Credit card application data processing method and device, storage medium and electronic equipment

Abstract

The invention discloses a credit card application data processing method and device, a storage medium and electronic equipment, and relates to the technical field of real-time data calculation. The method comprises the following steps: collecting channel end data corresponding to any flow node in a credit card application process in real time; if the channel end data corresponding to any flow node is not the channel end data corresponding to the first flow node, judging whether the channel end data corresponding to the previous flow node exists in the input data table or not; if the channel end data corresponding to the previous flow node exists, carrying out associative storage on the channel end data corresponding to any flow node and the channel end data corresponding to the previous flow node so as to realize multi-channel end data fusion; and if the channel end data corresponding to the previous flow node does not exist, writing the channel end data corresponding to any flow node into an abnormal data table, and starting an abnormal retry timing task. According to the invention, real-time acquisition and processing of credit card application data can be realized.

Description

Technical Field

[0001] This application relates to the field of real-time data computing technology, and in particular to a method, apparatus, storage medium and electronic device for processing credit card application data. Background Technology

[0002] With the rapid development of internet technology, banks in the financial industry offer various application channels, such as telephone sales, online sales, and offline document collection, to effectively increase the number of credit card applications, supporting customers in quickly applying for credit cards. To formulate effective operational strategies to improve customer enthusiasm for applying for cards and their usage activity, real-time operational analysis of credit card application and usage information is necessary.

[0003] Currently, when collecting credit card application data, the system typically collects data offline first, and then processes it uniformly. However, this time-consuming data processing, which takes days, cannot cope with rapid changes in data status and cannot meet the needs of real-time data query and analysis. Summary of the Invention

[0004] In view of this, this application provides a method, apparatus, storage medium and electronic device for processing credit card application data, which mainly enables real-time collection and processing of credit card application data, thereby meeting the needs for real-time query and analysis of credit card application data.

[0005] According to a first aspect of this application, a method for processing credit card application data is provided, the method comprising: Real-time data collection from the channel side at any process node during the credit card application process, with different process nodes corresponding to different channel sides; If the channel data corresponding to any one of the process nodes is not the channel data corresponding to the first process node, then it is determined whether the incoming data table contains channel data corresponding to the previous process node of any one of the process nodes. If the incoming data table contains channel data corresponding to the previous process node, then the channel data corresponding to any one process node is associated with the channel data corresponding to the previous process node, and the associated channel data is written into the incoming data table to achieve multi-channel data fusion. If the channel data corresponding to the previous process node is not found in the incoming data table, the channel data corresponding to any one of the process nodes is written into the abnormal data table, and an abnormal retry timer task is started.

[0006] According to a second aspect of this application, a credit card application data processing apparatus is provided, the apparatus comprising: The data acquisition unit is used to collect channel-side data at any process node during the credit card application process in real time. Different process nodes correspond to different channel terminals. The determination unit is used to determine whether the channel data corresponding to the previous process node of any process node exists in the incoming data table if the channel data corresponding to any process node is not the channel data corresponding to the first process node. The association unit is used to associate the channel data corresponding to any process node with the channel data corresponding to the previous process node if the incoming data table contains channel data corresponding to the previous process node, and write the associated channel data into the incoming data table to achieve multi-channel data fusion. The retry unit is used to write the channel data corresponding to any process node into the abnormal data table and start the abnormal retry timer task if the incoming data table does not contain the channel data corresponding to the previous process node.

[0007] According to a third aspect of this application, a storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the above-described credit card application data processing method.

[0008] According to a fourth aspect of this application, an electronic device is provided, including a storage medium, a processor, and a computer program stored on the storage medium and executable on the processor, wherein the processor executes the program to implement the above-described credit card application data processing method.

