Business optimization method, apparatus, device, medium, and program product

Abstract

This application provides a business optimization method, apparatus, device, medium, and program product, which can be applied to the field of artificial intelligence technology, involving the application of large models in fintech scenarios. The method is executed by a management server, which communicates with a terminal device. The method includes: receiving queuing information sent by the terminal device; sending a first input interface to the terminal device based on the queuing information; in response to receiving a candidate business type input through the first input interface, determining the current queuing state corresponding to the candidate business type, generating queuing information corresponding to the current queuing state, and sending it to the terminal device; sending a second input interface to the terminal device; and in response to receiving a target business type input through the second input interface, using a preset time estimation model based on the target business type and queuing information to estimate the expected waiting time for the user on the terminal device and sending it to the terminal device.

Description

Technical Field

[0001] This application relates to the field of artificial intelligence technology, to the application of large models in fintech scenarios, and more specifically to a business optimization method, apparatus, device, medium, and program product. Background Technology

[0002] Currently, bank lobby services generally follow the traditional process of "taking a number from a ticket machine—queuing with a paper slip—counter service." Upon arriving at the branch, customers obtain a paper queue number from the ticket machine and then enter an indiscriminate waiting queue. During this waiting period, customers can only piecemeal understanding of the general process and required documents by recalling information, asking the lobby manager, or consulting scattered promotional materials. In most cases, customers passively wait until their number is called, at which point a teller informs them of the document requirements or eligibility criteria. If, at this point, it is discovered that documents are missing, information is incomplete, or the customer does not meet the eligibility requirements, they must leave to supplement the documents or re-enter the queue, resulting in multiple trips and repeated use of service windows for a single transaction. Summary of the Invention

[0003] In view of the above problems, embodiments of this application provide a service optimization method, apparatus, device, medium, and program product.

[0004] According to a first aspect of this application, a service optimization method is provided, executed by a management server, which is communicatively connected to a terminal device. The method includes: receiving queuing information sent by the terminal device; sending a first input interface to the terminal device based on the queuing information to prompt the user to select a candidate service type from multiple parent service types; in response to receiving the candidate service type input through the first input interface, determining the current queuing state corresponding to the candidate service type, generating queuing information corresponding to the current queuing state, and sending it to the terminal device; sending a second input interface to the terminal device to prompt the user to select a target service type from multiple sub-service types of the candidate service type; and in response to receiving the target service type input through the second input interface, using a preset time estimation model to estimate the expected waiting time of the user on the terminal device based on the target service type and the queuing information, and sending it to the terminal device.

[0005] According to an embodiment of this application, receiving queuing information sent by a terminal device includes: receiving a queuing request sent by the terminal device, wherein the queuing request is generated by the terminal device after scanning the identification information of the self-service terminal; and in response to the queuing request, obtaining queuing information corresponding to the identification information.

[0006] According to an embodiment of this application, the method further includes: after sending a second input interface to a terminal device, sending a third input interface to the terminal device, wherein the third input interface displays attribute questions associated with the target business type; in response to receiving feedback content on the attribute questions input through the third input interface, determining target attribute information corresponding to the target business type based on the feedback content; and determining a target material list for the target business type based on the target attribute information.

[0007] According to an embodiment of this application, the method further includes: after determining the target material list for the target business type, color-coding the target material list, and sending the color-coded target material list to a terminal device; wherein the target material list includes core materials and auxiliary materials, and color-coding the target material list includes: color-coding the core materials with a first color and color-coding the auxiliary materials with a second color, wherein the first color is more prominent than the second color.

[0008] According to an embodiment of this application, there are multiple attribute questions, and the third input interface includes multiple sub-interfaces corresponding to the multiple attribute questions; sending the third input interface to the terminal device includes: determining the associated initial attribute question based on the target service type, and sending the initial sub-interface corresponding to the initial attribute question to the terminal device; in response to receiving feedback content for the initial attribute question input through the initial sub-interface, determining the next attribute question based on the feedback content; and taking the next attribute question as the initial attribute question and returning to the step of sending the initial sub-interface corresponding to the initial attribute question to the terminal device.

[0009] According to an embodiment of this application, the method further includes: retrieving a corresponding basic material list from a preset material list library based on the target business type; and determining a target material list for the target business type based on target attribute information, including: supplementing the basic material list based on the target attribute information to obtain the target material list.

[0010] According to an embodiment of this application, a preset time estimation model is used to estimate the expected waiting time of users of the terminal device based on the target service type and queuing information, including: determining the baseline time of the target service type; calculating the correction coefficient corresponding to the queuing information; and correcting the baseline time based on the correction coefficient to obtain the expected waiting time.

[0011] According to an embodiment of this application, the method further includes: after estimating the expected waiting time of the target service type using a preset time estimation model and sending it to the terminal device, calculating the cumulative waiting time of the user of the terminal device based on the initiation time of the terminal device initiating the number retrieval information and the current time; when the cumulative waiting time exceeds a first time threshold, pushing a first reminder event information; when the cumulative waiting time exceeds a second time threshold, pushing a second reminder event information; wherein, the second time threshold is greater than the first time threshold; and the importance of the second reminder event information is higher than that of the first reminder event information.

[0012] According to a second aspect of this application, a service optimization apparatus is provided, comprising: an information receiving module, configured to receive queuing information sent by a terminal device, and send a first input interface to the terminal device based on the queuing information to prompt the user to select a candidate service type from multiple parent service types; an information generation module, configured to, in response to receiving the candidate service type input through the first input interface, determine the current queuing state corresponding to the candidate service type, generate queuing information corresponding to the current queuing state, and send it to the terminal device; a service determination module, configured to send a second input interface to the terminal device to prompt the user to select a target service type from multiple sub-service types of the candidate service type; and a time estimation module, configured to, in response to receiving the target service type input through the second input interface, use a preset time estimation model to estimate the expected waiting time of the user on the terminal device based on the target service type and the queuing information, and send it to the terminal device.

