Data processing method, data processing device, electronic equipment and storage medium
By extracting and updating customer information in multiple messages of financial institutions, the cumbersome problem of repeated modification of customer information in multiple messages is solved, and data governance efficiency and data consistency and accuracy are improved.
Patent Information
- Application Number
- CN202411618471.9
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-13
- Publication Date
- 2025-02-28
AI Technical Summary
In the financial basic data statistics system, the cumbersome process of repeated modification of customer information in multiple messages can easily lead to repeated modification or missed modification of information, affecting the efficiency of data governance and the consistency and accuracy of data.
By extracting the initial object information of the service object from multiple initial messages of the financial institution, abnormal identification and exception list are performed, exception information is scheduled to the corresponding sub-institution for processing, and target object information is feedback, and multiple initial messages are finally updated.
It improves the degree of information aggregation, clarifies the data attribution organization, improves data governance efficiency, and ensures the consistency and accuracy of data.
Smart Images
Figure CN119537356A_ABST
Abstract
Description
Technical Field
[0001] The present disclosure relates to the field of data processing technology, and in particular to a data processing method, a data processing device, an electronic device and a storage medium. Background Art
[0002] The financial basic data statistics system requires financial institutions to submit 45 messages, covering information on customers, loans, bills, deposits, bonds, equity, etc. These messages not only record specific business data, but also contain rich customer information, such as customer ID type, ID number, national economic sector, administrative division code, economic component code, enterprise size code, industry classification code, etc. These customer information appears repeatedly in multiple messages to ensure the consistency and integrity of the data.
[0003] However, with the continuous improvement of the financial basic data statistical system and the increasing number of messages, the management and maintenance of customer information faces new challenges. Specifically, when some customer information needs to be modified, it must be modified repeatedly in multiple messages. For example, if a customer's ID number changes, it needs to be modified one by one in multiple messages such as loan messages, bill messages, deposit messages, and bond messages. This process is not only cumbersome, but also prone to repeated or missed modifications of information, which greatly affects the efficiency of data governance and makes it difficult to ensure data consistency and accuracy. Summary of the invention
[0004] The present disclosure provides a data processing method, a data processing device, an electronic device and a storage medium to at least solve one of the technical problems in the related art to a certain extent. The technical solution of the present disclosure is as follows:
[0005] According to a first aspect of an embodiment of the present disclosure, there is provided a data processing method, including:
[0006] Extracting initial object information of multiple service objects of the financial institution from multiple initial messages of the financial institution;
[0007] Performing abnormal identification on the initial object information, and generating an abnormal list according to the identified abnormal object information; wherein the abnormal list includes the abnormal object information and the sub-institution of the financial institution to which the service object to which the abnormal object information belongs belongs;
[0008] Dispatching the abnormal object information in the abnormal list to the processing object in the corresponding sub-organization for abnormal processing, so as to obtain the target object information fed back by the processing object;
[0009] The multiple initial messages are updated according to the target object information to obtain a target message.
[0010] According to a second aspect of an embodiment of the present disclosure, there is provided a data processing device, including:
[0011] An extraction module, used to extract initial object information of multiple service objects of the financial institution from multiple initial messages of the financial institution;
[0012] An abnormality identification module is used to identify abnormalities of the initial object information and generate an abnormality list according to the identified abnormal object information; wherein the abnormality list includes the abnormal object information and the sub-institution of the financial institution to which the service object to which the abnormal object information belongs belongs;
[0013] A scheduling module, used for scheduling the abnormal object information in the abnormal list to the processing object in the corresponding sub-organization for abnormal processing, so as to obtain the target object information fed back by the processing object;
[0014] An updating module is used to update the multiple initial messages according to the target object information to obtain a target message.
[0015] According to a third aspect of an embodiment of the present disclosure, an electronic device is provided, comprising: a processor; and a memory for storing instructions executable by the processor; wherein the processor is configured to execute the instructions to implement the method as described in the above embodiment of the present disclosure.
[0016] According to a fourth aspect of an embodiment of the present disclosure, a computer-readable storage medium is provided. When instructions in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device is enabled to execute the method described in the above embodiment of the present disclosure.
[0017] According to a fifth aspect of an embodiment of the present disclosure, a computer program product is provided, including: a computer program, which implements the method described in the above embodiment of the present disclosure when executed by a processor.
