Data processing method, device, electronic device, medium and computer program

Abstract

The present disclosure provides a data processing method, device, electronic device, medium and computer program for account opening. The above method includes: setting multiple approval task pools according to regions, determining the approval parameters of each approval task pool; obtaining m groups of data when m customers open accounts, wherein the m groups of data come from n regions, m is an integer greater than or equal to 1, and n is an integer greater than or equal to 1; determining the account opening bank information corresponding to each group of data, and the account opening bank information includes regional information; according to the regional information, extracting the data corresponding to the regional information to the approval task pool corresponding to the regional information; and approving the data according to the approval parameters. In this way, the problem of uneven busyness of each branch can be alleviated, and the labor cost can be reduced, so that the centralized account approval business can be automated, differentiated and direct, and the diversity, accuracy, timeliness and compliance of the account opening business can be effectively improved.

Description

Technical Field

[0001] The present disclosure relates to the field of artificial intelligence technology, and more specifically, to a data processing method, device, electronic device, computer-readable storage medium and computer program for account opening. Background Art

[0002] Due to the gradual implementation of the cancellation of the corporate bank account licensing system by relevant departments, banks have changed the approval system to a filing system for opening basic deposit accounts and temporary deposit accounts for corporate customers, and the filing of corporate basic accounts has been changed from prior filing to immediate filing upon account opening, which has greatly increased the timeliness requirements for review and filing; coupled with the principle of local account management, that is, the standards for review and filing required by relevant departments in various places are not unified, which has further increased the cost of manual reporting at each branch outlet.

[0003] Based on the above problems, it is necessary to provide a set of efficient and accurate public account process systems from a business perspective that can differentiate the audit and filing requirements of each branch, so as to simplify personnel operations, shorten the account opening cycle, and improve branch service efficiency and customer satisfaction. In the context of localized account management, the current public account business in various places has different audit and filing requirements, and there are links that are highly dependent on manual operations such as image recognition, voucher information entry, uniqueness verification, consistency verification, and long-suspended account verification. Therefore, there are many and scattered account management systems, high manual error rates in business processing, and uneven busyness and idleness of branches due to different distributions of population resources. Summary of the invention

[0004] In view of this, the present disclosure provides a data processing method, device, electronic device, computer-readable storage medium and computer program for account opening that are low-cost and can improve the diversity, accuracy, timeliness and compliance of account opening services.

[0005] One aspect of the present disclosure provides a data processing method for account opening, including: setting up multiple approval task pools according to regions, and determining approval parameters for each of the approval task pools; obtaining m groups of data materials when m customers open accounts, wherein the m groups of data materials come from n regions, m is an integer greater than or equal to 1, and n is an integer greater than or equal to 1; determining account opening bank information corresponding to each group of the data materials, the account opening bank information includes regional information; based on the regional information, extracting the data materials corresponding to the regional information to the approval task pool corresponding to the regional information; and approving the data materials according to the approval parameters.

[0006] According to the data processing method for account opening in the embodiment of the present disclosure, by extracting data corresponding to the regional information into the approval task pool corresponding to the regional information; approving the data according to the approval parameters, the transition from manual review to differentially configurable review can be achieved, which meets the diversity of approval rules and improves the adaptability of the system to the business of each branch; the tasks of each branch are concentrated in the approval task pool for processing, which alleviates the problem of uneven workload of each branch and reduces labor costs, thereby realizing automation, differentiation and directness of centralized account approval business, effectively improving the diversity, accuracy, timeliness and compliance of account opening business.

[0007] In some embodiments, obtaining m groups of data when m customers open accounts includes: setting up a data processing pool; obtaining image data of the account opening information of m customers to the data processing pool; and converting the m groups of image data into m groups of data.

[0008] In some embodiments, converting m groups of the image data into m groups of the data data includes: labeling the image data according to the type of the image data to obtain labeling information; extracting text information from the image data; and generating the data data based on the labeling information and the text information.

[0009] In some embodiments, labeling the image data according to the type of the image data to obtain labeling information includes: performing semantic recognition on the type of each image sub-data in each group of image data to obtain identification information; matching the identification information with the labeling value in the labeling information library; when the identification information is matched in the labeling information library, using the identification information as the labeling information; when the identification information is not matched in the labeling information library, obtaining manual labeling results and using the manual labeling results as the labeling information; and storing the manual labeling results in the labeling information library.