[0013] According to a third aspect of this application, an electronic device is provided, comprising: one or more processors; and a memory for storing one or more computer programs, wherein the one or more processors execute the one or more computer programs to implement the steps of the method described above.

[0014] According to a fourth aspect of this application, a computer-readable storage medium is also provided, on which a computer program or instructions are stored, wherein the computer program or instructions, when executed by a processor, implement the steps of the above-described method.

[0015] According to a fifth aspect of this application, a computer program product is also provided, including a computer program or instructions that, when executed by a processor, implement the steps of the above-described method.

[0016] The business optimization methods, apparatus, equipment, media, and program products in the embodiments of this application obtain electronic queuing numbers through terminal devices, realizing contactless queuing and reducing physical contact and paper waste; they can automatically synchronize queuing information to the management server to ensure real-time data updates; they can automatically identify specific business types and estimate the current waiting time based on a time prediction model, providing customers with reference time planning; at the same time, through dynamic collection of attribute issues, real-time generation of material lists, and visual coding layered presentation, they transform vague business intentions into clear and actionable action guidelines, and achieve visual saliency layering of core materials and auxiliary materials through color coding, greatly reducing the cognitive load and risk of omissions in material preparation. Attached Figure Description

[0017] The above-mentioned contents, other objects, features and advantages of this application will become clearer from the following description of embodiments with reference to the accompanying drawings, in which:

[0018] Figure 1 The illustrations depict application scenarios of service optimization methods, apparatus, devices, media, and program products according to embodiments of this application.

[0019] Figure 2 A flowchart illustrating a service optimization method according to an embodiment of this application is shown schematically.

[0020] Figure 3 A flowchart illustrating the generation of a target bill of materials according to an embodiment of this application is shown.

[0021] Figure 4 This schematic diagram illustrates a structural block diagram of a service optimization apparatus according to an embodiment of the present application;

[0022] Figure 5 A block diagram of an electronic device suitable for implementing a service optimization method according to an embodiment of this application is shown schematically. Detailed Implementation

[0023] The embodiments of this application will now 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 this application. In the following detailed description, numerous specific details are set forth to provide a thorough understanding of the embodiments of this application for ease of explanation. However, it will be apparent that one or more embodiments may be implemented without these specific details. Furthermore, descriptions of well-known structures and technologies are omitted in the following description to avoid unnecessarily obscuring the concepts of this application.

[0024] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of this application. The terms “comprising,” “including,” etc., as used herein indicate the presence of the stated features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0025] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein are to be interpreted in a manner consistent with the context of this specification, and not in an idealized or overly rigid way.

[0026] In the technical solution of this application, the user information (including but not limited to user personal information, user image information, user device information, such as location information) and data (including but not limited to data used for analysis, stored data, and displayed data) involved are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, storage, use, processing, transmission, provision, disclosure, and application of related data all comply with relevant laws, regulations, and standards, take necessary confidentiality measures, do not violate public order and good morals, and provide corresponding operation entry points for users to choose to authorize or refuse.

[0027] In scenarios where personal information is used for automated decision-making, the methods, devices, and systems provided in this application all provide users with corresponding operation entry points for users to choose to agree to or reject the automated decision results; if the user chooses to reject, the process enters the expert decision-making process.

[0028] As used in this paper, the term "model" refers to a model that learns the relationship between inputs and outputs from training data, enabling it to generate corresponding outputs for a given input after training. Model generation can be based on machine learning techniques. Deep learning is a machine learning algorithm that processes inputs and provides corresponding outputs using multiple layers of processing units. A neural network model is an example of a deep learning-based model. In this paper, "model" may also be referred to as a "machine learning model," "learning model," "machine learning network," or "learning network," and these terms are used interchangeably.

[0029] It's important to note that the term "neural network" can refer to a machine learning network based on deep learning. A neural network processes input and provides corresponding output, typically consisting of an input layer, an output layer, and one or more hidden layers between them. Neural networks used in deep learning applications often include many hidden layers, increasing the network's depth. The layers of a neural network are connected sequentially, so that the output of the previous layer serves as the input to the next layer. The input layer receives the input to the neural network, while the output layer's output becomes the final output. Each layer of a neural network includes one or more nodes (also called processing nodes or neurons), each processing the input from the layer above.

[0030] It should be understood that machine learning generally includes three phases: training, testing, and application (also known as inference). In the training phase, a given model is trained using a large amount of training data, iteratively updating parameter values ​​until the model can consistently generate inferences that meet the expected goals from the training data. Through training, the model can be considered to have learned the relationship between inputs and outputs (also known as the input-output mapping) from the training data. The parameter values ​​of the trained model are determined. In the testing phase, test inputs are applied to the trained model to test whether it can provide the correct output, thus determining the model's performance. In the application phase, the model can be used to process actual inputs based on the trained parameter values ​​to determine the corresponding output.

[0031] In one or more embodiments described herein, the term "large model" can refer to a deep learning model with a large number of model parameters, which can include hundreds of millions, tens of billions, hundreds of billions, trillions, or even tens of trillions of model parameters. Large models can also be called foundational models or basic models. They are pre-trained using large-scale unlabeled corpora to produce pre-trained models with hundreds of millions of parameters. Such models can adapt to a wide range of downstream tasks and have good generalization ability, such as large language models and multimodal pre-trained models. It should be understood that in practical applications, large models only require a small number of samples to fine-tune the pre-trained model before being applied to different tasks. Large models can be widely used in natural language processing, computer vision, and other fields. Specifically, they can be applied to computer vision tasks such as visual question answering, image captioning, and image generation, as well as natural language processing tasks such as text-based sentiment classification, text summarization, and machine translation. Major application scenarios for large models can include digital assistants, intelligent robots, search, online education, office software, e-commerce, and intelligent design.