[0009] By employing the above technical solutions, this application provides a credit card application data processing method, apparatus, storage medium, and electronic device. Compared with existing offline data collection methods, this method can collect channel-end data corresponding to any process node in the credit card application process in real time. If the channel-end data corresponding to any process node is not the channel-end data corresponding to the first process node, it determines whether the application data table contains channel-end data corresponding to the previous process node. If the application data table contains channel-end data corresponding to the previous process node, it associates the channel-end data corresponding to any process node with the channel-end data corresponding to the previous process node and writes the associated channel-end data into the application data table to achieve multi-channel data fusion. If the application data table does not contain channel-end data corresponding to the previous process node, it writes the channel-end data corresponding to any process node into an abnormal data table and initiates an abnormal retry timer task. Therefore, this application, by collecting credit card application data scattered across multiple channels in real time, associating it in real time, and storing and using it, can meet the real-time query and analysis needs of credit card application data. Simultaneously, it can provide unified data service management for the credit card application process, thus optimizing the credit card application process.

[0010] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description

[0011] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings: Figure 1 A flowchart illustrating a credit card application data processing method provided in an embodiment of this application is shown. Figure 2 A schematic diagram of the system architecture provided in an embodiment of this application is shown; Figure 3 A schematic diagram illustrating the real-time data calculation process provided in an embodiment of this application is shown; Figure 4 This application illustrates a schematic diagram of the credit card application process for car purchase installment customers provided in an embodiment of this application. Figure 5 A schematic diagram of the structure of a credit card application data processing device provided in an embodiment of this application is shown. Detailed Implementation

[0012] The present application will be described in detail below with reference to the accompanying drawings and embodiments. It should be noted that, unless otherwise specified, the embodiments and features described in the embodiments of the present application can be combined with each other.

[0013] Existing technologies typically involve collecting system data offline first, followed by unified processing. However, this time-consuming, day-long data processing capability struggles to cope with rapid changes in data status and cannot meet the demands for real-time data querying and analysis.

[0014] To address the aforementioned problems, embodiments of the present invention provide a method for processing credit card application data, such as... Figure 1 As shown, the method includes: Step 101: Collect channel-side data at any process node during the credit card application process in real time.

[0015] Different process nodes correspond to different channel terminals, including application submission, approval, card activation, and transaction. Application submission refers to receiving a credit card application submitted by a user. Correspondingly, channel terminals include application submission channel terminals, approval channel terminals, card activation channel terminals, and transaction channel terminals. The system databases of different channel terminals store different data. The system database of the application submission channel terminal stores user application records and user application information, the system database of the approval channel terminal stores credit card application approval operation data, the system database of the card activation channel terminal stores user credit card activation data, and the system database of the transaction channel terminal stores user credit card activation and first transaction data. The above system databases can be relational databases such as MySQL.

[0016] The embodiments of the present invention are mainly applicable to the real-time collection and processing of credit card application data. The executing entity of the embodiments of the present invention is a device or equipment capable of collecting and processing credit card application data in real time, which can be set on the server side.

[0017] To enable real-time collection and processing of credit card application data and meet the needs for real-time querying and analysis of credit card application data, embodiments of the present invention provide a system architecture, such as... Figure 2 As shown, the system mainly includes: the channel end, the real-time processing end, and the operation end. The channel end comprises the data application system nodes involved in the credit card application process, recording user application records, user application information, credit card application approval operation data, and user credit card activation and first-time swipe data. Each channel end system stores its data in relational databases such as MySQL. The real-time processing end is a key part of this embodiment, divided into five modules based on function: data acquisition module, data synchronization module, data calculation module, data query module, and data storage module. After data extraction, transformation, and processing, it can be uniformly stored in the real-time analysis database Doris. This embodiment integrates the data from multiple channel end systems involved in the entire credit card application process and provides unified credit card application data query and statistical analysis services. The operation end is mainly for credit card users and credit card operation management analysts. This embodiment provides highly efficient unified query capabilities by uniformly processing the dispersed multi-channel end data in real time. It supports querying application progress information via mobile devices, computers, mini-programs, and data dashboards, meeting various business scenarios such as business data monitoring and operational monitoring analysis.

