WO2019100684A1 - 电子装置、征信数据处理的方法、系统及存储介质 - Google Patents

电子装置、征信数据处理的方法、系统及存储介质 Download PDF

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WO2019100684A1
WO2019100684A1 PCT/CN2018/089462 CN2018089462W WO2019100684A1 WO 2019100684 A1 WO2019100684 A1 WO 2019100684A1 CN 2018089462 W CN2018089462 W CN 2018089462W WO 2019100684 A1 WO2019100684 A1 WO 2019100684A1
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node
processing
data
credit
processing node
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French (fr)
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吴启
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Ping An Technology Shenzhen Co Ltd
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Ping An Technology Shenzhen Co Ltd
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    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G06F11/30—Monitoring
    • G06F11/3003—Monitoring arrangements specially adapted to the computing system or computing system component being monitored
    • G06F11/3006—Monitoring arrangements specially adapted to the computing system or computing system component being monitored where the computing system is distributed, e.g. networked systems, clusters, multiprocessor systems
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G06F11/07—Responding to the occurrence of a fault, e.g. fault tolerance
    • G06F11/0703—Error or fault processing not based on redundancy, i.e. by taking additional measures to deal with the error or fault not making use of redundancy in operation, in hardware, or in data representation
    • G06F11/0706—Error or fault processing not based on redundancy, i.e. by taking additional measures to deal with the error or fault not making use of redundancy in operation, in hardware, or in data representation the processing taking place on a specific hardware platform or in a specific software environment
    • G06F11/0709—Error or fault processing not based on redundancy, i.e. by taking additional measures to deal with the error or fault not making use of redundancy in operation, in hardware, or in data representation the processing taking place on a specific hardware platform or in a specific software environment in a distributed system consisting of a plurality of standalone computer nodes, e.g. clusters, client-server systems
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G06F11/07—Responding to the occurrence of a fault, e.g. fault tolerance
    • G06F11/0703—Error or fault processing not based on redundancy, i.e. by taking additional measures to deal with the error or fault not making use of redundancy in operation, in hardware, or in data representation
    • G06F11/0751—Error or fault detection not based on redundancy
    • G06F11/0754—Error or fault detection not based on redundancy by exceeding limits
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G06F11/30—Monitoring
    • G06F11/3055—Monitoring arrangements for monitoring the status of the computing system or of the computing system component, e.g. monitoring if the computing system is on, off, available, not available
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G06F11/30—Monitoring
    • G06F11/3089—Monitoring arrangements determined by the means or processing involved in sensing the monitored data, e.g. interfaces, connectors, sensors, probes, agents
    • G06F11/3093—Configuration details thereof, e.g. installation, enabling, spatial arrangement of the probes
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G06F11/30—Monitoring
    • G06F11/32—Monitoring with visual or acoustical indication of the functioning of the machine
    • G06F11/324—Display of status information
    • G06F11/327—Alarm or error message display

Definitions

  • the present application relates to the field of communications technologies, and in particular, to an electronic device, a method, system, and storage medium for processing data.
  • the bank in the event of an abnormal situation, the bank usually needs to manually interrupt the abnormality, and then manually modify the abnormal state or manually suspend it. After the confirmation, the re-operation or subsequent operation can be supported. There are many operations, and the efficiency of exception handling in the credit reporting process is low.
  • the purpose of the present application is to provide an electronic device, a method, a system, and a storage medium for processing data processing, which are intended to reduce manual processing and improve processing efficiency of abnormalities in the credit reporting process.
  • the present application provides an electronic device including a memory and a processor coupled to the memory, the memory storing a processing system operable on the processor, the processing The system implements the following steps when executed by the processor:
  • the state value step is set, before the credit data is reported, the processing nodes are divided according to the processing process of the credit data, and the state values are respectively set in each processing node;
  • Processing the credit data step when the processing node processes the credit data, if the processing node generates an error message, the status value of the processing node is set to an abnormal state value based on the error message, and the processing node is recorded The abnormal state is once; in the timing scanning step, each processing node is periodically scanned by using a preset scanning task, and the number of abnormal states corresponding to each processing node is counted;
  • the step of generating a reminder message if the number of abnormal states of the processing node is greater than or equal to the preset number, generating a reminder message based on the credit information corresponding to the abnormality of the processing node for manual intervention.
  • the present application further provides a method for processing credit information, and the method for processing the credit data includes:
  • the processing nodes are divided according to the processing process of the credit data, and the state values are respectively set at each processing node;
  • the present application further provides a system for processing credit information, and the system for processing credit information includes:
  • a dividing module configured to divide the processing nodes according to the processing process of the credit information before reporting the credit data, and respectively set the state values in each processing node;
  • the processing module is configured to: when the processing node processes the credit data, if the processing node generates an error message, the state value of the processing node is set to an abnormal state value based on the error message, and the processing node is abnormal. State once;
  • a scanning module configured to periodically scan each processing node by using a preset scan task, and count the number of abnormal states corresponding to each processing node;
  • the generating module is configured to generate a reminder message based on the credit information corresponding to the abnormality state of the processing node if the number of abnormal states of the processing node is greater than or equal to a preset number, to perform manual intervention.
  • the present application also provides a computer readable storage medium having stored thereon a processing system, the processing system being executed by a processor to implement the steps of the method of credit data processing described above.
  • the beneficial effects of the present application are: before the report data is reported, the processing node is divided according to the processing process of the credit data, and the state value is set at each processing node, and when the credit data is processed, each processing node is scanned by using the scan task.
  • the number of abnormal states is reminded when the number of abnormal states of the processing node is greater than or equal to the preset number, which can solve the problem of low processing efficiency caused by the existing manual processing of the credit abnormality, thereby reducing manual operations and improving credit reporting.
  • the effect of abnormal processing efficiency in the process is: before the report data is reported, the processing node is divided according to the processing process of the credit data, and the state value is set at each processing node, and when the credit data is processed, each processing node is scanned by using the scan task.
  • the number of abnormal states is reminded when the number of abnormal states of the processing node is greater than or equal to the preset number, which can solve the problem of low processing efficiency caused by the existing manual processing of the credit abnormality, thereby
  • FIG. 1 is a schematic diagram of a hardware architecture of an embodiment of an electronic device according to the present application.
