Insurance proposal system and insurance proposal information processing method

Abstract

To provide an insurance proposal system and an insurance proposal method for presenting a future risk so that an examiner can easily imagine the future risk.SOLUTION: An insurance proposal space is composed of a first space, a second space, and a third space. The insurance proposal space is a space in which a proposer proposes insurance to an examiner, and is, for example, an area within a site of an insurance company. In the first space, a sensor 100 senses the examiner and outputs a sensing result to a server. The second space is a presentation space in which a display unit 200 is provided. The third space is a space for a reviewer to review an insurance contract. Unlike the second space, the third space is preferably a space in which a display unit is not used to produce an extraordinary feeling. In the third space, by allowing the examiner to consider purchasing insurance in a relaxed state, effect of reducing probability of cancellation after purchasing insurance can be expected.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present technology relates to a system and method for offering insurance. [Background technology]

[0002] A person considering purchasing insurance (hereinafter referred to as "considerer") imagines his or her future self and risks based on explanations from insurance proposers at insurance companies and the contents of pamphlets and other documents describing the insurance details, and considers which insurance plan to purchase. A system has been proposed in which the considerer can input his or her current situation, such as his or her current annual income and family situation, into the system, and receive recommendations regarding insurance plans after being presented with estimated future risks (for example, Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2020-190807 Summary of the Invention [Problem to be solved by the invention]

[0004] However, even when future risks are presented using the above-mentioned systems, it is often difficult for participants to perceive them as personal risks. In particular, when future risks are presented as numerical or text data on a small display, participants find it difficult to perceive them as personal risks. This is because a small display reduces the sense of immersion, and numerical or text data alone do not stimulate participants' imaginations.

[0005] This technology was developed in light of these circumstances, and makes it possible to present future risks in a way that makes it easier for examiners to imagine them. [Means for solving the problem]

[0006] An insurance proposal system according to one aspect of the present technology includes a sensor that senses a person considering a purchase in a first space, a display device that displays, in a second space, a presentation image for the person considering a purchase, the presentation image including an image including a future risk and insurance candidates extracted based on the future risk, and an information processing device that generates the image, wherein the information processing device has one or more processors and one or more storage devices that store a program, and the processor executes the program to read out advance information entered by the person considering a purchase in a space different from the first space and an advance purchaser ID assigned to the person considering a purchase, writes the output result of the sensor as advance purchaser information linked to the advance purchaser ID, estimates the future risk based on the advance information, and generates the image based on the future risk and the advance purchaser information. [Brief explanation of the drawings]

[0007] [Figure 1] 1 is a diagram illustrating an overview of an insurance proposal system realized by an information processing system according to an embodiment of the present technology. [Figure 2] 1 is a diagram showing an example of an insurance proposal space to which an insurance proposal system is applied. [Figure 3] FIG. 2 is a diagram showing an example of a second space to which the insurance proposal system is applied. [Figure 4] FIG. 1 is a diagram showing the overall flow of an insurance proposal system. [Figure 5] FIG. 10 is a diagram showing an example of an avatar in a presentation image generated by the insurance proposal system. [Figure 6] FIG. 10 is a diagram showing an example of a presentation image generated by the insurance proposal system. [Figure 7] FIG. 1 illustrates an example of a customer record generated by a system for insurance proposals. [Figure 8] FIG. 2 is a diagram illustrating an example of a configuration of a server of the insurance proposal system. [Figure 9] FIG. 1 is a diagram illustrating an example of a machine learning model of an insurance proposal system. DETAILED DESCRIPTION OF THE INVENTION

[0008] Hereinafter, embodiments of the present technology will be described in the following order. 1. About the insurance proposal system 2. Insurance proposal space 3. Overall processing flow 4. Presentation video 5. Variations

[0009] <1. About the insurance proposal system> FIG. 1 is a diagram illustrating an overview of an insurance proposal system realized by an information processing system according to an embodiment of the present technology.

[0010] As shown in FIG. 1, the insurance proposal system 1 is an information processing system that includes a sensor 100, a display device 200, a communication terminal 300, and a server 400, which are connected via a network 500.

[0011] The sensor 100 is a sensor capable of sensing at least the appearance of the examinee in the first space, and is, for example, a camera or a ToF (Time Of Flight) sensor. The sensor 100 may be two or more sensors, or may include different types of sensors. For example, the sensor 100 may be a sensor group configured by combining a camera and a healthcare device that measures the health condition of the examinee.