[0018] The data acquisition process for the data acquisition module includes: using a preset data acquisition tool to monitor the database logs of the channel-side system corresponding to different process nodes in real time; when a channel-side data change event corresponding to any process node is detected, publishing the channel-side data corresponding to that process node to a Kafka message queue to collect the channel-side data corresponding to that process node in real time. The preset data acquisition tool can specifically be the Canal data acquisition tool, or other data acquisition tools; this embodiment of the invention does not specifically limit its use.

[0019] Specifically, since the credit card application data in this embodiment of the invention involves multiple channel-side systems, it is necessary to acquire user data, credit card application approval operation data, user credit card activation data, user credit card activation and first-time transaction data, etc., respectively. This data is scattered across the system databases of different channel-side systems, and the data storage formats and structures of these systems are complex and diverse. To integrate data from multiple channel-side systems and perform unified data storage and querying, this embodiment of the invention uses the Canal data acquisition tool to monitor the MySQL database logs of each channel-side system to obtain data change events for add and modify operations, and publishes the channel-side data to a Kafka message queue to achieve real-time incremental data acquisition from multiple channel-side systems.

[0020] Regarding the data synchronization process of the data synchronization module, the method includes: storing the channel-side data corresponding to any one process node as is in the target data table; and / or widening the fields of the data tables with the same primary key in the channel-side data corresponding to any one process node, and storing the widened data in the target data table. Specifically, the target data table can refer to a data table in the Doris database.

[0021] Specifically, to meet the demands of large-scale real-time stream processing, this embodiment of the invention develops real-time synchronous tasks based on the distributed stream processing real-time computing engine Apache Flink. Flink supports stateful computation on both unbounded and bounded data streams, offering high throughput, low latency, state management, and an exact-once processing guarantee. These characteristics ensure that Flink is suitable for various real-time processing scenarios, such as financial transaction monitoring and real-time risk control. In particular, FlinkSQL allows users to define real-time data processing using standard SQL syntax, lowering the barrier to entry and improving development efficiency.

[0022] This invention primarily includes two types of real-time tasks responsible for consuming Kafka data and synchronously writing it to the Doris database. One type is a single-table synchronization task, which saves the channel-side data as is into a single table in the Doris database without any processing; this is mainly implemented based on FlinkSQL code. The other type is a multi-table synchronization task, which widens the fields of multiple data tables with the same primary key from the channel-side data and saves them into a single table in the Doris database; this is mainly implemented based on custom Flink Datastream code. For example, if a table in the channel-side data has 50 fields, and an extended table is added later to facilitate external queries, this invention merges these into a single table during synchronization. The data synchronization module in this invention only filters the data and does not perform any logical processing on the data; it stores the data as is.

[0023] This data synchronization module synchronizes system data from multiple channels and performs unified storage management, providing strong support for data association queries in the data calculation module and analysis queries of credit card application data.

[0024] Step 102: If the channel data corresponding to any process node is not the channel data corresponding to the first process node, then determine whether the incoming data table contains channel data corresponding to the previous process node of any process node.

[0025] The incoming data table is used to store data from multiple channels after association.

[0026] In this embodiment of the invention, channel identification information corresponding to any process node is obtained. Based on the channel identification information, it is determined whether the channel-end data corresponding to any process node is the same as the channel-end data corresponding to the first process node. If the channel-end data corresponding to any process node is the same as the channel-end data corresponding to the first process node, then the channel-end data corresponding to any process node is directly written into the incoming data table. If the channel-end data corresponding to any process node is not the same as the channel-end data corresponding to the first process node, it is determined whether the incoming data table contains channel-end data corresponding to the previous process node of any process node. Specifically, the channel identification information can be a channel ID.

