Staff training method of financial institution, electronic equipment, storage medium and product

Abstract

The invention discloses an employee training method of a financial institution, electronic equipment, a storage medium and a product, and relates to the technical field of financial science and technology. The method comprises the following steps: in response to a starting instruction of a training task of a target financial institution, determining a target training virtual environment matched with the training task; issuing a learning instruction of the preset task operation to the target training employee, and receiving a target operation action made by the target training employee for the preset task operation; determining whether the target operation action is matched with a preset operation action or not; and under the condition of determining that the target operation action is matched with the preset operation action, determining that the learning of the preset task operation is completed, and continuously issuing a learning instruction of the next preset task operation to the target training employee until the learning instructions of all the preset task operations are completely learned. According to the scheme, the training efficiency of financial institution employees can be improved, the employees can truly feel the working environment, and real-time interaction and feedback in the training process are achieved.

Description

Technical Field

[0001] The present invention relates to the field of financial technology, and in particular to an employee training method, electronic equipment, storage medium, and product for a financial institution. Background Art

[0002] Financial institutions' employee training aims to enhance their professional skills, compliance awareness, and service capabilities, ensuring they can effectively perform their tasks and provide high-quality services to clients. Effective training programs not only enhance employee capabilities but also improve the overall performance and competitiveness of financial institutions.

[0003] At present, financial institutions mainly conduct employee training through face-to-face classroom teaching, supplemented by paper materials or simple multimedia presentations, to provide training on product knowledge, business processes, customer service, etc.; alternatively, courses are provided through online learning platforms, where employees can independently learn basic operating procedures, product knowledge, etc. through videos, documents and online tests.

[0004] The above solution cannot reproduce the complex situations in the real working environment of financial institutions, and the operational capabilities of employees cannot be fully improved; at the same time, it also lacks real-time interaction and feedback. Employees cannot correct mistakes or ask questions in time during the learning process, resulting in poor learning effects.

[0005] How to improve the training efficiency of financial institution employees, enable employees to truly experience the working environment, and achieve real-time interaction and feedback during the training process is a key issue in industry research. Summary of the Invention

[0006] The present invention provides an employee training method, electronic equipment, storage medium and product for a financial institution, so as to improve the training efficiency of the financial institution employees, enable the employees to truly experience the working environment, and realize real-time interaction and feedback during the training process.

[0007] According to one aspect of the present invention, a method for training employees of a financial institution is provided, the method comprising:

[0008] In response to a start instruction of a training task of a target financial institution, determining a target training virtual environment that matches the training task of the target financial institution;

[0009] In response to a successful instruction of the target training employee logging into the target training virtual environment, issuing a learning instruction for a preset task operation to the target training employee, and receiving a target operation action performed by the target training employee for the preset task operation;

[0010] Determining whether the target operation action matches a preset operation action; wherein the preset operation action matches the preset task operation instruction;

[0011] When it is determined that the target operation action matches the preset operation action, it is determined that the preset task operation learning is completed, and the learning instruction of the next preset task operation is continued to be issued to the target training employee until the learning instructions of all preset task operations are completed.

[0012] According to another aspect of the present invention, there is provided an employee training device for a financial institution, the device comprising:

[0013] A first response module is configured to respond to a start instruction of a training task of a target financial institution and determine a target training virtual environment that matches the training task of the target financial institution;

[0014] a second response module, configured to, in response to a successful instruction of the target training employee logging into the target training virtual environment, issue a learning instruction of a preset task operation to the target training employee, and receive a target operation action performed by the target training employee in response to the preset task operation;

[0015] A first determining module is configured to determine whether the target operation action matches a preset operation action; wherein the preset operation action matches the preset task operation instruction;

[0016] The second determination module is used to determine that the learning of the preset task operation is completed when it is determined that the target operation action matches the preset operation action, and continue to issue the learning instructions of the next preset task operation to the target training employee until the learning instructions of all preset task operations are completed.

[0017] According to another aspect of the present invention, an electronic device is provided, comprising:

[0018] at least one processor; and

[0019] a memory communicatively connected to the at least one processor; wherein,

[0020] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the employee training method for a financial institution according to any embodiment of the present invention.

[0021] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the employee training method for a financial institution according to any embodiment of the present invention when executed.

[0022] According to another aspect of the present invention, a computer program product is provided, comprising a computer program, wherein when the computer program is executed by a processor, the computer program implements the employee training method of a financial institution according to any embodiment of the present invention.