[0012] The display device 200 is a device capable of displaying a presentation image to the examiner in the second space, and is, for example, a projector or a display. The display is preferably a large display of at least 50 inches or more. The display device 200 may also be a combination of multiple projectors or displays, or a combination of a projector and a large monitor.

[0013] The communication terminal 300 is a device that transmits advance information about the examiner to the server 400, and is, for example, a PC (Personal Computer), a Pad-type device, or a smartphone.

[0014] The server 400 is an information processing device that generates a presentation image based on the results of sensing by the sensor 100 in the first space and prior information, and is, for example, a dedicated network-connected information processing device. The server 400 has at least a CPU and a storage device that stores programs (instructions), and the CPU executes the programs to realize the functions of the insurance proposal system 1. The server 400 may be a network server configured by the cooperation of multiple information processing devices. The server 400 may also be a cloud server configured on cloud computing. Various types of memory are collectively referred to as storage devices.

[0015] The sensor 100, the display device 200, the communication terminal 300, and the server 400 are connected by a network 500. The network 500 is a communication network such as a local area network (LAN), a wide area network (WAN), a cellular network, a fixed telephone network, a regional internet protocol (IP) network, or the Internet. The network 500 may include a wired network or a wireless network. The network 500 may also include a core network. The core network is, for example, an evolved packet core (EPC) or a 5G core network (5GC). The network 500 may also include a data network other than the core network. The data network may be a service network of a telecommunications carrier, for example, an IP multimedia subsystem (IMS) network. The data network may also be a private network such as an in-house network. The sensor 100, the display device 200, the communication terminal 300, and the server 400 are connected to the network 500 using a radio access technology (RAT) such as LTE (Long Term Evolution), NR (New Radio), Wi-Fi, Bluetooth (registered trademark), or a wired access technology.

[0016] The insurance proposal system 1 senses the potential insurer using a sensor 100 installed in a first space, and displays a presentation image in a second space using a display device 200, the presentation image including an image based on the sensing results and prior information generated by a server 400. The insurance proposal system 1 allows the potential insurer to easily imagine future risks by viewing the presentation image based on the results of sensing the potential insurer and the prior information. Therefore, the insurance proposal system 1 can present the potential insurer with an image that makes it easy to imagine future risks.

[0017] Next, the insurance proposal space including the first space and the second space will be described.

[0018] <2. About the Insurance Proposal Space> FIG. 2 is a diagram showing an example of an insurance proposal space to which the insurance proposal system is applied. The insurance proposal space is composed of a first space, a second space, and a third space. The insurance proposal space is a space where a proposer proposes insurance to a prospective buyer, and may be, for example, an area within the premises of an insurance company. The proposer is someone who proposes insurance to a prospective buyer, and may be, for example, an employee, consultant, or planner of the insurance company.

[0019] The first space is a sensing space (sensing area) in which a sensor 100 is installed. In the first space, the sensor 100 senses the examiner and outputs the sensing result (output result) to the server 400. A motion sensor may be further installed in the first space, and when the motion sensor detects the presence of a person, the sensor 100 may perform sensing. This eliminates the need to constantly sense the first space with the sensor 100, thereby reducing power consumption. A projector or display may be installed in the first space, and an opening video that creates a space atmosphere for the examiner while sensing the examiner. This not only provides an extraordinary experience for the examiner, but also motivates the examiner to stop in the first space, thereby improving sensing accuracy. The opening video is, for example, a video that adds color to the space. The projector installed in the first space is connected to the server 400, and the server 400 may change the type of opening video based on advance information input by the examiner in advance. Furthermore, by changing the lighting in the first space or the brightness of the opening video, it may be possible to sense the appearance of the examinee when illuminated from various light amounts or angles.

[0020] The second space is a space for presentation (presentation area) where the display device 200 is installed. FIG. 3 is a diagram showing an example of the second space to which the insurance proposal system is applied. The second space is preferably connected to the first space via a door. The second space will be described in detail with reference to FIG. 3.