[0018] The technical solution provided by the embodiments of the present disclosure brings at least the following beneficial effects:
[0019] In the present disclosure, the initial object information of multiple service objects of the financial institution is first extracted from multiple initial messages of the financial institution, and then the initial object information is identified as abnormal, and an abnormal list is generated based on the identified abnormal object information, wherein the abnormal list contains the abnormal object information and the sub-institution under the financial institution to which the service object to which the abnormal object information belongs belongs, and then the abnormal object information in the abnormal list is dispatched to the processing object in the corresponding sub-institution for abnormal processing to obtain the target object information fed back by the processing object, and finally, based on the target object information, multiple initial messages are updated to obtain the target message. Thus, the present disclosure integrates and collects the abnormal information and its source in multiple messages to improve the information aggregation degree, clarify the data belonging institution, and distributes the abnormal information to the corresponding institution processing object to improve the data governance efficiency and ensure the consistency and accuracy of the data.
[0020] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS
[0021] The drawings herein are incorporated into and constitute a part of the specification, illustrate embodiments consistent with the present disclosure, and together with the description are used to explain the principles of the present disclosure, and do not constitute improper limitations on the present disclosure.
[0022] Figure 1 is a flowchart of a data processing method shown in the first embodiment of the present disclosure;
[0023] Figure 2 is a flowchart of the abnormal object information identification process shown in the second embodiment of the present disclosure;
[0024] Figure 3 is a flowchart of the process of identifying abnormal object information shown in the third embodiment of the present disclosure;
[0025] Figure 4 is a flowchart of a process for generating an exception list according to the fourth embodiment of the present disclosure;
[0026] Figure 5 is a block diagram of a data processing device shown in the fifth embodiment of the present disclosure;
[0027] Figure 6 It is a schematic structural diagram of an electronic device shown in an exemplary embodiment of the present disclosure. DETAILED DESCRIPTION
[0028] In order to enable ordinary persons in the art to better understand the technical solutions of the present disclosure, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the accompanying drawings.
[0029] It should be noted that the terms "first", "second", etc. in the specification and claims of the present disclosure and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present disclosure described herein can be implemented in an order other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. Instead, they are merely examples of devices and methods consistent with some aspects of the present disclosure as detailed in the appended claims.
[0030] It should be noted that the acquisition, storage, use, and processing of data in the technical solution disclosed in this disclosure are in compliance with the provisions of relevant laws and regulations and do not violate public order and good morals.
[0031] It should also be noted that the information (including but not limited to user device information, user personal information, etc.), data (including but not limited to data used for analysis, stored data, displayed data, etc.) and signals involved in this disclosure are all authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant laws, regulations and standards.
[0032] It should also be noted that in the embodiments of the present disclosure, certain software, components, models and other existing solutions in the industry may be mentioned, which should be regarded as exemplary. Their purpose is only to illustrate the feasibility of implementing the technical solution of the present disclosure, but it does not mean that the applicant has or will necessarily use the solution.
[0033] The data processing method, data processing device, electronic device, and storage medium according to the embodiments of the present disclosure are described below with reference to the accompanying drawings.
[0034] Figure 1 It is a flowchart of the data processing method shown in the first embodiment of the present disclosure.
[0035] The embodiment of the present disclosure is illustrated by an example in which the data processing method is configured in a data processing device. The data processing device can be applied to any electronic device so that the electronic device can perform a data processing function.
[0036] Among them, the electronic device can be any device with computing capabilities, such as a personal computer, a mobile terminal, a server (or cloud), etc. The mobile terminal can be, for example, a vehicle-mounted device, a mobile phone, a tablet computer, a personal digital assistant, a wearable device, and other hardware devices with various operating systems, touch screens and / or display screens.
[0037] like Figure 1 As shown, the data processing method of the embodiment of the present disclosure may include the following steps S1 to S4.
[0038] In step S1, initial object information of multiple service objects of the financial institution is extracted from multiple initial messages of the financial institution.
[0039] The implementation process of step S1 is as follows: a plurality of initial messages are read from a database or a file system of a financial institution, and the initial messages may include loan messages, bill messages, deposit messages, bond messages, etc. Then, a parser such as an XML parser, a JSON parser, etc. is used to parse the initial messages, and initial object information of a plurality of service objects is extracted from the parsed messages, including but not limited to certificate type, certificate number, industry, enterprise size, economic component, economic part, region code, etc., and then the extracted initial object information is stored in a temporary data structure, such as a data table, for subsequent processing.
[0040] Assume that we read the following message from the database of a financial institution and extract the initial object information of multiple service objects from the message:
[0041] Loan message:
[0042] Document type: ID card
[0043] ID number: 123456789012345678
[0044] Industry: Manufacturing
[0045] Enterprise size: Large enterprise
[0046] Economic composition: 1 (state-owned enterprise)
[0047] Economic sector: Manufacturing
[0048] Area code: 110105
[0049] Deposit message:
[0050] Document type: ID card
[0051] ID number: 123456789012345678
[0052] Industry: Manufacturing
[0053] Enterprise size: Large enterprise
[0054] Economic composition: 1 (state-owned enterprise)
[0055] Economic sector: Manufacturing
[0056] Area code: 110105
[0057] Store this information in a temporary data table for subsequent processing.
