reporting method and the target group data.

[0108] For example, if the data indicator is the loan balance and the reporting method is single reporting, the data reporting device obtains the data value corresponding to the current loan balance of the user from the target group data; if the data indicator is the loan balance and the reporting method is combined reporting, the data reporting device obtains the loan balance data corresponding to all loans of the user from the target group data, and obtains the data value corresponding to all loan balances of the user based on the loan balance data.

[0109] S67. The data reporting device combines the data values ​​according to the preset data segment reporting format to obtain combined data.

[0110] It should be noted that the preset data segments include customer data segments, loan account data segments, credit agreement data segments, and mortgage (pledge) contract data segments.

[0111] For example, if the preset data segment is a loan account data segment, the data reporting device obtains the loan account data value that matches the reporting format of the loan account data segment from the data value; the data reporting device assembles the loan account data value into a corresponding data segment, thereby obtaining the loan account data segment.

[0112] For example, if the preset data segment is a credit agreement data segment, the data reporting device obtains the credit agreement data value that matches the reporting format of the credit agreement data segment from the data value; the data reporting device assembles the credit agreement data value into a corresponding data segment, thereby obtaining the credit agreement data segment.

[0113] S68. The data reporting device uses the combined data as the reporting data.

[0114] S69. The data reporting device generates a credit reporting message based on the reported data and reports the credit reporting message to the credit reporting device.

[0115] For example, taking a loan account information table as an example, such as Figure 7 As shown: In distributed big data computing, data from the same group of computing units is distributed to the same machines for computation based on the grouping field. For example, authorization information (L1), loan information (A1, A2), and account type (R1) are transmitted to machine 1 for computation, resulting in R1 (merged calculation), which is then stored in a Hive table. Authorization information (L2, L3), loan information (A3, A4, A5, A6), and account type (R1, R4) are transmitted to machine 2 for computation (L2(A3, A4, A5)), resulting in R1 (merged calculation). Machine 2 then performs calculations on (L3(A6)) to obtain R4 (single calculation). Each transaction is calculated individually and stored in a Hive table. Authorization information (L4, L5, L6), loan information (A7, A8, A9, A10, A11), and account type (R1, R4) are transmitted to machine 3 for calculation (L4(A7)) to obtain single transaction D1. Machine 3 is used to calculate (L5(A8)) to obtain single transaction R4. Machine 3 is used to calculate (L6(A9, A10, A11)) to obtain combined transaction D1, and stored in a Hive table.

[0116] For example, using a consolidated loan account for revolving credit limits as an example: 1. A customer successfully applied for a credit limit of 100,000 yuan on January 1, 2021, valid for one year, and borrowed 10,000 yuan on the same day, repaying it in 10 installments of equal principal and interest, with each installment's principal + interest payment being 1,100 yuan. The first repayment date for this loan was February 1. 2. The customer successfully borrowed 20,000 yuan on January 20, 2021, with the first repayment date for this loan being March 1. It was to be repaid in 10 installments of equal principal and interest, with each installment's principal + interest payment being 2,200 yuan. 3. The customer repaid the principal + interest of 1,100 yuan on February 1, 2021.

[0117] Engine Calculation: 1. On January 1, 2021, the case data was processed according to the rules for merging and reporting revolving credit limits. The engine calculated two reporting records: one for the loan account opening date equal to the current date (report 10 - account opening); and another for the credit approval effective date equal to the current date (report 10 - credit approval effective). Collateral contracts were not involved. Specifically, such as... Figure 8As shown: The data reporting device acquires credit source data (credit grant data (credit information), loan receipt data (loan receipt information), repayment plan data (repayment plan), repayment transaction data (repayment transaction), guarantee data (guarantee information), and product configuration) corresponding to the credit business; and groups the credit source data to obtain grouped data (Group 1: revolving credit limit merged reporting and the grouping field is the credit agreement number); when the credit reporting time arrives, the data reporting device determines the data indicators corresponding to the credit reporting time (account opening date (2021-01-01), loan type (1-loan), loan amount (10000), loan balance (10000), overdue amount (0), overdue principal (0), overdue period (0), account status (normal), repayment status (normal), repayment method (principal and interest calculated periodically), repayment frequency (monthly)). ), Settlement due date (2021-01-01), Amount due this month (0), Actual amount repaid this month (0), Last repayment date (2021-01-01), Five-level classification (1), Five-level classification adjustment date (2021-01-01), Related repayment responsibility (none), Collateral contract (none), Authorization agreement number (C1), Credit effective date (2021-01-01), Credit expiration date (2021-01-01), Credit adjustment expiration date (empty), Credit amount (100000), Co-creditors (none) and expiration date (2021-01-01); Obtain target group data matching the data indicators from the group data (merge and calculate the merged data); Determine the reporting data from the target group data; Generate credit reports (loan accounts, credit agreements) based on the reporting data.