  • FIG. 2 is a schematic flow chart of an embodiment of a method for processing credit data according to the present application.
  • the electronic device 1 is a schematic diagram of a hardware architecture of an embodiment of an electronic device of the present application.
  • the electronic device 1 is an apparatus capable of automatically performing numerical calculation and/or information processing in accordance with an instruction set or stored in advance.
  • the electronic device 1 may be a computer, a single network server, a server group composed of multiple network servers, or a cloud-based cloud composed of a large number of hosts or network servers, where cloud computing is a type of distributed computing.
  • a super virtual computer consisting of a group of loosely coupled computers.
  • the electronic device 1 may include, but is not limited to, a memory 11 communicably connected to each other through a system bus, a processor 12, and a network interface 13, and the memory 11 stores a processing system operable on the processor 12. It should be noted that FIG. 1 only shows the electronic device 1 having the components 11-13, but it should be understood that not all illustrated components are required to be implemented, and more or fewer components may be implemented instead.
  • the memory 11 includes a memory and at least one type of readable storage medium.
  • the memory provides a cache for the operation of the electronic device 1;
  • the readable storage medium may be, for example, a flash memory, a hard disk, a multimedia card, a card type memory (eg, SD or DX memory, etc.), a random access memory (RAM), a static random access memory (SRAM).
  • a non-volatile storage medium such as a read only memory (ROM), an electrically erasable programmable read only memory (EEPROM), a programmable read only memory (PROM), a magnetic memory, a magnetic disk, an optical disk, or the like.
  • the readable storage medium may be an internal storage unit of the electronic device 1, such as a hard disk of the electronic device 1; in other embodiments, the non-volatile storage medium may also be external to the electronic device 1.
  • a storage device such as a plug-in hard disk equipped with an electronic device 1, a smart memory card (SMC), a Secure Digital (SD) card, a flash card, or the like.
  • the readable storage medium of the memory 11 is generally used to store an operating system installed in the electronic device 1 and various types of application software, such as program codes of the processing system in an embodiment of the present application. Further, the memory 11 can also be used to temporarily store various types of data that have been output or are to be output.
  • the processor 12 may be a Central Processing Unit (CPU), controller, microcontroller, microprocessor, or other data processing chip in some embodiments.
  • the processor 12 is typically used to control the overall operation of the electronic device 1, such as performing control and processing associated with data interaction or communication with the other devices.
  • the processor 12 is configured to run program code or process data stored in the memory 11, such as running a processing system or the like.
  • the network interface 13 may comprise a wireless network interface or a wired network interface, which is typically used to establish a communication connection between the electronic device 1 and other electronic devices.
  • the processing system is stored in the memory 11 and includes at least one computer readable instruction stored in the memory 11, the at least one computer readable instruction being executable by the processor 12 to implement the methods of various embodiments of the present application;
  • the at least one computer readable instruction can be classified into different logic modules depending on the functions implemented by its various parts.
  • the state value step is set, before the credit data is reported, the processing nodes are divided according to the processing process of the credit data, and the state values are respectively set in each processing node;
  • the credit information refers to an activity of collecting, sorting, storing, and providing credit information according to law.
  • Individual or corporate credit information messages need to go through several processing procedures before being reported to the predetermined credit information system (such as the People's Bank of China's credit information system).
  • the predetermined credit information system such as the People's Bank of China's credit information system.
  • the credit data can be transmitted between the processing nodes in the form of a network.
  • the credit information system provides three data exchange methods: FTP, HTTP and SMTP.
  • the collecting node collects the credit data of the individual or the enterprise from the credit business system, and the credit information includes personal or enterprise information, amount information, repayment information, and overdue information, etc., and the collected credit data collected by the node degree.
  • the pre-processing node performs the verification processing on the assembled credit information according to a predetermined rule engine, and the reporting node reports the credit data after the verification processing to the predetermined credit information system. .
  • a state value is set at each processing node, and the state value includes, for example, “0” and “1”, wherein the abnormal state value is “1”, and the normal state value is “0”. Of course, only the abnormality may be set. Status value, not the normal status value.
  • Processing the credit data step when the processing node processes the credit data, if the processing node generates an error message, the status value of the processing node is set to an abnormal state value based on the error message, and the processing node is recorded Abnormal state once;
  • each processing node if an abnormality occurs in the processing, an error message or an error prompt is generated, and the status value of the processing node may be set to an abnormal state value based on the error message or the error prompt, for example, 1", based on the set abnormal state value, the processing node is in an abnormal state once. Otherwise, if no abnormality occurs in the processing, the state value of the processing node may be directly set to a normal state value, for example, set to "0". Or do not do any processing, count the number of times the processing node is in an abnormal state. Specifically, each processing node continuously processes the credit data.
  • the step of processing the credit data includes:
  • the collection node collects the credit data
  • an acquisition task is interrupted or the credit data of the storage is abnormal
  • an error message is generated at the collection node, where the collection task is interrupted or the credit data of the storage is abnormal.
  • the code is interrupted during processing.
  • the collected credit data is assembled according to the data items and data segments in the predetermined assembly specification (for example, the assembly specification corresponding to the credit system of the People's Bank of China) (post-assembly levy)
  • the letter data is transmitted in the form of a credit message. If there is a missing data item or data segment corresponding to the credit information, for example, if the data item "Resident Identity Card” is missing or the data segment "ID card number" is missing, then the data is The assembly node generates an error message;
  • the predetermined rule engine (for example, the rule engine corresponding to the credit system of the People's Bank of China) is used to verify the assembled credit data, if there is data corresponding to the data item.
  • the segment does not conform to the predetermined format or logical error between the data segments, etc., for example, the date data segment does not conform to the predetermined format, or the repayment amount is greater than 0 and has expired, but the repayment information is normal as the logic between the data segments. If an error occurs, an error message is generated at the preprocessing node;
  • reporting data is reported by the reporting node
  • the reporting node When the reporting data is reported by the reporting node, if the reporting task is interrupted, the reporting node generates an error message, and the crediting data to be reported is returned to the assembly node for reassembly, and then the preprocessing node processes The assembled credit data is again reported by the reporting node.