[0010] In some embodiments, the extracting of text information from the image material includes: extracting information from the image material for a first time to obtain first text information; extracting information from the image material for a second time to obtain second text information; comparing the first text information and the second text information; and when the first text information and the second text information are different, obtaining a manual modification result, and using the manual modification result as the text information.

[0011] In some embodiments, approving the data according to the approval parameters includes: obtaining approval factors from an external system according to the approval parameters; comparing the data with the approval factors to determine whether the data are consistent with the approval factors; and when the data are consistent with the approval factors, the data is approved.

[0012] In some embodiments, the method further includes: filing at least part of the customer's account opening information after the data is approved; and archiving the customer's account opening information when the filing is successful.

[0013] In some embodiments, archiving the customer's account opening information includes: transmitting the customer's account opening information to the counter so that the counter can query and print the account opening information; sending the customer's query password to the customer's communication device; and transmitting the customer's account opening information to the electronic approval screen so that the customer can confirm at least one of the account opening information.

[0014] In some embodiments, approving the data according to approval parameters, filing at least part of the customer's account opening information after the data is approved, and archiving the customer's account opening information when the filing is successful are all completed through robotic process automation technology.

[0015] Another aspect of the present disclosure provides a data processing device for account opening, including: a setting module, the setting module is used to set multiple approval task pools according to regions, and determine the approval parameters of each approval task pool; an acquisition module, the acquisition module is used to obtain m groups of data when m customers open accounts, wherein the m groups of data come from n regions, m is an integer greater than or equal to 1, and n is an integer greater than or equal to 1; a determination module, the determination module is used to determine the account opening bank information corresponding to each group of the data, and the account opening bank information includes regional information; an extraction module, the extraction module is used to extract the data corresponding to the regional information to the approval task pool corresponding to the regional information according to the regional information; and an approval module, the approval module is used to approve the data according to the approval parameters.

[0016] Another aspect of the present disclosure provides an electronic device, comprising one or more processors and one or more memories, wherein the memories are used to store executable instructions, and when the executable instructions are executed by the processors, the above-mentioned method is implemented.

[0017] Another aspect of the present disclosure provides a computer-readable storage medium storing computer-executable instructions, which are used to implement the method described above when executed.

[0018] Another aspect of the present disclosure provides a computer program, which includes computer executable instructions, and the instructions are used to implement the method described above when executed. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The above and other objects, features and advantages of the present disclosure will become more apparent through the following description of the embodiments of the present disclosure with reference to the accompanying drawings, in which:

[0020] Figure 1 An exemplary system architecture to which the method and apparatus according to an embodiment of the present disclosure can be applied is schematically shown;

[0021] Figure 2 A flowchart schematically shows a data processing method for account opening according to an embodiment of the present disclosure;

[0022] Figure 3 A flowchart schematically shows a data processing method for account opening according to an embodiment of the present disclosure;

[0023] Figure 4 A flowchart schematically shows how to obtain m sets of data when m customers open accounts according to an embodiment of the present disclosure;

[0024] Figure 5 A flowchart of labeling image data according to the type of image data to obtain labeling information according to an embodiment of the present disclosure is schematically shown;

[0025] Figure 6 A flowchart of extracting text information from image data according to an embodiment of the present disclosure is schematically shown;

[0026] Figure 7 A flowchart of approving data materials according to approval parameters according to an embodiment of the present disclosure is schematically shown;

[0027] Figure 8 Schematically shows a flow chart of archiving a customer's account opening information according to an embodiment of the present disclosure;

[0028] Fig. 9 Schematically shows a flow chart of archiving a customer's account opening information according to an embodiment of the present disclosure;

[0029] Fig.10 Schematically shows a flow chart of archiving a customer's account opening information according to an embodiment of the present disclosure;

[0030] Fig.11 A block diagram schematically shows a data processing device for account opening according to an embodiment of the present disclosure;

[0031] Fig.12 A block diagram of an electronic device according to an embodiment of the present disclosure is schematically shown. DETAILED DESCRIPTION

[0032] Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the present disclosure. In the following detailed description, for ease of explanation, many specific details are set forth to provide a comprehensive understanding of the embodiments of the present disclosure. However, it is obvious that one or more embodiments may be implemented without these specific details. In addition, in the following description, descriptions of well-known structures and technologies are omitted to avoid unnecessary confusion of the concepts of the present disclosure. In the technical solution of the present disclosure, the acquisition, storage and application of user personal information involved are in compliance with the provisions of relevant laws and regulations, necessary confidentiality measures are taken, and do not violate public order and good morals.