[0032] Figure 1 The illustration shows an application scenario diagram of the service optimization method, apparatus, device, medium, and program product according to embodiments of this application.

[0033] like Figure 1 As shown, application scenario 100 according to an embodiment of this application may include a first terminal device 101, a second terminal device 102, a self-service terminal 103, a network 104, and a server 105. The network 104 serves as a medium for providing a communication link between the first terminal device 101, the second terminal device 102, the self-service terminal 103, and the server 105. The network 104 may include various connection types, such as wired or wireless communication links or fiber optic cables. For example, a user can use the first terminal device 101 and the second terminal device 102 to interact with the server 105 and / or the self-service terminal 103 through the network 104 to receive or send information, etc.

[0034] The first terminal device 101 and the second terminal device 102 can be electronic devices such as smartphones, wearable devices, personal computers, intelligent voice interaction devices, smart home appliances, intelligent vehicles, in-vehicle terminals, aircraft, unmanned vending terminals, and extended reality devices. Extended reality devices can include virtual reality devices, augmented reality devices, and mixed reality devices. The terminal devices can install and run a client application for the target application, which can include, but is not limited to, financial transaction applications, payment applications, shopping applications, web browser applications, search applications, instant messaging tools, email clients, social media platform software, etc. (these are just examples). Furthermore, this application embodiment does not limit the form of the target application, including but not limited to applications, mini-programs, etc., installed on the terminal device, and can also be in web page form.

[0035] Server 105 can be a server providing various services, such as a backend management server supporting websites browsed by users using the first terminal device 101 and the second terminal device 102 (this is just an example). The backend management server can analyze and process received user requests and other data, and feed back the processing results (such as web pages, information, or data obtained or generated according to user requests) to the terminal devices. The server can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services such as cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks, and big data. The server can be the management server for the aforementioned target application, used to provide backend services to the user end of the target application.

[0036] Self-service terminal 103 can be a bank ticket dispensing terminal, serving as the primary venue for face-to-face communication between the bank and customers, and is responsible for the initial processing of various customer service requests. Self-service terminal 103 includes, but is not limited to, smartphones, tablets, laptops, desktop computers, and servers providing various services.

[0037] It should be noted that the service optimization method provided in this application embodiment can generally be executed by server 105. Accordingly, the service optimization device provided in this application embodiment can generally be set in server 105.

[0038] It should be understood that Figure 1 The number of terminal devices, networks, self-service terminals, and servers shown is merely illustrative. Depending on implementation needs, any number of terminal devices, networks, self-service terminals, and servers can be included.

[0039] Figure 2 A flowchart illustrating a service optimization method according to an embodiment of this application is shown schematically. Figure 2 As shown, the service optimization method 200 according to the embodiment of this application is executed by a management server. The management server is communicatively connected to the terminal device. The method 200 includes steps S210 to S240.

[0040] In step S210, the system receives number retrieval information sent by the terminal device and sends a first input interface to the terminal device based on the number retrieval information, prompting the user to select a candidate service type from multiple parent service types.

[0041] In embodiments of this application, user consent or authorization can be obtained before sending the first input interface to the terminal device. For example, a request for the first input interface can be sent to the terminal device before step S210. Step S210 is executed if the user consents or authorizes the sending of the first input interface to the terminal device.

[0042] For example, a terminal device can be a user-side electronic device used by a user in a bank lobby service scenario to scan identification information, receive instructions from the management server, display an interactive interface, and collect user operation feedback, such as a smartphone, tablet, or wearable device.

[0043] For example, a management server refers to a back-end computing device deployed in a bank's data center or cloud, responsible for handling front-end service requests in the bank lobby and executing core business logic. This management server is the central control unit of the bank's intelligent pre-processing system. It interacts bidirectionally with user terminal devices, teller terminals, lobby manager mobile terminals, and the bank's core business systems via encrypted communication protocols, undertaking full-process calculation and control functions such as number generation, dynamic question-and-answer engine, business type identification, material list generation, waiting time estimation, queue status monitoring, and reminder triggering.

[0044] For example, queuing information refers to the service request data sent by a user to the management server through their terminal device. This queuing information includes at least: device identifier, scanning time, branch number, and entry channel identifier, which is used to uniquely identify a queuing behavior and trigger subsequent service processes.

[0045] For example, the first input interface refers to the first interactive graphical user interface pushed to the user's terminal device by the management server after receiving the queuing information. This interface follows a progressive disclosure principle, displaying only one core question and 3-5 options per screen, and adopting a card-style layout to adapt to mobile operation. For example, after the user scans the code, the terminal device displays an interface titled "Please select the category of business you wish to handle," with two card-style buttons below: "Personal Business" and "Corporate Business."

[0046] For example, the parent business type refers to a first-level category node in the banking service business classification system, which is the root or top-level node of the business tree logical structure. This category has the coarsest business granularity and the widest coverage, and is used to perform initial coarse-grained segmentation of user needs at the beginning of the service. For example, personal banking and corporate banking.

[0047] For example, candidate service types refer to one or more parent service types that are presented to the user in the first input interface and are available for selection.

[0048] In step S220, in response to receiving the candidate service type input through the first input interface, the current queuing status corresponding to the candidate service type is determined, queuing information corresponding to the current queuing status is generated and sent to the terminal device.

[0049] For example, the candidate service type refers to the major service category selected and confirmed by the user from multiple parent service types through the first input interface. This selection result will serve as the initial service type for this service session, used to trigger subsequent dynamic question-and-answer processes, determine queue assignment, and associate with the business rule base and question database. For example, if user Zhang clicks the "Personal Services" button on the first input interface, then "Personal Services" will be the candidate service type for this session.

