Method for bank employee to create approval process, approval platform, equipment and medium

Abstract

The invention belongs to the technical field of approval management, and discloses a method for bank employees to create an approval process, an approval platform, equipment and a medium, and the method comprises the steps: obtaining a business demand of a user, recognizing the business demand of the user, and obtaining a recognition result; matching a required component from a preset component library based on the identification result, wherein the matched required component can be used by a user to customize and create a form item of the approval process; obtaining a preset approval configuration, and adding the preset approval configuration to the approval process to obtain a configured approval process; acquiring an approval request of a front end, and performing approval prediction on the approval request based on a pre-constructed intelligent approval model to obtain an approval prediction result; executing an approval operation based on the configured approval process and the approval prediction result to obtain an approval completion result; and an approval completion result is fed back to the front end. According to the invention, manual intervention can be reduced, and the data processing efficiency and accuracy are improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of approval management, and particularly relates to a method for bank employees to create an approval process, an approval platform, a device, and a medium. Background Art

[0002] In banking operations, the approval process is one of the core links, involving multiple aspects such as loans, investments, and project management. The traditional approval process relies on manual operations and paper documents, suffering from problems such as low efficiency, high error rates, and difficulty in tracing data. With the development of fintech, zero-code platforms have gradually become an effective means to solve these problems. However, existing zero-code platforms still have the following deficiencies in data viewing, exporting, printing, and sharing of approval process templates, and cannot meet the complex needs of banking operations.

[0003] 1. High complexity in approval process design: When constructing complex approval processes on traditional zero-code platforms, there are often problems of numerous nodes and complex conditions, and manual configuration is both time-consuming and error-prone; 2. Large amount of approval data and difficult to process: The amount of data generated during the approval process is huge, and the data formats are diverse, making it difficult to handle with traditional processing methods; 3. Low collaboration efficiency between approval nodes: In the approval process, collaboration between different nodes requires frequent communication, affecting the approval efficiency; 4. Poor flexibility and adaptability of approval rules: When configuring approval rules on traditional zero-code platforms, there is often a lack of flexibility and adaptability, making it difficult to handle complex and changing business requirements; 5. Security and compliance issues during the approval process: Sensitive data and key business information are involved in the approval process, and security and compliance are difficult to guarantee. Summary of the Invention

[0004] The purpose of the present invention is to provide a method for bank employees to create an approval process, an approval platform, a device, and a medium, so as to solve the problems of high complexity in approval process design, large amount of approval data and difficult to process, and low collaboration efficiency between approval nodes existing in the prior art.

[0005] To achieve the above purpose, the present invention adopts the following technical solutions: In the first aspect, the present invention provides a method for bank employees to create an approval process, and the method includes: Obtaining the business requirements of the user, identifying the business requirements of the user, and obtaining an identification result; Based on the identification result, matching the required components from a preset component library, and the matched required components can be used by the user to customize and create form items of the approval process; Obtaining a preset approval configuration, adding the preset approval configuration to the approval process, and obtaining a configured approval process; Obtain the approval request from the front end, perform approval prediction on the approval request based on a pre-built intelligent approval model, and obtain an approval prediction result; Perform an approval operation based on the configured approval process and the approval prediction result to obtain an approval completion result; Feed back the approval completion result to the front end.

[0006] Preferably, the approval operation at least includes: automatic approval, multi-level approval, and transfer to manual review.

[0007] Preferably, the preset approval configuration at least includes: approval node configuration, approver configuration, and approval condition configuration; Among them, the approval node configuration is: customizing the number and order of nodes in the approval process, and the nodes at least include: start node, approval node, and end node; Among them, the approver configuration is: customizing the roles, responsibilities, and approval order of approvers in the approval process; Among them, the approval condition configuration is: customizing the approval conditions in the approval process.

[0008] Preferably, before performing approval prediction on the approval request based on the pre-built intelligent approval model, the method further includes: validating and preprocessing the approval request.

[0009] Preferably, the method further includes: monitoring the approval operation to obtain status monitoring data and log record data.

[0010] Preferably, the method further includes: based on a visualization tool, visually displaying the required components, approval prediction results, configured approval processes, approval completion results, and process nodes in the approval operation.