[0027] When determining whether channel-side data corresponding to the previous process node exists in the incoming data table, a unified index is obtained from the channel-side data corresponding to any process node, and the channel identifier information corresponding to the previous process node is determined. Then, based on the unified index and the channel identifier information corresponding to the previous process node, it is determined whether the channel-side data corresponding to the previous process node exists in the incoming data table. Alternatively, a target index can be obtained from the channel-side data corresponding to any process node. The target index is jointly agreed upon by the channel-side data corresponding to any process node and the channel-side data corresponding to the previous process node. Then, the channel identifier information corresponding to the previous process node is determined, and finally, based on the target index and the channel identifier information corresponding to the previous process node, it is determined whether the channel-side data corresponding to the previous process node exists in the incoming data table.

[0028] For example, the credit card application processing flow includes the following nodes in sequence: application submission, approval, card activation, and transaction. The application submission node is the first node. If, based on the channel ID, the channel data corresponding to any given node is the same as the data corresponding to the application submission node, then that data is directly written into the application submission data table. If, based on the channel ID, the channel data corresponding to any given node is the same as the data corresponding to the card activation node, then it is checked whether the application submission data table contains data corresponding to the approval process node. In specific judgments, the existence of channel-side data corresponding to the approval process node in the application data table can be determined based on the index uniformly agreed upon by the channel-side systems corresponding to each process node (such as the credit card application approval ID) and the channel ID corresponding to the approval process node. In addition, the existence of channel-side data corresponding to the approval process node in the application data table can also be determined based on the target index agreed upon between the channel-side systems corresponding to the card opening process node and the channel-side systems corresponding to the approval process node (such as the transaction ID) and the channel ID corresponding to the approval process node. The target index is not transmitted throughout the entire system, but is generally only transmitted to the channel-side systems corresponding to adjacent process nodes. If multiple systems can agree on a unique index for use throughout the entire process, the complexity of credit card application data processing can be effectively simplified.

[0029] Step 103: If the incoming data table contains channel data corresponding to the previous process node, then associate the channel data corresponding to any one process node with the channel data corresponding to the previous process node, and write the associated channel data into the incoming data table to achieve multi-channel data fusion.

[0030] Regarding the aforementioned data computation process of the data computation module, this embodiment of the invention implements real-time computation tasks for various channel ends based on custom development of Flink Datastream code, such as... Figure 3 As shown, after each channel's real-time task consumes the corresponding channel-side Kafka data, it first filters the data to remove invalid data (such as empty channel identifier information), and then obtains valid channel-side data. For any process node's corresponding channel-side data, it checks whether the application data table contains channel-side data corresponding to the previous process node. If it does, it associates the channel-side data corresponding to any process node with the channel-side data corresponding to the previous process node, and writes the associated channel-side data into the application data table to achieve the fusion of data from different channels. In the specific data association process, a primary key ID can be created to merge multiple different channel-side data entries for the same application into a single data entry stored in a Doris database table. This entry contains key information from each channel system, such as channel ID, application ID, application time, applicant information, approval status, card activation time, and first swipe time, thus providing a query service.

[0031] Following the example above, for the channel data corresponding to the card opening process node, if it is determined that the channel data corresponding to the approval process node already exists in the application data table, then the channel data corresponding to the card opening process node and the channel data corresponding to the approval process node are associated through the primary key ID, and written as a data record stored in a data table of the Doris database.

[0032] This invention achieves unified data service management for the application process by collecting credit card application data scattered across multiple channel systems in real time, processing it, and storing it for use. This optimizes the application process, enables real-time acquisition of the status of each process node in the entire credit card application process, monitors application data in real time, and promptly follows up and handles abnormal applications. It also supports scientific operation management and analysis of operational and performance indicators such as application volume and approval volume.