[0058] In step S2, the initial object information is identified for abnormalities, and an abnormal list is generated based on the identified abnormal object information; wherein the abnormal list includes the abnormal object information and the sub-institutions under the financial institution to which the service object to which the abnormal object information belongs belongs.
[0059] The implementation process of step S2 is as follows: before identifying the abnormality of the initial object information, first define the abnormality identification rules, such as the document number format error, the economic component code is not within the valid range, etc., and then use the defined abnormality rules to detect the initial object information to identify the abnormal object information that does not comply with the rules. Finally, the identified abnormal object information and the sub-institution information of the financial institution to which the service object belongs are recorded in the abnormality list, and the abnormality list is stored in a database or file for subsequent processing.
[0060] For example:
[0061] Assume that the following exception identification rules are defined:
[0062] The ID number must be 18 digits.
[0063] The economic component code must be within the valid range (1-5).
[0064] The following anomalies were found when checking the extracted initial object information:
[0065] Loan message:
[0066] ID number: 12345678901234567 (one less)
[0067] Economic component: 6 (not within the valid range)
[0068] The following exception list is generated:
[0069] Exception list:
[0070] ID number: 12345678901234567
[0071] Economic component: 6
[0072] Subsidiary: Branch A
[0073] The exception list is stored in the database for subsequent processing.
[0074] In step S3, the abnormal object information in the abnormal list is dispatched to the processing object in the corresponding sub-organization for abnormal processing to obtain the target object information fed back by the processing object.
[0075] The implementation process of step S3 is as follows: according to the sub-institution information in the exception list, the abnormal object information scheduling value corresponds to the sub-institution to which it belongs, and the processing object in the sub-institution processes the abnormal object information, including but not limited to supplementary recording, correction, etc. After the processing is completed, the processing object feeds back the supplemented or corrected target object information to the server of the financial institution. The server of the financial institution stores the target object information fed back by the object in a database or file for subsequent update of the message.
[0076] For example:
[0077] Assume that Branch A receives an exception list and the processing object processes the exception information:
[0078] The processing results are as follows:
[0079] ID number: 123456789012345678 (complete)
[0080] Economic component: 1 (corrected for state-owned enterprises)
[0081] Branch A feeds back the processing results to the server of the financial institution, and the server stores the target object information in the database for subsequent message updates.
[0082] In step S4, multiple initial messages are updated according to the target object information to obtain a target message.
[0083] The processing process of step S4 is as follows: determine the messages that need to be updated from multiple initial messages, which may include loan messages, bill messages, deposit messages, bond messages, etc., and then extract the specific fields that need to be updated from the target object information, such as certificate number, area code, etc., compare the extracted specific fields with the corresponding fields in the initial message, determine the fields that need to be updated, and update them, update the corresponding fields in the initial message, and ensure that the object information in all related messages is consistent.
[0084] After updating the corresponding fields in the initial message, detailed log information of each update operation can also be recorded, including update time, update content, operator, etc., for subsequent audit and verification.
[0085] For example:
[0086] Assume that the messages to be updated include loan messages and deposit messages, and the target object information is as follows:
[0087] Target audience information:
[0088] ID number: 123456789012345678
[0089] Economic composition: 1 (state-owned enterprise)
[0090] Extract the specific fields that need to be updated from the loan message and deposit message, compare and update them:
[0091] Loan message:
[0092] ID number: 12345678901234567→123456789012345678
[0093] Economic component: 6 → 1
[0094] Deposit message:
[0095] ID number: 12345678901234567→123456789012345678
[0096] Economic component: 6 → 1
[0097] The updated message is as follows:
[0098] Loan message:
[0099] ID number: 123456789012345678
[0100] Economic composition: 1 (state-owned enterprise)
[0101] Deposit message:
[0102] ID number: 123456789012345678
[0103] Economic composition: 1 (state-owned enterprise)
[0104] Record detailed log information of update operations:
[0105] Log information:
[0106] Update time: ****-**-**(year-month-day)**:**(hour-minute)
[0107] Updated content: ID number, economic composition
[0108] Operator: ***
[0109] In the present disclosure, the initial object information of multiple service objects of the financial institution is first extracted from multiple initial messages of the financial institution, and then the initial object information is identified as abnormal, and an abnormal list is generated based on the identified abnormal object information, wherein the abnormal list contains the abnormal object information and the sub-institution under the financial institution to which the service object to which the abnormal object information belongs belongs, and then the abnormal object information in the abnormal list is dispatched to the processing object in the corresponding sub-institution for abnormal processing to obtain the target object information fed back by the processing object, and finally, based on the target object information, multiple initial messages are updated to obtain the target message. Thus, the present disclosure integrates and collects the abnormal information and its source in multiple messages to improve the information aggregation degree, clarify the data belonging institution, and distributes the abnormal information to the corresponding institution processing object to improve the data governance efficiency and ensure the consistency and accuracy of the data.