[0011] In a second aspect, the present invention provides a platform for bank employees to create an approval process, and the platform includes: An approval process management module, which is used for: obtaining the business requirements of users, identifying the business requirements of users to obtain an identification result; matching the required components from a preset component library based on the identification result, and the matched required components can be used by users to customize the form items for creating an approval process; obtaining the preset approval configuration, adding the preset approval configuration to the approval process to obtain a configured approval process; obtaining the approval request from the front end, performing approval prediction on the approval request based on a pre-built intelligent approval model to obtain an approval prediction result; performing an approval operation based on the configured approval process and the approval prediction result to obtain an approval completion result; feeding back the approval completion result to the front end; A form management module, which is used for validating the content of the form of the approval process based on preset validation rules.

[0012] Preferably, the platform further includes: A role and permission management module for managing the assignment of roles and permissions; A data processing and analysis module for performing data preprocessing, feature extraction, and model training and prediction; A data storage management module for storing approval data and model parameters according to a distributed database, and encrypting sensitive data in the approval data through an encryption algorithm.

[0013] In a third aspect, the present invention provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the method for a bank employee to create an approval process described above is implemented.

[0014] In a fourth aspect, the present invention provides a computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, the method for a bank employee to create an approval process described above is implemented.

[0015] Advantageous effects: 1. By identifying and understanding the business requirements of users, the present invention facilitates the automatic generation of a preliminary approval process, which can improve the efficiency of approval process design; 2. By using a pre-built intelligent approval model to perform approval prediction on approval requests and executing approval operations based on the configured approval process and approval prediction results, the present invention reduces manual intervention and improves the efficiency and accuracy of data processing. Description of the Drawings

[0016] The drawings are used to provide a further understanding of the embodiments of the present invention, and constitute a part of the specification. Together with the following specific embodiments, they are used to explain the embodiments of the present invention, but do not constitute a limitation to the embodiments of the present invention. In the drawings: Figure 1 is a flowchart of the method for a bank employee to create an approval process provided by an embodiment of the present invention; Figure 2 is a block diagram of an approval platform provided by an embodiment of the present invention. Detailed Embodiments

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the present invention in combination with the descriptions of the accompanying drawings and embodiments or the prior art. Obviously, the following descriptions of the structures of the accompanying drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other accompanying drawings can be obtained based on these drawings without creative efforts. It should be noted here that the descriptions of these embodiments are used to help understand the present invention, but do not constitute a limitation to the present invention.

[0018] Embodiment 1 Figure 1 It is a flowchart of a method for a bank employee to create an approval process provided by an embodiment of the present invention. As Figure 1 shown, this embodiment provides a method for a bank employee to create an approval process. This method is applied to an approval platform, and the approval platform can be devices such as a cloud server and a cloud terminal. The front end (devices such as mobile phones and PC computers) accesses the approval platform to create an approval process and initiate an approval request; the method includes: Step S10: Obtain the business requirements of the user, identify the business requirements of the user, and obtain an identification result; in this embodiment, natural language processing and deep learning algorithms in AI (Artificial Intelligence) modeling technology are used to understand the business requirements of the user and automatically generate a preliminary approval process design.

[0019] For example: The user describes the business requirements in natural language, such as "The loan approval process needs to first conduct a risk assessment, then be approved by the credit manager, and finally be signed by the bank president". After obtaining this business requirement, use NLP (Neuro-Linguistic Programming) technology to analyze the text input by the user, identify information such as keywords, entities, and relationships, and convert it into structured data; Then use a deep learning model to infer a preliminary approval process design that meets the user's needs based on the structured data input by the user and historical approval data, and use the preliminary approval process design that meets the user's needs as the identification result.

[0020] Step S20: Based on the identification result, match the required components from a preset component library, and the matched required components can be used by the user to customize the form items for creating an approval process.

[0021] In this embodiment, the component library contains component tools such as text boxes, number boxes, date pickers, drop-down selection boxes, etc. According to the component tools required in the preliminary approval process design, the required components are matched from the preset component library, and then the user can complete the creation of form items for the custom approval process based on the matched required components; therefore, business personnel of the present invention do not need to have programming skills, and can describe business requirements through natural language, and the platform automatically generates approval process designs, improving the business response speed; with an automated process design process, it reduces the time and effort of manual configuration and improves work efficiency.