[0033] Regarding the data storage module, in the current wave of enterprise digital transformation, enterprise data is diverse and massive in scale. The demand for big data query services will gradually increase, and big data operational analysis plays a crucial role in business decision-making. Therefore, the rational collection, organization, and storage of data, and the effective mining of its potential value, will greatly contribute to improving enterprise operational efficiency and making decisions more scientific and intelligent. This invention uses the real-time analytics database Doris to provide unified data storage and query services. Doris is an analytical database based on an MPP (Massively Parallel Processing) architecture, supporting rapid response and providing multiple data models. It features columnar storage, a vectorized engine, and multi-level indexes, effectively optimizing data retrieval efficiency. It boasts high availability, scalability, and high performance, and is widely used in application log retrieval, user behavior analysis, and real-time data reporting. Furthermore, the Doris database is compatible with the MySQL protocol and SQL standards, improving developer delivery efficiency and lowering the barrier to entry for business personnel in data analysis.

[0034] Step 104: If the incoming data table does not contain channel data corresponding to the previous process node, write the channel data corresponding to any process node into the exception data table and start the exception retry timer task.

[0035] To effectively address the issues of out-of-order message delivery and channel-side data latency in Kafka message queues, this embodiment of the invention adds an exception retry task. Specifically, if the channel-side data corresponding to the previous process node is not present in the incoming data table, the channel-side data corresponding to any process node will first be written into the exception data table, and an exception retry timer task will be started. This means that the channel-side data corresponding to any process node will be written as exception data into the exception data table, and then exception data will be retrieved from the exception data table at preset time intervals for retry processing. The calculation logic during retry is the same as the normal data calculation and processing logic.

[0036] When the channel data corresponding to a certain process node fails to be found due to delay, the main task will temporarily save the channel data that cannot be processed in real time to the abnormal data table. The abnormal retry scheduled task will then retrieve the data that was not processed normally from the abnormal data table and retry the processing, thereby avoiding data loss and ensuring business continuity.

[0037] For the data query module, users can query the status of their credit card applications. Based on this, the method includes: receiving a user's credit card application status query request; querying the current process node of the user's credit card application and its corresponding latest status, and feeding back the current process node and its corresponding latest status to the user.

[0038] Users can also query credit card application progress information. Based on this, the method includes: receiving a user's credit card application progress query request; querying the current process node of the user's credit card application, and splicing the link trajectory of the current process node and the previous process nodes to obtain application progress information; and feeding back the application progress information to the user.

[0039] Furthermore, the data query module provides an application information query service for customer display and internal querying. Through the application information query interface, data can be queried from the incoming application data table and the channel-side data table, which stores raw data from the channel-side system. In addition, the data query module also provides an application data statistics query service for operational management analysis. Through the application data statistics query interface, statistics can be performed on the data in the incoming application data table and the channel-side data table, and the results can be fed back to operational analysts. In terms of development mode, the data query module can adopt the traditional method of customizing interfaces based on Java code, or it can be developed using various data development platforms with low-code configuration of SQL statements and dynamic generation of query interfaces, thereby enabling rapid delivery of requirements and improving overall R&D efficiency. Since the Doris database supports standard SQL, the above methods can be used to develop interfaces for simple queries, complex relational queries, or other statistical analysis queries.

[0040] To make the technical solutions of the embodiments of the present invention clearer, the real-time data processing process in the entire credit card application process is illustrated using the credit card application process for car installment customers as an example. Figure 4As shown, customers first fill in basic information and submit a credit card application by scanning a store's QR code. A customer manager then verifies the application information and submits it for initial screening. The approval system performs a preliminary screening, and after that, the customer manager contacts the customer to request supplementary information. The approval system then conducts a final review of the credit card application. Upon approval, a physical card is mailed to the customer, who can then activate the card and use it for purchases. In this entire credit card application process, this embodiment of the invention collects and synchronizes data from various process nodes in real time, performs real-time calculations, and manages unified storage. This allows customers to check their credit card application progress in real time, and business personnel can quickly obtain the application status. Any abnormal situations can be promptly addressed, thereby improving the customer's credit card application experience and achieving complete closed-loop data management throughout the entire credit card application process.