[0033] The terms used herein are only for describing specific embodiments and are not intended to limit the present disclosure. The terms "comprise", "include", etc. used herein indicate the existence of the features, steps, operations and / or components, but do not exclude the existence or addition of one or more other features, steps, operations or components.

[0034] When using expressions such as "at least one of A, B or C, etc.", it should generally be interpreted in accordance with the meaning of the expression generally understood by those skilled in the art (for example, "a system having at least one of A, B or C" should include but is not limited to a system having A alone, B alone, C alone, A and B, A and C, B and C, and / or A, B, C, etc.). The terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, features defined as "first" and "second" may explicitly or implicitly include one or more of the said features.

[0035] Figure 1 The exemplary system architecture 100 of the data processing method, data processing device, electronic device, computer-readable storage medium and computer program for account opening according to the embodiment of the present disclosure is schematically shown. It should be noted that: Figure 1 What is shown is merely an example of a system architecture to which the embodiments of the present disclosure can be applied, in order to help those skilled in the art understand the technical content of the present disclosure, but it does not mean that the embodiments of the present disclosure cannot be used in other devices, systems, environments or scenarios.

[0036] like Figure 1 As shown, the system architecture 100 according to this embodiment may include terminal devices 101, 102, 103, a network 104 and a server 105. The network 104 is used to provide a medium for communication links between the terminal devices 101, 102, 103 and the server 105. The network 104 may include various connection types, such as wired, wireless communication links or optical fiber cables, etc.

[0037] Users can use terminal devices 101, 102, 103 to interact with server 105 through network 104 to receive or send messages, etc. Various communication client applications can be installed on terminal devices 101, 102, 103, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients, social platform software, etc. (only examples).

[0038] The terminal devices 101 , 102 , and 103 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smart phones, tablet computers, laptop computers, and desktop computers.

[0039] The server 105 may be a server that provides various services, such as a background management server (only an example) that provides support for websites browsed by users using the terminal devices 101, 102, and 103. The background management server may analyze and process the received data such as user requests, and feed back the processing results (such as web pages, information, or data obtained or generated according to user requests) to the terminal device.

[0040] It should be noted that the data processing method provided in the embodiment of the present disclosure can generally be executed by the server 105. Accordingly, the data processing device provided in the embodiment of the present disclosure can generally be set in the server 105. The data processing method provided in the embodiment of the present disclosure can also be executed by a server or server cluster that is different from the server 105 and can communicate with the terminal devices 101, 102, 103 and / or the server 105. Accordingly, the data processing device provided in the embodiment of the present disclosure can also be set in a server or server cluster that is different from the server 105 and can communicate with the terminal devices 101, 102, 103 and / or the server 105.

[0041] It should be understood that Figure 1 The number of terminal devices, networks and servers in the embodiment is only for illustration. Any number of terminal devices, networks and servers may be provided according to implementation requirements.

[0042] The following will be based on Figure 1 The scene described by Figure 2 to Figure 10 The data processing method for account opening according to an embodiment of the present disclosure is described in detail.

[0043] Figure 2 The flowchart of the data processing method for account opening according to the embodiment of the present disclosure is schematically shown.

[0044] like Figure 2 As shown, the data processing method of this embodiment includes operations S210 to S250.

[0045] In operation S210, multiple approval task pools are set according to regions, and approval parameters of each approval task pool are determined. For example, multiple approval task pools can be set, and Hunan, Hubei, and Jiangsu regions are divided into one approval task pool, Henan, Hebei, and Shandong regions are divided into one approval task pool, Guangxi, Guangdong, and Yunnan regions are divided into one approval task pool, and so on. Setting multiple approval task pools according to regions is not limited to this, but any combination of regions can be divided into one approval task pool, and the above is only for example description and cannot be understood as a limitation of the present disclosure.

[0046] Among them, each approval task pool can have a separate approval parameter, and the approval parameters in multiple approval task pools can be the same or different. For example, the approval parameter can be the depositor's name, that is, the customer's legal name or account name, the registration area code, the depositor's category, the unified social credit code, the name of the legal representative or person in charge, the type of the legal representative or person in charge's certificate, the legal representative or person in charge's certificate number, the legal representative or person in charge's certificate validity period, registered capital, business scope, certification document type, certification document validity period, certification document number, account nature, account opening bank name, account number, depositor's statement, etc. Each approval task pool can select one or more of the approval parameters as the approval parameters of the approval task pool.

