CN115271970A - Intelligent auditing system, method and device for security business - Google Patents
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Abstract
The system comprises a K-AIAM system and a K-RPA system, wherein the K-AIAM system can be in butt joint with a plurality of systems such as a field service handling system, the K-RPA system, an AI interface, an asset system and the like, a solution thought for intelligent auditing facing operation is provided, a standardized and intelligent account service auditing system is established through an intelligent auditing platform, and the intellectualization and automation of operation work such as authentication/authorization service of various customer services and the like are realized.
Description
Technical Field
The application relates to the field of security intelligent auditing, in particular to an intelligent auditing system, method and device for security business.
Background
In recent years, with the rapid development of a security industry service platform, people have higher and higher requirements on speed and efficiency, and various ticket merchants are continuously improving customer experience and enhancing customer service in all aspects. Under the tide of mobile internet, more and more security dealer first pushes the internet to open an account. However, it is not easy for investors to open accounts smoothly in securities companies. The remote video witnesses which increase personnel cost, influence customer experience and cause customer churn are common pain points of security industry transportation.
Therefore, the above technical problems of the related art need to be solved.
Disclosure of Invention
The present application is directed to solving one of the technical problems in the related art. Therefore, the embodiment of the application provides an intelligent auditing system, method and device for securities business, which can be externally connected with a plurality of systems to intelligently audit securities.
According to an aspect of an embodiment of the present application, an intelligent auditing system for securities business is provided, the system including: K-AIAM system, K-RPA system;
the K-AIAM system deploys an installation package through a Linux server, wherein the K-AIAM system needs to be opened with a related docking system and a network strategy of related interface authority;
the production environment program of the K-AIAM system is separated from the database and is independently deployed;
the K-RPA system comprises an RPA server used for intelligent auditing, and the RPA server is shared with an RPA server of the financial management system;
the K-RPA system captures data and writes back the data, and inserts, inquires and modifies the data by accessing a table and a table structure fixed by the K-AIAM system;
the K-AIAM system inquires a large table of the K-RPA inserting system, wherein the large table inserted by the K-RPA system comprises a single number of a record, a service scene and a JSON large field of a page element;
and the K-AIAM system stores the JSON large field of the page element into a data table according to the service scene classification, and is used for front-end page display, audit result storage and third-party docking result storage.
In one embodiment, when a client accesses a service scene page in the K-AIAM system to process auditing, the page in the K-AIAM system displays a result after a third-party interface is called, corresponding third-party data is processed and called in a background, and the client saves the relevant auditing result and data to a corresponding service scene data table.
In one embodiment, the K-AIAM system backfills data after customer review back to a big data table, wherein the big data table stores JSON big fields of page elements, and the number fetching pages are called by the K-RPA system to be written back.
In one embodiment, the K-AIAM system interfaces with a field service transaction system;
the K-AIAM system captures a worksheet number of a field business handling system handling end claim list and page display public information of a plurality of related scenes through Google browser webpage elements;
the K-AIAM system calls page acquisition scripts of different scene types through the worksheet numbers and the scene types of the list to acquire data of different service scene types;
the K-AIAM system combines all elements contained in the page according to JSON specification, uniformly returns the elements to a page content field, and records all element values to be grabbed in the elements in a key-value form.
In one embodiment, the K-AIAM system interfaces with an AI interface, asset system;
the K-AIAM system analyzes, compares and judges the business order data captured by the K-RPA system with an AI platform, and verifies the identification result of the file through the OCR capability of the AI platform;
the K-AIAM system analyzes, compares and judges the business order data captured by the K-RPA system and the asset data of the big data platform; judging whether the asset data of the applicant in the business meets the business handling requirement
In one embodiment, the K-AIAM system interfaces with an intelligent dual-recording video system;
the K-AIAM system inquires the flow sheet page nesting of the intelligent double-recording video system corresponding to the service sheet captured by the K-RPA system;
and the K-AIAM system writes back the auditing result of the business list to the running list of the intelligent double-recording video system.