  • each processing node is periodically scanned by using a preset scanning task, and the number of abnormal states corresponding to each processing node is counted;
  • the step of generating a reminder message if the number of abnormal states of the processing node is greater than or equal to the preset number, generating a reminder message based on the credit information corresponding to the abnormality of the processing node for manual intervention.
  • the number of abnormal states corresponding to each processing node is periodically scanned by using a scan task set in advance, for example, the number of abnormal states corresponding to each processing node is scanned every one hour. Because the exceptions of the processing nodes in the process of processing the credit data can be automatically processed without manual intervention, the present embodiment reminds, for example, an abnormality when the number of abnormal states of the processing node is greater than or equal to the preset number. If the number of states is greater than or equal to 5, a reminder message is generated for manual intervention.
  • the present embodiment divides the processing nodes according to the processing process of the credit information before reporting the credit data, sets the state value at each processing node, and scans each processing by using the scan task when processing the credit data.
  • the number of abnormal state of the node is reminded when the number of abnormal states of the processing node is greater than or equal to the preset number, which can solve the problem of low processing efficiency caused by the existing manual processing of the abnormality of the credit, thereby reducing manual operations and improving credit reporting. Report the effect of abnormal processing efficiency in the process.
  • the corresponding credit data is used in the pre-processing node when the abnormality is not abnormal. Encryption is performed for reporting to the reporting node.
  • the credit data of the abnormality may be encrypted by using a predetermined encryption rule, and the credit data processing mechanism and the credit information processing mechanism
  • the credit information system stipulates encryption rules, such as encrypting credit data by asymmetric encryption, encrypting with smart contracts, or encrypting and encrypting.
  • FIG. 2 is a schematic flowchart of a method for processing a credit data according to an embodiment of the present invention.
  • the method for processing the credit data includes the following steps:
  • Step S1 Before the credit data is reported, the processing nodes are divided according to the processing process of the credit data, and the state values are respectively set in each processing node;
  • the credit information refers to an activity of collecting, sorting, storing, and providing credit information according to law.
  • Individual or corporate credit information messages need to go through several processing procedures before being reported to the predetermined credit information system (such as the People's Bank of China's credit information system).
  • the predetermined credit information system such as the People's Bank of China's credit information system.
  • the credit data can be transmitted between the processing nodes in the form of a network.
  • the credit information system provides three data exchange methods: FTP, HTTP and SMTP.
  • the collecting node collects the credit data of the individual or the enterprise from the credit business system, and the credit information includes personal or enterprise information, amount information, repayment information, and overdue information, etc., and the collected credit data collected by the node degree.
  • the pre-processing node performs the verification processing on the assembled credit information according to a predetermined rule engine, and the reporting node reports the credit data after the verification processing to the predetermined credit information system. .
  • a state value is set at each processing node, and the state value includes, for example, “0” and “1”, wherein the abnormal state value is “1”, and the normal state value is “0”. Of course, only the abnormality may be set. Status value, not the normal status value.
  • step S2 when the processing node processes the credit data, if the processing node generates an error message, the status value of the processing node is set to an abnormal state value based on the error message, and the processing node is recorded in an abnormal state once. ;
  • each processing node if an abnormality occurs in the processing, an error message or an error prompt is generated, and the status value of the processing node may be set to an abnormal state value based on the error message or the error prompt, for example, 1", based on the set abnormal state value, the processing node is in an abnormal state once. Otherwise, if no abnormality occurs in the processing, the state value of the processing node may be directly set to a normal state value, for example, set to "0". Or do not do any processing, count the number of times the processing node is in an abnormal state. Specifically, each processing node continuously processes the credit data.
  • the step of processing the credit data includes:
  • the collection node collects the credit data
  • an acquisition task is interrupted or the credit data of the storage is abnormal
  • an error message is generated at the collection node, where the collection task is interrupted or the credit data of the storage is abnormal.
  • the code is interrupted during processing.
  • the collected credit data is assembled according to the data items and data segments in the predetermined assembly specification (for example, the assembly specification corresponding to the credit system of the People's Bank of China) (post-assembly levy)
  • the letter data is transmitted in the form of a credit message. If there is a missing data item or data segment corresponding to the credit information, for example, if the data item "Resident Identity Card” is missing or the data segment "ID card number" is missing, then the data is The assembly node generates an error message;
  • the predetermined rule engine (for example, the rule engine corresponding to the credit system of the People's Bank of China) is used to verify the assembled credit data, if there is data corresponding to the data item.
  • the segment does not conform to the predetermined format or logical error between the data segments, etc., for example, the date data segment does not conform to the predetermined format, or the repayment amount is greater than 0 and has expired, but the repayment information is normal as the logic between the data segments. If an error occurs, an error message is generated at the preprocessing node;
  • reporting data is reported by the reporting node
  • the reporting node When the reporting data is reported by the reporting node, if the reporting task is interrupted, the reporting node generates an error message, and the crediting data to be reported is returned to the assembly node for reassembly, and then the preprocessing node processes The assembled credit data is again reported by the reporting node.
  • Step S3 periodically scan each processing node by using a preset scan task, and count the number of abnormal states corresponding to each processing node;
  • step S4 if the number of abnormal states of the processing node is greater than or equal to the preset number, a reminder message is generated based on the credit information corresponding to the processing node in the abnormal state to perform manual intervention.
  • the number of abnormal states corresponding to each processing node is periodically scanned by using a scan task set in advance, for example, the number of abnormal states corresponding to each processing node is scanned every one hour. Because the exceptions of the processing nodes in the process of processing the credit data can be automatically processed without manual intervention, the present embodiment reminds, for example, an abnormality when the number of abnormal states of the processing node is greater than or equal to the preset number. If the number of states is greater than or equal to 5, a reminder message is generated for manual intervention.
  • the present embodiment divides the processing nodes according to the processing process of the credit information before reporting the credit data, sets the state value at each processing node, and scans each processing by using the scan task when processing the credit data.
  • the number of abnormal state of the node is reminded when the number of abnormal states of the processing node is greater than or equal to the preset number, which can solve the problem of low processing efficiency caused by the existing manual processing of the abnormality of the credit, thereby reducing manual operations and improving credit reporting. Report the effect of abnormal processing efficiency in the process.
  • the corresponding credit data is used in the pre-processing node when the abnormality is not abnormal. Encryption is performed for reporting to the reporting node.