[0047] In operation S220, m groups of data information when m customers open accounts are obtained, wherein the m groups of data information are from n regions, m is an integer greater than or equal to 1, and n is an integer greater than or equal to 1.

[0048] As a possible way to achieve this, Figure 3 As shown, operation S220 of obtaining m groups of data when m customers open accounts includes operations S221 to S223.

[0049] In operation S221, a data processing pool is set.

[0050] In operation S222, the image data of the account opening data of m customers are obtained and sent to the data processing pool. It is understandable that each customer needs to prepare account opening data when opening an account, such as company business license, legal person identity certificate and other documents, and the account opening data can be scanned as image data and uploaded to the data processing pool. The data processing pool can be understood as a processing pool for unified processing of image data shared by all regions. The unified processing of image data in all regions can centrally train data processing personnel, thereby reducing the cost of training and management of personnel in each region.

[0051] In operation S223, the m sets of image data are converted into m sets of data data.

[0052] In some specific examples, such as Figure 4 As shown, operation S223 converts m groups of image data into m groups of data data and includes operations S2231 to S2233.

[0053] In operation S2231, the image data is labeled according to the type of the image data to obtain labeling information. For example, the type of the image data can be identified by intelligent character recognition technology, such as the image data is an identity document or a business license. After the type of the image data is identified, the image data can be labeled according to the type of the image data to obtain labeling information. For example, when the identified image data is an identity document, the labeling information is "identity document", and when the identified image data is a business license, the labeling information is "business license".

[0054] As some specific examples, Figure 5 As shown, operation S2231 labels the image data according to the type of the image data, and obtaining the labeling information includes operations S22311 to S22315.

[0055] In operation S22311, semantic recognition is performed on the type of each image sub-data in each set of image data to obtain identification information. It should be noted that each set of image data may include at least one image sub-data. For example, when a customer opens an account, a company business license and a legal person ID card are required, where the business license and the ID card can be understood as a set of image data, the business license is an image sub-data, and the ID card is an image sub-data. By performing semantic recognition on the characters on each image sub-data, identification information can be obtained.

[0056] In operation S22312, the identification information is matched with the annotation value in the annotation information library.

[0057] In operation S22313, when the identification information is matched in the annotation information library, the identification information is used as the annotation information.

[0058] In operation S22314, when the identification information is not matched in the annotation information library, the manual annotation result is obtained and the manual annotation result is used as the annotation information. It is understandable that when the identification information is not matched in the annotation information library, the unidentified image sub-data can be manually annotated, and after the manual annotation result is obtained, the manual annotation result can be used as the annotation information.

[0059] In operation S22315, the manual annotation results are stored in the annotation information library.

[0060] Thus, through operations S22311 to S22315, it is easy to annotate the image data according to the type of the image data to obtain the annotation information. In addition, by storing the manual annotation results in the annotation information library, the annotation model can be trained, so that the matching values ​​in the annotation information library are increasingly rich, thereby making the matching rate of subsequent recognition information higher, so that the level of intelligence of annotating the image data according to the type of the image data is higher.

[0061] In operation S2232, text information in the image data is extracted. For example, the characters in the image data can be converted into text information by using technologies such as intelligent character recognition (ICR).

[0062] As a possible implementation method, Figure 6 As shown, operation S2232 of extracting text information from image data includes operations S22321 to S22324.

[0063] In operation S22321, information in the image data is extracted for the first time to obtain first text information.

[0064] In operation S22322, information in the image data is extracted for a second time to obtain second text information.

[0065] In operation S22323, the first text information and the second text information are compared.

[0066] In operation S22324, when the first text information and the second text information are different, the manual modification result is obtained and the manual modification result is used as the text information. It can be understood that when the information extracted from the image data twice is different, that is, the first text information and the second text information are different, it means that the intelligent character recognition technology fails to accurately recognize the information on the image data. At this time, the extracted text information can be manually intervened, that is, the text information can be manually modified. After the manual modification result is obtained, the manual modification result can be used as the text information.

[0067] In operation S2233, data materials are generated according to the annotation information and text information. The data materials may include sub-data materials corresponding to the image sub-materials one by one, each sub-data material includes annotation information, the annotation information records the type of the sub-data material, such as business license data or identity document data; the text information records the specific content of the corresponding type of sub-data material, such as the specific display content on the business license, such as the specific display content on the identity document.

[0068] Therefore, through operations S2231 to S2233, it is possible to easily convert m groups of image data into m groups of data data.

