Cross-domain business order data processing method and device, equipment, medium and product

Abstract

The invention provides a cross-domain business order data processing method and device, equipment, a medium and a product, and relates to the technical field of business data processing. The method comprises the following steps: preprocessing cross-domain service order data to obtain a cross-domain service result set; performing multi-frequency cross-domain business auditing of the same job number according to the result set and first pre-stored business historical experience data to obtain multi-frequency threshold-exceeding cross-domain business data; obtaining over-threshold cross-domain main and auxiliary card service data according to the result set and second pre-stored service historical experience data; performing data association on the multi-frequency over-threshold cross-domain service data and the over-threshold cross-domain main and auxiliary card service data to obtain an abnormal data list; performing early warning association on the list and system early warning rule configuration data to obtain early warning data; and executing instant early warning according to the early warning data. And data association is carried out on the multi-frequency over-threshold cross-domain service data and the over-threshold cross-domain main and auxiliary card service data, so that multi-dimensional and deep acceptance behavior monitoring is realized, and the job number behavior monitoring accuracy is effectively improved.

Description

Technical Field

[0001] This application relates to the field of business data processing technology, and in particular to a method, apparatus, equipment, medium and product for cross-domain business order data processing. Background Technology

[0002] With the rapid development of telecommunications services, cross-domain services have become an important means for telecom operators to improve user experience and expand their market. Driven by emerging technologies such as 5G, cloud computing, and artificial intelligence, operators are integrating resources from different regions, networks, and service areas to provide users with a more seamless and efficient communication experience. However, the rapid expansion of cross-domain services also faces the risk of unauthorized operations by some employee accounts, which can not only affect user experience but also pose security risks. Therefore, establishing a sound employee behavior monitoring mechanism to monitor and warn of risks in real time during the cross-domain service process is crucial for ensuring business compliance, protecting user rights, and preventing operational risks.

[0003] Currently, employee behavior monitoring mechanisms mainly rely on simple rule matching and basic log analysis, which are relatively limited in scope, resulting in low accuracy. Summary of the Invention

[0004] This application provides a method, apparatus, equipment, medium, and product for processing cross-domain business order data, in order to solve the problem of low accuracy in monitoring employee behavior caused by the limited availability of existing technologies.

[0005] Firstly, this application provides a method for processing cross-domain business order data, including:

[0006] Obtain cross-domain business order data and preprocess the cross-domain business order data to obtain a cross-domain business result set;

[0007] Based on the cross-domain business result set and the first pre-stored business historical experience data, the audit processing of multiple cross-domain business with the same work number is carried out to obtain the data of multiple cross-domain business exceeding the threshold accepted by the same work number.

[0008] Based on the cross-domain business result set and the second pre-stored business historical experience data, the cross-domain primary and secondary card business auditing process of the same work number is carried out to obtain the cross-domain primary and secondary card business data exceeding the threshold accepted by the same work number.

[0009] Data association processing is performed on the frequent cross-domain service data exceeding the threshold and the cross-domain primary and secondary card service data exceeding the threshold to obtain an abnormal data list;

[0010] Obtain system early warning rule configuration data, and perform early warning association processing based on the abnormal data list and the system early warning rule configuration data to obtain early warning data;

[0011] Perform immediate warning operations based on the warning data.

[0012] In one possible design, the step of performing multi-frequency cross-domain business auditing for the same work number based on the cross-domain business result set and the first pre-stored historical experience data of the business, to obtain the multi-frequency cross-domain business data exceeding the threshold accepted by the same work number, includes:

[0013] Based on the cross-domain business result set, feature extraction processing is performed to obtain the completed feature set;

[0014] The first entity channel set is obtained by filtering the completed feature set.

[0015] The first work number acceptance data is determined based on the first entity channel set, and cross-domain business data accepted by the same work number is determined based on the first work number acceptance data and the first entity channel set.

[0016] Based on the cross-domain business data and the first pre-stored historical experience data, the cross-domain business volume threshold parameter for the same work number is determined, and the first abnormal data extraction processing is performed based on the cross-domain business volume threshold parameter and the cross-domain business data to obtain the cross-domain business data of the same work number that exceeds the threshold multiple times.

[0017] In one possible design, the step of determining the cross-domain service volume threshold parameter for the same employee number based on the cross-domain service data and the first pre-stored historical experience data, and performing a first abnormal data extraction process based on the cross-domain service volume threshold parameter and the cross-domain service data to obtain the multiple-frequency cross-domain service data exceeding the threshold processed by the same employee number, includes:

[0018] Based on the cross-domain business data and the first pre-stored business historical experience data, set the cross-domain business volume threshold parameter for the same work number;

[0019] The business data exceeding the cross-domain business volume threshold parameter is extracted from the cross-domain business data and used as the multiple-frequency cross-domain business data exceeding the threshold accepted by the same employee number.

[0020] In one possible design, the step of performing cross-domain primary and secondary card business auditing based on the cross-domain business result set and the second pre-stored business historical experience data to obtain the cross-domain primary and secondary card business data exceeding the threshold processed by the same work number includes:

[0021] Based on the cross-domain business result set, primary and secondary card orders are extracted to obtain the completed cross-domain processing data of primary and secondary cards. The completed cross-domain processing data of primary and secondary cards is then filtered to obtain the completed cross-domain processing data of primary and secondary cards belonging to different categories.

[0022] Based on the completed cross-domain processing data of primary and secondary cards belonging to different categories, a second entity channel set is obtained by filtering and processing.

[0023] The second work number acceptance data is determined based on the second entity channel set, and the cross-domain primary and secondary card business data accepted by the same work number is determined based on the second work number acceptance data and the second entity channel set.

[0024] Based on the cross-domain primary and secondary card service data and the second pre-stored service historical experience data, the cross-domain primary and secondary card service volume threshold parameter for the same work number is determined. Then, based on the cross-domain primary and secondary card service volume threshold parameter for the same work number and the cross-domain primary and secondary card service data, a second abnormal data extraction process is performed to obtain the cross-domain primary and secondary card service data exceeding the threshold accepted by the same work number.