[0023] The technical solution of the embodiment of the present invention determines a target training virtual environment that matches the training task of the target financial institution in response to a start instruction of the training task of the target financial institution; can determine the operating space of the training employee, so that the training employee can truly experience the working environment, and provide assistance for achieving real-time interaction and feedback during the training process; in response to a successful instruction of the target training employee logging into the target training virtual environment, a learning instruction for a preset task operation is issued to the target training employee, and a target operation action performed by the target training employee for the preset task operation is received; it is determined whether the target operation action matches the preset operation action; wherein the preset operation action matches the preset task operation instruction; it can accurately determine whether the training employee's operation is correct during the training process; if it is determined that the target operation action matches the preset operation action, it is determined that the learning of the preset task operation is completed, and the learning instruction for the next preset task operation is continued to be issued to the target training employee until the learning instructions of all preset task operations are completed, which can improve the training efficiency of financial institution employees, enable employees to truly experience the working environment, and achieve real-time interaction and feedback during the training process.

[0024] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present invention, nor is it intended to limit the scope of the present invention. Other features of the present invention will become readily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0026] Figure 1 This is a flow chart of an employee training method for a financial institution provided according to the first embodiment of the present invention;

[0027] Figure 2 is a flow chart of a method for generating a target training virtual environment according to a second embodiment of the present invention;

[0028] Figure 3 is a flowchart of another method for generating a target training virtual environment according to the second embodiment of the present invention;

[0029] Figure 4 This is a flow chart of an employee training method for a financial institution provided according to a third embodiment of the present invention;

[0030] Figure 5 is a flow chart of another employee training method for a financial institution provided according to a third embodiment of the present invention;

[0031] Figure 6 This is a schematic structural diagram of an employee training device for a financial institution according to a fourth embodiment of the present invention;

[0032] Figure 7 The figure is a schematic structural diagram of an electronic device for implementing the employee training method for a financial institution according to an embodiment of the present invention. DETAILED DESCRIPTION

[0033] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

[0034] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0035] Example 1

[0036] Figure 1 This is a flow chart of a method for training employees of a financial institution according to a first embodiment of the present invention. This embodiment is applicable to business training for employees of a financial institution's branches. The method can be executed by an employee training device of a financial institution. The employee training device of a financial institution can be implemented in the form of hardware and / or software. The employee training device of a financial institution can be configured in an electronic device such as a computer, a server, or a tablet computer. Figure 1 As shown, the method includes:

[0037] Step 110: In response to the start instruction of the training task of the target financial institution, determine a target training virtual environment that matches the training task of the target financial institution.

[0038] Among them, the training tasks of the target financial institution can be business processing tasks (for example, loan business, remittance business or deposit business, etc.) generated in the financial institution outlets (for example, bank outlets), customer service tasks (for example, account management tasks such as opening a new account or modifying account information, or consulting service tasks, etc.), electronic banking service tasks (for example, online banking registration and activation tasks, digital certificate issuance tasks, etc.) or other value-added service tasks (for example, insurance service tasks, precious metal trading tasks or tax consulting tasks, etc.).

[0039] In this embodiment, the instruction to start the training task of the target financial institution can be issued by a superior organization (for example, the superior management organization of the bank branch, or the headquarters, etc.), or the instruction to start the training task of the target financial institution can be automatically initiated by the bank branch, which is not limited in this embodiment.

[0040] Optionally, in this embodiment, after the electronic device deployed with the employee training device of a financial institution receives the start instruction of the training task of the target financial institution, it can further determine the target training virtual environment that matches the training task of the target financial institution; it can be understood that in this embodiment, the target training virtual environment is a pre-established virtual model that matches the bank's late check-in, which is a virtual three-dimensional space model composed of multiple spatial points.

[0041] Step 120 : In response to a successful instruction of the target training employee logging into the target training virtual environment, a learning instruction of a preset task operation is issued to the target training employee, and a target operation action performed by the target training employee for the preset task operation is received.

[0042] The target training employee may be any employee to be trained, such as a counter staff, lobby manager, account manager, credit specialist, or financial advisor, and this embodiment does not limit this.

[0043] In this embodiment, the preset task operation can be any operation action in the training task of the target financial institution; for example, if the training task of the target financial institution is to open a new account, then the preset task operation can be to collect the user's facial image, or to collect the user's signature information, etc.; if the training task of the target financial institution is remittance business, then the preset task operation can be to obtain the remitter's account information, or to obtain the remittance amount, etc., which is not limited in this embodiment.

[0044] Optionally, in this embodiment, after determining that a target training virtual environment is obtained that matches the training task of the target financial institution, it is possible to further determine whether the target training employee has successfully logged into the target training virtual environment. When it is determined that the target training employee has successfully logged into the target training virtual environment, illustratively, the username and password of the target training employee for logging into the target training virtual environment are correct, then learning instructions for preset task operations can be further issued to the target training employee. For example, specific operating procedures, precautions or operation videos of the preset task operations can be issued so that the target training employee can learn.

[0045] Furthermore, after the learning is completed, the target operation actions made by the target training employee for the preset task operation are received, so that the target training employee can directly operate in the template training virtual environment, and it can be directly determined whether the target training employee has mastered the preset operation task.

[0046] Step 130: Determine whether the target operation action matches a preset operation action.

