KR20230105668A - Apparatus and method for providing the guaranteeability of insurance - Google Patents

Abstract

The purpose of the present invention is to provide insurance products that provide optimal guarantees compared to machine contract guarantee information through machine learning by imaging them with differences in color and brightness so that policyholders can quickly and accurately identify the insurance products they need. It relates to an apparatus and method for providing guaranteed fitness. To this end, the present invention can build a model integration process by extracting machine contract guarantee details for each channel through an insurance company dataset, and perform machine learning learning for comparative analysis through the model integration process.

Description

Apparatus and method for providing insurance guarantee suitability {APPARATUS AND METHOD FOR PROVIDING THE GUARANTEEABILITY OF INSURANCE}

The present invention relates to an apparatus and method for providing guarantee conformity in insurance.

Insurance is a system in which people pay for financial protection from unforeseen circumstances and their potential consequences. In other words, insurance refers to an economic system in which a number of economic entities cooperate to procure and pay a reasonably calculated amount in order to relieve the economic damage or burden caused by a certain risk or accident that occurs accidentally.

To this end, an individual or company enters into an insurance contract with an insurance company to manage risks and protect against unexpected financial loss, and pays for the premium. In return for the premium paid by the policyholder, the insurer agrees to pay some or all of the unforeseen expenses that may arise in the circumstances covered by the insurance contract.

However, policyholders who have purchased insurance are not familiar with the specific coverage items or conditions of the insurance they subscribe to, so they cannot receive insurance money even after spending money on treatment for a disease corresponding to the payment item, or fail to meet the coverage conditions. There are frequent cases in which insurance claims are denied, such as not receiving actual treatment expenses due to misunderstanding.

In addition, the policyholder has difficulties in directly understanding the insurance guarantee management, asset management, and risk management even though he or she has already subscribed to an insurance product.

Insurance policyholders need a technology to analyze and compare insurance policies subscribed to with personal information consent to identify guarantee information, but there is no technical solution related to this. In addition, an individual or company looking for an insurance product needs a customized solution that can provide an optimal guarantee against a rate by analyzing and comparing guarantees of machine medicine product information.

Republic of Korea Patent Registration No. 10-2187740 (2020.01.16)

It is an object of the present invention to provide an apparatus and method for providing insurance suitability in insurance so that policyholders can quickly and accurately and intuitively grasp the insurance products they need.

In one aspect of the present disclosure, a user's insurance subscription information is collected through a dataset of a plurality of insurance company servers, machine contract insurance is identified based on the collected insurance subscription information, and machine contract coverage details corresponding thereto are provided in insurance terms and conditions A model storage unit configured to store a machine learning model extracted for each channel from and compared and analyzed through a model integration process; a data storage unit for updating and storing machine contract guarantee details from insurance terms and insurance information when subscription information is received from the new insurance company server; a processor for controlling to update another model to the machine learning model when it is determined that at least one new data of new insurance information or insurance terms and conditions is determined based on machine contract guarantee details based on the machine learning model; and an interface for comparing and analyzing guarantee details based on the machine learning model in conjunction with the processor and providing the same to a user.

For example, an external management module is further included to convert machine contract guarantee details from the plurality of insurance company data sets into unstructured data based on the subscription information, and the data storage unit stores insurance subscription information of the user based on the user information. When is collected, information is received from the user or insurance company, a neural network model is trained according to the information, and the acquired learning information is divided into stratified channels according to a predetermined guarantee diagnosis and performed.

For example, the user's insurance subscription information collection data of the data storage unit further includes a local unit receiving information learned from a neural network model according to a predetermined criterion in the external management module, and the information generated by the local unit is received. The learning information is characterized in that it is not directly reflected in the update of the neural network model.