[0110] In order to make those skilled in the art more clearly understand the identification process of abnormal object information in the above step S2, Figure 2 The identification process of abnormal object information in the above step S2 is described as follows: Figure 2 As shown, the process of identifying abnormal object information in the embodiment of the present disclosure includes the following steps:
[0111] In step S21, a plurality of to-be-compared messages containing initial object information of the same service object are determined from a plurality of initial messages.
[0112] From the multiple initial messages, multiple messages containing initial object information of the same service object are screened out as messages to be compared.
[0113] For example:
[0114] Assume that we have the following three initial messages, all containing the initial object information of the same service object (client A):
[0115] Loan message:
[0116] ID number: 123456789012345678
[0117] Industry: Manufacturing
[0118] Enterprise size: Large enterprise
[0119] Economic composition: 1 (state-owned enterprise)
[0120] Area code: 110105
[0121] Attributable to subsidiary: Branch A
[0122] Deposit message:
[0123] ID number: 123456789012345678
[0124] Industry: Manufacturing
[0125] Enterprise size: Large enterprise
[0126] Economic composition: 1 (state-owned enterprise)
[0127] Area code: 110105
[0128] Attributable to subsidiary: Branch A
[0129] Ticket message:
[0130] ID number: 123456789012345678
[0131] Industry: Manufacturing
[0132] Enterprise size: Large enterprise
[0133] Economic component: 2 (private enterprise)
[0134] Area code: 110104
[0135] Attributable to subsidiary: Branch B
[0136] These messages all contain the initial object information of client A, so they are determined as messages to be compared.
[0137] In step S22, multiple messages to be compared are compared to determine an abnormal message from the multiple messages to be compared; wherein the initial object information of the same service object in the abnormal message has missing items, or the initial object information of the same service object in the abnormal message is inconsistent with the initial object information of the same service object in other messages to be compared.
[0138] The initial object information of the same service object in multiple messages to be compared is compared to determine whether there are missing items or inconsistencies. If there are missing items or inconsistencies, the message is marked as an abnormal message.
[0139] Continuing with the above example, the initial object information of the same service object in the loan message, deposit message and bill message is compared, and it is found that the economic component in the bill message (2, private enterprise) is inconsistent with the economic component in the loan message and deposit message (1, state-owned enterprise), so the bill message is marked as an abnormal message.
[0140] In step S23, the initial object information of the same service object in the abnormal message is used as the abnormal object information.
[0141] The initial object information of the same service object in the message marked as abnormal is extracted as the abnormal object information.
[0142] For example:
[0143] Exception object information:
[0144] Ticket message:
[0145] Economic component: 2 (private enterprise)
[0146] Area code: 110104
[0147] Attributable to subsidiary: Branch B
[0148] Therefore, the present disclosure can effectively identify abnormal information in the initial message through the abnormal object information identification process shown in steps S21-S23, and generate an abnormal list, thereby improving the accuracy and efficiency of data processing.
[0149] In order to make those skilled in the art more clearly understand the identification process of abnormal object information in the above step S2, Figure 3 The identification process of abnormal object information in the above step S2 is described as follows: Figure 3 As shown, the process of identifying abnormal object information in the embodiment of the present disclosure includes the following steps:
[0150] In step S31, for any initial object information in a plurality of initial messages, the field type to which each field in any initial object information belongs is identified.
[0151] For example:
[0152] Assume we have an initial object with the following information:
[0153] Initial object information:
[0154] ID number: 12345678901234567
[0155] Industry: Manufacturing
[0156] Enterprise size: Large enterprise
[0157] Economic component: 6
[0158] Area code: 110105
[0159] Identify the field type for each field:
[0160] ID number: string
[0161] Industry: String
[0162] Company Size: string
[0163] Economic component: integer
[0164] regioncode: string
[0165] In step S32, based on the verification rules matching the field types of the fields, the field values under each field in any initial object information are verified.
[0166] According to the field type of each field, apply the corresponding verification rules to verify the field value. For example, the certificate number must be 18 digits, the industry must be a valid industry code, the enterprise size must be a valid size code, the economic component must be in the range of 1-5, and the region code must be a valid region code.
[0167] Verify the initial object information:
[0168] Loan message:
[0169] ID number: 12345678901234567 (does not comply with the rules)
[0170] Industry: Manufacturing (compliant with regulations)
[0171] Enterprise size: Large enterprise (in compliance with the rules)
[0172] Economic component: 6 (does not meet the rules)
[0173] Area code: 110105 (compliant)
[0174] In step S33, when there is at least one field whose field value fails to pass the verification, any initial object information is regarded as abnormal object information.