[0025] In one possible design, the step of determining the cross-domain primary and secondary card service volume threshold parameter for the same work ID based on the cross-domain primary and secondary card service data and the second pre-stored service historical experience data, and performing a second abnormal data extraction process based on the cross-domain primary and secondary card service volume threshold parameter for the same work ID and the cross-domain primary and secondary card service data to obtain the cross-domain primary and secondary card service data exceeding the threshold processed by the same work ID, includes:

[0026] Based on the cross-domain primary and secondary card service data and the second pre-stored service historical experience data, set the cross-domain primary and secondary card service volume threshold parameter for the same work number;

[0027] The service data exceeding the cross-domain primary and secondary card service volume threshold parameter is extracted from the cross-domain primary and secondary card service data and used as the cross-domain primary and secondary card service data exceeding the threshold accepted by the same employee number.

[0028] In one possible design, the preprocessing of the cross-domain business order data to obtain a cross-domain business result set includes:

[0029] The cross-domain business order data is formatted to obtain formatted source data;

[0030] The formatted source data is cleaned to obtain a cross-domain business result set after removing redundant and invalid information.

[0031] In one possible design, before performing data association processing based on the frequent cross-domain service data exceeding the threshold and the cross-domain primary and secondary card service data exceeding the threshold to obtain the abnormal data list, the method further includes:

[0032] Based on the cross-domain business result set and the third pre-stored business historical experience data, the cross-domain fixed-mobile fusion business auditing process of the same work number is performed to obtain the abnormal cross-domain fixed-mobile business data accepted by the same work number.

[0033] Secondly, this application provides a cross-domain business order data processing apparatus, comprising:

[0034] The preprocessing module is used to acquire cross-domain business order data and preprocess the cross-domain business order data to obtain a cross-domain business result set;

[0035] The multi-frequency cross-domain business audit processing module is used to perform multi-frequency cross-domain business audit processing for the same work number based on the cross-domain business result set and the first pre-stored business historical experience data, to obtain the multi-frequency cross-domain business data exceeding the threshold accepted by the same work number.

[0036] The cross-domain primary and secondary card business audit processing module is used to perform cross-domain primary and secondary card business audit processing for the same work number based on the cross-domain business result set and the second pre-stored business historical experience data, to obtain the cross-domain primary and secondary card business data exceeding the threshold accepted by the same work number;

[0037] The data association processing module is used to perform data association processing based on the multi-frequency cross-domain business data exceeding the threshold and the cross-domain primary and secondary card business data exceeding the threshold, and obtain an abnormal data list;

[0038] The early warning association processing module is used to obtain system early warning rule configuration data, and perform early warning association processing based on the abnormal data list and the system early warning rule configuration data to obtain early warning data;

[0039] The early warning module is used to perform real-time early warning operations based on the early warning data.

[0040] Thirdly, this application provides an electronic device, including: a processor, and a memory communicatively connected to the processor;

[0041] The memory stores computer-executed instructions;

[0042] The processor executes computer execution instructions stored in the memory to implement the cross-domain business order data processing method provided in the first aspect of this application.

[0043] Fourthly, this application provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the cross-domain business order data processing method provided in the first aspect of this application.

[0044] Fifthly, this application provides a computer program product, including a computer program, which, when executed by a processor, is used to implement the cross-domain business order data processing method provided in the first aspect of this application.

[0045] This application provides a method, apparatus, device, medium, and product for processing cross-domain business order data. The method includes: acquiring cross-domain business order data and preprocessing the cross-domain business order data to obtain a cross-domain business result set; performing multi-frequency cross-domain business auditing processing for the same work number based on the cross-domain business result set and first pre-stored historical experience data to obtain multi-frequency cross-domain business data exceeding the threshold accepted by the same work number; performing cross-domain primary and secondary card business auditing processing for the same work number based on the cross-domain business result set and second pre-stored historical experience data to obtain cross-domain primary and secondary card business data exceeding the threshold accepted by the same work number; performing data association processing based on the multi-frequency cross-domain business data exceeding the threshold and the cross-domain primary and secondary card business data exceeding the threshold to obtain an abnormal data list; acquiring system early warning rule configuration data and performing early warning association processing based on the abnormal data list and system early warning rule configuration data to obtain early warning data; and executing real-time early warning operations based on the early warning data. Based on the above methods, the following technical effects were achieved: By performing data correlation processing on frequently exceeding threshold cross-domain business data and exceeding threshold cross-domain primary and secondary card business data, multi-dimensional and in-depth monitoring of cross-domain business irregularities was realized, effectively improving the accuracy of employee behavior monitoring. Simultaneously, the application of these methods can effectively prevent revenue loss risks in cross-domain business processing, reduce fraud risks, and achieve high-quality development. Attached Figure Description

[0046] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0047] Figure 1 A flowchart illustrating the cross-domain business order data processing method provided in this application embodiment. Figure 1 ;

[0048] Figure 2 A flowchart illustrating the cross-domain business order data processing method provided in this application embodiment. Figure 2 ;

[0049] Figure 3 A flowchart illustrating the cross-domain business order data processing method provided in this application embodiment. Figure 3 ;

[0050] Figure 4 A flowchart illustrating the cross-domain business order data processing method provided in this application embodiment. Figure 4 ;

[0051] Figure 5A flowchart illustrating the cross-domain business order data processing method provided in this application embodiment. Figure 4 ;

[0052] Figure 6 A schematic diagram of the structure of the cross-domain business order data processing device provided in the embodiments of this application;

[0053] Figure 7 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0054] Explanation of reference numerals in the attached figures:

[0055] 901 - Processor; 902 - Memory; 903 - Communication components; 904 - Bus. Detailed Implementation

[0056] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0057] In the embodiments of this application, the terms "first" and "second" are used to distinguish identical or similar items with substantially the same function and effect. Those skilled in the art will understand that the terms "first" and "second" do not limit the quantity or execution order, and that "first" and "second" do not necessarily imply difference. It should be noted that in the embodiments of this application, words such as "exemplary" or "for example" are used to indicate examples, illustrations, or explanations. Any embodiment or design scheme described as "exemplary" or "for example" in this application should not be construed as being more preferred or advantageous than other embodiments or design schemes. Specifically, the use of words such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner. In the embodiments of this application, "at least one" refers to one or more, and "more than one" refers to two or more.