In one embodiment, the K-AIAM system interfaces with a counter system, a portal system;
the K-AIAM system acquires a paperless protocol video file path, a signature picture and an electronic protocol path acquisition interface provided by a counter;
the K-AIAM system acquires qualification auditing data provided by the field business handling system, compares the qualification auditing data with the data captured by the K-RPA system, and judges whether the auditing data pass
According to an aspect of the embodiments of the present application, there is provided an intelligent auditing method for securities business, which is applied to the intelligent auditing system for securities business described in the previous embodiments, the method includes:
the K-AIAM system deploys an installation package through a Linux server, wherein the K-AIAM system needs to be opened with a related docking system and a network strategy of related interface authority;
capturing data and writing back the data, and performing insertion, query and modification by accessing a table and a table structure fixed by the K-AIAM system;
inquiring a large table of the K-RPA system insertion system, wherein the large table of the K-RPA system insertion system comprises a single number of a record, a service scene and a JSON large field of a page element;
and inserting the JSON large field of the page element into a corresponding service scene data table according to the service scene classification, and storing the front-end page display, the verification result and the third-party docking result.
According to an aspect of the embodiments of the present application, there is provided an intelligent auditing apparatus for securities business, the apparatus including:
the system comprises a first module, a second module and a third module, wherein the first module is used for deploying a system installation package by a K-AIAM system through a Linux server, and the K-AIAM system needs to be opened with a related docking system and a network strategy of a related interface authority;
the second module is used for capturing data and writing back the data, and performing insertion, query and modification by accessing a table and a table structure fixed by the K-AIAM system;
the third module is used for inquiring a large table of a K-RPA inserting system, wherein the large table of the K-RPA inserting system comprises a single number of a record, a service scene and a JSON large field of a page element;
and the fourth module is used for storing the JSON large field of the page element into a data table according to the service scene classification, and is used for front-end page display, audit result storage and third-party docking result storage.
According to an aspect of the embodiments of the present application, there is provided an intelligent auditing apparatus for securities business, the apparatus including:
at least one processor;
at least one memory for storing at least one program;
at least one of the programs, when executed by at least one of the processors, implements an intelligent auditing method for securities business as described in previous embodiments.
The intelligent auditing system, method and device for securities business provided by the embodiment of the application have the beneficial effects that: the system comprises a K-AIAM system and a K-RPA system, wherein the K-AIAM system can be in butt joint with a plurality of systems such as a field service handling system, the K-RPA system, an AI interface, an asset system and the like, a solution thought of intelligent auditing facing operation is provided, a standardized and intelligent account service auditing system is established through an intelligent auditing platform, and intellectualization and automation of operation work such as authentication/authorization service of various client services and the like are realized.
Additional aspects and advantages of the present application will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the present application.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
FIG. 1 is a system architecture diagram of an intelligent auditing system, method and apparatus for securities business provided by embodiments of the present application;
FIG. 2 is a flowchart of an intelligent auditing system, method and apparatus for securities business according to an embodiment of the present application;
FIG. 3 is a schematic diagram of an intelligent auditing apparatus for securities business provided by an embodiment of the present application;
fig. 4 is a schematic diagram of another intelligent auditing apparatus for securities business provided in the embodiments of the present application.
Detailed Description
In order to make the technical solutions better understood by those skilled in the art, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only partial embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The terms "first," "second," "third," and "fourth," etc. in the description and claims of this application and the accompanying drawings are used for distinguishing between different objects and not for describing a particular order. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.
With the rapid development of the service platform in the securities industry in recent years, people have higher and higher requirements on speed and efficiency, and various securities trades are continuously improving customer experience and enhancing customer service in various aspects. Under the tide of mobile internet, more and more security dealer first pushes the internet to open an account. However, it is not easy for investors to open accounts smoothly in securities companies. The remote video witnesses which increase personnel cost, affect customer experience and cause customer loss are common pain points of security industry transportation management.
AI and RPA techniques are widely used, and various repetitive work which consumes a large amount of manpower and time can be handed over to a 'robot' to replace labor. Based on the background, the application provides an intelligent auditing system, method and device for security business, and automatic auditing is realized for 7 × 24 hours by an AI + RPA technology. As shown in fig. 2, the intelligent auditing system, method and device for securities business provided by the application can replace a large amount of manual repeated operations to reduce the pressure of personnel and resource consumption, standardize the auditing execution flow, improve the working efficiency and enhance the reliability of auditing; more importantly, the waiting time of the client is greatly shortened, and the satisfaction degree of the client is improved.