[0047] The preset operation action matches the preset task operation instruction, that is, the preset operation action is a predetermined standard operation action that matches the preset task operation instruction.

[0048] Optionally, in this embodiment, after receiving the target operation action performed by the target training employee for the preset task operation, it can be further determined whether the target operation action matches the preset operation action.

[0049] Optionally, in this embodiment, determining whether the target operation action matches the preset operation action may include: determining the similarity between the target operation action and the preset operation action, and when it is determined that the similarity meets a set similarity threshold, determining that the target operation action matches the preset operation action; otherwise, determining that the target operation action does not match the preset operation action.

[0050] The similarity threshold may be set to 0.9, 0.95, or 0.99, etc., which is not limited in this embodiment.

[0051] In an optional implementation of this embodiment, after receiving the target operation action performed by the target training employee for the preset task operation, the target operation action can be further converted into a target operation action vector. Furthermore, the similarity between the target operation action vector and the preset operation action corresponding to the preset operation action can be calculated. If the determined similarity is greater than or equal to the set similarity threshold, then it can be determined that the target operation action matches the preset operation action; otherwise, the two do not match.

[0052] In an example of this embodiment, if the similarity between the target operation action vector and the preset operation action vector corresponding to the preset operation action is determined to be 0.99, which is greater than the set similarity threshold of 0.98, then it can be determined that the target operation action matches the preset operation action.

[0053] The advantage of this setting is that it can quickly determine whether the target operation action matches the preset operation action, can detect the training task in real time, and can make real-time prompts when the template training employees operate in an irregular manner, providing a basis for improving training efficiency.

[0054] Step 140: When it is determined that the target operation action matches the preset operation action, it is determined that the preset task operation learning is completed, and the learning instruction of the next preset task operation is continuously issued to the target training employee until the learning instruction of all preset task operations is completed.

[0055] The next preset task operation is any task operation in the training task of the target financial institution except the preset task operation.

[0056] Optionally, in this embodiment, if it is determined that the target operation action matches the preset operation action, then it can be determined that the target training employee has completed the learning of the preset task operation, and the next preset task operation can be continued to be issued to the target training employee, and the target operation action made by the target training employee for the next preset task operation can be received. When it is determined that the target operation action matches the preset operation action, it is determined that the target training employee has also completed the learning of the next preset task operation; when all preset task operations in the training task of the target financial institution are learned, it is determined that the training of the target training employee is completed, and the training of the target training employee is qualified.

[0057] The technical solution of this embodiment determines a target training virtual environment that matches the training task of the target financial institution in response to a start instruction of the training task of the target financial institution; determines the operating space of the training employee, enables the training employee to truly experience the working environment, and provides assistance for achieving real-time interaction and feedback during the training process; in response to a successful instruction of the target training employee logging into the target training virtual environment, issues a learning instruction for a preset task operation to the target training employee, and receives a target operation action performed by the target training employee for the preset task operation; determines whether the target operation action matches the preset operation action; wherein the preset operation action matches the preset task operation instruction; accurately determines whether the training employee's operation is correct during the training process; when it is determined that the target operation action matches the preset operation action, determines that the learning of the preset task operation is completed, and continues to issue a learning instruction for the next preset task operation to the target training employee until the learning instructions of all preset task operations are completed, which can improve the training efficiency of financial institution employees, enable employees to truly experience the working environment, and achieve real-time interaction and feedback during the training process.

[0058] Example 2

[0059] Figure 2 This is a flow chart of a method for generating a target training virtual environment according to the second embodiment of the present invention. This embodiment is a further refinement of the above technical solution, that is, a description of the generation process of the target virtual environment. Figure 2 As shown, the method includes:

[0060] Step 210: Collect environmental data of target financial institution outlets.

[0061] The environmental data includes environmental image data, sensor data, and spatial geometry and positioning data.

[0062] It should be noted that, in this embodiment, the number of outlets of the target financial institution may be one or more, which is not limited in this embodiment; illustratively, it may be multiple outlets of the same financial institution in different regions.

[0063] It should also be noted that the target financial institution involved in this embodiment can be the same branch of the same financial institution as the target financial institution in the training task involved in the above embodiment, or it can be a different branch of the same financial institution, which is not limited in this embodiment.

[0064] Optionally, in this embodiment, sensors such as binocular cameras, gyroscopes, or odometers are deployed in key areas of the target financial institution outlets (for example, counter areas or self-service machine areas, etc.); in a specific implementation, these sensors can be used to collect environmental data of the target financial institution outlets; for example, environmental image data can be collected by binocular cameras; sensor data can be collected by gyroscopes; and spatial geometry and positioning data can be collected by odometers, etc.

[0065] Step 220: Process the environmental data and construct a virtual model of the target financial institution branch based on the processing results.