[0069] In operation S230, the account opening bank information corresponding to each set of data is determined, and the account opening bank information includes regional information. For example, when a customer opens an account, the account opening bank can provide the account opening bank information. The account opening bank information includes the regional information where the account opening bank is located.

[0070] In operation S240, based on the region information, data corresponding to the region information is extracted into an approval task pool corresponding to the region information.

[0071] The following continues to use the example in operation S210 to explain that since the Hunan region, Hubei region and Jiangsu region are divided into one approval task pool, for the convenience of description, the approval task pool is named the first task pool, so if the geographical information of the account opening bank is any one of Hunan, Hubei and Jiangsu, the data corresponding to the geographical information will be extracted to the first task pool. Since the Henan region, Hebei region and Shandong region are divided into one approval task pool, for the convenience of description, the approval task pool is named the second task pool, so if the geographical information of the account opening bank is any one of Henan, Hebei and Shandong, the data corresponding to the geographical information will be extracted to the second task pool.

[0072] In operation S250, the data material is approved according to the approval parameters.

[0073] In some specific examples, such as Figure 7 As shown, operation S250 of approving data according to the approval parameters includes operations S251 to S253.

[0074] In operation S251, approval factors are obtained from an external system according to the approval parameters. Here, the external system can be understood as a third-party system, that is, the system of the regulatory department, and the approval factors can be understood as the specific requirements made by the regulatory department for each approval parameter.

[0075] In operation S252, the data is compared with the approval factors to determine whether the data is consistent with the approval factors.

[0076] Specifically, the text information on the data can be compared with the approval factors obtained from the regulatory authorities, for example, comparing the depositor's name with the regulatory authorities' specific requirements for the depositor's name; for example, comparing the registered place area code with the regulatory authorities' specific requirements for the registered place area code; for example, comparing the depositor's category with the regulatory authorities' specific requirements for the depositor's category; for example, comparing the unified social credit code with the regulatory authorities' specific requirements for the unified social credit code; for example, comparing the name of the legal representative or person in charge with the regulatory authorities' specific requirements for the legal representative or person in charge; for example, comparing the registered capital with the regulatory authorities' specific requirements for the registered capital; for example, comparing the business scope with the regulatory authorities' specific requirements for the business scope.

[0077] In operation S253, when the data and the approval factors are consistent, the data are approved.

[0078] According to the data processing method for account opening in the embodiment of the present disclosure, by extracting data corresponding to the regional information into the approval task pool corresponding to the regional information; approving the data according to the approval parameters, the transition from manual review to differentially configurable review can be achieved, which meets the diversity of approval rules and improves the adaptability of the system to the business of each branch; the tasks of each branch are concentrated in the approval task pool for processing, which alleviates the problem of uneven workload of each branch and reduces labor costs, thereby realizing automation, differentiation and directness of centralized account approval business, effectively improving the diversity, accuracy, timeliness and compliance of account opening business.

[0079] like Figure 2 As shown, the data processing method for account opening also includes operations S260 to S270.

[0080] In operation S260, after the data is approved, at least part of the account opening information of the customer is filed. It is understandable that after the data is approved, part or all of the account opening information needs to be filed with the regulatory department, and the specific filing content is determined according to the requirements of the regulatory department. Here, the account opening information may include but is not limited to the name of the depositor, the registration area code, the depositor category, the unified social credit code, the name of the legal representative or the person in charge, the type of the legal representative or the person in charge's certificate, the legal representative or the person in charge's certificate number, the legal representative or the person in charge's certificate validity period, the registered capital, the business scope, the type of certification document, the validity period of the certification document, the certification document number, the nature of the account, the name of the bank where the account is opened, the account number, the depositor's statement and at least one of the bank where the account is opened. By filing at least part of the customer's account opening information, the customer's account opening information can be transmitted to the regulatory department, which is convenient for the regulatory department to supervise the account opening behavior.

[0081] Operation S270: When the record is successful, the customer's account opening information is archived. Thus, by archiving the customer's account opening information, subsequent services can be better provided to the customer, and it is convenient for the account opening bank and the customer to query the account opening information.

[0082] As an implementable approach, Figure 8-Figure 10 As shown, operation S270 of archiving the customer's account opening information includes at least one of operations S271 to S273.

[0083] In operation S271, the customer's account opening information is transmitted to the counter so that the counter can query and print the account opening information.

[0084] In operation S272, the customer's query password is sent to the customer's communication device.