[0118] It should be noted that the data corresponding to Group 1 includes: loan receipts, authorization information, guarantee information, repayment plans, and repayment transactions. Specifically, the loan receipt includes the loan receipt number (L1), loan disbursement date (2021-01-01), loan amount (10000), balance (9000), due date (2021-11-01), loan status (1-Normal), repayment method (equal principal and interest payments), authorization agreement number (C1), overdue days (0), overdue amount (0), and overdue principal. The authorization information includes: credit agreement number (C1), credit start date (2021-01-01), credit end date (2022-01-01), credit adjustment date (empty), renewal date (empty), and credit amount (1000000). The repayment plan includes: loan receipt number (L1), settlement repayment date (2021-02-01), principal due (1000), and interest due (100).

[0119] It should be noted that the loan account includes: reporting time (10-account opening), account opening date (2021-01-01), loan type (1-loan), loan amount (10000), overdue amount (0), overdue principal (0), number of overdue periods (0), repayment method (principal and interest repaid periodically), repayment frequency (monthly), settlement due date (2021-01-01), amount due this month (0), amount actually repaid this month (0), last repayment date (2021-01-01), five-level classification (1), five-level classification adjustment date (2021-02-01), related repayment liability (none), account status (normal), repayment status (normal), credit agreement number (C1).

[0120] It should be noted that the credit agreement includes: the reporting date (10-credit limit effective date), credit agreement number (C1), credit effective date (2021-01-01), credit expiration date (2022-01-01), and co-creditors (none).

[0121] Engine calculations: 2. Data calculation results for February 1, 2021 include: the settlement due date is that day, and the loan account reports monthly settlements. The credit line change date is blank and does not need to be reported; collateral contracts are not involved. Specifically, such as... Figure 9As shown: The data reporting device acquires credit source data (credit grant data (credit information), loan receipt data (loan receipt information), repayment plan data (repayment plan), repayment transaction data (repayment transaction), guarantee data (guarantee information), and product configuration) corresponding to the credit business; and groups the credit source data to obtain grouped data (Group 1: revolving credit limit merged reporting and the grouping field is the credit agreement number); when the credit reporting time arrives, the data reporting device determines the data indicators corresponding to the credit reporting time (account opening date (2021-01-01), loan type (1-loan), loan amount (10000), loan balance (10000), overdue amount (0), overdue principal (0), overdue period (0), account status (normal), repayment status (normal), repayment method (principal and interest calculated on schedule), repayment frequency) Rate (monthly), Settlement due date (2021-01-01), Amount due this month (0), Actual amount repaid this month (0), Last repayment date (0), Five-level classification (1), Five-level classification adjustment date (2021-01-01), Related repayment liability (none), Collateral contract (none), Authorization agreement number (C1), Credit effective date (2021-01-01), Credit expiry date (2021-01-01), Adjustment expiry date (empty), Credit amount (1,000,000), Co-creditors (none) and expiry date (2021-01-01); Obtain target group data matching the data indicators from the group data (merge and calculate the merged data); Determine the reporting data from the target group data; Generate credit reports (loan accounts, credit agreements) based on the reporting data.