[0058] It should be noted that the phrase "at...time" in the embodiments of this application can refer to the instant at which a certain situation occurs, or to a period of time after the occurrence of a certain situation; the embodiments of this application do not specifically limit this. Furthermore, the cross-domain business order data processing method provided in the embodiments of this application is merely an example, and the cross-domain business order data processing method may include more or less content.

[0059] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, use and processing of the relevant data must comply with relevant laws, regulations and standards, and corresponding operation entry points are provided for users to choose to authorize or refuse.

[0060] To clearly understand the technical solution of this application, the solutions of the prior art will be described in detail first.

[0061] Currently, employee behavior monitoring mechanisms mainly rely on simple rule matching and basic log analysis, which are relatively limited in scope, resulting in low accuracy.

[0062] In summary, how to design a method that can solve the problem of low accuracy in monitoring employee behavior due to the limited availability of existing technologies is the urgent problem that this application needs to address.

[0063] Therefore, in view of the above-mentioned technical problems existing in the prior art, the embodiments of this application provide a cross-domain business order data processing method, apparatus, equipment, medium and product, which aims to effectively improve the accuracy of employee behavior monitoring.

[0064] The following describes the application scenarios of the cross-domain business order data processing method, apparatus, equipment, medium, and product provided in the embodiments of this application. The following application scenarios are merely examples, intended to help those skilled in the art understand the technical content of this application, but do not imply that the embodiments of this application cannot be used in other devices, systems, environments, or scenarios.

[0065] Cross-provincial business processing monitoring: The cross-regional business order data processing method provided in this application embodiment can correlate abnormal cross-regional business data and abnormal cross-regional primary and secondary card business data, which can effectively improve the accuracy of employee behavior monitoring. It is applicable to monitoring the compliance of operators' employee numbers in accepting business across regions, identifying unauthorized agency and unauthorized operations, and ensuring that cross-regional business is carried out in a standardized manner within the authorized scope.

[0066] The embodiments of this application are described below with reference to the accompanying drawings.

[0067] The technical solution of this application and how it solves the above-mentioned technical problems will be described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will be described below with reference to the accompanying drawings.

[0068] Figure 1A flowchart illustrating the cross-domain business order data processing method provided in this application embodiment. Figure 1 The cross-domain business order data processing method provided in this embodiment includes the following steps:

[0069] S101. Obtain cross-domain business order data and preprocess the cross-domain business order data to obtain the cross-domain business result set.

[0070] In this embodiment, cross-domain services include cross-domain SIM card replacement and cross-provincial broadband installation. Cross-domain service order data is collected during billing period T, and key information is extracted from the order data based on certain conditions. This information includes transaction number, order number, service agent number, agent number attributes, agent number location, user number, number location, service acceptance location, processing time, and service type. After extracting the key information, preprocessing steps such as data cleaning, field normalization, and logical verification are performed to obtain the cross-domain service result set, which is then used as result set A. This embodiment does not impose specific restrictions on the preprocessing method.

[0071] S102. Based on the cross-domain business result set and the first pre-stored business historical experience data, perform audit processing on the multiple frequency cross-domain business of the same work number to obtain the data of multiple frequency cross-domain business exceeding the threshold accepted by the same work number.

[0072] In this embodiment, after obtaining the cross-domain business result set and the first pre-stored historical experience data, a warning threshold is generated for each work number based on the benchmark value in the first pre-stored historical experience data and the business fluctuation coefficient. By comparing the cross-domain business data in the cross-domain business result set with the warning threshold, work numbers whose cross-domain business data exceeds the warning threshold are marked, thus obtaining multiple instances of cross-domain business data exceeding the threshold accepted by the same work number. This embodiment does not impose specific restrictions on the method for obtaining multiple instances of cross-domain business data exceeding the threshold accepted by the same work number.

[0073] S103. Based on the cross-domain business result set and the second pre-stored business historical experience data, perform cross-domain primary and secondary card business auditing for the same work number to obtain cross-domain primary and secondary card business data exceeding the threshold accepted by the same work number.

[0074] In this embodiment, after obtaining the cross-domain business result set and the second pre-stored historical experience data, a warning threshold is generated for each work number based on the benchmark value in the second pre-stored historical experience data and the business fluctuation coefficient. The cross-domain primary and secondary card business data in the cross-domain business result set are compared with the warning threshold, and the work numbers whose cross-domain primary and secondary card business data exceeds the warning threshold are marked, thus obtaining the cross-domain primary and secondary card business data exceeding the threshold accepted by the same work number. This embodiment does not impose specific restrictions on the method of obtaining the cross-domain primary and secondary card business data exceeding the threshold accepted by the same work number.

[0075] S104. Perform data association processing based on the frequent cross-domain business data exceeding the threshold and the cross-domain primary and secondary card business data exceeding the threshold to obtain an abnormal data list.

[0076] In this embodiment, based on the frequent cross-domain business data exceeding the threshold and the cross-domain primary and secondary card business data exceeding the threshold, data association processing is performed according to single-dimensional / combined-dimensional data to integrate into a specific combination of abnormal data list, and the abnormal data list is used as the result set G.

[0077] By performing data correlation processing on frequently exceeding threshold cross-domain business data and exceeding threshold cross-domain primary and secondary card business data, multi-dimensional and in-depth monitoring of cross-domain business irregularities is achieved, effectively improving the accuracy of employee behavior monitoring. Simultaneously, the application of these methods can effectively prevent revenue loss risks in cross-domain business processing, reduce fraud risks, and achieve high-quality development.

[0078] S105. Obtain the system early warning rule configuration data, and perform early warning association processing based on the abnormal data list and the system early warning rule configuration data to obtain early warning data.

[0079] In this embodiment, based on the result set G, system early warning rule configuration data is obtained. This data includes the early warning name, early warning status, early warning type, early warning content, service type, handler, and recipient. The result set G and the system early warning rule configuration data are then used to perform early warning association processing to generate early warning data, which is then used as the result set H.