[0041] This invention provides a credit card application data processing method that can collect channel-side data corresponding to any process node in the credit card application process in real time. If the channel-side data corresponding to any process node is not the channel-side data corresponding to the first process node, it determines whether the application data table contains channel-side data corresponding to the previous process node. If the application data table contains channel-side data corresponding to the previous process node, it associates the channel-side data corresponding to any process node with the channel-side data corresponding to the previous process node and writes the associated channel-side data into the application data table to achieve multi-channel data fusion. If the application data table does not contain channel-side data corresponding to the previous process node, it writes the channel-side data corresponding to any process node into an exception data table and starts an exception retry timer task. Therefore, this invention, by collecting credit card application data scattered across multiple channels in real time, associating it in real time, and storing and using it, can meet the real-time query and analysis needs of credit card application data, and at the same time, can provide unified data service management for the credit card application process, thus optimizing the credit card application process.

[0042] Furthermore, as Figure 1 The specific implementation of the method shown in this embodiment provides a credit card application data processing device, such as... Figure 5 As shown, the device includes: a data acquisition unit 31, a decision unit 32, an association unit 33, and a retry unit 34.

[0043] The acquisition unit 31 can be used to collect channel data corresponding to any process node in the credit card application process in real time, wherein different process nodes correspond to different channels.

[0044] The determination unit 32 can be used to determine whether the channel data corresponding to the previous process node of any process node exists in the incoming data table if the channel data corresponding to any process node is not the channel data corresponding to the first process node.

[0045] The association unit 33 can be used to associate the channel data corresponding to any process node with the channel data corresponding to the previous process node if the incoming data table contains channel data corresponding to the previous process node, and write the associated channel data into the incoming data table to achieve multi-channel data fusion.

[0046] The retry unit 34 can be used to write the channel data corresponding to any process node into the abnormal data table and start an abnormal retry timer task if the incoming data table does not contain the channel data corresponding to the previous process node.

[0047] In some embodiments, the acquisition unit 31 can also be used to acquire channel identification information corresponding to any one of the process nodes.

[0048] The determination unit 32 can also be used to determine, based on the channel identification information, whether the channel end data corresponding to any one process node is the channel end data corresponding to the first process node.

[0049] The association unit 33 can also be used to directly write the channel data corresponding to any process node into the incoming data table if the channel data corresponding to any process node is the channel data corresponding to the first process node.

[0050] In some embodiments, the acquisition unit 31 can be specifically used to monitor the database logs of the channel system corresponding to different process nodes in real time using a preset data acquisition tool; when a channel data change event corresponding to any process node is detected, the channel data corresponding to any process node is published to the Kafka message queue in order to collect the channel data corresponding to any process node in real time.

[0051] In some embodiments, the determination unit 32 may be specifically used to obtain the unified index in the channel end data corresponding to any one process node; determine the channel identification information corresponding to the previous process node; and determine whether the channel end data corresponding to the previous process node exists in the incoming data table based on the unified index and the channel identification information corresponding to the previous process node.

[0052] In some embodiments, the determination unit 32 may be specifically used to obtain the target index in the channel data corresponding to any one process node, wherein the target index is jointly agreed upon by the channel corresponding to the any one process node and the channel corresponding to the previous process node; determine the channel identification information corresponding to the previous process node; and determine whether the channel data corresponding to the previous process node exists in the incoming data table based on the target index and the channel identification information corresponding to the previous process node.

[0053] In some embodiments, the retry unit 34 may be specifically used to write the channel-end data corresponding to any one of the process nodes as abnormal data into the abnormal data table; and to retrieve the abnormal data from the abnormal data table for retry processing at preset time intervals.

[0054] In some embodiments, the apparatus further includes a synchronization unit.

[0055] The synchronization unit can be used to store the channel-end data corresponding to any one of the process nodes into the target data table as is; and / or to widen the fields of the data tables with the same primary key in the channel-end data corresponding to any one of the process nodes, and store the widened data into the target data table.