[0050] For example, the current queue status refers to the dynamic operational data of the queue corresponding to the selected service type, which the management server obtains in real time from the queue management system. The current queue status is a snapshot of the queue load, used to support waiting time estimation, window scheduling decisions, and user notification. For instance, after a user selects "Personal Services," the management server queries the Personal Comprehensive Services queue and obtains the following current queue status: 15 people are waiting ahead, 3 windows are currently open, window 2 is processing a recurring account opening transaction (estimated remaining 3 minutes), window 3 is idle, and window 4 is processing a card loss report transaction (estimated remaining 7 minutes).

[0051] For example, queue information refers to a data object generated by the management server based on the current queue status. Queue information includes at least the number of people ahead of you and your queue number, which are of most concern to the user. This queue information will be pushed to the user's terminal device and presented to the user in a visual format. For example, the terminal device might display: "There are 15 people ahead of you, queue number A20."

[0052] In step S230, a second input interface is sent to the terminal device to prompt the user to select a target service type from multiple sub-service types of the candidate service type.

[0053] For example, the second input interface refers to the second interactive graphical user interface pushed to the terminal device by the management server after the user selects a candidate business type (parent business type). This interface follows the principle of progressive disclosure and is used to guide users to select the specific business they want to handle from multiple sub-business types within the same business category. The second input interface is the first branch node in the dynamic tree-like question-and-answer process, marking the transition from coarse-grained triage to fine-grained identification. For example, after the user selects "Personal Business" on the first input interface, the phone screen jumps to the second input interface, with the title "Please select the specific personal business you want to handle," and below it arranged in a card-style layout with five option buttons: "Deposit Business," "Transfer and Remittance," "Account Management," and "Credit Card Services."

[0054] For example, a sub-business type refers to a second-level business category node belonging to a parent business type (candidate business type), and is the second-level node in the business tree logical structure. Compared with the parent business type, sub-business types have finer business granularity and clearer business boundaries, and can more accurately reflect the user's true processing intentions, serving as the business benchmark for triggering subsequent attribute questions, material lists, and risk warnings. For example, under the parent type "Personal Business," there are sub-types such as "Deposit Business" and "Account Management."

[0055] For example, the target business type refers to the specific business sub-category that the user actually selects and confirms from multiple sub-business types in the second input interface. The target business type is the core business label of this service session and directly determines all subsequent interaction content. For example, if the user clicks the "Transfer and Remittance" option in the "Personal Business" sub-type list in the second input interface, then "Transfer and Remittance" is the target business type for this session. Based on this, the management server triggers the following actions: loading the attribute questions corresponding to "Transfer and Remittance" (same bank / interbank, amount range, whether it involves foreign countries); retrieving the material list template corresponding to "Transfer and Remittance" (ID card, bank card, payee information); and associating the risk warning corresponding to "Transfer and Remittance".

[0056] In step S240, in response to receiving the target service type input through the second input interface, a preset time estimation model is used to estimate the expected waiting time of the user of the terminal device based on the target service type and queuing information, and the estimate is sent to the terminal device.

[0057] For example, a time estimation model refers to a mathematical algorithm or calculation logic built into the management server to calculate the waiting time for a user from the time they obtain a number to the time their number is called. This model is trained on historical business processing data and uses methods such as weighted average, regression analysis, or machine learning to establish a mapping relationship between business type and processing time.

[0058] For example, the estimated waiting time refers to the estimated time interval from the current moment to the moment when the user is called, calculated by the time estimation model based on the baseline time of the target business type and the queuing information correction coefficient.

[0059] For example, when user Li clicks "transfer money" on the second input interface, the management server receives the selection, immediately calls the time estimation model, inputs the target business type and real-time queuing information, calculates 24 minutes, and then sends the time to Li's mobile phone, and the waiting time number on the interface is refreshed to 24.

[0060] The business optimization method based on the embodiments of this application eliminates the traditional single step of taking a number by coordinating the operation of the management server and the terminal device. The electronic queue number is obtained through the terminal device, realizing contactless number taking and reducing physical contact and paper waste. This function automatically synchronizes the queue information to the management server to ensure that the data is updated in real time. Through the business segmentation guidance of the second input interface, users do not need to have banking business knowledge. They can clearly define their actual needs by simply clicking through the steps. The management server automatically identifies the business type and dynamically estimates the current waiting time based on historical business processing data, providing users with reference time planning.

[0061] In the embodiments of this application, receiving the number retrieval information sent by the terminal device includes: receiving the number retrieval request sent by the terminal device, the number retrieval request being generated by the terminal device after scanning the identification information of the self-service terminal; and in response to the number retrieval request, obtaining the number retrieval information corresponding to the identification information.

[0062] For example, a number retrieval request refers to a service instruction sent by a terminal device to the management server after scanning the self-service terminal's identification information. A number retrieval request must at least carry the self-service terminal's identification information, and may also include contextual data such as the terminal device's identification, scanning time, and geographical location.

[0063] For example, a self-service terminal refers to a physical access device deployed in a bank lobby, allowing users to initiate service requests independently. Its core function is to provide the terminal device with a binding identifier between the branch and the queue through identification information. For example, a self-service terminal can be a ticket dispenser or a low-cost information board.

[0064] For example, identification information refers to the unique identification code stored or generated by the self-service terminal to uniquely identify the service entry point. The management server parses this identification information to determine which branch, queue, and service channel the user belongs to.

[0065] Based on the business optimization method of this application embodiment, the terminal device can instantly complete the identity association and queue binding by scanning the identification information of the self-service terminal, realize contactless number retrieval, and reduce physical contact and paper waste.

[0066] Figure 3 A flowchart illustrating the generation of a target bill of materials according to an embodiment of this application is shown.

[0067] like Figure 3 As shown, in some embodiments, after sending the second input interface to the terminal device in step S230, the service optimization method according to the embodiments of this application may include steps S310 to S330.

[0068] In step S310, a third input interface is sent to the terminal device, wherein the third input interface displays attribute questions associated with the target service type.