[0022] As a further optimization of this embodiment, the method further includes: verifying the content of the form of the approval process based on a preset verification rule; the preset verification rule can be customized, for example: mandatory items, data type verification, value range verification, etc.; this can ensure the compliance and accuracy of the form and avoid data errors and omissions.

[0023] Step S30: Obtain a preset approval configuration, add the preset approval configuration to the approval process, and obtain a configured approval process.

[0024] In this embodiment, the preset approval configuration at least includes: approval node configuration, approver configuration, and approval condition configuration; Among them, the approval node configuration is: customizing the number and order of nodes in the approval process, and the nodes at least include: start node, approval node, and end node; the user can flexibly set the number and order of nodes in the approval process according to the rules of business requirements; Among them, the approver configuration is: customizing the roles, responsibilities, and approval order of approvers in the approval process, which can ensure the rationality and efficiency of the approval process and avoid duplication and redundancy in the approval process; Among them, the approval condition configuration is: customizing the approval conditions in the approval process, such as: approval amount, approval level, approval time, etc. This can ensure the flexibility and accuracy of the approval process and conduct approvals according to different business scenarios.

[0025] After completing the approval process, based on the actual content filled in by the user in the form of the approval process, the user initiates an approval request at the front end and sends the approval request to the approval platform.

[0026] Step S40: Obtain the approval request from the front end, and perform approval prediction on the approval request based on a pre-constructed intelligent approval model to obtain an approval prediction result; In this embodiment, the approval request contains all the information required for approval, such as applicant information, application content, application amount, etc.; the intelligent approval model is constructed based on deep learning algorithms. For example, a deep learning model (such as a convolutional neural network CNN or a recurrent neural network RNN) is used to extract features and recognize patterns from the approval data, learn the rules and trends in the approval process, and machine learning algorithms (such as logistic regression, decision tree, random forest, etc.) are used to classify and predict the approval data to determine whether the application is compliant and the possible approval results; NLP techniques (such as text classification, entity recognition, keyword extraction, etc.) are used to analyze the text information in the approval documents, extract key information, and assist the model in making predictions.

[0027] The approval platform receives the approval request transmitted from the front end and uses the trained intelligent approval model for prediction. The prediction content includes: whether the application is compliant, the possible approval results, and potential risk points, etc. At the same time, the approval result is automatically judged. The approval result may include: approved, rejected, requiring manual review, etc.; therefore, through automatic judgment, manual intervention can be reduced, the risk of human error can be lowered, and the approval efficiency and accuracy can be improved.

[0028] Step S50: Perform an approval operation based on the configured approval process and approval prediction result to obtain an approval completion result. Among them, the approval operation at least includes: automatic approval, multi-level approval, and transfer to manual review. Automatic approval: The platform automatically completes the approval process without manual intervention; multi-level approval: The application needs to be reviewed through multiple approval nodes; transfer to manual review: The application is transferred to a designated approver for manual review.

[0029] Step S60: Feed back the approval completion result to the front end; after the approval is completed, the complete approval result is sent to the front end of the requester to inform the requester of the approval situation.

[0030] As a further optimization of this embodiment, before performing approval prediction on the approval request based on the pre-constructed intelligent approval model, the method further includes: verifying and preprocessing the approval request to ensure the legality and integrity of the approval request.

[0031] As a further optimization of this embodiment, the method further includes: monitoring the approval operation to obtain status monitoring data and log record data; by monitoring the status of each node in the approval process in real time, the traceability and security of the approval process are realized.

[0032] As a further optimization of this embodiment, the method further includes: based on a visualization tool, visually display the required components, approval prediction results, configured approval processes, approval completion results, and process nodes in the approval operation.

[0033] In this embodiment, the visualization tools include, but are not limited to: charts, texts, and heatmaps; Among them, for charts: bar charts, line charts, pie charts, etc. are used to display relevant data such as required components, approval prediction results, configured approval processes, approval completion results, and process nodes in approval operations; Among them, for texts: text forms are used to display explanatory information related to required components, approval prediction results, configured approval processes, approval completion results, and process nodes in approval operations; Among them, for heatmaps: heatmaps are used to display the probability distribution of different results.