  • the credit data of the abnormality may be encrypted by using a predetermined encryption rule, and the credit data processing mechanism and the credit information processing mechanism
  • the credit information system stipulates encryption rules, such as encrypting credit data by asymmetric encryption, encrypting with smart contracts, or encrypting and encrypting.
  • the present application also provides a computer readable storage medium having stored thereon a processing system, the processing system being executed by a processor to implement the above-described method of credit data processing: in the credit data
  • a processing system being executed by a processor to implement the above-described method of credit data processing: in the credit data
  • Each of the processing nodes respectively sets a state value; when each processing node processes the credit data, if a processing node generates an error message, the state value corresponding to the processing node is set to an abnormal state value based on the error message, and the statistics are counted.
  • the credit information corresponding to the abnormal state value generates a reminder message for manual intervention, and the like.
  • the foregoing embodiment method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be through hardware, but in many cases, the former is better.
  • Implementation Based on such understanding, the technical solution of the present application, which is essential or contributes to the prior art, may be embodied in the form of a software product stored in a storage medium (such as ROM/RAM, disk,
  • the optical disc includes a number of instructions for causing a terminal device (which may be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to perform the methods described in various embodiments of the present application.

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Abstract

本申请涉及一种电子装置、征信数据处理的方法、系统及存储介质，该方法包括：在征信数据上报之前，按照征信数据的处理进程划分处理节点，在各个处理节点分别设置状态值；在各个处理节点处理征信数据时，若有处理节点生成错误报文，则基于该错误报文将该处理节点的状态值设为异常状态值，并记录该处理节点处于异常状态一次；利用预先设置的扫描任务定时扫描各个处理节点，统计各个处理节点对应的异常状态次数；若有处理节点的异常状态次数大于等于预设的数量，则基于该处理节点处于异常状态对应的征信数据生成提醒消息。本申请能够解决现有的手动处理征信异常导致的处理效率低的问题，达到减少人工操作、提高征信上报流程中异常的处理效率的效果。

Description

电子装置、征信数据处理的方法、系统及存储介质
优先权申明
本申请基于巴黎公约申明享有2017年11月21日递交的申请号为CN201711167777.7、名称为“电子装置、征信数据处理的方法及存储介质”中国专利申请的优先权，该中国专利申请的整体内容以参考的方式结合在本申请中。
技术领域
本申请涉及通信技术领域，尤其涉及一种电子装置、征信数据处理的方法、系统及存储介质。
背景技术
目前，银行在上报征信报文的过程中，一旦出现异常情况，通常需要人工进行异常的中断，然后人工修改异常状态或手动挂起，在确认后，才能支持重新操作或接着操作，人工干预的操作较多，征信上报流程中异常处理的效率低。
发明内容
本申请的目的在于提供一种电子装置、征信数据处理的方法、系统及存储介质，旨在减少人工操作、提高征信上报流程中异常的处理效率。
为实现上述目的，本申请提供一种电子装置，所述电子装置包括存储器及与所述存储器连接的处理器，所述存储器中存储有可在所述处理器上运行的处理系统，所述处理系统被所述处理器执行时实现如下步骤：
设置状态值步骤，在征信数据上报之前，按照征信数据的处理进程划分处理节点，在各个处理节点分别设置状态值；
处理征信数据步骤：在各个处理节点处理征信数据时，若有处理节点生 成错误报文，则基于该错误报文将该处理节点的状态值设为异常状态值，并记录该处理节点处于异常状态一次；定时扫描步骤，利用预先设置的扫描任务定时扫描各个处理节点，统计各个处理节点对应的异常状态次数；