As shown in fig. 1, the present application provides an intelligent auditing system for securities business, which comprises: K-AIAM system, K-RPA system; the K-AIAM system deploys a system installation package through a Linux server, wherein the K-AIAM system needs to be opened with a related docking system and a network strategy of related interface authority; the production environment program and the database of the K-AIAM system are separated and independently deployed; the K-RPA system comprises an RPA server used for intelligent auditing, and the RPA server is shared with an RPA server of the financial management system; the K-RPA system grabs data and writes back data, and inserts, inquires and modifies the data by accessing a table and a table structure fixed by the K-AIAM system; the K-AIAM system inquires a large table of the K-RPA inserting system, and the large table inserted by the K-RPA system comprises a single number of a record, a service scene and a JSON large field of a page element; and the K-AIAM system inserts the JSON large field of the page element into a corresponding service scene data table according to service scene classification for front-end page display, audit result storage and third-party docking result storage.
In the system of this embodiment, when a client accesses a service scene page in the K-AIAM system to process auditing, the page in the K-AIAM system displays a result after a third-party interface is called, corresponding third-party data is processed and invoked in the background, and the client saves a relevant auditing result and also saves data in a corresponding service scene data table.
The K-AIAM system according to this embodiment backfills data after customer review back to a big data table, where a JSON big field of a page element is stored in the big data table, so that the K-RPA system calls a fetch page to write back.
If necessary, the K-AIAM system is in butt joint with the field service handling system; the K-AIAM system captures a work order number of a field business handling system handling end claim list and public information of a plurality of related scenes through webpage elements of a Google browser; the K-AIAM system calls page acquisition scripts of different scene types through the worksheet numbers and the scene types of the list to acquire data of different service scene types; the K-AIAM system combines all elements contained in the page according to JSON specification, uniformly returns the elements to a page content field, and records all element values to be grabbed in the elements in a key-value form.
In addition, the K-AIAM system can be in butt joint with an AI interface and an asset system; the K-AIAM system analyzes, compares and judges the service order data captured by the K-RPA system and an AI platform; and the K-AIAM system analyzes, compares and judges the service order data captured by the K-RPA system and the asset data of the big data platform.
In addition, the K-AIAM system can be in butt joint with an intelligent double-recording video system; the K-AIAM system inquires the flow sheet page nesting of intelligent audit corresponding to the service sheet captured by the RPA system; and the K-AIAM system writes back the auditing result of the business list to the running list of the intelligent double-recording video system.
Furthermore, the K-AIAM system can be also interfaced with a counter system and a portal system; the K-AIAM system acquires a paperless protocol video file path, a signature picture and an electronic protocol path acquisition interface provided by a counter; and the K-AIAM system acquires qualification verification data provided by the field business handling system and compares the qualification verification data with the captured data.
Specifically, the K-AIAM system of the present application has the following characteristics: deploying a system installation package through a Linux server provided by a client; network strategies requiring connection with a relevant docking system and a relevant interface authority are opened; the programs and the database of the production environment are separated and are independently deployed. The disaster recovery scheme of the K-AIAM system comprises the following steps: hot standby of a database and cold standby of a program; there is no cluster.
Specifically, the K-RPA system of the application has the following characteristics: the K-RPA system is deployed through one Windows system. The RPA server for intelligent audit is shared with the RPA server for finance; and the robots for Agent capture and write back are not shared. The disaster recovery scheme of the K-RPA system is deployed according to automatic double-click mutual recovery.
It should be noted that the K-AIAM system of the present application can interface with multiple systems, and specifically includes:
(1) K-RPA interfaces with the field service handling system
Data capturing:
a) The work order number of the on-site business handling system handling end claim list and the public information of the related 25 scenes are captured through webpage elements of a Google browser, for example: a service scenario type field.
b) And judging and calling page acquisition scripts of different scene types according to the work order number and the scene type of the list to acquire data of different service scene types.
c) All elements contained in the page are combined according to JSON specification, a page content field is returned uniformly, and all element values to be grabbed in the elements are recorded in the page content field in a key-value mode.
And (3) writing back data:
a) The K-RPA directly searches the work order information of the relevant service scene, enters a transaction page (the system can automatically claim), then writes back the audit data in the large table, and modifies the identification of the large table after writing back
And (3) implementing the specification:
a) The JSON specification combination key field is consistent with the AIAM service table field.
b) The large fields of the partial traffic table (e.g.: picture JSON) directly stores the related JSON, and then displays the data through code parsing.
c) And (3) capturing a script field naming rule: the field names are typically not more than three english words, either in terms of hump specifications or spaced by underlining.