[0034] By identifying and understanding the business requirements of users, the present invention facilitates the automatic generation of a preliminary approval process, which can improve the efficiency of approval process design; moreover, by using a pre-built intelligent approval model to perform approval prediction on approval requests and execute approval operations based on the configured approval process and approval prediction results, manual intervention is reduced, and the efficiency and accuracy of data processing are improved.

[0035] Embodiment Two Figure 2 is a block diagram of a platform for bank employees to create an approval process provided by an embodiment of the present invention. As Figure 2 shown, this embodiment provides a platform for bank employees to create an approval process, and the platform includes: An approval process management module, which is used for: obtaining the business requirements of users, identifying the business requirements of users to obtain an identification result; based on the identification result, matching the required components from a preset component library, and the matched required components can be used by users to customize the form items for creating an approval process; obtaining a preset approval configuration, adding the preset approval configuration to the approval process to obtain a configured approval process; obtaining an approval request from the front end, performing approval prediction on the approval request based on a pre-built intelligent approval model to obtain an approval prediction result; performing an approval operation based on the configured approval process and the approval prediction result to obtain an approval completion result; feeding back the approval completion result to the front end; the specific implementation steps of each step of the approval process management module have been elaborated in detail in Embodiment One, so they will not be elaborated one by one in this embodiment.

[0036] A form management module, which is used for validating the content of the form of the approval process based on preset validation rules, where the preset validation rules can be customized, for example: mandatory items, data type verification, value range verification, etc.; this can ensure the compliance and accuracy of the form, and avoid data errors and omissions.

[0037] As a further optimization of this embodiment, the platform further includes: a role and permission management module, a data processing and analysis module, and a data storage management module; The role and permission management module is used to manage role assignment and permission assignment; Specifically, the platform provides role assignment and permission setting functions to ensure that each employee can only access and operate the functions and data within their permission scope; through role assignment, users can flexibly assign different roles to different employees to achieve the initial division of permissions. Further, the permission setting function allows users to configure detailed operation permissions such as viewing, editing, and deleting for different roles, thus building a solid data security barrier; this management mechanism not only improves the security and compliance of data but also effectively avoids the risks of data leakage and abuse, providing strong guarantee for the stable operation of the enterprise.

[0038] The data processing and analysis module is used to perform data preprocessing, feature extraction, and model training and prediction; Specifically, the data processing and analysis module performs data preprocessing, feature extraction, and model training and prediction, providing high-quality data support for the business logic layer. It is one of the core components of the zero-code platform, focusing on in-depth data processing, feature extraction, and model training and prediction. This module integrates cutting-edge technologies such as Hadoop / Spark big data processing, PCA / LDA feature extraction, and TensorFlow / PyTorch deep learning.

[0039] In the data preprocessing stage, the module uses the Hadoop / Spark framework to clean, transform, and store the original data (historical approval data) to ensure the accuracy and consistency of the data. This process includes removing invalid, duplicate, and abnormal data, laying a foundation for subsequent analysis.

[0040] In terms of feature extraction, the module uses PCA / LDA algorithms to extract key features, simplify the model complexity, and improve the prediction performance; at the same time, it provides visualization display and result analysis functions to help users understand the data patterns.

[0041] In terms of model training and prediction, the module uses TensorFlow / PyTorch to build an intelligent approval model, which is trained and optimized through historical data to achieve accurate prediction of approval results. In addition, it also provides model evaluation and optimization functions to ensure that the prediction performance remains at a high level.

[0042] The data storage management module is used to store approval data and model parameters according to a distributed database, and encrypt sensitive data in the approval data through encryption algorithms; Specifically, the data storage and management module adopts distributed database technology to efficiently and securely store key information such as approval data and model parameters. This layer protects the security of sensitive data through data encryption technology and provides data backup and recovery strategies to ensure the reliability and integrity of the data. The design of the distributed database not only provides high availability and scalability support to meet the platform's requirements for storage and access performance, but also ensures that only authorized users can access and operate the data through permission management and access control functions. These technical details together constitute the core functions of the data storage layer, providing solid data support for the stable operation and efficient approval services of the low-code approval platform.