[0069] For example, the third input interface refers to the third interactive graphical user interface pushed to the terminal device by the management server after the user selects the target business type. This interface follows the principle of progressive disclosure, displaying only one attribute question and 3-5 preset options per screen, presented sequentially in a card-style layout. The core task of the third input interface is to collect the personalized decision parameters necessary to complete the business transaction, based on the target business type.

[0070] For example, attribute questions refer to decision-point questions displayed in the third input interface that are strongly correlated with the target business type and are used to collect key parameters for business processing. Each attribute question corresponds to a value selection for a business dimension, and the answers to all attribute questions together constitute a complete feature profile of a business.

[0071] In step S320, in response to receiving feedback on the attribute issue input through the third input interface, the target attribute information corresponding to the target service type is determined based on the feedback.

[0072] For example, feedback content refers to the specific answers or information entered by the user through a third input interface for attribute questions.

[0073] For example, target attribute information refers to the set of business parameters generated by the management server after performing structured parsing and standardized mapping of the feedback content submitted by users.

[0074] In step S330, a target material list for the target business type is determined based on the target attribute information.

[0075] For example, the target materials list refers to the list of documents and certificates required for this user's current business, generated by the management server based on a combination of target business type and target attribute information, retrieved in real time from the preset materials list library, dynamically assembled, and customized.

[0076] For example, when the target business type is a special business, such as inheritance, an additional link to download legal document templates will pop up, which helps users prepare materials in advance.

[0077] For example, when the target business type is foreign exchange business, the terminal device will display a warning about exchange rate fluctuation risk.

[0078] The business optimization method based on the embodiments of this application, through the collection of attribute questions on the third input interface and the dynamic generation of the target material list, completely advances the material verification process that relies on tellers asking questions one by one and users passively supplementing documents in the traditional mode to be completed within the user's waiting period; at the same time, the user feedback content is mapped into structured attribute information in real time, and after the teller terminal receives the pre-review list synchronously, the material verification time is realized, effectively improving the processing efficiency of bank windows.

[0079] In an embodiment of this application, the method further includes: after determining the target material list for the target business type, color-coding the target material list, and sending the color-coded target material list to a terminal device; wherein the target material list includes core materials and auxiliary materials, and color-coding the target material list includes: color-coding the core materials with a first color and color-coding the auxiliary materials with a second color, wherein the first color is more prominent than the second color.

[0080] For example, color coding refers to the data processing process in which the management server assigns different visual colors to each material item in the target bill of materials according to its importance and whether it is mandatory.

[0081] For example, core materials refer to documents or certificates that are mandatory requirements of laws, regulations, regulatory policies, or bank risk control systems when processing the target transaction. The absence of core materials will result in the transaction being rejected, failing the review, or violating compliance requirements. Examples include the original and a copy of the ID card required for personal account opening; and withdrawal slips, reservation records, and the original ID card required for large withdrawals.

[0082] For example, supporting documents refer to non-mandatory documents that, while helpful in expediting the approval process, increasing credit limits, reducing risk premiums, or meeting internal management requirements, are not mandatory for the target business. Examples include overseas school admission letters and copies of visa pages required for foreign exchange transactions.

[0083] For example, the first color code refers to a preset color scheme specifically used to mark core materials. The first color code follows the design principles of high prominence and high contrast, and usually selects hues such as red and dark orange, which have strong warning and prompting attributes, to ensure that users can identify the items that must be prepared at a glance when they open the list.

[0084] For example, secondary color coding refers to a preset color scheme specifically used to mark auxiliary materials. Secondary color coding uses mild hues with low salience and low interference, such as yellow, light blue, and gray, which can clearly distinguish it from the core materials while preventing users from ignoring the truly essential items due to information overload.

[0085] For example, in color perception dimensions such as hue saturation, brightness contrast, background contrast, and visual weight, the first color code has a stronger visual capture ability and cognitive priority than the second color code.

[0086] The business optimization method based on the embodiments of this application achieves visual saliency stratification of core materials and auxiliary materials through color coding, which greatly reduces the cognitive load and risk of omission in material preparation and improves the accuracy and efficiency of material preparation.

[0087] In the embodiments of this application, there are multiple attribute questions, and the third input interface includes multiple sub-interfaces corresponding to the multiple attribute questions; sending the third input interface to the terminal device includes: determining the associated initial attribute question based on the target service type, and sending the initial sub-interface corresponding to the initial attribute question to the terminal device; in response to receiving feedback content for the initial attribute question input through the initial sub-interface, determining the next attribute question based on the feedback content; and taking the next attribute question as the initial attribute question and returning to the step of sending the initial sub-interface corresponding to the initial attribute question to the terminal device.

[0088] For example, a sub-interface refers to an independent interactive page unit that, when presented on a device terminal, breaks down and displays multiple attribute questions one by one.

[0089] For example, the initial attribute question refers to the first attribute question presented to the user at the current interaction node. The initial attribute question is the current starting point of the dynamic question-and-answer sequence, determined by the management server based on the target business type when the user first enters the third input interface. In subsequent loops, the next attribute question is assigned to the initial attribute question, thus achieving iterative progress.

[0090] For example, if a user selects "Account Inquiry" in the personal services section, the management server will select and display relevant questions based on this selection, instead of displaying all personal services questions.

[0091] For example, the management server can adjust the question based on the context of the current attribute question. If the user has already provided some information in a previous attribute question, the management server will avoid asking the same question repeatedly.

[0092] In some embodiments, determining the next attribute question based on the feedback content means matching the feedback content with business rules to determine the next attribute question. These business rules can be branching rules used to determine the attribute question navigation path based on the feedback content, priority rules used to determine the display priority among multiple candidate attribute questions, and termination rules used to determine whether to end the third input interface.

[0093] For example, when resetting passwords in high-frequency services, the number of attribute questions can be reduced to three or less. These could be: First, identity verification, requiring the user to enter one or more of the following information: account number or username, personal identification information such as ID card number; Second, verification code confirmation, where the management server sends a verification code to the terminal device, and the user enters the verification code in the designated input box to prove their identity; Third, setting a new password, where the user is required to enter a new password and confirm it again to avoid input errors.