[0021] As shown in FIG. 3, the second space is provided with a desk 8, a chair 2 for the proposer, a chair 3 for the examiner, and a display device 200 on a floor 7. The display device (projector) 200 is preferably provided so that it can present a projection image on a wall 6, and a plurality of display devices are preferably provided so that the projection image can be projected onto at least two walls. Furthermore, it is preferable that at least one of the walls 6 onto which the projection image is projected includes a door 5 used to enter the second space. By superimposing the projection image on the door 5 through which the examiner enters, the examiner can feel as if the second space is an extraordinary space separated from ordinary spaces.

[0022] Returning to Figure 2, the third space will be described. The third space is a space where prospective buyers consider purchasing insurance. The third space is preferably connected to the second space via a door and not connected to the first space. Unlike the second space, the third space is preferably a space that does not create an extraordinary feeling using display devices or the like. It is also preferable that music that allows prospective buyers to relax is played. In an extraordinary space like the second space, prospective buyers may not be able to make sound decisions and may reverse their decisions after leaving the second space. Therefore, the second space presents prospective buyers with a presentation video to encourage them to imagine future risks, and the third space allows prospective buyers to consider purchasing insurance in a relaxed state, which is expected to have the effect of reducing the probability of cancellation after purchasing insurance.

[0023] The third space may be provided with a sensor 600. The sensor 600 is a sensor that senses the considerator and the proposer, and may be, for example, a camera, a ToF (Time Of Flight) sensor, a microphone, or the like. The sensor 600 may be two or more sensors, or may include different types of sensors. The sensor 600 may be connected to the server 400 via the network 500. The sensor 600 detects facial and body movements of the considerator and the proposer to detect the considerator's consideration status and the proposer's proposal level, etc. For example, the server 400 determines whether the considerator has settled into a relaxed state by detecting changes in the considerator's face after moving from the second space to the third space based on the sensing results (image) of the sensor 600. The server 400 then notifies the proposer's device that the considerator has changed to a relaxed state, and the proposer can prompt the considerer to confirm the proposal content based on the notification, thereby enabling the considerator to consider purchasing insurance in a relaxed state. Furthermore, the server 400 can analyze whether the proposer's proposal is a desirable proposal method by analyzing the video of the proposer and detecting features such as facial and body movement features and voice features when the proposer made the proposal. Machine learning can be used as a method for detecting the state of these reviewers and proposers. Machine learning is a machine learning method using, for example, a neural network, and inputs the sensing results of the sensor 600 into a generator in which parameters are set based on a parameter group generated by inputting learning data into a machine learning model, and performs feature extraction, classification, etc.

[0024] By using the above-described insurance proposal space to make an insurance proposal, future risks can be presented in a way that makes it easier for the examiner to imagine future risks. Next, the overall processing flow of the insurance proposal system will be described.

[0025] <3. Overall processing flow> 4 is a diagram showing the overall flow of the insurance proposal system. The insurance proposal system executes a flow including the following steps S101 to S103 by having the processor of the server 400 execute a program stored in the server 400.

[0026] In step S101, the server 400 acquires sensing results generated by the sensor 100 sensing the examiner. The sensing results are, for example, image data of the examiner. The image data may be a single image or a video consisting of multiple images. The sensing results are assigned to the examiner, associated with a examiner ID used to identify the examiner, and stored in the server 400 as examiner information. The proposer may select which examiner ID to link the sensing results to, or the examiner ID associated with the prior information acquired immediately before may be automatically selected.

[0027] In step S102, the server 400 generates an image video based on the sensing results and the prior information. The image video is generated in the following procedure. First, the server 400 reads the prior information associated with the input examiner ID and estimates a future risk based on the prior information. The future risk is estimated by selecting a future risk corresponding to the prior information acquired by the server 400 using a lookup table containing the prior information and the future risks. Note that the future risk may be estimated using a machine learning method that outputs a future risk based on the input prior information. The server 400 generates an image video based on the sensing results and the estimated future risk. For example, the server 400 generates a face model of the examiner from the sensing results, and performs a process of replacing the face model of an avatar included in a story video generated based on the future risk with the face model of the examiner, thereby generating an image video. Note that the future risk may be estimated based on the prior information and the sensing results.

[0028] The advance information is data input by the examiner in a space different from the first space, and is information including at least one of the family structure of the examiner, the annual income of the examiner, whether the examiner owns a home, the medical history of the examiner, and the health condition of the examiner. The advance information may also be data input by the examiner using the communication terminal 300 before the examiner enters the first space. The advance information is stored in the server 400 in association with the examiner ID.