[0080] S106. Execute real-time early warning operations based on early warning data.

[0081] In this embodiment, the result set H is used as the final result set of the method for identifying cross-domain business abnormal processing risks, and an immediate warning operation is performed based on the result set H.

[0082] This application provides a method for processing cross-domain business order data. The method includes: acquiring cross-domain business order data and preprocessing the data to obtain a cross-domain business result set; performing audit processing on multiple cross-domain business transactions with the same work number based on the cross-domain business result set and first pre-stored historical experience data to obtain multiple cross-domain business transactions exceeding the threshold processed by the same work number; performing audit processing on cross-domain primary and secondary card transactions with the same work number based on the cross-domain business result set and second pre-stored historical experience data to obtain cross-domain primary and secondary card transactions exceeding the threshold processed by the same work number; performing data association processing on the multiple cross-domain business transactions exceeding the threshold and the cross-domain primary and secondary card transactions exceeding the threshold to obtain an abnormal data list; acquiring system early warning rule configuration data and performing early warning association processing on the abnormal data list and system early warning rule configuration data to obtain early warning data; and executing an immediate early warning operation based on the early warning data. Based on the above methods, the following technical effects were achieved: By performing data correlation processing on frequently exceeding threshold cross-domain business data and exceeding threshold cross-domain primary and secondary card business data, multi-dimensional and in-depth monitoring of cross-domain business irregularities was realized, effectively improving the accuracy of employee behavior monitoring. Simultaneously, the application of these methods can effectively prevent revenue loss risks in cross-domain business processing, reduce fraud risks, and achieve high-quality development.

[0083] Figure 2 A flowchart illustrating the cross-domain business order data processing method provided in this application embodiment. Figure 2 This embodiment is in Figure 1 Based on the provided embodiments, the method for processing cross-domain business order data is further explained. For example... Figure 2 As shown, in the cross-domain business order data processing method of this embodiment, S102 includes:

[0084] S201. Perform feature extraction processing based on the cross-domain business result set to obtain the completed feature set.

[0085] In this embodiment, feature extraction processing is performed based on result set A. Order data with the status of "completed" is filtered out from the order numbers of cross-domain business order data to obtain the completed feature set, and the completed feature set is used as result set B1.

[0086] S202. Based on the completed feature set, perform filtering to obtain the first entity channel set.

[0087] In this embodiment, channel data of social entity channels and self-owned entity channels are filtered out from result set B1 to generate cross-domain business entity channel dataset, namely the first entity channel set, and the first entity channel set is used as result set C1.

[0088] S203. Determine the first work number acceptance data based on the first entity channel set, and determine the cross-domain business data accepted by the same work number based on the first work number acceptance data and the first entity channel set.

[0089] In this embodiment, the corresponding service number is determined based on each piece of data contained in result set C1, and each corresponding service number is used as the first service number service data. Data corresponding to the same service number in the first service number service data is filtered from result set C1 to obtain the cross-domain business data served by the same service number, and this cross-domain business data served by the same service number is used as result set D1.

[0090] S204. Based on cross-domain business data and historical experience data of the first pre-stored business, determine the cross-domain business volume threshold parameter for the same work number, and perform the first abnormal data extraction processing based on the cross-domain business volume threshold parameter and cross-domain business data to obtain the cross-domain business data of multiple times exceeding the threshold accepted by the same work number.

[0091] In this embodiment, historical cross-domain business data grouped by acceptance number is obtained based on the first pre-stored historical experience data. The average business volume and highest monthly business volume of each acceptance number over the past N months are analyzed in the historical cross-domain business data. Based on the average business volume, highest monthly business volume, and actual cross-domain business data, a cross-domain business volume threshold parameter for the same acceptance number is determined. No specific restrictions are placed on the method for obtaining the cross-domain business volume threshold parameter for the same acceptance number.

[0092] Extract data from cross-domain business data processed under the same work number that exceeds the cross-domain business volume threshold parameter, and treat it as multiple-time cross-domain business data exceeding the threshold processed under the same work number.

[0093] This paper provides a specific method for obtaining cross-domain business data with multiple frequency exceeding the threshold processed under the same work number. The calculation of cross-domain business data with multiple frequency exceeding the threshold is performed based on the selected completed feature set and the first entity channel set. This method can effectively capture abnormal operations of cross-domain business data and improve the accuracy of identifying cross-domain business data with multiple frequency exceeding the threshold.

[0094] Figure 3 A flowchart illustrating the cross-domain business order data processing method provided in this application embodiment. Figure 3 This embodiment further explains the cross-domain business order data processing method based on the above embodiments. For example... Figure 3 As shown, in the cross-domain business order data processing method of this embodiment, S204 includes:

[0095] S301. Based on cross-domain business data and historical experience data of the first pre-stored business, set the threshold parameter for cross-domain business volume for the same work number.

[0096] In this embodiment, based on the result set D1 and the first pre-stored historical experience data of services, a threshold parameter X1 for cross-domain service volume of the same service number is set. In this embodiment, X1 is 200, and can be dynamically adjusted between 150 and 250. This embodiment does not impose specific restrictions on the value of X1 or its dynamic adjustment range.

[0097] S302. Extract business data exceeding the cross-domain business volume threshold parameter from the cross-domain business data as multiple-frequency cross-domain business data exceeding the threshold accepted by the same work number.

[0098] In this embodiment, the threshold parameter X1 is applied to the result set D1 and the data is filtered to obtain the data in the result set D1 that exceeds the threshold parameter X1, thereby obtaining the cross-domain business data with multiple frequencies exceeding the threshold accepted by the same work number, and using it as the result set E1.

[0099] By setting a threshold parameter for cross-domain business volume for the same employee ID, and treating business data exceeding the threshold parameter as multiple-time cross-domain business data exceeding the threshold for the same employee ID, the boundary between normal business acceptance and abnormal operation is clearly defined through quantitative indicators, significantly improving the objectivity and operability of monitoring. At the same time, the threshold-based screening mechanism can quickly focus on high-risk employee IDs, significantly improving monitoring efficiency and providing an accurate data foundation for subsequent correlation analysis.