[0094] For example, when handling large-amount transfer requests in complex transactions, branched validation logic is implemented: First, document checklist template retrieval: Based on the transfer type selected by the user, a pre-set document checklist template is retrieved in real time. Second, conditional branching: Based on the answers provided by the user, the system will trigger different validation logic. Third, real-time verification: Files uploaded by the user will be verified in real time by the management server to ensure the correctness of file type, format, and content. If the file does not meet the requirements, the user will be immediately notified and guided on how to upload the correct file. Fourth, based on user feedback and document verification results, the issue path is dynamically adjusted to guide the user through the entire large-amount transfer process.

[0095] For example, if the sub-interface does not receive feedback within 10 seconds, a lightweight notification overlay will pop up on the terminal device.

[0096] The business optimization method based on the embodiments of this application can intelligently select the next attribute question, adjust the focus of the inquiry, and end the process at an appropriate time according to the user's real-time feedback data. Users do not need to understand complex business logic, which effectively reduces the difficulty of users' business processing.

[0097] In embodiments of this application, the method further includes: retrieving a corresponding basic material list from a preset material list library based on the target business type; and determining a target material list for the target business type based on target attribute information, including: supplementing the basic material list based on the target attribute information to obtain the target material list.

[0098] For example, the bill of materials library refers to a set of standardized material templates that are pre-stored in the management server and cover all business types across the entire bank.

[0099] For example, the basic materials list refers to a standardized materials template retrieved by the management server from the materials list library based on the target business type selected by the user. The basic materials list represents the complete compliance requirements under the general scenario of this type of business. It is the minimum set of necessary materials that all users handling this business must meet, and does not include special materials items caused by individual user differences.

[0100] For example, supplementing the basic materials list refers to a rule-based process of dynamically adding, deleting, or replacing materials based on target attribute information. For instance, if a user's target attribute information includes: the purpose of the remittance is tuition fees for studying abroad; the remittance amount is US$45,000; and the recipient is a child, based on the rule that the purpose is studying abroad and the amount is large, supplementary materials are required: an overseas school admission notice or tuition payment notification.

[0101] For example, the target material list refers to the final complete material list generated by the management server after completing supplementary processing, which is specific to the user's current business. It inherits the compliance baseline of the basic template and incorporates the special requirements of the user's individual scenario.

[0102] The business optimization method based on the embodiments of this application upgrades the material list generation from static template output to dynamic adaptation list through a two-stage design of basic material list retrieval and target attribute information dynamic supplementation. This generates a highly personalized and accurate material list, prompts the required materials, helps users prepare in advance, reduces the problem of missing materials when processing at the window, and provides users with clear and specific preparation guidance.

[0103] In the embodiments of this application, a preset time estimation model is used to estimate the expected waiting time of the user of the terminal device based on the target service type and queuing information, including: determining the baseline time of the target service type; calculating the correction coefficient corresponding to the queuing information; and correcting the baseline time based on the correction coefficient to obtain the expected waiting time.

[0104] For example, the baseline processing time refers to the historical average processing time of the target business type under standard operating conditions, retrieved by the management server from the time estimation model. The baseline processing time is the basic time for this type of business under an idealized scenario where "the window is open normally, there is no queue, and the user's materials are complete".

[0105] For example, the correction factor refers to the multiplier factor used to adjust the base duration, which is calculated in real time by the management server based on queuing information. This queuing information may include variables such as the number of currently open windows and the number of people in the queue in real time.

[0106] For example, after preparing each material item in the target bill of materials, the user can calculate the processing time if the relevant materials are provided in advance.

[0107] The business optimization method based on the embodiments of this application achieves an intelligent upgrade from static reference to dynamic prediction of waiting time by integrating the business baseline duration and real-time queue dynamics. This provides users with transparent waiting expectations and effectively improves the autonomy of time scheduling. At the same time, the accurate prediction capability enables banks to more scientifically schedule window resources and manage user traffic, thereby optimizing the allocation of service resources.

[0108] In embodiments of this application, the method further includes: after estimating the expected waiting time of the target service type using a preset time estimation model and sending it to the terminal device, calculating the cumulative waiting time of the user of the terminal device based on the initiation time of the terminal device initiating the number retrieval information and the current time; when the cumulative waiting time exceeds a first time threshold, pushing a first reminder event information; when the cumulative waiting time exceeds a second time threshold, pushing a second reminder event information; wherein, the second time threshold is greater than the first time threshold; and the importance of the second reminder event information is higher than that of the first reminder event information.

[0109] For example, the first and second time-limit thresholds are adjusted based on current business volume, user traffic, and processing speed. For instance, if increased business volume leads to a decrease in processing speed, the management server will automatically raise the threshold to avoid triggering unnecessary alerts due to short wait times. Similarly, for complex transactions requiring longer processing times, the management server will raise the threshold accordingly. Furthermore, for high-end users, the management server will set a lower threshold to provide faster service responses.

[0110] For example, the prerequisites for the first and second reminder event information include: 1. Real-time monitoring and recording of user waiting time; 2. The current threshold has been calculated based on real-time data and preset rules; 3. Condition trigger: The user's waiting time exceeds the calculated threshold; 4. Complete user information: The management server must contain complete user information, including queue number, predicted service type, etc.; 5. Lobby manager terminal online: The lobby manager's terminal device must be online to receive reminder information.

[0111] For example, the first alert information is sent to the lobby manager's terminal through the bank's intranet system, including the user's queue number, cumulative waiting time, and target business type. At this time, the lobby manager can promptly reassure the user.

[0112] For example, when the second notification event information is sent to the lobby manager's terminal via the bank's intranet system, it will simultaneously be pushed to the teller's terminal and trigger an audio-visual alert. The teller can then click to view the user's relevant information, prepare necessary documents in advance, and use the priority adjustment function to insert the user's transaction into the queue at the appropriate time.