[0085] In operation S273, the customer's account opening information is transmitted to the electronic signature approval screen so that the customer confirms the account opening information.

[0086] In some embodiments of the present disclosure, approving data materials according to approval parameters, filing at least part of the customer's account opening information after the data materials are approved, and archiving the customer's account opening information when the filing is successful are all completed through robotic process automation technology. Therefore, in the account opening process, the robotic process automation technology can be used to improve the automation level of account opening, reduce labor costs and reduce the probability of manual errors.

[0087] According to some embodiments of the present disclosure, before obtaining m sets of data when m customers open accounts, it also includes performing identification processing based on identity information, wherein the identification processing based on identity information includes at least one of verifying the authenticity of the identity information, verifying whether the account type included in the identity information has a long-suspended account, and verifying whether the customer corresponding to the identity information is a risky user. When the identity information is true, the identification processing result is passed; when the account type included in the identity information does not have a long-suspended account, the identification processing result is passed; when the customer corresponding to the identity information is a non-risky user, the identification processing result is passed.

[0088] It is understandable that the identity information may be information corresponding to an identity document. By identifying the identity information, it is possible to know whether the customer opening the account is genuine, whether it is a long-suspended account, or whether it is a risky user. When the identity information is identified, the next step can be continued, that is, m sets of data when m customers open accounts can be obtained. When the identity information is not identified, the account opening can be terminated. This can reduce unnecessary procedures and save resources.

[0089] According to some embodiments of the present disclosure, when the filing is successful, before archiving the customer's account opening information, the process further includes: performing system maintenance based on at least one of the account management approval declaration, the account opening license and the customer information.

[0090] Among them, account management approval declaration includes account status modification, such as changing from sealed to normal, which will be synchronized to the deposit component later. The account opening license can come from the regulatory department. Customer information can include but is not limited to the national tax / local tax registration certificate number, registered capital currency, registered capital amount, region code, etc. Robotic process automation technology can obtain the basic deposit account number and basic deposit account opening bank from the regulatory department, which will be synchronized to the customer component later.

[0091] Based on the above data processing method for account opening, the present disclosure also provides a data processing device 10 for account opening. Fig.11 The data processing device 10 for account opening is described in detail.

[0092] Fig.11 The structural block diagram of a data processing device 10 for account opening according to an embodiment of the present disclosure is schematically shown.

[0093] The data processing device 10 for account opening includes a setting module 1 , an acquisition module 2 , a determination module 3 , an extraction module 4 and an approval module 5 .

[0094] Setting module 1, setting module 1 is used to execute S210: setting multiple approval task pools according to regions, and determining approval parameters of each approval task pool.

[0095] Acquisition module 2, acquisition module 2 is used to execute S220: obtain m groups of data when m customers open accounts, wherein the m groups of data come from n regions, m is an integer greater than or equal to 1, and n is an integer greater than or equal to 1.

[0096] Determining module 3, determining module 3 is used to execute S230: determine the bank information corresponding to each set of data, and the bank information includes regional information.

[0097] Extraction module 4, extraction module 4 is used to execute S240: according to the regional information, extract the data corresponding to the regional information to the approval task pool corresponding to the regional information.

[0098] Approval module 5, the approval module 5 is used to execute S250: approve data materials according to approval parameters.

[0099] Since the above-mentioned data processing device is arranged based on the data processing method, the beneficial effects of the above-mentioned data processing device are the same as those of the data processing method, which will not be described in detail here.

[0100] In addition, according to the embodiments of the present disclosure, any multiple modules among the setting module 1, the acquisition module 2, the determination module 3, the extraction module 4 and the approval module 5 can be combined into one module for implementation, or any one of the modules can be split into multiple modules. Alternatively, at least part of the functions of one or more of these modules can be combined with at least part of the functions of other modules and implemented in one module.

[0101] According to an embodiment of the present disclosure, at least one of the setting module 1, the acquisition module 2, the determination module 3, the extraction module 4 and the approval module 5 can be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on a chip, a system on a substrate, a system on a package, an application-specific integrated circuit (ASIC), or can be implemented by hardware or firmware such as any other reasonable way of integrating or packaging the circuit, or can be implemented in any one of the three implementation methods of software, hardware and firmware, or in an appropriate combination of any of them.

[0102] Alternatively, at least one of the setting module 1, the acquisition module 2, the determination module 3, the extraction module 4 and the approval module 5 may be at least partially implemented as a computer program module, and when the computer program module is executed, the corresponding function may be executed.