生成提醒消息步骤，若有处理节点的异常状态次数大于等于预设的数量，则基于该处理节点处于异常状态对应的征信数据生成提醒消息，以进行人工干预。
为实现上述目的，本申请还提供一种征信数据处理的方法，所述征信数据处理的方法包括：
S1，在征信数据上报之前，按照征信数据的处理进程划分处理节点，在各个处理节点分别设置状态值；
S2，在各个处理节点处理征信数据时，若有处理节点生成错误报文，则基于该错误报文将该处理节点的状态值设为异常状态值，并记录该处理节点处于异常状态一次；
S3，利用预先设置的扫描任务定时扫描各个处理节点，统计各个处理节点对应的异常状态次数；
S4，若有处理节点的异常状态次数大于等于预设的数量，则基于该处理节点处于异常状态对应的征信数据生成提醒消息，以进行人工干预。
为实现上述目的，本申请还提供一种征信数据处理的系统，所述征信数据处理的系统包括：
划分模块，用于在征信数据上报之前，按照征信数据的处理进程划分处理节点，在各个处理节点分别设置状态值；
处理模块，用于在各个处理节点处理征信数据时，若有处理节点生成错误报文，则基于该错误报文将该处理节点的状态值设为异常状态值，并记录该处理节点处于异常状态一次；
扫描模块，用于利用预先设置的扫描任务定时扫描各个处理节点，统计 各个处理节点对应的异常状态次数；
生成模块，用于若有处理节点的异常状态次数大于等于预设的数量，则基于该处理节点处于异常状态对应的征信数据生成提醒消息，以进行人工干预。
本申请还提供一种计算机可读存储介质，所述计算机可读存储介质上存储有处理系统，所述处理系统被处理器执行时实现上述的征信数据处理的方法的步骤。
本申请的有益效果是：本申请在征信数据上报之前，按照征信数据的处理进程划分处理节点，在各个处理节点处设置状态值，在处理征信数据时，利用扫描任务扫描各个处理节点的异常状态次数，在有处理节点的异常状态次数大于等于预设的数量时进行提醒，能够解决现有的手动处理征信异常导致的处理效率低的问题，达到减少人工操作、提高征信上报流程中异常的处理效率的效果。
附图说明
图1为本申请电子装置一实施例的硬件架构的示意图；
图2为本申请征信数据处理的方法一实施例的流程示意图。
具体实施方式
为了使本申请的目的、技术方案及优点更加清楚明白，以下结合附图及实施例，对本申请进行进一步详细说明。应当理解，此处所描述的具体实施例仅用以解释本申请，并不用于限定本申请。基于本申请中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本申请保护的范围。
需要说明的是，在本申请中涉及“第一”、“第二”等的描述仅用于描述 目的，而不能理解为指示或暗示其相对重要性或者隐含指明所指示的技术特征的数量。由此，限定有“第一”、“第二”的特征可以明示或者隐含地包括至少一个该特征。另外，各个实施例之间的技术方案可以相互结合，但是必须是以本领域普通技术人员能够实现为基础，当技术方案的结合出现相互矛盾或无法实现时应当认为这种技术方案的结合不存在，也不在本申请要求的保护范围之内。
参阅图1所示，是本申请电子装置一实施例的硬件构架示意图。电子装置1是一种能够按照事先设定或者存储的指令，自动进行数值计算和/或信息处理的设备。所述电子装置1可以是计算机、也可以是单个网络服务器、多个网络服务器组成的服务器组或者基于云计算的由大量主机或者网络服务器构成的云，其中云计算是分布式计算的一种，由一群松散耦合的计算机集组成的一个超级虚拟计算机。
在本实施例中，电子装置1可包括，但不仅限于，可通过系统总线相互通信连接的存储器11、处理器12、网络接口13，存储器11存储有可在处理器12上运行的处理系统。需要指出的是，图1仅示出了具有组件11-13的电子装置1，但是应理解的是，并不要求实施所有示出的组件，可以替代的实施更多或者更少的组件。
其中，存储器11包括内存及至少一种类型的可读存储介质。内存为电子装置1的运行提供缓存；可读存储介质可为如闪存、硬盘、多媒体卡、卡型存储器(例如，SD或DX存储器等)、随机访问存储器(RAM)、静态随机访问存储器(SRAM)、只读存储器(ROM)、电可擦除可编程只读存储器(EEPROM)、可编程只读存储器(PROM)、磁性存储器、磁盘、光盘等的非易失性存储介质。在一些实施例中，可读存储介质可以是电子装置1的内部存储单元，例如该电子装置1的硬盘；在另一些实施例中，该非易失性存储介质也可以是电子装置1的外部存储设备，例如电子装置1上配备的插接 式硬盘，智能存储卡(Smart Media Card,SMC)，安全数字(Secure Digital,SD)卡，闪存卡(Flash Card)等。本实施例中，存储器11的可读存储介质通常用于存储安装于电子装置1的操作系统和各类应用软件，例如本申请一实施例中的处理系统的程序代码等。此外，存储器11还可以用于暂时地存储已经输出或者将要输出的各类数据。
所述处理器12在一些实施例中可以是中央处理器(Central Processing Unit，CPU)、控制器、微控制器、微处理器、或其他数据处理芯片。该处理器12通常用于控制所述电子装置1的总体操作，例如执行与所述其他设备进行数据交互或者通信相关的控制和处理等。本实施例中，所述处理器12用于运行所述存储器11中存储的程序代码或者处理数据，例如运行处理系统等。
所述网络接口13可包括无线网络接口或有线网络接口，该网络接口13通常用于在所述电子装置1与其他电子设备之间建立通信连接。
所述处理系统存储在存储器11中，包括至少一个存储在存储器11中的计算机可读指令，该至少一个计算机可读指令可被处理器器12执行，以实现本申请各实施例的方法；以及，该至少一个计算机可读指令依据其各部分所实现的功能不同，可被划为不同的逻辑模块。
在一实施例中，上述处理系统被所述处理器12执行时实现如下步骤：
设置状态值步骤，在征信数据上报之前，按照征信数据的处理进程划分处理节点，在各个处理节点分别设置状态值；
本实施例中，征信是指依法收集、整理、保存及提供信用信息的活动。个人或者企业的征信报文在上报至预定的征信系统(例如中国人民银行的征信系统)之前，需要经过若干的处理程序。在征信报文上报前的处理阶段，对其按照处理进程分节点，优选地，按照处理的先后顺序可以分为征信数据的采集节点、组装节点、预处理节点及上报节点。各个处理节点之间可通过 网络的形式传送征信数据。征信系统提供FTP、HTTP及SMTP三种数据交换方式。
其中，采集节点从信贷业务系统中采集个人或企业的征信数据，征信数据包括个人或者企业信息、金额信息、还款信息及是否逾期的信息等等，组装节点度将采集的征信数据进行按照预定的征信系统的格式进行组装，预处理节点将组装后的征信数据按照预定的规则引擎进行校验处理，上报节点将校验处理后的征信数据上报至预定的征信系统。