[0056] In some embodiments, the apparatus further includes a query unit.

[0057] The query unit can be used to receive a user's credit card application status query request; query the current process node of the user's credit card application and its corresponding latest status, and feed back the current process node and its corresponding latest status to the user.

[0058] The query unit can also be used to receive a user's credit card application progress trajectory query request; query the current process node of the user's credit card application, and splice the link trajectory of the current process node and the previous process nodes to obtain application progress trajectory information; and feed back the application progress trajectory information to the user.

[0059] It should be noted that other corresponding descriptions of the functional units involved in the credit card application data processing device provided in this embodiment can be found in [reference]. Figure 1 The corresponding descriptions in [the document] will not be repeated here.

[0060] Based on the above, Figure 1 Accordingly, this embodiment also provides a storage medium storing a computer program that, when executed by a processor, implements the above-described method. Figure 1 The method for processing credit card application data is shown.

[0061] Based on this understanding, the technical solution of this application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as CD-ROM, USB flash drive, mobile hard drive, etc.) and includes several instructions to cause an electronic device (such as personal computer, server, or network device, etc.) to execute the methods of various implementation scenarios of this application.

[0062] Based on the above, Figure 1 The method shown, and Figure 5 To achieve the above objectives, the present application also provides an electronic device, specifically a personal computer, tablet computer, server, or other network device, as shown in the virtual device embodiment. This device includes a storage medium and a processor; the storage medium stores a computer program; the processor executes the computer program to achieve the above-described objectives. Figure 1 The method for processing credit card application data is shown.

[0063] Optionally, the aforementioned physical devices may also include a user interface, a network interface, a camera, radio frequency (RF) circuitry, sensors, audio circuitry, a Wi-Fi module, etc. The user interface may include a display screen, input units such as a keyboard, etc., and optional user interfaces may also include USB interfaces, card reader interfaces, etc. The network interface may optionally include standard wired interfaces, wireless interfaces (such as Wi-Fi interfaces), etc.

[0064] Those skilled in the art will understand that the physical device structure provided in this embodiment does not constitute a limitation on the physical device, and may include more or fewer components, or combine certain components, or have different component arrangements.

[0065] The storage medium may also include an operating system and a network communication module. The operating system is a program that manages the hardware and software resources of the aforementioned physical device, supporting the operation of information processing programs and other software and / or programs. The network communication module is used to enable communication between the various components within the storage medium, as well as communication with other hardware and software in the information processing physical device.

[0066] Through the above description of the embodiments, those skilled in the art can clearly understand that this application can be implemented by means of software plus necessary general-purpose hardware platform, or it can be implemented by hardware.

[0067] This invention, through real-time collection of credit card application data from multiple channels and real-time correlation and storage, can meet the real-time query and analysis needs of credit card application data, and at the same time, can provide unified data service management for the credit card application process, thus optimizing the credit card application process.

[0068] Those skilled in the art will understand that the accompanying drawings are merely schematic diagrams of a preferred embodiment, and the modules or processes shown in the drawings are not necessarily essential for implementing this application. Those skilled in the art will understand that the modules in the apparatus of the embodiment can be distributed within the apparatus of the embodiment as described, or can be modified to be located in one or more apparatuses different from this embodiment. The modules of the above-described embodiment can be combined into one module, or further divided into multiple sub-modules.

[0069] The serial numbers in this application are for descriptive purposes only and do not represent the superiority or inferiority of any particular implementation scenario. The above disclosures are merely a few specific implementation scenarios of this application; however, this application is not limited thereto, and any variations conceived by those skilled in the art should fall within the protection scope of this application.