[0029] Future risks are risks that may occur in the future, such as the possibility of a life event occurring or the possibility of an illness occurring. Life events include events such as the examiner's marriage, the birth of a child, a child's entry into school, and home purchase. The possibility of an illness occurring is the risk of developing cancer or a lifestyle-related disease. Because the occurrence of a life event can significantly change life planning, it is preferable to consider not only the possibility of an illness occurring as a future risk, but also the occurrence of a life event as a future risk.

[0030] The story video includes a video area that reflects the examiner's sensing results and changes according to the prior information. The video area that reflects the examiner's sensing results is, for example, an area that displays an avatar that includes an area that reflects the examiner's sensing results. It is preferable that the story video be set for each future risk set based on the prior information. For example, it is preferable that the story video changes the background and the avatars that appear based on the prior information, and that the story of the video changes based on the future risk. For example, if the prior information includes information indicating that the examiner has one child and owns a home, the story video is a video that shows how future financial risks occur over time, such as the child's tuition fees and home repairs. It is preferable that the story video is a video that shows how the examiner's life will change due to the future risk through changes in the avatar's appearance, changes in the background, and visual expressions.

[0031] In step S103, the server 400 generates a presented image including an image and candidate insurance plans. The candidate insurance plans are extracted from multiple insurance plans using at least one of the sensing results and the prior information. There may be one or more candidate insurance plans. The method for extracting candidate insurance plans is preferably based on a pre-stored lookup table. For example, the server 400 extracts the corresponding insurance plan in the lookup table as the optimal insurance plan for the examiner based on the family structure, annual income, and age of the examiner from the prior information. Then, a presented image is generated in which the image and candidate insurance plans are included in a single image.

[0032] Through the above processing, the server 400 can present the prospective buyer with a presentation image in the insurance proposal space that reflects the prospective buyer's sensing results and future risks, making it easier for the prospective buyer to imagine future risks.

[0033] <4. Presentation video> An example of the presented image will be described with reference to FIGS.

[0034] Fig. 5 is a diagram showing an example of an avatar in a presentation image generated by the insurance proposal system, and Fig. 6 is a diagram showing an example of a presentation image generated by the insurance proposal system.

[0035] The appearance of avatar 140 is set based on the examiner's sensing results, and the appearance changes depending on the examiner's set age. For example, as shown in FIG. 5, avatar 140a is an avatar with an appearance that is assumed to be 30 years old, avatar 140b is 50 years old, and avatar 140c is 70 years old. The face and body shape of avatar 140 are set based on the examiner's sensing results, and age adjustment is further performed on the appearance based on prior information and the set age. For example, in order to allow the examiner to imagine what the examiner will look like in 20 years, adjustment is made to avatar 140 set based on the sensing results so that the avatar becomes 20 years older than the examiner's age obtained from prior information.

[0036] The setting of the appearance of the avatar 140 based on the sensing results is, for example, performed by the server 400, by extracting facial information and physique information of the examinee from a captured image of the examinee, and setting the appearance of the avatar 140 based on the extracted facial information and physique information of the avatar 140. The setting of the appearance of the avatar 140 is a method of setting the avatar 140 from a captured image of the examinee using, for example, a machine learning model based on a neural network.

[0037] The face information is, for example, a feature amount of the examinee's face. The physique information is, for example, a feature amount of the examinee's physique. The physique feature amount may be a feature amount indicating a physique classification such as small, medium, or large.

[0038] As shown in Fig. 6, the presentation image is an image composed of an image image area including an avatar area where an avatar is displayed, and an insurance presentation area. The image image area is an area where an image image is displayed. The insurance presentation area is an area where insurance options are displayed.

[0039] The server 400 generates an image video including an avatar that reflects the examiner's sensing results and further changes the avatar in accordance with changes in the story video. For example, if the story video is a story video presenting how future risks arise as the avatar ages, the image video becomes an image in which the avatar's face is replaced with the examiner's face and presents how future risks arise as the avatar ages. In this case, it is preferable to age-adjust the avatar's face, such as by adding wrinkles according to the set age. In other words, the avatar reflecting the examiner's appearance changes as time passes in the video. This allows the examiner to visually see how future risks arise as the examiner ages in the avatar projected on it, making it easier to recognize future risks as events that could occur to them. In other words, because the presented video displays an image based on the examiner's sensing results and future risks, the examiner can easily imagine their own future risks. At the same time, potential insurance policies to prepare for future risks are presented, making it easier for the examiner to recognize insurance that should be considered for future risks.