[0122] It should be noted that the data corresponding to Group 1 includes: loan receipts, authorization information, guarantee information, repayment plans, and repayment transactions. Specific loan receipts include: Loan Receipt Number (L1), Loan Date (2021-01-01), Loan Amount (10000), Balance (9000), Maturity Date (2021-11-01), Loan Status (1-Normal), Repayment Method (Equal Principal and Interest Repayment), Authorization Agreement Number (C1), Overdue Days (0), Overdue Amount (0), and Overdue Principal; Loan Receipt Number (L2), Loan Date (2021-01-01), Loan Amount (20000), Balance (20000), Maturity Date (2021-12-01), Loan Status (1-Normal), Repayment Method (Equal Principal and Interest Repayment), Authorization Agreement Number (C1), Overdue Days (0), Overdue Amount (0), and Overdue Principal (0). Authorization information includes: Credit Agreement No. (C1), Credit Start Date (2021-01-01), Credit End Date (2022-01-01), Credit Adjustment Date (blank), Renewal Date (blank), Credit Amount (1,000,000). Guarantee information (none). Repayment plan includes: IOU No. (L1), Settlement Repayment Date (2021-02-01), Principal Due (1000), Interest Due (100); IOU No. (L2), Settlement Repayment Date (2021-03-01), Principal Due (2000), Interest Due (200). Repayment transaction includes: IOU No. (L1), Repayment Date (2021-02-01), Repayment Principal (1000), Repayment Interest (100).

[0123] It should be noted that the loan account includes: reporting date (30-monthly settlement), account opening date (2021-01-01), loan type (1-loan), loan amount (29000), overdue amount (0), overdue principal (0), overdue period (0), repayment method (principal and interest calculated periodically), repayment frequency (monthly), settlement due date (2021-02-01), amount due this month (1100), amount actually repaid this month (1100), last repayment date (2021-01-01), five-level classification (1), five-level classification adjustment date (2021-02-01), related repayment liability (none), account status (normal), repayment status (normal), credit agreement number (C1).

[0124] Understandably, the data reporting device obtains grouped data by grouping credit source data; and when the credit reporting time arrives, it retrieves the target group data from the grouped data; it determines the reporting data from the target group data; and it generates a credit report based on the reporting data. This simplifies the steps of generating a credit report based on the credit source data corresponding to the credit business, shortens the time to obtain the credit report, and thus improves the speed of credit report reporting.

[0125] Example 2

[0126] Based on the same inventive concept as Embodiment 1, this application provides a data reporting device 1, corresponding to a data reporting method; Figure 10 A schematic diagram of the composition structure of a data reporting device provided in this application embodiment. Figure 1 The data reporting device 1 may include:

[0127] Acquisition unit 11 is used to acquire credit source data corresponding to credit business; when the credit reporting time arrives, it acquires target group data from the group data;

[0128] Grouping unit 12 is used to group the credit source data to obtain grouped data;

[0129] The determining unit 13 is used to determine the reporting data from the target group data;

[0130] The generation unit 14 is used to generate credit information messages based on the reported data;

[0131] The reporting unit 15 is used to report the credit reporting message to the credit reporting device.

[0132] In some embodiments of this application, the apparatus further includes a screening unit;

[0133] The filtering unit is used to filter the credit source data for a first source of data containing revolving credit loans with unified repayment management; or, to filter the credit source data for a second source of data containing revolving credit loans with non-unified repayment management; or, to filter the credit source data for a third source of data containing non-revolving credit loans issued in a one-time manner; or, to filter the credit source data for a fourth source of data containing non-revolving credit loans issued in a non-one-time manner.

[0134] The grouping unit 12 is used to group the first source data using the credit agreement number as the grouping field to obtain the grouped data; or, to group the second source data using the loan receipt number as the grouping field to obtain the grouped data; or, to group the third source data using the loan receipt number as the grouping field to obtain the grouped data; or, to group the fourth source data using the credit agreement number as the grouping field to obtain the grouped data.

[0135] In some embodiments of this application, the apparatus further includes a compression unit;

[0136] The compression unit is used to compress the credit source data to obtain compressed data;

[0137] The grouping unit 12 is used to group the compressed data to obtain the grouped data.

[0138] In some embodiments of this application, the acquisition unit 11 is used to acquire credit data, loan receipt data, repayment plan data, repayment transaction data, guarantee data, and customer data corresponding to the credit business; and to use the credit data, loan receipt data, repayment plan data, repayment transaction data table, guarantee data, and customer data as the source data.