Claims

1. A method for processing credit card application data, characterized in that, include: Real-time data collection from the channel side at any process node during the credit card application process, with different process nodes corresponding to different channel sides; If the channel data corresponding to any one of the process nodes is not the channel data corresponding to the first process node, then it is determined whether the incoming data table contains channel data corresponding to the previous process node of any one of the process nodes. If the incoming data table contains channel data corresponding to the previous process node, then the channel data corresponding to any one process node is associated with the channel data corresponding to the previous process node, and the associated channel data is written into the incoming data table to achieve multi-channel data fusion. If the channel data corresponding to the previous process node is not found in the incoming data table, the channel data corresponding to any one of the process nodes is written into the abnormal data table, and an abnormal retry timer task is started.

2. The method according to claim 1, characterized in that, The method further includes: Obtain the channel identifier information corresponding to any one of the process nodes; Based on the channel identification information, determine whether the channel data corresponding to any one process node is the same as the channel data corresponding to the first process node; If the channel data corresponding to any one of the process nodes is the same as the channel data corresponding to the first process node, then the channel data corresponding to any one of the process nodes will be directly written into the incoming data table.

3. The method according to claim 1, characterized in that, The real-time collection of channel-side data corresponding to any process node in the credit card application process includes: Use preset data acquisition tools to monitor the database logs of the channel-side system corresponding to different process nodes in real time. When a channel-side data change event corresponding to any process node is detected, the channel-side data corresponding to that process node is published to the Kafka message queue to collect the channel-side data corresponding to that process node in real time.

4. The method according to claim 1, characterized in that, The determination of whether the incoming data table contains channel-side data corresponding to the previous process node of any of the process nodes includes: Obtain the unified index from the channel-side data corresponding to any one of the process nodes; Determine the channel identification information corresponding to the previous process node; Based on the unified index and the channel identifier information corresponding to the previous process node, determine whether the incoming data table contains channel-end data corresponding to the previous process node; or Obtain the target index from the channel data corresponding to any one of the process nodes, wherein the target index is jointly agreed upon by the channel corresponding to the any one of the process nodes and the channel corresponding to the previous process node; Determine the channel identification information corresponding to the previous process node; Based on the target index and the channel identifier information corresponding to the previous process node, determine whether the incoming data table contains channel data corresponding to the previous process node.

5. The method according to claim 1, characterized in that, The step of writing the channel-side data corresponding to any one of the process nodes into the abnormal data table and starting the abnormal retry timer task includes: Write the channel-side data corresponding to any one of the process nodes as abnormal data into the abnormal data table. Abnormal data is retrieved from the abnormal data table at preset time intervals for retry processing.

6. The method according to claim 1, characterized in that, The method further includes: Store the channel-end data corresponding to any of the process nodes into the target data table as is; and / or Widen the fields of data tables with the same primary key in the channel data corresponding to any of the process nodes, and store the widened data in the target data table.

7. The method according to any one of claims 1-6, characterized in that, The method further includes: Receive user's credit card application status query request; Query the current process node of the user's credit card application and its latest status, and return the current process node and its latest status to the user; and / or Receive user requests to check the progress of their credit card application; The system queries the current process node of the user's credit card application and splices the link trajectories of the current process node and the previous process nodes to obtain the application progress trajectory information. The application progress tracking information will be fed back to the user.

8. A credit card application data processing device, characterized in that, include: The data acquisition unit is used to collect channel-side data at any process node during the credit card application process in real time. Different process nodes correspond to different channel terminals. The determination unit is used to determine whether the channel data corresponding to the previous process node of any process node exists in the incoming data table if the channel data corresponding to any process node is not the channel data corresponding to the first process node. The association unit is used to associate the channel data corresponding to any process node with the channel data corresponding to the previous process node if the incoming data table contains channel data corresponding to the previous process node, and write the associated channel data into the incoming data table to achieve multi-channel data fusion. The retry unit is used to write the channel data corresponding to any process node into the abnormal data table and start the abnormal retry timer task if the incoming data table does not contain the channel data corresponding to the previous process node.

9. A storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1 to 7.

10. An electronic device comprising a storage medium, a processor, and a computer program stored on the storage medium and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method of any one of claims 1 to 7.

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