[0175] Since the document number and economic component failed to pass the verification, the initial object information is marked as abnormal object information.
[0176] Exception object information:
[0177] Loan message:
[0178] ID number: 12345678901234567
[0179] Economic component: 6
[0180] Therefore, the present disclosure can effectively identify abnormal information in the initial message through the abnormal object information identification process shown in steps S31-S33, and generate an abnormal list, thereby improving the accuracy and efficiency of data processing.
[0181] In order to make those skilled in the art more clearly understand the generation process of the exception list in the above step S2, Figure 4 The generation process of the exception list in the above step S2 is described as follows: Figure 4 As shown, the process of generating the exception list in the embodiment of the present disclosure includes the following steps:
[0182] In step S41, the source mechanism of the abnormal object information is obtained.
[0183] That is to say, the abnormal object information is obtained from which initial message.
[0184] For example:
[0185] Suppose we have two exception object information, each coming from a different initial message:
[0186] Exception object information 1:
[0187] Loan message:
[0188] ID number: 123456789012345678
[0189] Industry: Manufacturing
[0190] Enterprise size: Large enterprise
[0191] Economic composition: 1 (state-owned enterprise)
[0192] Area code: 110105
[0193] Source institution: Credit department of branch A
[0194] Exception object information 2:
[0195] Deposit message:
[0196] ID number: 12345678901234567
[0197] Industry: Manufacturing
[0198] Enterprise size: Large enterprise
[0199] Economic component: 6
[0200] Area code: 110105
[0201] Source institution: Deposit Department of Branch B
[0202] In step S42, the sub-institution corresponding to the abnormal object information is determined according to the source institution. It should be noted that the sub-institution is usually a specific business department or branch of a financial institution.
[0203] For example:
[0204] Exception object information 1:
[0205] Loan message:
[0206] Source institution: Branch A
[0207] Subsidiary: Credit Department of Branch A
[0208] Exception object information 2:
[0209] Deposit message:
[0210] Source institution: Branch B
[0211] Subsidiary: Deposit Department of Branch B
[0212] In step S43, an exception list is generated based on the exception object information and the corresponding sub-organization.
[0213] For example:
[0214] Exception list:
[0215] Exception object information 1:
[0216] Loan message:
[0217] ID number: 123456789012345678
[0218] Economic composition: 1 (state-owned enterprise)
[0219] Subsidiary: Credit Department of Branch A
[0220] Exception object information 2:
[0221] ID number: 12345678901234567
[0222] Economic component: 6 (private enterprises)
[0223] Subsidiary: Deposit Department of Branch B
[0224] In order to further optimize the generation process of the exception list and ensure the efficiency and accuracy of exception handling, before generating the exception list based on the exception object information and the corresponding sub-organization, the following steps are also included:
[0225] Classify the abnormal object information to determine the error type to which the abnormal object information belongs; wherein the error type includes format error, data omission and logic error; determine the corresponding processing priority of the abnormal object information according to the error type to which the abnormal object information belongs;
[0226] Correspondingly, an exception list is generated based on the exception object information and the corresponding sub-organization, including:
[0227] Generate an exception list based on the exception object information, the corresponding sub-organization and the corresponding processing priority.
[0228] Example
[0229] Exception object information 1:
[0230] Deposit message:
[0231] Error type of ID number: Format error (ID number is missing one digit)
[0232] Exception object information 2:
[0233] Economic component error type: logical error (economic component is not within the valid range)
[0234] The present disclosure assigns a higher priority to format errors, a normal priority to logic errors, and a lower priority to data omissions.
[0235] For example:
[0236] Exception object information 1:
[0237] Deposit message:
[0238] Error type of ID number: Format error
[0239] Processing priority: High
[0240] Exception object information 2:
[0241] Types of economic error: logical error
[0242] Processing priority: General
[0243] Then the generated exception list is as follows:
[0244] Deposit message:
[0245] ID number: 12345678901234567
[0246] Economic component: 6
[0247] Subsidiary: Deposit Department of Branch B
[0248] Error type: logical error
[0249] Processing priority: General
[0250] In order to ensure the efficiency and accuracy of exception processing, when dispatching the exception object information in the exception list to the processing object in the corresponding sub-organization for exception processing, the following steps may also be included:
[0251] The abnormal object information in the abnormal list is dispatched to the processing objects in the corresponding sub-organizations according to the corresponding processing priorities for abnormal processing, so as to obtain the target object information fed back by the processing objects.