[0103] Fig.12 A block diagram of an electronic device suitable for implementing data processing for account opening according to an embodiment of the present disclosure is schematically shown.

[0104] like Fig.12 As shown, the electronic device 900 according to an embodiment of the present disclosure includes a processor 901, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 902 or a program loaded from a storage part 908 into a random access memory (RAM) 903. The processor 901 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or a related chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 901 may also include an onboard memory for caching purposes. The processor 901 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present disclosure.

[0105] In RAM 903, various programs and data required for the operation of electronic device 900 are stored. Processor 901, ROM 902 and RAM 903 are connected to each other via bus 904. Processor 901 performs various operations of the method flow according to the embodiment of the present disclosure by executing the program in ROM 902 and / or RAM 903. It should be noted that the program can also be stored in one or more memories other than ROM 902 and RAM 903. Processor 901 can also perform various operations of the method flow according to the embodiment of the present disclosure by executing the program stored in the one or more memories.

[0106] According to an embodiment of the present disclosure, the electronic device 900 may further include an input / output (I / O) interface 905, which is also connected to the bus 904. The electronic device 900 may further include one or more of the following components connected to the I / O interface 905: an input portion 906 including a keyboard, a mouse, etc.; an output portion 907 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage portion 908 including a hard disk, etc.; and a communication portion 909 including a network interface card such as a LAN card, a modem, etc. The communication portion 909 performs communication processing via a network such as the Internet. A drive 910 is also connected to the input / output (I / O) interface 905 as needed. A removable medium 911, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 910 as needed, so that a computer program read therefrom is installed into the storage portion 908 as needed.

[0107] The present disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or may exist independently without being assembled into the device / apparatus / system. The above computer-readable storage medium carries one or more programs, and when the above one or more programs are executed, the method according to the embodiment of the present disclosure is implemented.

[0108] According to an embodiment of the present disclosure, a computer-readable storage medium may be a non-volatile computer-readable storage medium, for example, may include but is not limited to: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, an apparatus, or a device. For example, according to an embodiment of the present disclosure, a computer-readable storage medium may include the ROM 902 and / or RAM 903 described above and / or one or more memories other than ROM 902 and RAM 903.

[0109] The embodiment of the present disclosure also includes a computer program product, which includes a computer program, and the computer program contains program code for executing the method shown in the flowchart. When the computer program product is run in a computer system, the program code is used to enable the computer system to implement the method of the embodiment of the present disclosure.

[0110] The above functions defined in the system / device of the embodiment of the present disclosure are performed when the computer program is executed by the processor 901. According to the embodiment of the present disclosure, the system, device, module, unit, etc. described above can be implemented by a computer program module.

[0111] In one embodiment, the computer program may be based on a tangible storage medium such as an optical storage device, a magnetic storage device, etc. In another embodiment, the computer program may also be transmitted and distributed in the form of a signal on a network medium, and downloaded and installed through the communication part 909, and / or installed from a removable medium 911. The program code contained in the computer program may be transmitted using any appropriate network medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0112] In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 909, and / or installed from the removable medium 911. When the computer program is executed by the processor 901, the above functions defined in the system of the embodiment of the present disclosure are performed. According to the embodiment of the present disclosure, the system, device, means, module, unit, etc. described above can be implemented by a computer program module.

[0113] According to an embodiment of the present disclosure, the program code for executing the computer program provided by the embodiment of the present disclosure can be written in any combination of one or more programming languages. Specifically, these computing programs can be implemented using high-level process and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, Java, C++, python, "C" language or similar programming languages. The program code can be executed entirely on the user computing device, partially on the user device, partially on the remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (for example, using an Internet service provider to connect through the Internet).

[0114] The flow charts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each box in the flow chart or block diagram can represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of a code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flow chart, and the combination of the boxes in the block diagram or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0115] It will be appreciated by those skilled in the art that the features described in the various embodiments and / or claims of the present disclosure may be combined and / or combined in a variety of ways, even if such combinations and / or combinations are not explicitly described in the present disclosure. In particular, the features described in the various embodiments and / or claims of the present disclosure may be combined and / or combined in a variety of ways without departing from the spirit and teachings of the present disclosure. All of these combinations and / or combinations fall within the scope of the present disclosure.