[0040] <5. Variations> The results of sensing the examiner (customer) described in the above embodiment can be a valuable record for the examiner. For example, the sensing results obtained when confirming or reviewing insurance details in the insurance proposal space described in the above embodiment once a year can be recorded as a customer record, and provided to the examiner as an annual record, allowing the examiner's growth and thoughts at the time to be recorded.

[0041] Fig. 7 is a diagram showing an example of a customer record generated by an insurance proposal system. As shown in Fig. 7, the customer record is preferably the result of sensing not only the prospective customer but also the prospective customer's family together, or the result of capturing images taken by a recording camera. Furthermore, if the prospective customer's family, who have already signed an insurance contract, visit the insurance proposal space, entertainment video different from the insurance proposal may be presented in the insurance proposal space.

[0042] The customer record is linked to the considerer ID and recorded as an annual record in the server 400. This motivates the considerer to visit the proposer or the insurance proposal space at least once a year, allowing the proposer to make proposals that are more suited to the considerer's situation. At this time, a system may be added that links the considerer's contact information to each considerer ID, detects that a certain period of time has passed since the last recorded customer record, and sends a message to the proposer or the like to prompt the considerer's contact information to notify that a certain period of time has passed since the last recorded date.

[0043] Furthermore, the customer record is preferably 3D data (volumetric video) of the prospective buyer or their family members captured by multiple cameras using volumetric capture technology (volumetric imaging). Volumetric capture technology is a technology that generates 3D data that allows the subject to be displayed from any viewpoint by combining multiple captured images of the subject, each captured from a different angle. Furthermore, the customer record preferably also includes audio and video recordings of the prospective buyer's thoughts when they signed the insurance contract. This allows for a more detailed record of the prospective buyer's thoughts and memories at the time.

[0044] The following provides additional information about each technology.

[0045] Server 400 configuration FIG. 8 is a diagram illustrating an example of a configuration of a server in the insurance proposal system.

[0046] 8, the server 400 is configured by a computer. The server 400 may be configured by a plurality of computers. When the server 400 is configured by a plurality of computers, the various processes described above are realized by the cooperation of the respective computers.

[0047] A CPU (Central Processing Unit) 101, a ROM (Read Only Memory) 102, and a RAM (Random Access Memory) 103 are interconnected by a bus 104.

[0048] An input / output interface 105 is further connected to the bus 104. An input unit 106, an output unit 107, a storage unit 108, a communication unit 109, and a drive 110 are connected to the input / output interface 105.

[0049] The input unit 106 is composed of a keyboard, a mouse, etc. The output unit 107 is composed of a display, etc.

[0050] The storage unit 108 is configured by a hard disk, a nonvolatile memory, etc. The storage unit 108 stores various information such as programs executed by the CPU 101.

[0051] The communication unit 109 is an interface to the Internet.

[0052] The drive 110 controls writing of data to and reading of data from the removable medium 111 .

[0053] Machine learning models In the insurance proposal system, detection of the state of the examiner or proposer and generation of image video are preferably performed using a computational model generated by machine learning. The machine learning model is, for example, a machine learning model configured based on a neural network having multiple layers. The machine learning model based on a neural network is a model in which hyperparameters are set based on learning parameters generated by inputting multiple learning data into the learning model. The machine learning model classifies states and generates images according to the input data. An example of the machine learning model used for state classification is a convolutional neural network (CNN). An example of the machine learning model used for image generation is a CycleGAN or StyleGAN.

[0054] FIG. 9 is a diagram showing an example of a machine learning model of an insurance proposal system. As shown in FIG. 9, the machine learning model is configured based on a neural network having multiple layers. The machine learning model is a machine learning model that outputs an image video when video material (story material) and sensing results are input. In the machine learning model, hyperparameters are set based on learning parameters generated by learning pairs of video material, sensing results, and image video, for example.