[0252] For example:
[0253] Exception object information 2:
[0254] Subsidiary: Deposit Department of Branch B
[0255] The results of processing in sequence:
[0256] ID number: 12345678901234567 (complete)
[0257] Economic composition: 1 (state-owned enterprise)
[0258] In order to further optimize the generation process of the exception list and ensure that there is no duplicate exception object information in the exception list, the following steps are also included before generating the exception list:
[0259] From the multiple identified abnormal object information, judging whether there is the same abnormal object information according to the multiple fields of the abnormal object information;
[0260] In response to the existence of the same exception object information, the same exception object information is merged.
[0261] For example:
[0262] Suppose we have the following two exception object information:
[0263] Exception object information 1:
[0264] Deposit message:
[0265] ID number: 12345678901234567
[0266] Industry: Manufacturing
[0267] Enterprise size: Large enterprise
[0268] Economic component: 6
[0269] Area code: 110105
[0270] Exception object information 2:
[0271] Deposit message:
[0272] ID number: 12345678901234567
[0273] Industry: Manufacturing
[0274] Enterprise size: Large enterprise
[0275] Economic component: 6
[0276] Area code: 110105
[0277] By comparing, it is found that the information of these two abnormal objects is the same.
[0278] If it is determined that the same abnormal object information exists, these same abnormal object information are merged to ensure that each abnormal object information in the abnormal list is unique.
[0279] Merged exception object information:
[0280] Deposit message:
[0281] ID number: 12345678901234567
[0282] Industry: Manufacturing
[0283] Enterprise size: Large enterprise
[0284] Economic component: 6
[0285] Area code: 110105
[0286] Therefore, the exception list generation process in the embodiment of the present disclosure can effectively identify and process abnormal object information, generate an accurate exception list, and ensure the efficiency and accuracy of exception processing.
[0287] Corresponding to the data processing method provided in the above-mentioned embodiment, the present disclosure also provides a data processing device. Since the data processing device provided in the embodiment of the present disclosure corresponds to the data processing method provided in the above-mentioned embodiment, the implementation method of the data processing method is also applicable to the data processing device provided in the embodiment of the present disclosure, and will not be described in detail in the embodiment of the present disclosure.
[0288] Figure 5 It is a block diagram of a data processing device shown in the fifth embodiment of the present disclosure.
[0289] like Figure 5 As shown, the data processing device 500 of the embodiment of the present disclosure includes:
[0290] An extraction module 510, for extracting initial object information of multiple service objects of a financial institution from multiple initial messages of the financial institution;
[0291] The abnormality identification module 520 is used to identify the abnormality of the initial object information and generate an abnormality list according to the identified abnormal object information; wherein the abnormality list includes the abnormal object information and the sub-institution of the financial institution to which the service object to which the abnormal object information belongs belongs;
[0292] The dispatching module 530 is used to dispatch the abnormal object information in the abnormal list to the processing object in the corresponding sub-organization for abnormal processing, so as to obtain the target object information fed back by the processing object;
[0293] The updating module 540 is used to update the multiple initial messages according to the target object information to obtain the target message.
[0294] In one embodiment of the present disclosure, when the abnormality identification module 520 is used to identify the abnormality of the initial object information, it includes:
[0295] Determine, from the multiple initial messages, multiple messages to be compared that contain initial object information of the same service object;
[0296] Comparing multiple messages to be compared to determine an abnormal message from the multiple messages to be compared; wherein the initial object information of the same service object in the abnormal message has missing items, or the initial object information of the same service object in the abnormal message is inconsistent with the initial object information of the same service object in other messages to be compared;
[0297] The initial object information of the same service object in the abnormal message is used as the abnormal object information.
[0298] In one embodiment of the present disclosure, when the abnormality identification module 520 is used to identify the abnormality of the initial object information, it includes:
[0299] For any initial object information in the multiple initial messages, identifying the field type to which each field in any initial object information belongs;
[0300] Based on the validation rules matching the field types of the fields, the field values under each field in any initial object information are validated;
[0301] In the case where the field value of at least one field fails to pass the verification, any initial object information is treated as abnormal object information.
[0302] In one embodiment of the present disclosure, the abnormality identification module 520 is used to generate an abnormality list according to the identified abnormal object information, including:
[0303] The source organization for obtaining abnormal object information;
[0304] According to the source organization, determine the sub-organization corresponding to the abnormal object information;
[0305] Generate an exception list based on the exception object information and the corresponding sub-organization.
[0306] In one embodiment of the present disclosure, the above-mentioned device further includes:
[0307] A determination module is used to classify the abnormal object information, determine the error type to which the abnormal object information belongs, and determine the corresponding processing priority of the abnormal object information according to the error type to which the abnormal object information belongs; wherein the error type includes format error, data omission and logic error;
[0308] Correspondingly, the abnormality identification module 520 is used to generate an abnormality list according to the abnormal object information and the corresponding sub-organization, including:
[0309] Generate an exception list based on the exception object information, the corresponding sub-organization and the corresponding processing priority.