[0066] Optionally, in this embodiment, after the environmental data of the target financial institution branch is collected by various sensors, the environmental data can be further processed, and a virtual model of the target financial institution branch can be constructed based on the processing results; wherein the virtual model of the target financial institution branch is the target training virtual environment that matches the training task of the target financial institution.

[0067] In an optional implementation of this embodiment, processing each of the environmental data and constructing a virtual model of the target financial institution branch based on the processing results may include: determining key points of each of the environmental data, determining the gradient direction of each of the key points, and generating a descriptive factor based on the gradient direction; performing depth estimation based on the gradient direction and the descriptive factor, and reconstructing the three-dimensional structure of the target financial institution branch based on the depth estimation; performing pose estimation on the target sensor that collects the environmental data based on the three-dimensional structure of the target financial institution branch, determining the position and posture of the target sensor in the target financial institution branch, and optimizing the map data based on the position and posture; and constructing a virtual model of the target financial institution branch based on the optimized map data.

[0068] Optionally, in this embodiment, key points in the image data can be detected based on a key point detection algorithm; for example, a pixel point p can be used to compare 16 pixels in the target p circle range, and each pixel can be divided into three categories: higher than, lower than, and close to p; further, a threshold T is set, and the brighter pixel will be the one with a brightness exceeding I p +T pixels, darker pixels will be those with brightness lower than I p -T, similar pixels will be pixels with brightness between these two values. If there are 9 or more connected pixels darker or brighter than p, then the pixel p is selected as the keypoint.

[0069] Furthermore, the gradient direction θ of the surrounding area can be calculated based on the following formula:

[0070]

[0071] Among them, I x (i, j) and I y (i, j) are the gradient values of the image in the x and y directions at positions i and j respectively, N is the pixel area around the key point, and atan2 is the angle calculation function.

[0072] Furthermore, binary values are generated by comparing the grayscale values of pixel pairs. All the generated binary values are connected in series to form a description factor. The specific formula can be:

[0073]

[0074] Among them, I(p i ) and I(q i ) represent the feature points p i and q i For each pair of pixels (p i ,q i ), binary value b i .

[0075] Furthermore, the descriptor can be rotated so that the descriptor remains consistent under the rotation transformation, thereby obtaining the key point features; specifically, the rotated descriptor d' can be achieved by aligning the original descriptor d with the main direction of the key point:

[0076] d′=ratate(d,θ);

[0077] Among them, θ is the main direction, and ratate(d,θ) means rotating the description factor d by angle θ.

[0078] It should be noted that, since the image data is collected by a binocular camera in this embodiment (the collected images can be left and right images), the matched features will have horizontal displacement (parallax) in the left and right images. In order to map each feature point from the image plane to the three-dimensional world coordinate system, it is also necessary to calculate the depth Z of each feature point based on the following formula:

[0079]

[0080] Where: Z is the depth of the feature point (relative to the camera); f is the focal length of the camera; B is the camera baseline (the distance between the left and right cameras); and d is the parallax, which is the horizontal displacement of the feature point in the left and right images.

[0081] For example, if the three-dimensional coordinates of the feature point of the current frame in the world coordinate system are X i =(X i ,Y i ,Z i ), and its projection in the left image is xi =(x i ,y i ); Based on the matched 3D points and 2D image points, the camera pose (rotation matrix and translation vector) can be further estimated:

[0082] x j =π(R i ,t i ,X j );

[0083] Where: x j is the two-dimensional feature point in the image, X j is the three-dimensional feature point obtained from depth estimation, R i is the camera's rotation matrix, t i is the camera's translation vector, and π is the camera projection model, which represents the mapping from a three-dimensional point to a two-dimensional image plane.

[0084] Furthermore, the camera pose can be optimized based on the following formula:

[0085]

[0086] Among them, π(RX i +t) is the position of the 3D point corresponding to the estimated pose R,t projected onto the image plane.

[0087] In this embodiment, by processing multiple key frames and feature points, a virtual bank branch scene that matches the actual environment can be generated; each feature point in the branch is calibrated as a position in three-dimensional space, and new feature points are accumulated as employees move in the bank branch, and global map optimization can be performed; it can be understood that based on the depth information of key frames and map points, the stability and synchronization of the virtual branch scene are continuously optimized to reduce deviations caused by sensor errors and environmental changes.

[0088] For example, global graph optimization can be performed using the following formula:

[0089]

[0090] Where: T i is the pose of each key frame (including rotation and translation), X j is a 3D point in the map; x ij is the reprojected two-dimensional point, π(T i ,X j ) is a projection model that represents the position of a 3D point projected onto the image plane. The pose and position of the map points are optimized by minimizing the reprojection error.

[0091] Furthermore, a virtual model of the target financial institution's branch can be constructed based on the optimized map data, and a target training virtual environment matching the training task of the target financial institution can be provided.