[0113] The business optimization method based on the embodiments of this application introduces a background continuous monitoring logic for the cumulative waiting time during the user's waiting period. Before user dissatisfaction arises, the bank's internal service recovery process is proactively triggered, which facilitates timely allocation of resources or activation of priority processing mechanisms to optimize service response efficiency.

[0114] Based on the above-described service optimization method, embodiments of this application also provide a service optimization apparatus. The following will combine... Figure 4 The device is described in detail.

[0115] Figure 4 A schematic block diagram of a service optimization apparatus according to an embodiment of this application is shown.

[0116] like Figure 4 As shown, the service optimization device 400 in this embodiment includes an information receiving module 410, an information generation module 420, a service determination module 430, and a time estimation module 440.

[0117] The information receiving module 410 is used to receive the number retrieval information sent by the terminal device, and based on the number retrieval information, sends a first input interface to the terminal device to prompt the user to select a candidate service type from multiple parent service types. In one embodiment, the information receiving module 410 can be used to execute step S210 described above, which will not be repeated here.

[0118] The information generation module 420 is used to respond to receiving a candidate service type input through the first input interface, determine the current queuing status corresponding to the candidate service type, generate queuing information corresponding to the current queuing status, and send it to the terminal device. In one embodiment, the information generation module 420 can be used to perform step S220 described above, which will not be repeated here.

[0119] The service determination module 430 is used to send a second input interface to the terminal device to prompt the user to select a target service type from multiple sub-service types of the candidate service type. In one embodiment, the service determination module 430 can be used to perform step S230 described above, which will not be repeated here.

[0120] The time estimation module 440, in response to receiving a target service type input through the second input interface, uses a preset time estimation model to estimate the expected waiting time for the user of the terminal device based on the target service type and queuing information, and sends the estimate to the terminal device. In one embodiment, the time estimation module 440 may be used to perform step S240 described above, which will not be repeated here.

[0121] According to embodiments of this application, any multiple modules among the information receiving module 410, information generating module 420, service determination module 430, and time estimation module 440 can be combined into one module, or any one of these modules can be split into multiple modules. Alternatively, at least some of the functions of one or more of these modules can be combined with at least some of the functions of other modules and implemented in one module. According to embodiments of this application, at least one of the information receiving module 410, information generating module 420, service determination module 430, and time estimation module 440 can be at least partially implemented as hardware circuitry, such as field-programmable gate arrays, programmable logic arrays, systems-on-a-chip, systems-on-a-substrate, systems-on-package, application-specific integrated circuits, or implemented in hardware or firmware by any other reasonable means of integrating or packaging circuitry, or implemented in software, hardware, and firmware, or in any appropriate combination of any of these three implementation methods. Alternatively, at least one of the information receiving module 410, information generating module 420, service determination module 430, and time estimation module 440 may be implemented at least partially as a computer program module, which can perform corresponding functions when the computer program module is run.

[0122] Figure 5 A block diagram of an electronic device suitable for implementing a service optimization method according to an embodiment of this application is shown schematically.

[0123] like Figure 5 As shown, an electronic device 500 according to an embodiment of this application includes a processor 501, which can perform various appropriate actions and processes according to a program stored in a read-only memory 502 or a program loaded from a storage portion 508 into a random access memory 503. The processor 501 may include, for example, a general-purpose microprocessor, an instruction set processor and / or an associated chipset and / or a dedicated microprocessor. The processor 501 may also include onboard memory for caching purposes. The processor 501 may include a single processing unit or multiple processing units for executing different steps of the method flow according to an embodiment of this application.

[0124] Random access memory 503 stores various programs and data required for the operation of electronic device 500. Processor 501, read-only memory 502, and random access memory 503 are interconnected via bus 504. Processor 501 executes various steps of the method flow according to embodiments of this application by executing programs in read-only memory 502 and / or random access memory 503. It should be noted that the programs may also be stored in one or more memories other than read-only memory 502 and random access memory 503. Processor 501 may also execute various steps of the method flow according to embodiments of this application by executing programs stored in said one or more memories.

[0125] According to embodiments of this application, the electronic device 500 may further include an input / output interface 505, which is also connected to a bus 504. The electronic device 500 may also include one or more of the following components connected to the input / output interface 505: an input section 506 including a keyboard, mouse, etc.; an output section 507 including a cathode ray tube, liquid crystal display, etc., and a speaker, etc.; a storage section 508 including a hard disk, etc.; and a communication section 509 including a network interface card, such as a local area network card, modem, etc. The communication section 509 performs communication processing via a network such as the Internet. A drive 510 is also connected to the input / output interface 505 as needed. A removable medium 511, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 510 as needed so that computer programs read from it can be installed into the storage section 508 as needed.

[0126] Embodiments of this application also provide a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or it may exist independently and not assembled into the device / apparatus / system. The computer-readable storage medium carries one or more programs, which, when executed, implement the method according to the embodiments of this application.

[0127] According to embodiments of this application, the computer-readable storage medium can be a non-volatile computer-readable storage medium, such as including but not limited to: portable computer disks, hard disks, random access memory, read-only memory, erasable programmable read-only memory, portable compact disk read-only memory, optical storage devices, magnetic storage devices, or any suitable combination thereof. In embodiments of this application, the computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. For example, according to embodiments of this application, the computer-readable storage medium may include the read-only memory 502, and / or random access memory 503, and / or one or more memories other than read-only memory 502 and random access memory 503 described above.

[0128] Embodiments of this application also include a computer program product comprising a computer program containing program code for performing the methods shown in the flowchart. When the computer program product is run on a computer system, the program code is used to cause the computer system to implement the methods provided in the embodiments of this application.