[0100] Figure 4 A flowchart illustrating the cross-domain business order data processing method provided in this application embodiment. Figure 4 This embodiment further explains the cross-domain business order data processing method based on the above embodiments. For example... Figure 4 As shown, in the cross-domain business order data processing method of this embodiment, S103 includes:

[0101] S401. Extract primary and secondary card orders based on the cross-domain business result set to obtain completed cross-domain processing data for primary and secondary cards. Then, filter the completed cross-domain processing data for primary and secondary cards to obtain completed cross-domain processing data for primary and secondary cards belonging to different categories.

[0102] In this embodiment, primary and secondary card orders are extracted based on result set A. The order numbers for cross-domain primary and secondary card transactions are extracted from the results set A. Order data with the status of "completed" are filtered to obtain the completed data for cross-domain primary and secondary card transactions. The completed data for cross-domain primary and secondary card transactions is then used as result set B2.

[0103] Based on result set B2, filter and process the data to extract order data where the province of origin of the supplementary card, the service number of the supplementary card, and the primary card are all different. For example, if the province of origin of the supplementary card number is A, the province of origin of the supplementary card service number is B, and the province of origin of the primary card number is C, then obtain the completed cross-regional processing data of primary and supplementary cards with different origins and use the completed cross-regional processing data of primary and supplementary cards with different origins as result set C2.

[0104] S402. Based on the completed cross-domain processing data of primary and secondary cards belonging to different entities, filter and process the data to obtain the second entity channel set.

[0105] In this embodiment, channel data of social entity channels and self-owned entity channels are filtered out from result set C2 to obtain a second entity channel set, and the second entity channel set is used as result set D2.

[0106] S403. Determine the second work number acceptance data based on the second entity channel set, and determine the cross-domain primary and secondary card business data accepted by the same work number based on the second work number acceptance data and the second entity channel set.

[0107] In this embodiment, the corresponding service number is determined for each piece of data contained in result set D2, and each corresponding service number is used as the second service number for service data. Data corresponding to the same service number in the second service number service data is filtered from result set D2 to obtain the cross-domain primary and secondary card service data accepted by the same service number, and this cross-domain primary and secondary card service data accepted by the same service number is used as result set E2.

[0108] S404. Based on cross-domain primary and secondary card business data and second pre-stored business historical experience data, determine the cross-domain primary and secondary card business volume threshold parameter for the same work number, and perform second abnormal data extraction processing based on the cross-domain primary and secondary card business volume threshold parameter and cross-domain primary and secondary card business data for the same work number to obtain the cross-domain primary and secondary card business data exceeding the threshold accepted by the same work number.

[0109] In this embodiment, historical cross-domain primary and secondary card business data grouped by acceptance number is obtained based on the second pre-stored historical experience data. The average business volume and highest monthly business volume of each acceptance number over the past N months are analyzed in the historical cross-domain primary and secondary card business data. Based on the average business volume, highest monthly business volume, and actual cross-domain primary and secondary card business data, a cross-domain primary and secondary card business volume threshold parameter for the same acceptance number is determined. No specific restrictions are placed on the method for obtaining the cross-domain primary and secondary card business volume threshold parameter for the same acceptance number.

[0110] Extract data from cross-domain primary and secondary card business data processed under the same work number that exceeds the cross-domain primary and secondary card business volume threshold parameter, and treat it as cross-domain primary and secondary card business data exceeding the threshold processed under the same work number.

[0111] This paper provides a specific method for obtaining cross-domain primary and secondary card business data exceeding the threshold processed under the same work number. The calculation of cross-domain primary and secondary card business data exceeding the threshold is performed based on the completed cross-domain processing data of primary and secondary cards belonging to different categories and the second entity channel set. This method can effectively capture abnormal operations of cross-domain primary and secondary card business data and improve the accuracy of identifying cross-domain primary and secondary card business data exceeding the threshold.

[0112] Figure 5 A flowchart illustrating the cross-domain business order data processing method provided in this application embodiment. Figure 4 This embodiment further explains the cross-domain business order data processing method based on the above embodiments. For example... Figure 5 As shown, in the cross-domain business order data processing method of this embodiment, S404 includes:

[0113] S501. Based on cross-domain primary and secondary card business data and second-pre-stored business historical experience data, set the cross-domain primary and secondary card business volume threshold parameter for the same work number.

[0114] In this embodiment, based on result set E2 and second-pre-stored historical service experience data, a threshold parameter X2 for cross-domain primary and secondary card service volume under the same work number is set. In this embodiment, X2 is 10, and can be dynamically adjusted between 5 and 15. This embodiment does not impose specific restrictions on the value of X2 or its dynamic adjustment range.

[0115] S502. Extract business data exceeding the cross-domain primary and secondary card business volume threshold parameter from the cross-domain primary and secondary card business data as cross-domain primary and secondary card business data exceeding the threshold accepted by the same work number.

[0116] In this embodiment, the threshold parameter X2 is applied to the result set E2 and the data is filtered to obtain the business data in the result set E2 that exceeds the threshold parameter X2. The cross-domain primary and secondary card business data exceeding the threshold accepted by the same work number is obtained and the cross-domain primary and secondary card business data exceeding the threshold accepted by the same work number is used as the result set F2.

[0117] By setting a threshold parameter for cross-domain primary and secondary card business volume for the same work ID, and treating business data exceeding the threshold parameter as cross-domain primary and secondary card business data exceeding the threshold for the same work ID, the boundary between normal business acceptance and abnormal operation is clearly defined through quantitative indicators, significantly improving the objectivity and operability of monitoring. At the same time, the threshold-based screening mechanism can quickly focus on high-risk work IDs, significantly improving monitoring efficiency and providing an accurate data foundation for subsequent correlation analysis.

[0118] Optionally, relevant data can be extracted manually, and manual judgment can be made based on experience to obtain frequent cross-domain business data exceeding the threshold and cross-domain primary and secondary card business data exceeding the threshold.

[0119] This embodiment further explains the cross-domain business order data processing method based on the above embodiments. In the cross-domain business order data processing method of this embodiment, step S101: preprocessing the cross-domain business order data to obtain a cross-domain business result set includes:

[0120] S601. Format the cross-domain business order data to obtain formatted source data.