[0092] In order to better understand the method for generating the target training virtual environment involved in this embodiment, Figure 3 is a flowchart of another method for generating a target training virtual environment according to the second embodiment of the present invention, referring to Figure 3 , which may include:

[0093] Step 310: Acquire sensor data;

[0094] Step 320: key point detection;

[0095] Step 330: Calculate the gradient direction and generate the descriptive factor;

[0096] Step 340: depth estimation and 3D point modeling;

[0097] Step 350: pose estimation;

[0098] Step 360: global graph optimization;

[0099] Step 370: Virtual network model.

[0100] The solution of this embodiment can construct a target training virtual environment by obtaining the environmental data of the target financial institution's branches before training employees, providing a basis for subsequent effective employee training, allowing employees to truly experience the working environment, and achieving real-time interaction and feedback during the training process.

[0101] Example 3

[0102] Figure 4 This is a flow chart of a method for employee training of a financial institution according to the third embodiment of the present invention. This embodiment is a further refinement of the above technical solution. The technical solution in this embodiment can be combined with each optional solution in one or more of the above embodiments. Figure 4 As shown, the method includes:

[0103] Step 410: In response to the start instruction of the training task of the target financial institution, determine a target training virtual environment that matches the training task of the target financial institution.

[0104] Optionally, in this embodiment, determining the target training virtual environment that matches the training task of the target financial institution may include: parsing the training task of the target financial institution to obtain attribute information of the training task of the target financial institution; determining the target financial institution branch that matches the training task of the target financial institution based on the attribute information, and obtaining a virtual model of the target financial institution branch; and determining the virtual model of the target financial institution branch as the target training virtual environment.

[0105] The attribute information includes at least one of the following: task name, task objective, task content, business knowledge, and process.

[0106] In an optional implementation of this embodiment, after receiving the start instruction of the training task of the target financial institution, the training task of the target financial institution can be further parsed to obtain attribute information such as the task name, task objective, task content, business knowledge or process of the training task of the target financial institution.

[0107] Furthermore, the target financial institution branch that matches the training task of the target financial institution can be determined based on the attribute information of the training task of the determined target financial institution. For example, the target financial institution branch can be determined based on the task name (for example, if the task name is loan business training for branch B of Bank A, then the target financial institution branch is branch B), or the target financial institution branch can be determined based on the task content (for example, if the task content is on-the-job training for new employees of branch C of Bank A, then the target financial institution branch is branch C).

[0108] Furthermore, the virtual model of the target financial institution branch can be determined as the target training virtual environment; illustratively, in the above example, the virtual model of branch B can be determined as the target training virtual environment, or the virtual model of branch C can be determined as the target training virtual environment; wherein, the virtual model of each branch is the virtual model determined by the above embodiment.

[0109] The advantage of this setting is that by analyzing the training tasks of the target financial institution, the target financial institution outlets that match the training tasks of the target financial institution can be quickly determined, which helps to determine the target training virtual environment.

[0110] Step 420: Determine whether the target training employee is wearing the target wearable device; if it is determined that the target training employee is wearing the target wearable device and the password for logging into the target training virtual environment is correct, determine that the target training employee has successfully logged into the target training virtual environment.

[0111] The target wearable device is a smart watch, smart glasses, smart headphones, virtual reality helmet or augmented reality helmet.

[0112] Optionally, in this embodiment, the employee training method of a financial institution may further include: determining whether the target training employee is wearing a target wearable device; if it is determined that the target training employee is wearing a target wearable device and the password for logging into the target training virtual environment is correct, determining that the target training employee has successfully logged into the target training virtual environment.

[0113] It should be noted that the target training employees can interact with the target training virtual environment by wearing corresponding wearable devices. For example, they can perform corresponding operations or learning actions in the target training virtual environment.

[0114] Optionally, in this embodiment, whether the target training employee is wearing a wearable device can be determined by obtaining facial image data of the target training employee; when it is determined that the target training employee is wearing the target wearable device and the password for logging into the target training virtual environment is correct, it can be determined that the target training employee has successfully logged into the target training virtual environment, that is, the target training employee can subsequently complete the corresponding training tasks based on the target training virtual environment.

[0115] The solution of this embodiment determines that the target training employee has successfully logged into the target training virtual environment by determining that the target training employee is wearing the target wearable device and the password is correct. This can prevent non-training employees from arbitrarily using the target training virtual environment and wasting the resources of the target training virtual environment.

[0116] Step 430: issuing a learning instruction for the preset task operation through the target wearable device worn by the target training employee; the target training employee views the target training virtual environment based on the target wearable device, and performs a target operation action for the preset task operation in the target training virtual environment; and providing feedback of the target operation action through the target wearable device.

[0117] The target operation action includes learning or demonstration.

[0118] Optionally, in this embodiment, after determining that the target training employee has successfully logged into the target training virtual environment, the learning instructions for the preset task operation can be further issued through the target wearable device worn by the target training employee; further, the target training employee can view the target training virtual environment based on the target wearable device, and perform the target operation action for the preset task operation in the target training virtual environment; further, the target operation action can be fed back through the target wearable device.