[0139] In some embodiments of this application, the grouping unit 12 is used to group credit data according to customer number and credit agreement number to obtain grouped credit data; group loan receipt data according to customer number, credit agreement number, and loan receipt number to obtain grouped loan receipt data; group repayment plan data according to loan receipt number to obtain grouped repayment plan data; group repayment transaction data according to loan receipt number to obtain grouped repayment transaction data; group guarantee data according to credit agreement number to obtain grouped guarantee data; and group customer data according to customer number to obtain grouped customer data.

[0140] The compression unit is used to compress the grouped credit data to obtain compressed credit data; compress the grouped loan agreement data to obtain compressed loan agreement data; compress the grouped repayment plan data to obtain compressed repayment plan data; compress the grouped repayment transaction data to obtain compressed repayment transaction data; compress the grouped guarantee data to obtain compressed guarantee data; and compress the grouped customer data to obtain compressed customer data. The compressed credit data, compressed loan agreement data, compressed repayment plan data, compressed guarantee data, compressed customer data, and compressed repayment transaction data are used as the compressed data.

[0141] In some embodiments of this application, the determining unit 13 is used to determine data indicators corresponding to the credit reporting time when the credit reporting time arrives;

[0142] The acquisition unit 11 is used to acquire the target group data that matches the data index from the group data.

[0143] In some embodiments of this application, the device further includes a combination unit;

[0144] The determining unit 13 is used to determine the reporting method corresponding to the target group data; and to determine the data value corresponding to the data indicator based on the reporting method and the target group data.

[0145] The combining unit is used to combine the data values ​​according to the reporting format of a preset data segment to obtain combined data; and to use the combined data as the reporting data.

[0146] It should be noted that, in practical applications, the aforementioned acquisition unit 11, grouping unit 12, determination unit 13, generation unit 14, and reporting unit 15 can be implemented by the processor 16 on the data reporting device 1, specifically by a CPU (Central Processing Unit), MPU (Microprocessor Unit), DSP (Digital Signal Processor), or Field Programmable Gate Array (FPGA), etc.; the aforementioned data storage can be implemented by the memory 17 on the data reporting device 1.

[0147] This application embodiment also provides a data reporting device 1, such as... Figure 11 As shown, the data reporting device 1 includes a processor 16, a memory 17, and a communication bus 18. The memory 17 communicates with the processor 16 through the communication bus 18. The memory 17 stores programs executable by the processor 16. When the program is executed, the processor 16 executes the data reporting method as described above.

[0148] In practical applications, the aforementioned memory 17 can be volatile memory, such as random-access memory (RAM); or non-volatile memory, such as read-only memory (ROM), flash memory, hard disk drive (HDD), or solid-state drive (SSD); or a combination of the above types of memory, and provide instructions and data to the processor 16.

[0149] This application provides a computer-readable storage medium having a computer program thereon, which, when executed by a processor 16, implements the data reporting method as described above.

[0150] Understandably, the data reporting device obtains grouped data by grouping credit source data; and when the credit reporting time arrives, it retrieves the target group data from the grouped data; it determines the reporting data from the target group data; and it generates a credit report based on the reporting data. This simplifies the steps of generating a credit report based on the credit source data corresponding to the credit business, shortens the time to obtain the credit report, and thus improves the speed of credit report reporting.

[0151] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of hardware embodiments, software embodiments, or embodiments combining software and hardware aspects. Furthermore, this application can take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage and optical storage) containing computer-usable program code.

[0152] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0153] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0154] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0155] The above description is merely a preferred embodiment of this application and is not intended to limit the scope of protection of this application.

Claims

1. A data reporting method, characterized in that, The method includes: Obtain credit source data corresponding to credit business; and group the credit source data to obtain grouped data; When the credit reporting time arrives, the target group data is obtained from the group data; Determine the data to be reported from the target group data; Based on the reported data, a credit reporting message is generated; and the credit reporting message is reported to the credit reporting device; the credit source data is grouped to obtain grouped data, including: The first source data of revolving credit loans with unified repayment management is filtered from the credit source data, and the first source data is grouped by the credit agreement number to obtain the grouped data; Alternatively, filter the second source data from the credit source data for revolving credit loans with non-uniform repayment management, and group the second source data by the loan receipt number to obtain the grouped data; Alternatively, third-source data of non-revolving credit loans issued in a single transaction can be filtered from the credit source data, and the third-source data can be grouped by the loan receipt number to obtain the grouped data; Alternatively, from the credit source data, a fourth source of data is selected, which includes non-revolving credit loans that are not issued in a one-time transaction. This fourth source data is then grouped using the credit agreement number as a grouping field to obtain the grouped data. The grouping of the credit source data to obtain the grouped data includes: The credit source data is compressed to obtain compressed data; The compressed data is grouped to obtain the grouped data.