(2) K-RPA interfacing with K-AIAM systems
a) The K-RPA fetches and writes back data, inserts and queries and modifies by accessing the K-AIAM fixed table (large table) and table structure.
b) The K-AIAM inquires a large table inserted by the K-RPA, and the large table contains related contents such as the number of the record belonging to the single number, the service scene belonging to the single number, the JSON large field of the page element and the like.
c) And the K-AIAM inserts the JSON large field of the page element into a corresponding service scene data table according to the service scene classification, and is used for front-end page display, audit result storage and third-party docking result storage.
d) And the client processes and audits a certain service scene page in the access K-AIAM system, the page displays the result of the third-party interface call, the butt joint call of the related third-party data is completed in the background process, and the data can be stored in the corresponding service scene data table when the client stores the related audit result.
e) And backfilling the data after the client is audited back to a big data table (storing JSON big fields of page elements) for the K-RPA to call and write back the access page.
And (3) implementing the specification:
a) A business scenario establishes a scenario.
b) And carrying out public packaging on the third-party system connected with each scene.
c) The table name is a function _ service, such as the iam _ open _ account intelligent audit account opening.
d) The field names are according to hump specifications and generally do not exceed three english words.
(3) K-AIAM system interfacing with AI interface
And analyzing, comparing and judging the service single data captured by the K-RPA and the AI platform.
(4) K-AIAM system interfacing with asset system
And analyzing, comparing and judging the service order data captured by the K-RPA and the asset data of the big data platform.
(5) K-AIAM system and intelligent double-recording video system butt joint
The butt joint briefly states: inquiring the flow sheet page nesting corresponding to intelligent audit of the service sheets captured by the RPA; and writing back the auditing result of the business list to the running list of the intelligent double-recording video system.
And docking logic: and taking two fields of a video audit state and a service audit state as a standard, and calling the result write-back of which type when the result is written back.
(6) K-AIAM system interfacing with counter system
The butt joint briefly describes: acquiring a paperless protocol video file path, a signature picture and an electronic version protocol path acquisition interface provided by a counter, and standing to form a paperless page; obtaining qualification auditing data provided by the counter, and comparing the qualification auditing data with the captured data
(7) K-AIAM interfacing with portal system
The butt joint briefly describes: and performing single-point nesting on the to-do list of the platform to the portal system.
In addition, the present application also provides an intelligent auditing method for securities business, which is applied to the intelligent auditing system for securities business described in the previous embodiments, and the method includes: the K-AIAM system deploys a system installation package through a Linux server, wherein the K-AIAM system needs to be opened with a related docking system and a network strategy of related interface authority; capturing data and writing back the data, and performing insertion, query and modification by accessing a table and a table structure fixed by the K-AIAM system; inquiring a large table of the K-RPA inserting system, wherein the large table of the K-RPA inserting system comprises a single number of a record, a service scene and a JSON large field of a page element; and inserting the JSON large field of the page element into a corresponding service scene data table according to the service scene classification, and storing the front-end page display, the verification result and the third-party docking result.
In addition, the present application also proposes an intelligent auditing apparatus for securities business, as shown in fig. 3, the apparatus includes:
a first module 301, configured to deploy a system installation package by the K-AIAM system through a Linux server, where the K-AIAM system needs to be opened with a network policy of a relevant docking system and a relevant interface authority;
a second module 302, configured to grab data and write back data, insert, query, and modify by accessing a table and a table structure fixed by the K-AIAM system;
a third module 303, configured to query a large table of the K-RPA insertion system, where the large table of the K-RPA insertion system includes a single number of a record, a service scene, and a JSON large field of a page element;
a fourth module 304, configured to insert the JSON large field of the page element into a corresponding service scene data table according to service scene classification, and use for front-end page display, audit result storage, and third-party docking result storage.
In addition, the present application also proposes an intelligent auditing apparatus for securities business, as shown in fig. 4, the apparatus includes:
at least one processor 401;
at least one memory 402, the memory 402 for storing at least one program;
when executed by at least one of the processors 401, at least one of the programs implements an intelligent auditing method for securities business as described in the previous embodiments.
In alternative embodiments, the functions/acts noted in the block diagrams may occur out of the order noted in the operational illustrations. For example, two blocks shown in succession may in fact be executed substantially concurrently or the blocks may sometimes be executed in the reverse order, depending upon the functionality/acts involved. Furthermore, the embodiments presented and described in the flowcharts of the present application are provided by way of example in order to provide a more comprehensive understanding of the technology. The disclosed methods are not limited to the operations and logic flows presented herein. Alternative embodiments are contemplated in which the order of various operations is changed and in which sub-operations described as part of larger operations are performed independently.