[0121] In this embodiment, after obtaining cross-domain business order data, the cross-domain business order data is formatted to obtain formatted source data.

[0122] S602. Perform data cleaning on the formatted source data to obtain a cross-domain business result set after removing redundant and invalid information.

[0123] In this embodiment, after obtaining the formatted source data, the formatted source data is cleaned to remove redundant and invalid information, and then standardized to obtain a cross-domain business result set, namely result set A.

[0124] By formatting and cleaning the cross-domain business order data, a cross-domain business result set after removing redundant and invalid information is obtained, laying a reliable foundation for subsequent multi-dimensional analysis and early warning processing.

[0125] This embodiment further explains the cross-domain business order data processing method based on the above embodiments. In this embodiment, before S104, the cross-domain business order data processing method further includes:

[0126] S701. Based on the cross-domain business result set and the third pre-stored business historical experience data, perform cross-domain fixed-mobile convergence business auditing for the same work number to obtain abnormal cross-domain fixed-mobile business data accepted by the same work number.

[0127] In this embodiment, the method and effect of auditing the cross-domain fixed-mobile converged service of the same work number based on the cross-domain service result set and the third pre-stored service historical experience data are similar to the method and effect of auditing the cross-domain primary and secondary card service of the same work number based on the cross-domain service result set and the second pre-stored service historical experience data provided in the above embodiment, and will not be repeated here.

[0128] Figure 6 This is a schematic diagram of the structure of the cross-domain business order data processing device provided in an embodiment of this application. Figure 6 As shown, in this embodiment, the cross-domain business order data processing device can be located in an electronic device. The cross-domain business order data processing device includes:

[0129] The preprocessing module 801 is used to acquire cross-domain business order data and preprocess the cross-domain business order data to obtain a cross-domain business result set.

[0130] The multi-frequency cross-domain business audit processing module 802 is used to perform multi-frequency cross-domain business audit processing for the same work number based on the cross-domain business result set and the first pre-stored business historical experience data, to obtain multi-frequency cross-domain business data exceeding the threshold accepted by the same work number.

[0131] The cross-domain primary and secondary card business audit processing module 803 is used to perform cross-domain primary and secondary card business audit processing for the same work number based on the cross-domain business result set and the second pre-stored business historical experience data, and obtain the cross-domain primary and secondary card business data exceeding the threshold accepted by the same work number.

[0132] The data association processing module 804 is used to perform data association processing based on the frequent cross-domain business data exceeding the threshold and the cross-domain primary and secondary card business data exceeding the threshold, and to obtain a list of abnormal data.

[0133] The early warning association processing module 805 is used to obtain the system early warning rule configuration data, and perform early warning association processing based on the abnormal data list and the system early warning rule configuration data to obtain early warning data;

[0134] The early warning module 806 is used to perform real-time early warning operations based on early warning data.

[0135] The cross-domain business order data processing device provided in this embodiment can execute... Figure 1 The technical solution of the cross-domain business order data processing method embodiment shown herein, its implementation principle and technical effects are similar to Figure 1 The cross-domain business order data processing method shown in the example is similar and will not be described in detail here.

[0136] Meanwhile, the cross-domain business order data processing device provided by the present invention further refines the cross-domain business order data processing device based on the cross-domain business order data processing device provided in the previous embodiment.

[0137] Optionally, in this embodiment, the high-frequency cross-domain business audit processing module 802 is further used for:

[0138] Based on the cross-domain business result set, feature extraction processing is performed to obtain the completed feature set;

[0139] The first entity channel set is obtained by filtering based on the completed feature set;

[0140] The first work number's acceptance data is determined based on the first entity channel set, and the cross-domain business data accepted by the same work number is determined based on the first work number's acceptance data and the first entity channel set.

[0141] Based on cross-domain business data and historical experience data of the first pre-stored business, the threshold parameter for cross-domain business volume of the same work number is determined. Then, based on the threshold parameter for cross-domain business volume and cross-domain business data, the first abnormal data extraction process is performed to obtain the cross-domain business data of multiple times exceeding the threshold accepted by the same work number.

[0142] Optionally, in this embodiment, the high-frequency cross-domain business audit processing module 802 is further used for:

[0143] Based on cross-domain business data and historical experience data of the first pre-stored business, set the threshold parameter for cross-domain business volume for the same work number;

[0144] Extract business data that exceeds the cross-domain business volume threshold parameter from the cross-domain business data and treat it as multiple cross-domain business data exceeding the threshold processed by the same employee number.

[0145] Optionally, in this embodiment, the cross-domain primary and secondary card business audit processing module 803 is further used for:

[0146] Based on the cross-domain business result set, primary and secondary card orders are extracted to obtain the completed cross-domain processing data for primary and secondary cards. The completed cross-domain processing data for primary and secondary cards is then filtered to obtain completed cross-domain processing data for primary and secondary cards belonging to different categories.

[0147] The completed cross-domain processing data of primary and secondary cards belonging to different entities is filtered and processed to obtain the second entity channel set;

[0148] The second work number is determined based on the second entity channel set, and the cross-domain primary and secondary card business data accepted by the same work number is determined based on the second work number acceptance data and the second entity channel set.

[0149] Based on cross-domain primary and secondary card business data and second-pre-stored business historical experience data, the threshold parameter for cross-domain primary and secondary card business volume for the same work number is determined. Then, based on the threshold parameter for cross-domain primary and secondary card business volume for the same work number and the cross-domain primary and secondary card business data, a second abnormal data extraction process is performed to obtain the cross-domain primary and secondary card business data exceeding the threshold accepted by the same work number.

[0150] Optionally, in this embodiment, the cross-domain primary and secondary card business audit processing module 803 is further used for:

[0151] Based on cross-domain primary and secondary card business data and second pre-stored business historical experience data, set the cross-domain primary and secondary card business volume threshold parameter for the same work number;

[0152] Extract business data exceeding the cross-domain primary and secondary card business volume threshold parameter from the cross-domain primary and secondary card business data and treat it as cross-domain primary and secondary card business data exceeding the threshold accepted by the same work number.