[0043] As a further optimization of this embodiment, the interaction between the platform of this embodiment and other systems is another important function of the approval process management module; through the API interface, this module can exchange and integrate data with other systems, support collaborative work with other systems, such as ERP (Enterprise Resource Planning), CRM (Customer Relationship Management), etc., to achieve data sharing and synchronization; at the same time, it provides data synchronization and conflict detection functions to ensure the accuracy and consistency of the data, providing strong support for the digital transformation and intelligent management of the bank.

[0044] Embodiment III This embodiment also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the method for a bank employee to create an approval process in Embodiment I.

[0045] This embodiment also provides a computer-readable storage medium, on which a computer program is stored. When the program is executed by the processor, it implements the method for a bank employee to create an approval process in Embodiment I.

[0046] The present invention identifies the business needs of users, understands the business needs of users, facilitates the automatic generation of a preliminary approval process, and can improve the efficiency of approval process design; moreover, by using a pre-built intelligent approval model to perform approval prediction on approval requests and executing approval operations based on the configured approval process and approval prediction results, it reduces manual intervention and improves the efficiency and accuracy of data processing.

[0047] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a platform, or a computer program product. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0048] The present application is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (platforms), and computer program products according to the embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, as well as the combination of flows and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate a platform for implementing the functions specified in one Figure 1 one flow or multiple flows and / or Figure 1 blocks or multiple blocks.

[0049] The above are only the embodiments of the present application and are not used to limit the present application. For those skilled in the art, various changes and modifications can be made to the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included within the scope of the claims of the present application.

Claims

1. A method for bank employees to create an approval process, characterized in that: The method comprises: Obtain the user's business needs, identify the user's business needs, and obtain identification results; Based on the recognition results, the required components are matched from the preset component library, and the matched required components can be used by users to customize the form items for creating approval processes; Get the preset approval configuration, add the preset approval configuration to the approval process, and get the configured approval process; Obtain the approval request from the front end, make approval predictions for the approval request based on the pre-built intelligent approval model, and obtain the approval prediction results; Execute approval operations based on the configured approval process and approval prediction results to obtain approval completion results; Feedback the approval completion results to the front end.

2. The method for bank employees to create an approval process according to claim 1, characterized in that: The approval operation includes at least: automatic approval, multi-level approval and transfer to manual review.

3. The method for bank employees to create an approval process according to claim 1, characterized in that: The preset approval configuration at least includes: approval node configuration, approver configuration and approval condition configuration; Wherein, the approval node configuration is: the number and order of nodes in the self-defined approval process, and the nodes at least include: a start node, an approval node, and an end node; The approver configuration includes: the role, responsibilities and approval order of the approver in the custom approval process; Wherein, the approval condition configuration is: the approval condition in the custom approval process.

4. The method for bank employees to create an approval process according to claim 1, characterized in that: Before making approval predictions for the approval request based on the pre-built intelligent approval model, the method further includes: verifying and pre-processing the approval request.

5. The method for bank employees to create an approval process according to claim 1, characterized in that: The method further includes: monitoring the approval operation to obtain status monitoring data and log record data.

6. The method for bank employees to create an approval process according to claim 1, characterized in that: The method further includes: based on a visualization tool, visually displaying the required components, approval prediction results, configured approval processes, approval completion results, and process nodes in the approval operation.

7. An approval platform, characterized in that: The platform includes: The approval process management module is used to: obtain the business needs of users, identify the business needs of users, and obtain the identification results; match the required components from the preset component library based on the identification results, and the matched required components can be used by users to customize the form items of the approval process; obtain the preset approval configuration, add the preset approval configuration to the approval process, and obtain the configured approval process; obtain the approval request from the front end, and make approval predictions on the approval request based on the pre-built intelligent approval model to obtain the approval prediction results; perform the approval operation based on the configured approval process and the approval prediction results to obtain the approval completion results; and feed back the approval completion results to the front end; The form management module is used to verify the content of the form in the approval process based on preset verification rules.

8. The approval platform according to claim 7, characterized in that: The platform also includes: Role and authority management module, used to manage the allocation of roles and authorities; Data processing and analysis module, used for data preprocessing, feature extraction, model training and prediction; The data storage management module is used to store the approval data and model parameters according to the distributed database, and encrypt the sensitive data in the approval data through the encryption algorithm.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the method for bank employees to create an approval process described in any one of claims 1 to 6 is implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method for bank employees to create an approval process described in any one of claims 1 to 6 is implemented.

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