[0055] About the program The above-described series of processes can be executed by hardware or software. When the series of processes is executed by software, the program constituting the software is installed in a computer incorporated in dedicated hardware or a general-purpose personal computer.

[0056] The program to be installed is provided by being recorded on removable media 111 such as an optical disk (CD-ROM (Compact Disc-Read Only Memory), DVD (Digital Versatile Disc), etc.) or semiconductor memory. Alternatively, the program may be provided via a wired or wireless transmission medium such as a local area network, the Internet, or digital broadcasting. The program can be installed in advance in ROM 102 or storage unit 108.

[0057] The program executed by the computer may be a program that processes in chronological order according to the order described in this specification, or may be a program that processes in parallel or at the required timing, such as when called.

[0058] In this specification, a system refers to a collection of multiple components (devices, modules (components), etc.), regardless of whether all the components are contained in the same housing. Therefore, multiple devices housed in separate housings and connected via a network, and a single device with multiple modules housed in a single housing, are both systems.

[0059] The effects described in this specification are merely examples and are not limiting, and other effects may also be present.

[0060] The embodiments of the present technology are not limited to the above-described embodiments, and various modifications are possible without departing from the spirit of the present technology.

[0061] For example, this technology can be configured as cloud computing, in which a single function is shared and processed collaboratively by multiple devices via a network.

[0062] Furthermore, each step described in the above flowchart can be executed by one device, or can be shared and executed by multiple devices.

[0063] Furthermore, when one step includes multiple processes, the multiple processes included in that one step can be executed by one device or can be shared and executed by multiple devices.

[0064] Configuration combination examples The present technology can also be configured as follows. (1) a sensor that senses the examinee in the first space; a display device that displays, in a second space, to the examiner, an image video including a future risk and a presentation video including insurance options extracted based on the future risk; an information processing device that generates the image video; Equipped with the information processing device has one or more processors and one or more storage devices storing programs; The processor executes the program, reading out advance information input by the examiner in a space different from the first space and an examiner ID assigned to the examiner; The output result of the sensor is written as examiner information linked to the examiner ID, estimating the future risk based on the prior information; generating the image video based on the future risk and the examiner information; Insurance proposal system. (2) The insurance proposal system according to (1), The processor executes the program, Estimating the future risk based on the prior information and the examiner information; generating the image video based on the future risk and the examiner information; Insurance proposal system. (3) The insurance proposal system according to (1), The processor executes the program to generate the image in which the examiner information is reflected in the image set based on the future risk. Insurance proposal system. (4) (3) The insurance proposal system according to the present invention, The processor executes the program to generate the image video in which the appearance of the examinee is reflected in the video set based on the future risk. Insurance proposal system. (5) (4) The insurance proposal system according to the present invention, the sensor is a camera; The processor executes the program to read a captured image including the appearance of the examinee generated by the camera, input the captured image into a predetermined machine learning model, and generate the image video including an avatar reflecting the appearance of the examinee. Insurance proposal system. (6) (5) The insurance proposal system according to the present invention, The processor executes the program to generate the image video in which the appearance of the avatar based on the appearance of the examinee changes according to time changes in the video. Insurance proposal system. (7) (3) The insurance proposal system according to the present invention, the processor executes the program to generate the image video including an avatar whose face is set based on facial features of the examinee extracted from the captured image of the examinee. Insurance proposal system. (8) The insurance proposal system according to (1), The prior information includes at least the family structure of the examiner, the annual income of the examiner, whether the examiner owns a home, and the medical history of the examiner. Insurance proposal system. (9) (8) The insurance proposal system according to the present invention, the processor executes the program to change the visual expression included in the image video based on the prior information; Insurance proposal system. (10) The insurance proposal system according to (1), The second space is a space that can be entered via the first space and is equipped with a projector that projects the presented image onto at least two walls. Insurance proposal system. (11) The insurance proposal system according to (1), The processor executes the program to present the reviewer with a customer record based on the reviewer information. Insurance proposal system. (12) The insurance proposal system according to (1), the sensor is a plurality of cameras capable of volumetrically imaging the examinee, The processor executes the program to generate a volumetric image based on the images captured by the plurality of cameras as the examiner information, and presents the volumetric image to the examiner as a customer record. Insurance proposal system. (13) An information processing method for insurance proposals, comprising: A sensor for sensing a person in a first space, a display device for displaying a presented image including an image video including a future risk and an insurance candidate extracted based on the future risk to the person in a second space, and an information processing device for generating the image video are used. reading out advance information input by the examiner in a space different from the first space and an examiner ID assigned to the examiner; The output result of the sensor is written as examiner information linked to the examiner ID, and the future risk is estimated based on the prior information. generating the image video based on the future risk and the examiner information; Information processing method for insurance proposals. [Explanation of symbols]