Furthermore, although the present application is described in the context of functional modules, it should be understood that, unless otherwise stated to the contrary, one or more of the functions and/or features may be integrated in a single physical device and/or software module, or one or more functions and/or features may be implemented in a separate physical device or software module. It will also be appreciated that a detailed discussion regarding the actual implementation of each module is not necessary for an understanding of the present application. Rather, the actual implementation of the various functional modules in the apparatus disclosed herein will be understood within the ordinary skill of an engineer given the nature, function, and interrelationships of the modules. Accordingly, those skilled in the art can, using ordinary skill, practice the present application as set forth in the claims without undue experimentation. It is also to be understood that the specific concepts disclosed are merely illustrative of and not intended to limit the scope of the application, which is defined by the appended claims and their full scope of equivalents.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The logic and/or steps represented in the flowcharts or otherwise described herein, e.g., an ordered listing of executable instructions that can be considered to implement logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device.
It should be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
In the foregoing description of the specification, reference to the description of "one embodiment/example," "another embodiment/example," or "certain embodiments/examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
While embodiments of the present application have been shown and described, it will be understood by those of ordinary skill in the art that: numerous changes, modifications, substitutions and variations can be made to the embodiments without departing from the principles and spirit of the application, the scope of which is defined by the claims and their equivalents.
The above embodiments are only used to illustrate the technical solutions of the present application, and not to limit the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions in the embodiments of the present application.
Claims (10)
1. An intelligent auditing system for securities business, the system comprising: K-AIAM system, K-RPA system;
the K-AIAM system deploys a system installation package through a Linux server, wherein the K-AIAM system needs to be opened with a related docking system and a network strategy of related interface authority;
the production environment program and the database of the K-AIAM system are separated and independently deployed;
the K-RPA system comprises an RPA server used for intelligent auditing, and the RPA server is shared with an RPA server of the financial management system;
the K-RPA system grabs data and writes back data, and inserts, inquires and modifies the data by accessing a table and a table structure fixed by the K-AIAM system;
the K-AIAM system inquires a large table of the K-RPA inserting system, and the large table inserted by the K-RPA system comprises a single number of a record, a service scene and a JSON large field of a page element;
and the K-AIAM system stores the JSON large field of the page element into a data table according to the service scene classification, and is used for front-end page display, audit result storage and third-party docking result storage.
2. The system of claim 1, wherein when a customer accesses a service scenario page in the K-AIAM system to perform a processing audit, the page in the K-AIAM system displays a result of a third-party interface call, the corresponding third-party data interface call is performed in a background, and the customer saves the relevant audit result and the data in the corresponding service scenario data table.
3. The system of claim 1, wherein the K-AIAM system backfills customer audited data back into a big data table, the big data table storing JSON big fields of page elements for the K-RPA system to call fetch page write back.
4. An intelligent auditing system for a security transaction according to claim 1, where the K-AIAM system interfaces with a field transaction system;
the K-AIAM system captures a work order number of a field business handling system handling end claim list and public information of a plurality of related scenes through webpage elements of a Google browser;
the K-AIAM system calls page acquisition scripts of different scene types through the worksheet numbers and the scene types of the list to acquire data of different service scene types;
the K-AIAM system combines all elements contained in the page according to JSON specification, uniformly returns all elements to a page content field, and records all element values to be grabbed in the elements in a key-value form.
5. An intelligent auditing system for a securities business according to claim 1, where the K-AIAM system interfaces with an AI interface, asset system;
the K-AIAM system analyzes, compares and judges the business single data captured by the K-RPA system with an AI platform;
and the K-AIAM system analyzes, compares and judges the service order data captured by the K-RPA system and the asset data of the big data platform.
6. An intelligent auditing system for a securities business according to claim 1, where the K-AIAM system interfaces with an intelligent double-recording video system;
the K-AIAM system inquires the flow sheet page nesting of intelligent audit corresponding to the service sheet captured by the RPA system;
and the K-AIAM system writes back the auditing result of the business list to the running list of the intelligent double-recording video system.
7. An intelligent auditing system for a security service according to claim 1 where the K-AIAM system interfaces with a counter system, a portal system;
the K-AIAM system acquires a paperless protocol video file path, a signature picture and an electronic version protocol path acquisition interface provided by a counter;
and the K-AIAM system acquires the acquired qualification auditing data provided by the field business handling system, compares the qualification auditing data with the data captured by the K-RPA system and judges whether the auditing is passed or not.