本实施例在每一处理节点处分别设置状态值，状态值例如包括“0”和“1”，其中，异常状态值为“1”，正常状态值为“0”，当然也可以仅仅设置异常状态值，而不设置正常状态值。
处理征信数据步骤：在各个处理节点处理征信数据时，若有处理节点生成错误报文，则基于该错误报文将该处理节点的状态值设为异常状态值，并记录该处理节点处于异常状态一次；
本实施例中，对于每一处理节点，如果处理出现异常，则生成出错报文或者出错提示，基于错报文或者出错提示可以将该处理节点的状态值置为异常状态值，例如置为“1”，基于所设置的异常状态值记录该处理节点处于异常状态一次，反之，如果处理未出现异常，则可以直接将该处理节点的状态值置为正常状态值，例如置为“0”，或者不做任何处理，统计该处理节点处于异常状态的次数。具体地，各个处理节点在不断地处理征信数据，如果某个处理节点出现异常生成错误报文，则将状态值设置为异常状态值，记录该处理节点处于异常状态一次，后续统计异常状态次数sum＝1，记录后状态值复位为未设置状态。该处理节点继续处理征信数据，如果又出现异常生成错误报文，则再次将状态值设置为异常状态值，后续统计异常状态次数sum＝sum+1，其他处理节点也依照该方法统计异常状态次数。
在一实施例中，所述处理征信数据步骤，具体包括：
在采集节点采集征信数据时，若出现采集任务中断或者入库的征信数据异常等，则在该采集节点生成错误报文，其中，采集任务中断或者入库的征信数据异常有可能是处理过程中代码中断导致的。
在组装节点组装采集的征信数据时，按照预定的组装规范(例如中国人民银行的征信系统对应的组装规范)中的数据项及数据段将采集的征信数据进行组装(组装后的征信数据以征信报文的形式传输)，若有数据项或数据段缺失对应的征信数据等，例如，数据项“居民身份证”缺失或者数据段“身份证号码”缺失，则在该组装节点生成错误报文；
在预处理节点处理组装后的征信数据时，利用预定的规则引擎(例如中国人民银行的征信系统对应的规则引擎)对组装后的征信数据进行校验，若有数据项对应的数据段不符合预定的格式或者数据段间的逻辑出错等，例如，日期数据段不符合预定的格式，或者应还款额大于0且已逾期，但还款信息正常时视为数据段间的逻辑出错，则在该预处理节点生成错误报文；
在上报节点上报预处理后的征信数据时，若出现上报任务中断，则在该上报节点生成错误报文，并将待上报的征信数据返回给组装节点进行重新组装，然后预处理节点处理组装后的征信数据，再次由上报节点执行上报。
本实施例中，在统计各个处理节点的异常状态次数的过程中，在某个处理节点第一次生成异常状态值时，次数为1，再次生成异常状态值时，在次数1的基础上加1，依此叠加类推，执行统计的操作。
定时扫描步骤，利用预先设置的扫描任务定时扫描各个处理节点，统计各个处理节点对应的异常状态次数；
生成提醒消息步骤，若有处理节点的异常状态次数大于等于预设的数量，则基于该处理节点处于异常状态对应的征信数据生成提醒消息，以进行人工干预。
本实施例中，利用预先设置的扫描任务定时扫描各个处理节点对应的异 常状态次数，例如每隔1小时扫描各个处理节点对应的异常状态次数。由于各个处理节点在处理征信数据的过程中异常是可以自动处理掉而不需要人工干预的，因此，本实施例在有处理节点的异常状态次数大于等于预设的数量时才提醒，例如异常状态次数大于等于5，则生成提醒消息，以进行人工干预。
与现有技术相比，本实施例在征信数据上报之前，按照征信数据的处理进程划分处理节点，在各个处理节点处设置状态值，在处理征信数据时，利用扫描任务扫描各个处理节点的异常状态次数，在有处理节点的异常状态次数大于等于预设的数量时进行提醒，能够解决现有的手动处理征信异常导致的处理效率低的问题，达到减少人工操作、提高征信上报流程中异常的处理效率的效果。
在一优选的实施例中，在上述图1的实施例的基础上，在预处理节点处理组装后的征信数据之后，将预处理节点未出现异常时对应的征信数据采用预定的加密规则进行加密，供上报节点上报。
本实施例中，在预处理节点处理组装后的征信数据之后，为了加强征信数据的安全性，可以对未出现异常的征信数据采用预定的加密规则进行加密，征信数据处理机构与征信系统约定加密规则，例如采用非对称加密方式对征信数据进行加密、采用智能合约进行加密或者加压加密等等。
如图2所示，图2为本申请征信数据处理的方法一实施例的流程示意图，该征信数据处理的方法包括以下步骤：
步骤S1，在征信数据上报之前，按照征信数据的处理进程划分处理节点，在各个处理节点分别设置状态值；
本实施例中，征信是指依法收集、整理、保存及提供信用信息的活动。 个人或者企业的征信报文在上报至预定的征信系统(例如中国人民银行的征信系统)之前，需要经过若干的处理程序。在征信报文上报前的处理阶段，对其按照处理进程分节点，优选地，按照处理的先后顺序可以分为征信数据的采集节点、组装节点、预处理节点及上报节点。各个处理节点之间可通过网络的形式传送征信数据。征信系统提供FTP、HTTP及SMTP三种数据交换方式。
其中，采集节点从信贷业务系统中采集个人或企业的征信数据，征信数据包括个人或者企业信息、金额信息、还款信息及是否逾期的信息等等，组装节点度将采集的征信数据进行按照预定的征信系统的格式进行组装，预处理节点将组装后的征信数据按照预定的规则引擎进行校验处理，上报节点将校验处理后的征信数据上报至预定的征信系统。
本实施例在每一处理节点处分别设置状态值，状态值例如包括“0”和“1”，其中，异常状态值为“1”，正常状态值为“0”，当然也可以仅仅设置异常状态值，而不设置正常状态值。
步骤S2，在各个处理节点处理征信数据时，若有处理节点生成错误报文，则基于该错误报文将该处理节点的状态值设为异常状态值，并记录该处理节点处于异常状态一次；
本实施例中，对于每一处理节点，如果处理出现异常，则生成出错报文或者出错提示，基于错报文或者出错提示可以将该处理节点的状态值置为异常状态值，例如置为“1”，基于所设置的异常状态值记录该处理节点处于异常状态一次，反之，如果处理未出现异常，则可以直接将该处理节点的状态值置为正常状态值，例如置为“0”，或者不做任何处理，统计该处理节点处于异常状态的次数。具体地，各个处理节点在不断地处理征信数据，如果某个处理节点出现异常生成错误报文，则将状态值设置为异常状态值，记录该处理节点处于异常状态一次，后续统计异常状态次数sum＝1，记录后状态值 复位为未设置状态。该处理节点继续处理征信数据，如果又出现异常生成错误报文，则再次将状态值设置为异常状态值，后续统计异常状态次数sum＝sum+1，其他处理节点也依照该方法统计异常状态次数。