2. The method according to claim 1, characterized in that, The acquisition of credit source data corresponding to the credit business includes: Obtain the corresponding credit data, loan agreement data, repayment plan data, repayment transaction data, guarantee data, and customer data for the aforementioned credit business; The credit granting data, the loan agreement data, the repayment plan data, the repayment transaction data table, the guarantee data, and the customer data are used as the credit source data.

3. The method according to claim 1, characterized in that, The compression of the credit source data to obtain compressed data includes: The credit data is grouped according to the customer number and credit agreement number to obtain grouped credit data; and the grouped credit data is compressed to obtain compressed credit data. The loan receipt data is grouped according to customer number, credit agreement number, and loan receipt number to obtain grouped loan receipt data; and the grouped loan receipt data is compressed to obtain compressed loan receipt data. The repayment plan data is grouped according to the loan receipt number to obtain grouped repayment plan data; and the grouped repayment plan data is compressed to obtain compressed repayment plan data. The repayment transaction data is grouped according to the loan receipt number to obtain grouped repayment transaction data; and the grouped repayment transaction data is compressed to obtain compressed repayment transaction data. The guarantee data is grouped according to the credit agreement number to obtain grouped guarantee data; and the grouped guarantee data is compressed to obtain compressed guarantee data. Customer data is grouped according to customer number to obtain grouped customer data; and the grouped customer data is compressed to obtain compressed customer data. The compressed data includes the compressed credit data, the compressed loan agreement data, the compressed repayment plan, the compressed guarantee data, the compressed customer data, and the compressed repayment transactions.

4. The method according to claim 1, characterized in that, The step of obtaining target group data from the group data when the credit reporting time arrives includes: When the credit reporting time arrives, determine the data indicators corresponding to the credit reporting time; Obtain the target group data that matches the data indicator from the group data.

5. The method according to claim 1, characterized in that, Determining the data to be reported from the target group data includes: Determine the reporting method corresponding to the target group data; The data values ​​corresponding to the data indicators are determined based on the reporting method and the target group data. The data values ​​are combined according to the preset data segment reporting format to obtain combined data; The combined data is used as the reported data.

6. A data reporting device, characterized in that, The device includes: The acquisition unit is used to acquire credit source data corresponding to credit business; when the credit reporting time arrives, it acquires target group data from the group data; A grouping unit is used to group the credit source data to obtain grouped data; The determining unit is used to determine the reporting data from the target group data; The generation unit is used to generate credit reports based on the submitted data; The reporting unit is used to report the credit reporting message to the credit reporting device; The device also includes a screening unit; The filtering unit is used to filter the credit source data for a first source of data containing revolving credit loans with unified repayment management; or, to filter the credit source data for a second source of data containing revolving credit loans with non-unified repayment management; or, to filter the credit source data for a third source of data containing non-revolving credit loans issued in a one-time manner; or, to filter the credit source data for a fourth source of data containing non-revolving credit loans issued in a non-one-time manner. The grouping unit is used to group the first source data using the credit agreement number as the grouping field to obtain the grouped data; or, to group the second source data using the loan receipt number as the grouping field to obtain the grouped data; or, to group the third source data using the loan receipt number as the grouping field to obtain the grouped data; or, to group the fourth source data using the credit agreement number as the grouping field to obtain the grouped data. The device also includes a compression unit; The compression unit is used to compress the credit source data to obtain compressed data; The grouping unit is used to group the compressed data to obtain the grouped data.

7. A data reporting device, characterized in that, The device includes: The system includes a memory, a processor, and a communication bus, wherein the memory communicates with the processor via the communication bus, and the memory stores a data reporting program executable by the processor. When the data reporting program is executed, the processor performs the method as described in any one of claims 1 to 5.

8. A storage medium having a computer program stored thereon, used in a data transmission device, characterized in that, When executed by a processor, the computer program implements the method described in any one of claims 1 to 5.

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