[0119] In a specific example of this embodiment, when a target trainee wears smart glasses and enters the target training virtual environment, their operational behavior can be tracked and analyzed in real time, compared with pre-set operational procedures, and provided with immediate feedback. If the employee's operation is correct, the system prompts "Operation Successful" and guides them to the next step. If an error occurs, the system indicates the cause and provides corresponding visual guidance to help the target trainee correct the error. Furthermore, training tasks and difficulty levels can be dynamically adjusted based on the target trainee's learning progress and operational performance, providing a personalized learning plan.

[0120] Step 440: Determine whether the target operation action matches a preset operation action.

[0121] Step 450: When it is determined that the target operation action matches the preset operation action, it is determined that the preset task operation learning is completed, and the learning instruction of the next preset task operation is continued to be issued to the target training employee until the learning instructions of all preset task operations are completed.

[0122] The solution of this embodiment realizes the communication between the target training employee and the target training virtual environment through wearable devices, and can provide instant feedback and guidance based on the target training employee's operating behavior, providing a basis for ensuring the efficiency and personalization of the training process.

[0123] In order to better understand the employee training method of the financial institution involved in this embodiment, Figure 5 This is a flowchart of another employee training method for a financial institution provided according to the third embodiment of the present invention. Figure 5 , which may include:

[0124] Step 510: Enter the target training virtual environment;

[0125] Step 520: Select a training task;

[0126] Step 530: Task operation interaction;

[0127] Step 540: Whether the operation is consistent with the preset;

[0128] If yes, execute step 550;

[0129] Otherwise, execute step 541;

[0130] Step 541: Display the error cause and provide visual guidance;

[0131] Step 550: Whether the task process is completed;

[0132] If so, end;

[0133] Otherwise, execute step 551;

[0134] Step 541: The task proceeds to the next step.

[0135] This embodiment improves the speed and accuracy of employee skill acquisition through precise environmental positioning and real-time feedback. Furthermore, the integration of virtual and real-world scenarios reduces training resource consumption, lowers costs, and provides a more flexible and sustainable solution for large-scale employee training.

[0136] Example 4

[0137] Figure 6 Schematic diagram of the structure of a staff training device for a financial institution according to the fourth embodiment of the present invention. Figure 6 As shown, the apparatus includes: a first response module 610 , a second response module 620 , a first determination module 630 and a second determination module 640 .

[0138] A first response module 610 is configured to respond to a start instruction of a training task of a target financial institution and determine a target training virtual environment that matches the training task of the target financial institution;

[0139] A second response module 620 is configured to, in response to a successful instruction of the target training employee logging into the target training virtual environment, issue a learning instruction of a preset task operation to the target training employee, and receive a target operation action performed by the target training employee in response to the preset task operation;

[0140] A first determining module 630 is configured to determine whether the target operation action matches a preset operation action; wherein the preset operation action matches the preset task operation instruction;

[0141] The second determination module 640 is used to determine that the learning of the preset task operation is completed when it is determined that the target operation action matches the preset operation action, and continue to issue the learning instructions of the next preset task operation to the target training employee until the learning instructions of all preset task operations are completed.

[0142] The solution of this embodiment is to respond to the start instruction of the training task of the target financial institution through the first response module to determine the target training virtual environment that matches the training task of the target financial institution; respond to the successful instruction of the target training employee to log into the target training virtual environment through the second response module, issue a learning instruction of the preset task operation to the target training employee, and receive the target operation action made by the target training employee for the preset task operation; determine whether the target operation action matches the preset operation action through the first determination module; wherein the preset operation action matches the preset task operation instruction; determine that the learning of the preset task operation is completed through the second determination module when it is determined that the target operation action matches the preset operation action, and continue to issue the learning instruction of the next preset task operation to the target training employee until the learning instructions of all preset task operations are completed. This can improve the training efficiency of financial institution employees, enable employees to truly experience the working environment, and realize real-time interaction and feedback during the training process.

[0143] In an optional implementation of this embodiment, the employee training device of a financial institution further includes: a target training virtual environment generation module, which is used to:

[0144] Collecting environmental data of the target financial institution's branch; the environmental data includes environmental image data, sensor data, and spatial geometry and positioning data;

[0145] The environmental data are processed, and a virtual model of the target financial institution branch is constructed based on the processing results.

[0146] In an optional implementation of this embodiment, the target training virtual environment generation module is specifically configured to:

[0147] Determining key points of each of the environmental data, determining a gradient direction of each of the key points, and generating a description factor based on the gradient direction;

[0148] Performing depth estimation based on the gradient direction and the descriptive factor, and reconstructing the three-dimensional structure of the target financial institution branch based on the depth estimation;

[0149] performing pose estimation on a target sensor that collects the environmental data based on the three-dimensional structure of the target financial institution outlet, determining the position and pose of the target sensor in the target financial institution outlet, and optimizing the map data based on the position and pose;

[0150] A virtual model of the target financial institution branch is constructed based on the optimized map data.