[0153] Optionally, in this embodiment, the preprocessing module 801 is further configured to:

[0154] The cross-domain business order data is formatted to obtain the formatted source data;

[0155] The formatted source data is cleaned to obtain a cross-domain business result set after removing redundant and invalid information.

[0156] Optionally, this embodiment also includes a cross-domain fixed-mobile converged service audit processing module, used for:

[0157] Based on the cross-domain business result set and the third pre-stored business historical experience data, the cross-domain fixed-mobile convergence business audit process for the same work number is carried out to obtain the abnormal cross-domain fixed-mobile business data accepted by the same work number.

[0158] The cross-domain business order data processing device provided in this embodiment can execute the technical solution of the above-described cross-domain business order data processing method embodiment. Its implementation principle and technical effect are similar to those of the above-described cross-domain business order data processing method embodiment, and will not be described in detail here.

[0159] Figure 7 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. The electronic device is intended for use with various electronic devices capable of performing cross-domain business order data processing methods, such as microcomputers, single-chip microcomputers, and other suitable computers. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0160] like Figure 7 As shown, the electronic device includes at least one processor 901 and a memory 902. The electronic device also includes a communication component 903. The processor 901, memory 902, and communication component 903 are connected via a bus 904.

[0161] In the specific implementation process, at least one processor 901 executes computer execution instructions stored in memory 902, causing at least one processor 901 to execute the cross-domain business order data processing method executed on the electronic device side as described above.

[0162] The specific implementation process of processor 901 can be found in the above embodiment of cross-domain business order data processing method. Its implementation principle and technical effect are similar, and will not be repeated here.

[0163] In the above embodiments, it should be understood that the processor 901 can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor 901 can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor.

[0164] The memory 902 may include high-speed RAM memory, and may also include non-volatile memory (NVM), such as at least one disk storage.

[0165] Bus 904 can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Bus 904 can be divided into address bus, data bus, control bus, etc. For ease of illustration, the bus 904 in the accompanying drawings of this application is not limited to only one bus or one type of bus.

[0166] The above description addresses the functions implemented by electronic devices and main control devices, and introduces the solutions provided in the embodiments of this application. It is understood that, in order to achieve the above functions, the electronic device or main control device includes hardware structures and / or software modules corresponding to the execution of each function. By combining the units and algorithm steps of the various examples described in the embodiments disclosed in this application, the embodiments of this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed by hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the technical solutions of the embodiments of this application.

[0167] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the above-mentioned cross-domain business order data processing method.

[0168] The aforementioned computer-readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.

[0169] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. The readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside in application-specific integrated circuits (ASICs). Alternatively, the processor and the readable storage medium can exist as discrete components in an electronic device or a host device.

[0170] The memory 902 is the non-transitory computer-readable storage medium provided by this invention. The non-transitory computer-readable storage medium of this invention stores computer instructions that cause a computer to execute the cross-domain business order data processing method provided by this invention.

[0171] Memory 902, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs, non-transitory computer-executable programs, and modules, such as the program instructions / modules corresponding to the cross-domain business order data processing method in the embodiments of this application (e.g., Figure 6 The preprocessing module 801, the high-frequency cross-domain business audit processing module 802, the cross-domain primary and secondary card business audit processing module 803, the data association processing module 804, the early warning association processing module 805, and the early warning module 806 are shown. The processor 901 executes various functional applications and data processing by running non-transient software programs, instructions, and modules stored in the memory 902, thereby implementing the cross-domain business order data processing method in the above method embodiment.

[0172] In addition, this embodiment also provides a computer program product, including a computer program, which, when executed by a processor, is used to implement the cross-domain business order data processing method of the above embodiment.

[0173] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily essential to this application.

[0174] It should be further noted that although the steps in the flowchart are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowchart may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0175] It should be understood that the above-described device embodiments are merely illustrative, and the device of this application can also be implemented in other ways. For example, the division of units / modules in the above embodiments is only a logical functional division, and there may be other division methods in actual implementation. For example, multiple units, modules, or components may be combined, or integrated into another system, or some features may be ignored or not executed.

[0176] Furthermore, unless otherwise specified, the functional units / modules in the various embodiments of this application can be integrated into one unit / module, or each unit / module can exist physically separately, or two or more units / modules can be integrated together. The integrated units / modules described above can be implemented in hardware or as software program modules.

[0177] When an integrated unit / module is implemented in hardware, the hardware can be digital circuits, analog circuits, etc. The physical implementation of the hardware structure includes, but is not limited to, transistors, memristors, etc. Unless otherwise specified, the processor can be any suitable hardware processor, such as a CPU, GPU, FPGA, DSP, and ASIC, etc. Unless otherwise specified, the storage unit can be any suitable magnetic or magneto-optical storage medium, such as Resistive Random Access Memory (RRAM), Dynamic Random Access Memory (DRAM), Static Random-Access Memory (SRAM), Enhanced Dynamic Random Access Memory (EDRAM), High-Bandwidth Memory (HBM), Hybrid Memory Cube (HMC), etc.

[0178] If the integrated unit / module is implemented as a software program module and sold or used as an independent product, it can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned memory includes various media capable of storing program code, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard drive, magnetic disk, or optical disk.

[0179] In the above embodiments, the descriptions of each embodiment have their own emphasis. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments. The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as the combination of these technical features does not contradict each other, it should be considered within the scope of this specification.

[0180] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this application are indicated by the following claims.

[0181] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A method for processing cross-domain business order data, characterized in that, include: Obtain cross-domain business order data and preprocess the cross-domain business order data to obtain a cross-domain business result set; Based on the cross-domain business result set and the first pre-stored business historical experience data, the audit processing of multiple cross-domain business with the same work number is carried out to obtain the data of multiple cross-domain business exceeding the threshold accepted by the same work number. Based on the cross-domain business result set and the second pre-stored business historical experience data, the cross-domain primary and secondary card business auditing process of the same work number is carried out to obtain the cross-domain primary and secondary card business data exceeding the threshold accepted by the same work number. Data association processing is performed on the frequent cross-domain service data exceeding the threshold and the cross-domain primary and secondary card service data exceeding the threshold to obtain an abnormal data list; Obtain system early warning rule configuration data, and perform early warning association processing based on the abnormal data list and the system early warning rule configuration data to obtain early warning data; Perform immediate warning operations based on the warning data.