[0129] In one embodiment, the computer program may rely on a tangible storage medium such as an optical storage device or a magnetic storage device. In another embodiment, the computer program may also be transmitted and distributed in the form of signals over a network medium, and may be downloaded and installed via the communication section 509, and / or installed from a removable medium 511. The program code contained in the computer program can be transmitted using any suitable network medium, including but not limited to: wireless, wired, etc., or any suitable combination thereof.

[0130] In embodiments of this application, the computer program can be downloaded and installed from a network via communication section 509, and / or installed from removable medium 511. When the computer program is executed by processor 501, it performs the functions defined in the system of this application embodiment. According to embodiments of this application, the systems, devices, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0131] According to embodiments of this application, program code for executing the computer programs provided in the embodiments of this application can be written in any combination of one or more programming languages. Specifically, these computational programs can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. The program code can be executed entirely on the user's computing device, partially on the user's device, partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0132] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0133] Those skilled in the art will understand that the features described in the various embodiments of this application can be combined and / or combined in various ways, even if such combinations or combinations are not explicitly described in this application. In particular, the features described in the various embodiments of this application can be combined and / or combined in various ways without departing from the spirit and teachings of this application. All such combinations and / or combinations fall within the scope of this application.

Claims

1. A business optimization method, executed by a management server, wherein the management server is communicatively connected to a terminal device, characterized in that, The method includes: Receive the number retrieval information sent by the terminal device, and send a first input interface to the terminal device based on the number retrieval information to prompt the user to select a candidate service type from multiple parent service types; In response to receiving a candidate service type input through the first input interface, the current queuing status corresponding to the candidate service type is determined, queuing information corresponding to the current queuing status is generated and sent to the terminal device; Send a second input interface to the terminal device to prompt the user to select a target service type from multiple sub-service types of the candidate service type; In response to receiving the target service type input through the second input interface, a preset time estimation model is used to estimate the expected waiting time of the user of the terminal device based on the target service type and the queuing information, and the estimate is sent to the terminal device.

2. The method according to claim 1, characterized in that, The receipt of the number retrieval information sent by the terminal device includes: Receive a number retrieval request sent by the terminal device, the number retrieval request being generated by the terminal device after scanning the identification information of the self-service terminal; In response to the number retrieval request, obtain the number retrieval information corresponding to the identification information.

3. The method according to claim 1, characterized in that, The method further includes: after sending the second input interface to the terminal device. Send a third input interface to the terminal device, wherein the third input interface displays attribute questions associated with the target service type; In response to receiving feedback on the attribute question input through the third input interface, the target attribute information corresponding to the target service type is determined based on the feedback content; Based on the target attribute information, a target material list for the target business type is determined.

4. The method according to claim 3, characterized in that, The method further includes: after determining the target material list for the target business type. The target material list is color-coded, and the color-coded target material list is sent to the terminal device. The target material list includes core materials and auxiliary materials. Color coding of the target material list includes: color coding the core materials with a first color and color coding the auxiliary materials with a second color, wherein the first color is more prominent than the second color.

5. The method according to claim 3, characterized in that, There are multiple attribute questions, and the third input interface includes multiple sub-interfaces corresponding to the multiple attribute questions; Sending the third input interface to the terminal device includes: Based on the target service type, determine the associated initial attribute question, and send the initial sub-interface corresponding to the initial attribute question to the terminal device; In response to receiving feedback on the initial attribute question input through the initial sub-interface, the next attribute question is determined based on the feedback. Using the next attribute question as the initial attribute question, return to the step of sending the initial sub-interface corresponding to the initial attribute question to the terminal device.

6. The method according to claim 3, characterized in that, The method further includes: retrieving the corresponding basic material list from the preset material list library based on the target business type; The process of determining the target material list for the target business type based on the target attribute information includes: The target material list is obtained by supplementing the basic material list based on the target attribute information.

7. The method according to claim 1, characterized in that, The method of using a preset time estimation model to estimate the expected waiting time of users of the terminal device based on the target service type and the queuing information includes: Determine the baseline duration for the target service type; Calculate the correction coefficient corresponding to the queuing information; The baseline duration is corrected based on the correction factor to obtain the expected waiting time.

8. The method according to claim 1, characterized in that, The method further includes: after estimating the expected waiting time of the target service type using a preset time estimation model and sending it to the terminal device. Based on the initiation time and current time of the number retrieval information initiated by the terminal device, calculate the cumulative waiting time of the user of the terminal device; When the cumulative waiting time exceeds the first time threshold, a first reminder event message is pushed. When the cumulative waiting time exceeds the second time threshold, a second reminder event message is pushed. Wherein, the second duration threshold is greater than the first duration threshold; and the importance of the second reminder event information is higher than that of the first reminder event information.

9. A business optimization device, characterized in that, The device includes: The information receiving module is used to receive the number retrieval information sent by the terminal device, and send a first input interface to the terminal device based on the number retrieval information to prompt the user to select a candidate service type from multiple parent service types. The information generation module is used to respond to receiving a candidate service type input through the first input interface, determine the current queuing status corresponding to the candidate service type, generate queuing information corresponding to the current queuing status, and send it to the terminal device. The service determination module is used to send a second input interface to the terminal device to prompt the user to select a target service type from multiple sub-service types of the candidate service type; and The time estimation module is used to respond to receiving the target service type input through the second input interface, using a preset time estimation model to estimate the expected waiting time of the user of the terminal device based on the target service type and the queuing information, and then send it to the terminal device.

10. An electronic device, comprising: One or more processors; Memory, used to store one or more computer programs. The characteristic feature is that the one or more processors execute the one or more computer programs to implement the steps of the method according to any one of claims 1 to 8.

11. A computer-readable storage medium having a computer program or instructions stored thereon, characterized in that, When the computer program or instructions are executed by a processor, they implement the steps of the method according to any one of claims 1 to 8.

12. A computer program product, comprising a computer program or instructions, characterized in that, When the computer program or instructions are executed by a processor, they implement the steps of the method according to any one of claims 1 to 8.

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