[0151] In an optional implementation of this embodiment, the first response module 610 is specifically configured to:

[0152] Parsing the training task of the target financial institution to obtain attribute information of the training task of the target financial institution; the attribute information includes at least one of the following: task name, task objective, task content, business knowledge, and process;

[0153] Determining a target financial institution branch that matches the training task of the target financial institution based on the attribute information, and obtaining a virtual model of the target financial institution branch;

[0154] The virtual model of the target financial institution branch is determined as the target training virtual environment.

[0155] In an optional implementation of this embodiment, the employee training apparatus of a financial institution further includes: a wear confirmation module of a wearable device, configured to:

[0156] Determining whether the target training employee is wearing a target wearable device; wherein the target wearable device is a smart watch, smart glasses, smart headphones, virtual reality helmet, or augmented reality helmet;

[0157] When it is determined that the target training employee wears the target wearable device and the password for logging into the target training virtual environment is correct, it is determined that the target training employee has successfully logged into the target training virtual environment.

[0158] In an optional implementation of this embodiment, the second response module 620 is specifically configured to:

[0159] issuing a learning instruction for the preset task operation through a target wearable device worn by the target training employee;

[0160] The target training employee views the target training virtual environment based on the target wearable device, and performs a target operation action for the preset task operation in the target training virtual environment; the target operation action includes learning or demonstrating;

[0161] The target operation action is fed back through the target wearable device.

[0162] In an optional implementation of this embodiment, the first determining module 630 is specifically configured to:

[0163] Determining a similarity between the target operation action and the preset operation action, and if it is determined that the similarity meets a set similarity threshold, determining that the target operation action matches the preset operation action;

[0164] Otherwise, it is determined that the target operation action does not match the preset operation action.

[0165] The employee training device for a financial institution provided by an embodiment of the present invention can execute the employee training method for a financial institution provided by any embodiment of the present invention, and has functional modules and beneficial effects corresponding to the execution method.

[0166] In the technical solution of the embodiment of the present invention, the collection, storage, use, processing, transmission, provision and disclosure of the target financial institutions (such as branch information, training information, etc.) are in compliance with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0167] Example 5

[0168] Figure 7 A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or claimed herein.

[0169] like Figure 7 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., which is communicatively connected to the at least one processor 11. The memory stores a computer program that can be executed by the at least one processor. The processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 into the random access memory (RAM) 13. Various programs and data required for the operation of the electronic device 10 can also be stored in the RAM 13. The processor 11, ROM 12, and RAM 13 are connected to each other via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0170] Multiple components in the electronic device 10 are connected to the I / O interface 15, including an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a magnetic disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0171] The processor 11 can be any general-purpose and / or specialized processing component with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as a method for employee training at a financial institution, which includes, in response to a start instruction for a training task at a target financial institution, determining a target training virtual environment that matches the training task at the target financial institution; in response to a successful instruction for a target training employee to log into the target training virtual environment, issuing a learning instruction for a preset task operation to the target training employee, and receiving a target operation action performed by the target training employee for the preset task operation; determining whether the target operation action matches the preset operation action; wherein the preset operation action matches the preset task operation instruction; if it is determined that the target operation action matches the preset operation action, determining that the preset task operation learning is complete, and continuing to issue a learning instruction for the next preset task operation to the target training employee until all learning instructions for the preset task operations are complete.

[0172] In some embodiments, the employee training method for a financial institution may be implemented as a computer program tangibly embodied in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the employee training method for a financial institution described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to execute the employee training method for a financial institution via any other suitable means (e.g., via firmware).

[0173] Various embodiments of the systems and techniques described herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), system-on-chip systems (SOCs), programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer programs that are executable and / or interpreted on a programmable system that includes at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0174] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when the computer program is executed by the processor, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The computer program may be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0175] In the context of the present invention, computer-readable storage media can be tangible media that can contain or store a computer program for use with an instruction execution system, device or equipment or used in combination with an instruction execution system, device or equipment. Computer-readable storage media can include but are not limited to electronic, magnetic, optical, electromagnetic, infrared or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, computer-readable storage media can be machine-readable signal media. More specific examples of machine-readable storage media can include electrical connections based on one or more lines, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0176] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0177] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0178] A computing system may include clients and servers. The clients and servers are typically remote from each other and typically interact via a communication network. This client-server relationship arises through computer programs running on the respective computers, creating a client-server relationship. The server may be a cloud server, also known as a cloud computing server or cloud host. This server is a hosting product within the cloud computing service ecosystem that addresses the management difficulties and limited scalability of traditional physical hosting and VPS services.

[0179] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in the present invention can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution of the present invention can be achieved. This is not limited herein.