[0310] In one embodiment of the present disclosure, the scheduling module 530 is used to schedule the abnormal object information in the abnormal list to the processing object in the corresponding sub-organization for abnormal processing to obtain the target object information fed back by the processing object, including:
[0311] The abnormal object information in the abnormal list is dispatched to the processing objects in the corresponding sub-organizations according to the corresponding processing priorities for abnormal processing, so as to obtain the target object information fed back by the processing objects.
[0312] In one embodiment of the present disclosure, the abnormality identification module 520 is further used to:
[0313] From the multiple identified abnormal object information, judging whether there is the same abnormal object information according to the multiple fields of the abnormal object information;
[0314] In response to the existence of the same exception object information, the same exception object information is merged.
[0315] The data processing device of the disclosed embodiment extracts the initial object information of multiple service objects of the financial institution from multiple initial messages of the financial institution through the extraction module, performs abnormal identification on the initial object information through the abnormal identification module, and generates an abnormal list according to the identified abnormal object information, wherein the abnormal list contains the abnormal object information and the sub-institution under the financial institution to which the service object to which the abnormal object information belongs belongs, and dispatches the abnormal object information in the abnormal list to the processing object in the corresponding sub-institution for abnormal processing through the scheduling module to obtain the target object information fed back by the processing object, and updates multiple initial messages according to the target object information through the update module to obtain the target message. Therefore, the disclosed invention improves the aggregation degree of the service object error information, clarifies the sub-institution to which the data belongs, facilitates the decomposition of data governance tasks, improves the data governance efficiency, and ensures the consistency and accuracy of the data.
[0316] In an exemplary embodiment, the present disclosure also provides an electronic device.
[0317] Among them, electronic equipment includes:
[0318] processor;
[0319] a memory for storing processor-executable instructions;
[0320] The processor is configured to execute instructions to implement the data processing method proposed in any of the above embodiments. Figure 6 is a schematic diagram of the structure of an electronic device 600 shown in an exemplary embodiment of the present disclosure, such as Figure 6 As shown, the electronic device 600 may further include:
[0321] The memory 610 and the processor 620, a bus 630 connecting different components (including the memory 610 and the processor 620), the memory 610 stores a computer program, and when the processor 620 executes the program, the data processing method described in the embodiment of the present disclosure is implemented.
[0322] Bus 630 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor or a local bus using any of a variety of bus architectures. By way of example, these architectures include, but are not limited to, an Industry Standard Architecture (ISA) bus, a Micro Channel Architecture (MAC) bus, an Enhanced ISA bus, a Video Electronics Standards Association (VESA) local bus, and a Peripheral Component Interconnect (PCI) bus.
[0323] The electronic device 600 typically includes a variety of electronic device readable media. These media can be any available media that can be accessed by the electronic device 600, including volatile and non-volatile media, removable and non-removable media.
[0324] The memory 610 may also include computer system readable media in the form of volatile memory, such as random access memory (RAM) 640 and / or cache memory 650. The server 600 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, the storage system 660 may be used to read and write non-removable, non-volatile magnetic media ( Figure 6 not shown, usually called a "hard drive"). Although Figure 6 Not shown, a disk drive for reading and writing to a removable non-volatile disk (e.g., a "floppy disk"), and an optical disk drive for reading and writing to a removable non-volatile optical disk (e.g., a CD-ROM, a DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to the bus 630 via one or more data medium interfaces. The memory 610 may include at least one program product having a set (e.g., at least one) of program modules that are configured to perform the functions of the various embodiments of the present disclosure.
[0325] A program / utility 680 having a set (at least one) of program modules 670 may be stored, for example, in the memory 610, such program modules 670 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment. The program modules 670 generally perform the functions and / or methods of the embodiments described in the present disclosure.
[0326] The electronic device 600 may also communicate with one or more external devices 690 (e.g., keyboard, pointing device, display 691, etc.), may also communicate with one or more devices that enable a user to interact with the electronic device 600, and / or communicate with any device that enables the electronic device 600 to communicate with one or more other computing devices (e.g., network card, modem, etc.). Such communication may be performed via an input / output (I / O) interface 692. Furthermore, the electronic device 600 may also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN) and / or public network, such as the Internet) via a network adapter 693. As shown, the network adapter 693 communicates with other modules of the electronic device 600 via a bus 630. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device 600, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.
[0327] The processor 620 executes various functional applications and data processing by running the programs stored in the memory 610 .