2. The cross-domain business order data processing method according to claim 1, characterized in that, The step of performing auditing on multiple cross-domain services with the same work number based on the cross-domain service result set and the first pre-stored historical experience data of services, to obtain the data on multiple cross-domain services exceeding the threshold accepted by the same work number, includes: Based on the cross-domain business result set, feature extraction processing is performed to obtain the completed feature set; The first entity channel set is obtained by filtering the completed feature set. The first work number acceptance data is determined based on the first entity channel set, and cross-domain business data accepted by the same work number is determined based on the first work number acceptance data and the first entity channel set. Based on the cross-domain business data and the first pre-stored historical experience data, the cross-domain business volume threshold parameter for the same work number is determined, and the first abnormal data extraction processing is performed based on the cross-domain business volume threshold parameter and the cross-domain business data to obtain the cross-domain business data of the same work number that exceeds the threshold multiple times.

3. The cross-domain business order data processing method according to claim 2, characterized in that, The step involves determining a threshold parameter for the cross-domain business volume of the same employee ID based on the cross-domain business data and the first pre-stored historical experience data, and performing a first abnormal data extraction process based on the threshold parameter and the cross-domain business data to obtain the multiple-times-exceeding-threshold cross-domain business data accepted by the same employee ID, including: Based on the cross-domain business data and the first pre-stored business historical experience data, set the cross-domain business volume threshold parameter for the same work number; The business data exceeding the cross-domain business volume threshold parameter is extracted from the cross-domain business data and used as the multiple-frequency cross-domain business data exceeding the threshold accepted by the same employee number.

4. The cross-domain business order data processing method according to claim 1, characterized in that, The step of performing cross-domain primary and secondary card business auditing based on the cross-domain business result set and the second pre-stored business historical experience data to obtain the cross-domain primary and secondary card business data exceeding the threshold accepted by the same work number includes: Based on the cross-domain business result set, primary and secondary card orders are extracted to obtain the completed cross-domain processing data of primary and secondary cards. The completed cross-domain processing data of primary and secondary cards is then filtered to obtain the completed cross-domain processing data of primary and secondary cards belonging to different categories. The completed cross-domain processing data of primary and secondary cards belonging to different categories is filtered to obtain the second entity channel set; The second work number acceptance data is determined based on the second entity channel set, and the cross-domain primary and secondary card business data accepted by the same work number is determined based on the second work number acceptance data and the second entity channel set. Based on the cross-domain primary and secondary card service data and the second pre-stored service historical experience data, the cross-domain primary and secondary card service volume threshold parameter for the same work number is determined. Then, based on the cross-domain primary and secondary card service volume threshold parameter for the same work number and the cross-domain primary and secondary card service data, a second abnormal data extraction process is performed to obtain the cross-domain primary and secondary card service data exceeding the threshold accepted by the same work number.

5. The cross-domain business order data processing method according to claim 4, characterized in that, The step involves determining the cross-domain primary and secondary card service volume threshold parameter for the same employee ID based on the cross-domain primary and secondary card service data and the second pre-stored service historical experience data. Then, based on the cross-domain primary and secondary card service volume threshold parameter for the same employee ID and the cross-domain primary and secondary card service data, a second abnormal data extraction process is performed to obtain the cross-domain primary and secondary card service data exceeding the threshold processed by the same employee ID, including: Based on the cross-domain primary and secondary card service data and the second pre-stored service historical experience data, set the cross-domain primary and secondary card service volume threshold parameter for the same work number; The service data exceeding the cross-domain primary and secondary card service volume threshold parameter is extracted from the cross-domain primary and secondary card service data and used as the cross-domain primary and secondary card service data exceeding the threshold accepted by the same employee number.

6. The cross-domain business order data processing method according to claim 1, characterized in that, The preprocessing of the cross-domain business order data to obtain the cross-domain business result set includes: The cross-domain business order data is formatted to obtain formatted source data; The formatted source data is cleaned to obtain a cross-domain business result set after removing redundant and invalid information.

7. The cross-domain business order data processing method according to any one of claims 1 to 6, characterized in that, Before performing data association processing based on the high-frequency cross-domain service data exceeding the threshold and the cross-domain primary and secondary card service data exceeding the threshold to obtain the abnormal data list, the process also includes: Based on the cross-domain business result set and the third pre-stored business historical experience data, the cross-domain fixed-mobile fusion business auditing process of the same work number is performed to obtain the abnormal cross-domain fixed-mobile business data accepted by the same work number.

8. A cross-domain business order data processing device, characterized in that, include: The preprocessing module is used to acquire cross-domain business order data and preprocess the cross-domain business order data to obtain a cross-domain business result set; The multi-frequency cross-domain business audit processing module is used to perform multi-frequency cross-domain business audit processing for the same work number based on the cross-domain business result set and the first pre-stored business historical experience data, to obtain the multi-frequency cross-domain business data exceeding the threshold accepted by the same work number. The cross-domain primary and secondary card business audit processing module is used to perform cross-domain primary and secondary card business audit processing for the same work number based on the cross-domain business result set and the second pre-stored business historical experience data, to obtain the cross-domain primary and secondary card business data exceeding the threshold accepted by the same work number; The data association processing module is used to perform data association processing based on the multi-frequency cross-domain business data exceeding the threshold and the cross-domain primary and secondary card business data exceeding the threshold, and obtain an abnormal data list; The early warning association processing module is used to obtain system early warning rule configuration data, and perform early warning association processing based on the abnormal data list and the system early warning rule configuration data to obtain early warning data; The early warning module is used to perform real-time early warning operations based on the early warning data.

9. An electronic device, characterized in that, include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory to implement the cross-domain business order data processing method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the cross-domain business order data processing method as described in 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 the processor, it is used to implement the cross-domain business order data processing method as described in any one of claims 1 to 7.

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