[0180] The above specific embodiments do not limit the scope of protection of the present invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention are intended to be included within the scope of protection of the present invention.

[0181] An embodiment of the present invention further provides a computer program product, including a computer program, which, when executed by a processor, implements the database detection method provided in any embodiment of the present application.

[0182] The computer program product may be implemented by writing computer program code for performing the operations of the present invention in one or more programming languages, or a combination thereof, including object-oriented programming languages such as Java, Smalltalk, C++, and conventional procedural programming languages such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0183] It should be noted that in the embodiments of the present application, certain software, components, models and other existing solutions in the industry may be mentioned. They should be regarded as exemplary. Their purpose is only to illustrate the feasibility of implementing the technical solution of the present application, but it does not mean that the applicant has or will necessarily use the solution.

[0184] Note that the above are only preferred embodiments of the present invention and the technical principles employed. Those skilled in the art will appreciate that the present invention is not limited to the specific embodiments herein, and that various obvious changes, readjustments, and substitutions are possible for those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in detail through the above embodiments, the present invention is not limited to the above embodiments and may include many other equivalent embodiments without departing from the scope of the present invention. The scope of the present invention is determined by the scope of the appended claims.

Claims

1. A method for training employees of a financial institution, characterized in that: include: In response to a start instruction of a training task of a target financial institution, determining a target training virtual environment that matches the training task of the target financial institution; In response to a successful instruction of the target training employee logging into the target training virtual environment, issuing a learning instruction for a preset task operation to the target training employee, and receiving a target operation action performed by the target training employee for the preset task operation; Determining whether the target operation action matches a preset operation action; wherein the preset operation action matches the preset task operation instruction; When it is determined that the target operation action matches the preset operation action, it is determined that the preset task operation learning is completed, and the learning instruction of the next preset task operation is continued to be issued to the target training employee until the learning instructions of all preset task operations are completed.

2. The employee training method of a financial institution according to claim 1, characterized in that: The target training virtual environment is generated by the following steps: Collecting environmental data of the target financial institution's branch; the environmental data includes environmental image data, sensor data, and spatial geometry and positioning data; The environmental data are processed, and a virtual model of the target financial institution branch is constructed based on the processing results.

3. The employee training method of a financial institution according to claim 2, characterized in that: The processing of the environmental data and constructing a virtual model of the target financial institution outlets according to the processing results include: Determining key points of each of the environmental data, determining a gradient direction of each of the key points, and generating a description factor based on the gradient direction; Performing depth estimation based on the gradient direction and the descriptive factor, and reconstructing the three-dimensional structure of the target financial institution branch based on the depth estimation; performing pose estimation on a target sensor that collects the environmental data based on the three-dimensional structure of the target financial institution outlet, determining the position and pose of the target sensor in the target financial institution outlet, and optimizing the map data based on the position and pose; A virtual model of the target financial institution branch is constructed based on the optimized map data.

4. The employee training method of a financial institution according to claim 1, characterized in that: The determining of a target training virtual environment that matches the training task of the target financial institution includes: Parsing the training task of the target financial institution to obtain attribute information of the training task of the target financial institution; the attribute information includes at least one of the following: task name, task objective, task content, business knowledge, and process; Determining a target financial institution branch that matches the training task of the target financial institution based on the attribute information, and obtaining a virtual model of the target financial institution branch; The virtual model of the target financial institution branch is determined as the target training virtual environment.

5. The employee training method of a financial institution according to claim 1, characterized in that: The method further comprises: Determining whether the target training employee is wearing a target wearable device; wherein the target wearable device is a smart watch, smart glasses, smart headphones, virtual reality helmet, or augmented reality helmet; When it is determined that the target training employee wears the target wearable device and the password for logging into the target training virtual environment is correct, it is determined that the target training employee has successfully logged into the target training virtual environment.

6. The employee training method of a financial institution according to claim 5, characterized in that: The sending of a learning instruction for a preset task operation to the target training employee and receiving a target operation action performed by the target training employee in response to the preset task operation includes: issuing a learning instruction for the preset task operation through a target wearable device worn by the target training employee; The target training employee views the target training virtual environment based on the target wearable device, and performs a target operation action for the preset task operation in the target training virtual environment; the target operation action includes learning or demonstrating; The target operation action is fed back through the target wearable device.

7. The employee training method of a financial institution according to claim 1, characterized in that: Determining whether the target operation action matches a preset operation action includes: Determining a similarity between the target operation action and the preset operation action, and if it is determined that the similarity meets a set similarity threshold, determining that the target operation action matches the preset operation action; Otherwise, it is determined that the target operation action does not match the preset operation action.

8. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to execute the employee training method for a financial institution according to any one of claims 1 to 7.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the employee training method for a financial institution according to any one of claims 1 to 7 when executed.

10. A computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the computer program implements the employee training method for a financial institution according to any one of claims 1 to 7.

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