[0116] The embodiments of the present disclosure are described above. However, these embodiments are only for illustrative purposes and are not intended to limit the scope of the present disclosure. Although the embodiments are described above separately, this does not mean that the measures in the various embodiments cannot be used in combination to advantage. The scope of the present disclosure is defined by the attached claims and their equivalents. Without departing from the scope of the present disclosure, those skilled in the art may make a variety of substitutions and modifications, which should all fall within the scope of the present disclosure.

Claims

1. A data processing method for account opening, characterized in that: include: Setting up multiple approval task pools according to regions, and determining approval parameters for each of the approval task pools; Obtain m sets of data when m customers open accounts, where the m sets of data come from n regions, m is an integer greater than or equal to 1, and n is an integer greater than or equal to 1; Determining bank information corresponding to each set of data, wherein the bank information includes geographical information; According to the regional information, extracting the data corresponding to the regional information to an approval task pool corresponding to the regional information; and Approving the data material according to the approval parameters; Wherein, the approving the data according to the approval parameters includes: Acquire approval elements from external systems based on approval parameters; Comparing the data with the approval factors to determine whether the data are consistent with the approval factors; and When the data and information are consistent with the approval factors, the data and information are approved.

2. The method according to claim 1, characterized in that The m groups of data obtained when m customers open accounts include: Set up a data processing pool; Obtaining image data of account opening data of m customers to the data processing pool; and The m groups of image data are converted into the m groups of data data.

3. The method according to claim 2, characterized in that The converting the m groups of image data into the m groups of data data comprises: Annotate the image data according to the type of the image data to obtain annotation information; Extracting text information from the image data; and The data material is generated according to the annotation information and the text information.

4. The method according to claim 3, characterized in that The step of labeling the image data according to the type of the image data to obtain the labeling information includes: Perform semantic recognition on the type of each image sub-data in each group of image data to obtain recognition information; Matching the identification information with the annotation value in the annotation information library; When the identification information is matched in the annotation information library, the identification information is used as the annotation information; When the identification information is not matched in the annotation information library, obtaining a manual annotation result, and using the manual annotation result as the annotation information; and The manual annotation results are stored in the annotation information library.

5. The method according to claim 3, characterized in that: The extracting of text information from the image data comprises: Extracting information from the image data for the first time to obtain first text information; extracting information from the image data for a second time to obtain second text information; comparing the first text information and the second text information; and When the first text information and the second text information are different, a manual modification result is obtained, and the manual modification result is used as the text information.

6. The method according to claim 1, characterized in that Also includes: When the data is approved, at least part of the customer's account opening information is filed; as well as When the filing is successful, the customer's account opening information is archived.

7. The method according to claim 6, characterized in that The archiving of the customer's account opening information includes: Transmitting the customer's account opening information to the counter so that the counter can query and print the account opening information; sending the customer's query password to the customer's communication device; and The customer's account opening information is transmitted to the electronic signature approval screen, so that the customer confirms at least one of the account opening information.

8. The method according to any one of claims 1 to 7, characterized in that The approving of the data according to the approval parameters, filing of at least part of the customer's account opening information after the data is approved, and archiving of the customer's account opening information when the filing is successful are all completed through robotic process automation technology.

9. A data processing device for account opening, characterized in that: include: A setting module, the setting module is used to set a plurality of approval task pools according to regions and determine the approval parameters of each of the approval task pools; An acquisition module, the acquisition module is used to acquire m sets of data when m customers open accounts, wherein the m sets of data come from n regions, m is an integer greater than or equal to 1, and n is an integer greater than or equal to 1; A determination module, the determination module is used to determine the bank information corresponding to each set of the data, the bank information including geographical information; An extraction module, the extraction module is used to extract the data corresponding to the regional information to the approval task pool corresponding to the regional information according to the regional information; An approval module, the approval module is used to approve the data according to the approval parameters; Wherein, the approving the data according to the approval parameters includes: Acquire approval elements from external systems based on approval parameters; Comparing the data with the approval factors to determine whether the data are consistent with the approval factors; and When the data and information are consistent with the approval factors, the data and information are approved.

10. An electronic device, characterized in that: include: one or more processors; One or more memories, used to store executable instructions, which, when executed by the processor, implement the method according to any one of claims 1 to 8.

11. A computer-readable storage medium, characterized in that: The storage medium stores executable instructions, which, when executed by a processor, implement the method according to any one of claims 1 to 8.

12. A computer program, characterized in that The computer program includes one or more executable instructions, and when the executable instructions are executed by a processor, the method according to any one of claims 1 to 8 is implemented.

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