在一实施例中，所述处理征信数据步骤，具体包括：
在采集节点采集征信数据时，若出现采集任务中断或者入库的征信数据异常等，则在该采集节点生成错误报文，其中，采集任务中断或者入库的征信数据异常有可能是处理过程中代码中断导致的。
在组装节点组装采集的征信数据时，按照预定的组装规范(例如中国人民银行的征信系统对应的组装规范)中的数据项及数据段将采集的征信数据进行组装(组装后的征信数据以征信报文的形式传输)，若有数据项或数据段缺失对应的征信数据等，例如，数据项“居民身份证”缺失或者数据段“身份证号码”缺失，则在该组装节点生成错误报文；
在预处理节点处理组装后的征信数据时，利用预定的规则引擎(例如中国人民银行的征信系统对应的规则引擎)对组装后的征信数据进行校验，若有数据项对应的数据段不符合预定的格式或者数据段间的逻辑出错等，例如，日期数据段不符合预定的格式，或者应还款额大于0且已逾期，但还款信息正常时视为数据段间的逻辑出错，则在该预处理节点生成错误报文；
在上报节点上报预处理后的征信数据时，若出现上报任务中断，则在该上报节点生成错误报文，并将待上报的征信数据返回给组装节点进行重新组装，然后预处理节点处理组装后的征信数据，再次由上报节点执行上报。
本实施例中，在统计各个处理节点的异常状态次数的过程中，在某个处理节点第一次生成异常状态值时，次数为1，再次生成异常状态值时，在次数1的基础上加1，依此叠加类推，执行统计的操作。
步骤S3，利用预先设置的扫描任务定时扫描各个处理节点，统计各个处理节点对应的异常状态次数；
步骤S4，若有处理节点的异常状态次数大于等于预设的数量，则基于该处理节点处于异常状态对应的征信数据生成提醒消息，以进行人工干预。
本实施例中，利用预先设置的扫描任务定时扫描各个处理节点对应的异常状态次数，例如每隔1小时扫描各个处理节点对应的异常状态次数。由于各个处理节点在处理征信数据的过程中异常是可以自动处理掉而不需要人工干预的，因此，本实施例在有处理节点的异常状态次数大于等于预设的数量时才提醒，例如异常状态次数大于等于5，则生成提醒消息，以进行人工干预。
与现有技术相比，本实施例在征信数据上报之前，按照征信数据的处理进程划分处理节点，在各个处理节点处设置状态值，在处理征信数据时，利用扫描任务扫描各个处理节点的异常状态次数，在有处理节点的异常状态次数大于等于预设的数量时进行提醒，能够解决现有的手动处理征信异常导致的处理效率低的问题，达到减少人工操作、提高征信上报流程中异常的处理效率的效果。
在一优选的实施例中，在上述图2的实施例的基础上，在预处理节点处理组装后的征信数据之后，将预处理节点未出现异常时对应的征信数据采用预定的加密规则进行加密，供上报节点上报。
本实施例中，在预处理节点处理组装后的征信数据之后，为了加强征信数据的安全性，可以对未出现异常的征信数据采用预定的加密规则进行加密，征信数据处理机构与征信系统约定加密规则，例如采用非对称加密方式对征信数据进行加密、采用智能合约进行加密或者加压加密等等。
本申请还提供一种计算机可读存储介质，所述计算机可读存储介质上存储有处理系统，所述处理系统被处理器执行时实现上述的征信数据处理的方法的步骤：在征信数据的各个处理节点分别设置状态值；在各个处理节点处 理征信数据时，若有处理节点生成错误报文，则基于该错误报文将该处理节点对应的状态值设置为异常状态值，统计该处理节点的异常状态值的数量；利用预先设置的扫描任务定时扫描各个处理节点对应的异常状态值的数量；若有处理节点的异常状态值的数量大于等于预设的数量，则基于该处理节点出现异常状态值对应的征信数据生成提醒消息，以进行人工干预，等等。
上述本申请实施例序号仅仅为了描述，不代表实施例的优劣。
通过以上的实施方式的描述，本领域的技术人员可以清楚地了解到上述实施例方法可借助软件加必需的通用硬件平台的方式来实现，当然也可以通过硬件，但很多情况下前者是更佳的实施方式。基于这样的理解，本申请的技术方案本质上或者说对现有技术做出贡献的部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质(如ROM/RAM、磁碟、光盘)中，包括若干指令用以使得一台终端设备(可以是手机，计算机，服务器，空调器，或者网络设备等)执行本申请各个实施例所述的方法。
以上仅为本申请的优选实施例，并非因此限制本申请的专利范围，凡是利用本申请说明书及附图内容所作的等效结构或等效流程变换，或直接或间接运用在其他相关的技术领域，均同理包括在本申请的专利保护范围内。

Claims (20)

  1. 一种电子装置，其特征在于，所述电子装置包括存储器及与所述存储器连接的处理器，所述存储器中存储有可在所述处理器上运行的处理系统，所述处理系统被所述处理器执行时实现如下步骤：
    设置状态值步骤，在征信数据上报之前，按照征信数据的处理进程划分处理节点，在各个处理节点分别设置状态值；
    处理征信数据步骤：在各个处理节点处理征信数据时，若有处理节点生成错误报文，则基于该错误报文将该处理节点的状态值设为异常状态值，并记录该处理节点处于异常状态一次；
    定时扫描步骤，利用预先设置的扫描任务定时扫描各个处理节点，统计各个处理节点对应的异常状态次数；
    生成提醒消息步骤，若有处理节点的异常状态次数大于等于预设的数量，则基于该处理节点处于异常状态对应的征信数据生成提醒消息，以进行人工干预。
  2. 根据权利要求1所述的电子装置，其特征在于，所述处理节点包括征信数据的采集节点、组装节点、预处理节点及上报节点。
  3. 根据权利要求2所述的电子装置，其特征在于，所述处理征信数据步骤，具体包括：
    在采集节点采集征信数据时，若出现采集任务中断或者入库的征信数据异常，则在该采集节点生成错误报文；
    在组装节点组装采集的征信数据时，按照预定的组装规范中的数据项及数据段将采集的征信数据进行组装，若有数据项或数据段缺失对应的征信数据，则在该组装节点生成错误报文；
    在预处理节点处理组装后的征信数据时，利用预定的规则引擎对组装后的征信数据进行校验，若有数据项对应的数据段不符合预定的格式或者数据 段间的逻辑出错，则在该预处理节点生成错误报文；
    在上报节点上报预处理后的征信数据时，若出现上报任务中断，则在该上报节点生成错误报文，并将待上报的征信数据返回给组装节点进行重新组装。
  4. 根据权利要求3所述的电子装置，其特征在于，在预处理节点处理组装后的征信数据之后，将预处理节点未出现异常时对应的征信数据采用预定的加密规则进行加密，供上报节点上报。