[0328] It should be noted that the implementation process and technical principles of the electronic device of this embodiment refer to the aforementioned explanation of the data processing method of the embodiment of the present disclosure, and will not be repeated here.
[0329] In an exemplary embodiment, a computer-readable storage medium including instructions is also provided, such as a memory including instructions, and the above instructions can be executed by a processor of an electronic device to complete the data processing method proposed in any of the above embodiments. Optionally, the computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.
[0330] In an exemplary embodiment, a computer program product is also provided, including a computer program / instruction, wherein the computer program / instruction implements the data processing method proposed in any of the above embodiments when executed by a processor.
[0331] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the invention disclosed herein. The present disclosure is intended to cover any variations, uses or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The description and examples are to be considered exemplary only, and the true scope and spirit of the present disclosure are indicated by the following claims.
[0332] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.
Claims
1. A data processing method, characterized in that: include: Extracting initial object information of multiple service objects of the financial institution from multiple initial messages of the financial institution; Performing abnormal identification on the initial object information, and generating an abnormal list according to the identified abnormal object information; wherein the abnormal list includes the abnormal object information and the sub-institution of the financial institution to which the service object to which the abnormal object information belongs belongs; Dispatching the abnormal object information in the abnormal list to the processing object in the corresponding sub-organization for abnormal processing, so as to obtain the target object information fed back by the processing object; The multiple initial messages are updated according to the target object information to obtain a target message.
2. The method according to claim 1, characterized in that The performing abnormality identification on the initial object information includes: Determining, from the multiple initial messages, multiple messages to be compared that contain initial object information of the same service object; Comparing the multiple messages to be compared to determine an abnormal message from the multiple messages to be compared; wherein the initial object information of the same service object in the abnormal message has missing items, or the initial object information of the same service object in the abnormal message is inconsistent with the initial object information of the same service object in other messages to be compared; The initial object information of the same service object in the abnormal message is used as the abnormal object information.
3. The method according to claim 1, characterized in that The performing abnormality identification on the initial object information includes: For any initial object information in the multiple initial messages, identifying the field type to which each field in the any initial object information belongs; Verifying the field value of each field in any of the initial object information based on a verification rule matching the field type of each field; In the case that the field value of at least one of the fields fails to pass the verification, any of the initial object information is used as the abnormal object information.
4. The method according to claim 1, characterized in that: The generating of an exception list according to the identified abnormal object information includes: Obtain the source organization of the abnormal object information; Determine, according to the source organization, a sub-organization to which the abnormal object information belongs; The exception list is generated according to the exception object information and the corresponding sub-organization.
5. The method according to claim 4, characterized in that Before generating the abnormal list according to the abnormal object information and the corresponding sub-organization, the method further includes: Classify the abnormal object information to determine the error type to which the abnormal object information belongs; wherein the error type includes format error, data omission and logic error; Determining a corresponding processing priority of the abnormal object information according to the error type to which the abnormal object information belongs; Correspondingly, generating the exception list according to the abnormal object information and the corresponding sub-organization includes: The exception list is generated according to the exception object information, the corresponding sub-organization and the corresponding processing priority.
6. The method according to claim 5, characterized in that The step of dispatching the abnormal object information in the abnormal list to a processing object in a corresponding sub-organization for abnormal processing to obtain target object information fed back by the processing object includes: The abnormal object information in the abnormal list is dispatched to the processing objects in the corresponding sub-organizations in sequence according to the corresponding processing priorities for abnormal processing, so as to obtain the target object information fed back by the processing objects.
7. The method according to claim 1, characterized in that Before generating the exception list according to the identified abnormal object information, the method further includes: From the multiple identified abnormal object information, judging whether there is the same abnormal object information according to the multiple fields of the abnormal object information; In response to the existence of the same exception object information, the same exception object information is merged.
8. A data processing device, characterized in that: include: An extraction module, used to extract initial object information of multiple service objects of the financial institution from multiple initial messages of the financial institution; An abnormality identification module is used to identify abnormalities of the initial object information and generate an abnormality list according to the identified abnormal object information; wherein the abnormality list includes the abnormal object information and the sub-institution of the financial institution to which the service object to which the abnormal object information belongs belongs; A scheduling module, used for scheduling the abnormal object information in the abnormal list to the processing object in the corresponding sub-organization for abnormal processing, so as to obtain the target object information fed back by the processing object; An updating module is used to update the multiple initial messages according to the target object information to obtain a target message.
9. An electronic device, characterized in that: include: processor; a memory for storing instructions executable by the processor; The processor is configured to execute the instructions to implement the data processing method according to any one of claims 1 to 7. 10 . A computer-readable storage medium, when instructions in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device is enabled to execute the data processing method according to any one of claims 1 to 7.
11. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the data processing method according to any one of claims 1 to 7 is implemented.