[0065] 1. Insurance proposal system 100 sensors 200 Display device 300 Communication terminal 400 servers

Claims

1. a sensor that senses the examinee in the first space; a display device that displays, in a second space, to the examiner, an image video including a future risk and a presentation video including insurance options extracted based on the future risk; an information processing device that generates the image video; Equipped with the information processing device has one or more processors and one or more storage devices storing programs; The processor executes the program, reading out advance information input by the examiner in a space different from the first space and an examiner ID assigned to the examiner; The output result of the sensor is written as examiner information in association with the examiner ID; estimating the future risk based on the prior information; generating the image video based on the future risk and the examiner information; An insurance proposal system, The prior information includes at least information on the examiner's family structure, the examiner's annual income, whether the examiner owns a home, and the examiner's medical history, The image video including the future risk includes at least an image corresponding to a life event or a disease that is estimated to occur in the future to the examiner, The processor: based on the prior information, refer to a lookup table stored in advance to estimate the future risks that may occur to the examinee, and generate the image video based on a story video set in advance for each of the future risks; Or, The prior information is input into a trained model to estimate the future risks that may occur to the examinee, and the image video is generated based on a story video set in advance for each of the future risks. Insurance proposal system.

2. The processor, by executing the program, generates the image video in which the examiner information is reflected in the video set based on the future risk. The insurance proposal system according to claim 1 .

3. The processor, by executing the program, generates the image video in which the appearance of the examinee is reflected in the video set based on the future risk. The insurance proposal system according to claim 2 .

4. The sensor is a camera, The processor executes the program to read a captured image including the appearance of the examinee generated by the camera, input the captured image into a predetermined machine learning model, and generate the image video including an avatar reflecting the appearance of the examinee. The insurance proposal system according to claim 3 .

5. The processor executes the program to generate the image video in which the appearance of the avatar based on the examinee's appearance changes according to time changes in the video. The insurance proposal system according to claim 4.

6. The processor, by executing the program, generates the image video including an avatar whose face is set based on facial features of the examinee extracted from the captured image of the examinee. The insurance proposal system according to claim 2 .

7. The processor executes the program to change the visual expression included in the image video based on the prior information. The insurance proposal system according to claim 1 .

8. The second space is a space that can be entered through the first space and is equipped with a projector that projects the presented image onto at least two walls. The insurance proposal system according to claim 1 .

9. The processor, by executing the program, presents the reviewer with a customer record based on the reviewer information. The insurance proposal system according to claim 1 .

10. The sensor is a plurality of cameras capable of volumetrically imaging the examinee, The processor executes the program to generate a volumetric image based on the images captured by the plurality of cameras as the examiner information, and presents the volumetric image to the examiner as a customer record. The insurance proposal system according to claim 1 .

11. An information processing method for insurance proposals, comprising: A sensor for sensing a person in a first space, a display device for displaying a presented image including an image video including a future risk and an insurance candidate extracted based on the future risk to the person in a second space, and an information processing device for generating the image video are used. reading out advance information input by the examiner in a space different from the first space and an examiner ID assigned to the examiner; The output result of the sensor is written as examiner information in association with the examiner ID; estimating the future risk based on the prior information; generating the image video based on the future risk and the examiner information; An information processing method for insurance proposals, comprising: The prior information includes at least information on the examiner's family structure, the examiner's annual income, whether the examiner owns a home, and the examiner's medical history, The image video including the future risk includes at least an image corresponding to a life event or a disease that is estimated to occur in the future to the examiner, The information processing device includes: based on the prior information, refer to a lookup table stored in advance to estimate the future risks that may occur to the examinee, and generate the image video based on a story video set in advance for each of the future risks; Or, The prior information is input into a trained model to estimate the future risks that may occur to the examinee, and the image video is generated based on a story video set in advance for each of the future risks. Information processing method for insurance proposals.

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