8. An intelligent auditing method for securities business, applied to an intelligent auditing system for securities business of claim 1, said method comprising:
the K-AIAM system deploys a system installation package through a Linux server, wherein the K-AIAM system needs to be opened with a related docking system and a network strategy of related interface authority;
capturing data and writing back the data, and performing insertion, query and modification by accessing a table and a table structure fixed by the K-AIAM system;
querying a large table of the K-RPA inserting system, wherein the large table of the K-RPA inserting system comprises a single number of a record, a service scene and a JSON large field of a page element;
and storing the JSON large field of the page element into a data table according to the service scene classification, and storing the front-end page display, the verification result and the third-party docking result.
9. An intelligent auditing apparatus for securities business, the apparatus comprising:
the system comprises a first module, a second module and a third module, wherein the first module is used for deploying an installation package by a K-AIAM system through a Linux server, and the K-AIAM system needs to be opened with a related docking system and a network strategy of related interface authority;
the second module is used for capturing data and writing back the data, and performing insertion, query and modification by accessing a table and a table structure fixed by the K-AIAM system;
the third module is used for inquiring a large table of a K-RPA inserting system, wherein the large table of the K-RPA inserting system comprises a single number of a record, a service scene and a JSON large field of a page element;
and the fourth module is used for inserting the JSON large field of the page element into a corresponding service scene data table according to service scene classification, and is used for front-end page display, audit result storage and third-party docking result storage.
10. An intelligent auditing apparatus for a security service, the apparatus comprising:
at least one processor;
at least one memory for storing at least one program;
an intelligent auditing method for a security service according to claim 8 when at least one of said programs is executed by at least one of said processors.
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Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR102008707B1 (en) * | 2019-03-26 | 2019-08-09 | 이종훈 | Risk management system |
| CN111783636A (en) * | 2020-06-30 | 2020-10-16 | 中国工商银行股份有限公司 | OCR-based international reimbursement network application data processing method and device |
| CN112541828A (en) * | 2020-12-15 | 2021-03-23 | 国泰君安证券股份有限公司 | System, method, device, processor and storage medium for realizing open securities management and open securities API access control |
| CN113034118A (en) * | 2021-04-25 | 2021-06-25 | 中国工商银行股份有限公司 | Business auditing method, system, readable storage medium and computer program product |
| CN114186019A (en) * | 2021-11-03 | 2022-03-15 | 北京来也网络科技有限公司 | Enterprise project auditing method and device combining RPA and AI |
| CN114445836A (en) * | 2022-01-26 | 2022-05-06 | 来也科技(北京)有限公司 | Information auditing method and device combining RPA and AI and electronic equipment |
| CN114693269A (en) * | 2022-04-07 | 2022-07-01 | 上海来也伯特网络科技有限公司 | Invoice verification service handling method and device combining RPA and AI and electronic equipment |
| CN115049353A (en) * | 2022-03-28 | 2022-09-13 | 湖南三湘银行股份有限公司 | RPA-based automatic flow implementation method |
-
2022
- 2022-09-28 CN CN202211186257.1A patent/CN115271970A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR102008707B1 (en) * | 2019-03-26 | 2019-08-09 | 이종훈 | Risk management system |
| CN111783636A (en) * | 2020-06-30 | 2020-10-16 | 中国工商银行股份有限公司 | OCR-based international reimbursement network application data processing method and device |
| CN112541828A (en) * | 2020-12-15 | 2021-03-23 | 国泰君安证券股份有限公司 | System, method, device, processor and storage medium for realizing open securities management and open securities API access control |
| CN113034118A (en) * | 2021-04-25 | 2021-06-25 | 中国工商银行股份有限公司 | Business auditing method, system, readable storage medium and computer program product |
| CN114186019A (en) * | 2021-11-03 | 2022-03-15 | 北京来也网络科技有限公司 | Enterprise project auditing method and device combining RPA and AI |
| CN114445836A (en) * | 2022-01-26 | 2022-05-06 | 来也科技(北京)有限公司 | Information auditing method and device combining RPA and AI and electronic equipment |
| CN115049353A (en) * | 2022-03-28 | 2022-09-13 | 湖南三湘银行股份有限公司 | RPA-based automatic flow implementation method |
| CN114693269A (en) * | 2022-04-07 | 2022-07-01 | 上海来也伯特网络科技有限公司 | Invoice verification service handling method and device combining RPA and AI and electronic equipment |
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