  5. 根据权利要求3所述的电子装置，其特征在于，所述处理系统被所述处理器执行时，还实现如下步骤：若处理节点未生成错误报文，则将该处理节点对应的状态值设置为正常状态值或者不做处理。
  6. 一种征信数据处理的方法，其特征在于，所述征信数据处理的方法包括：
    S1，在征信数据上报之前，按照征信数据的处理进程划分处理节点，在各个处理节点分别设置状态值；
    S2，在各个处理节点处理征信数据时，若有处理节点生成错误报文，则基于该错误报文将该处理节点的状态值设为异常状态值，并记录该处理节点处于异常状态一次；
    S3，利用预先设置的扫描任务定时扫描各个处理节点，统计各个处理节点对应的异常状态次数；
    S4，若有处理节点的异常状态次数大于等于预设的数量，则基于该处理节点处于异常状态对应的征信数据生成提醒消息，以进行人工干预。
  7. 根据权利要求6所述的征信数据处理的方法，其特征在于，所述处理节点包括征信数据的采集节点、组装节点、预处理节点及上报节点。
  8. 根据权利要求7所述的征信数据处理的方法，其特征在于，所述步骤S2，具体包括：
    在采集节点采集征信数据时，若出现采集任务中断或者入库的征信数据异常，则在该采集节点生成错误报文；
    在组装节点组装采集的征信数据时，按照预定的组装规范中的数据项及数据段将采集的征信数据进行组装，若有数据项或数据段缺失对应的征信数据，则在该组装节点生成错误报文；
    在预处理节点处理组装后的征信数据时，利用预定的规则引擎对组装后的征信数据进行校验，若有数据项对应的数据段不符合预定的格式或者数据段间的逻辑出错，则在该预处理节点生成错误报文；
    在上报节点上报预处理后的征信数据时，若出现上报任务中断，则在该上报节点生成错误报文，并将待上报的征信数据返回给组装节点进行重新组装。
  9. 根据权利要求8所述的征信数据处理的方法，其特征在于，在预处理节点处理组装后的征信数据之后，将预处理节点未出现异常时对应的征信数据采用预定的加密规则进行加密，供上报节点上报。
  10. 根据权利要求8所述的征信数据处理的方法，其特征在于，在步骤S1之后，还包括：若处理节点未生成错误报文，则将该处理节点对应的状态值设置为正常状态值或者不做处理。
  11. 一种征信数据处理的系统，其特征在于，所述征信数据处理的系统包括：
    划分模块，用于在征信数据上报之前，按照征信数据的处理进程划分处理节点，在各个处理节点分别设置状态值；
    处理模块，用于在各个处理节点处理征信数据时，若有处理节点生成错误报文，则基于该错误报文将该处理节点的状态值设为异常状态值，并记录该处理节点处于异常状态一次；
    扫描模块，用于利用预先设置的扫描任务定时扫描各个处理节点，统计 各个处理节点对应的异常状态次数；
    生成模块，用于若有处理节点的异常状态次数大于等于预设的数量，则基于该处理节点处于异常状态对应的征信数据生成提醒消息，以进行人工干预。
  12. 根据权利要求11所述的征信数据处理的系统，其特征在于，所述处理节点包括征信数据的采集节点、组装节点、预处理节点及上报节点。
  13. 根据权利要求12所述的征信数据处理的系统，其特征在于，所述处理模块，具体用于：
    在采集节点采集征信数据时，若出现采集任务中断或者入库的征信数据异常，则在该采集节点生成错误报文；
    在组装节点组装采集的征信数据时，按照预定的组装规范中的数据项及数据段将采集的征信数据进行组装，若有数据项或数据段缺失对应的征信数据，则在该组装节点生成错误报文；
    在预处理节点处理组装后的征信数据时，利用预定的规则引擎对组装后的征信数据进行校验，若有数据项对应的数据段不符合预定的格式或者数据段间的逻辑出错，则在该预处理节点生成错误报文；
    在上报节点上报预处理后的征信数据时，若出现上报任务中断，则在该上报节点生成错误报文，并将待上报的征信数据返回给组装节点进行重新组装。
  14. 根据权利要求13所述的征信数据处理的系统，其特征在于，所述处理模块，进一步用于：在预处理节点处理组装后的征信数据之后，将预处理节点未出现异常时对应的征信数据采用预定的加密规则进行加密，供上报节点上报。
  15. 根据权利要求13所述的征信数据处理的系统，其特征在于，还包括设置模块，用于若处理节点未生成错误报文，则将该处理节点对应的状态值 设置为正常状态值或者不做处理。
  16. 一种计算机可读存储介质，其特征在于，所述计算机可读存储介质上存储有处理系统，所述处理系统被处理器执行时实现步骤：
    设置状态值步骤，在征信数据上报之前，按照征信数据的处理进程划分处理节点，在各个处理节点分别设置状态值；
    处理征信数据步骤：在各个处理节点处理征信数据时，若有处理节点生成错误报文，则基于该错误报文将该处理节点的状态值设为异常状态值，并记录该处理节点处于异常状态一次；
    定时扫描步骤，利用预先设置的扫描任务定时扫描各个处理节点，统计各个处理节点对应的异常状态次数；
    生成提醒消息步骤，若有处理节点的异常状态次数大于等于预设的数量，则基于该处理节点处于异常状态对应的征信数据生成提醒消息，以进行人工干预。
  17. 根据权利要求16所述的计算机可读存储介质，其特征在于，所述处理节点包括征信数据的采集节点、组装节点、预处理节点及上报节点。
  18. 根据权利要求17所述的计算机可读存储介质，其特征在于，所述处理征信数据步骤，具体包括：
    在采集节点采集征信数据时，若出现采集任务中断或者入库的征信数据异常，则在该采集节点生成错误报文；
    在组装节点组装采集的征信数据时，按照预定的组装规范中的数据项及数据段将采集的征信数据进行组装，若有数据项或数据段缺失对应的征信数据，则在该组装节点生成错误报文；
    在预处理节点处理组装后的征信数据时，利用预定的规则引擎对组装后的征信数据进行校验，若有数据项对应的数据段不符合预定的格式或者数据段间的逻辑出错，则在该预处理节点生成错误报文；
    在上报节点上报预处理后的征信数据时，若出现上报任务中断，则在该上报节点生成错误报文，并将待上报的征信数据返回给组装节点进行重新组装。
  19. 根据权利要求18所述的计算机可读存储介质，其特征在于，在预处理节点处理组装后的征信数据之后，将预处理节点未出现异常时对应的征信数据采用预定的加密规则进行加密，供上报节点上报。
  20. 根据权利要求18所述的计算机可读存储介质，其特征在于，所述处理系统被所述处理器执行时，还实现如下步骤：若处理节点未生成错误报文，则将该处理节点对应的状态值设置为正常状态值或者不做处理。
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