For example, the machine promise guarantee details collected from the data storage unit for comparative analysis are divided into numerical data and categorical data to solve data imbalance, and the numerical data and the categorical data A pre-processing unit for scaling the pre-processing unit, wherein the pre-processing unit performs data analysis to detect whether distributions of the numerical data and the categorical data are imbalanced, and the numerical data and the categorical data are analyzed based on a sampling technique. The sample of the type data further includes a learning unit that controls the sample by extracting it for each channel.

For example, the model integrating process of the model storage unit extracts the machine contract insurance subscriber data preprocessed based on the machine contract insurance subscription information from the preprocessor, and applies the characteristics of the insurance subscriber to the insurance subscription information. a dimension reduction unit that compares and analyzes the characteristics of; a clustering unit that clusters groups of similar insurance subscribers based on the output result of the dimension reduction unit; a pattern detection unit for detecting a pattern of insurance subscribers based on the group of similar insurance subscribers clustered in the clustering unit; and a pattern result unit representing the result of the pattern detection unit in terms of color or saturation.

For example, the local unit may indicate results obtained through classification and prediction algorithms, and the classification and prediction algorithm local model results may be transmitted to the data storage unit in the form of local model weight parameters.

For example, the interface is characterized in providing a learning-based service capable of communicating with the processor.

In another aspect of the present disclosure, in the method of providing insurance coverage,

Analyzing insurance subscription patterns from user information based on machine learning models; an insurance subscription information extraction step of extracting insurance subscription information through a subscription pattern analysis of the user information; A pattern analysis step of setting standards according to the results of extracting insurance subscription information and setting a standard guaranteed amount; and after going through a process of superiority/inferiority determination from the pattern analysis step, based on the clustered group of similar insurance subscribers, the difference rate A gap rate range setting step of setting a range; and an image information generating step of imaging the result of the disparity rate range setting step.

For example, the image information generating step may include a superiority and inferiority chroma matching process; It is characterized in that it further includes; an output process of visualizing a result value of the superiority and inferiority saturation matching.

For example, the result value of the outputting process may be visualized based on saturation and color to provide the optimal guarantee compared to the machine guarantee guarantee diagnosis.

The various examples of the present disclosure described above are only some of the preferred examples of the present disclosure, and various examples in which the technical features of the various examples of the present disclosure are reflected are detailed descriptions to be detailed below by those of ordinary skill in the art. It can be derived and understood based on.

According to the present invention, there are the following effects.

The apparatus for providing guaranteed conformity according to the present invention provides a product that provides an optimal guarantee compared to machine-weak guarantee information through machine learning as an image with a difference in color and brightness. Accordingly, the apparatus for providing the degree of conformity of protection can enable the policyholder to quickly and accurately and intuitively grasp the insurance product he or she needs.

Effects obtainable from various examples of the present disclosure are not limited to the effects mentioned above, and other effects not mentioned are clearly derived to those skilled in the art based on the detailed description below and can be understood.

1 is a conceptual schematic diagram for explaining an apparatus for providing insurance suitability and a method for providing insurance suitability information according to the present invention;
FIG. 2 is a block diagram showing an example of an apparatus for providing guaranteed conformity of FIG. 1;
3 is a block diagram for explaining a storage unit in a system for providing a guaranteed fitness level of insurance in an apparatus and method for providing a guaranteed fitness level of insurance according to an embodiment;
4 is a structural diagram of a model storage system existing in a storage unit in an insurance guarantee conformance providing device according to an embodiment.
5 is a block diagram illustrating a system according to an embodiment performed in a data storage unit in an insurance guarantee conformance providing device;
6 is a flow chart showing the overall flow of the apparatus and method for providing insurance coverage conformity according to the present invention.
FIG. 7 is a flow chart showing in detail the flow of image information generation in the method for providing insurance coverage conformity illustrated in FIG. 6;
8 is a schematic view of the result of performing the sixth and seventh steps showing a method of extracting the details of insurance coverage as an image using a standard gap ratio in the method for providing the suitability of insurance coverage according to the present invention.
9 is an actual result value displayed on a screen of a user terminal of guarantee details according to a machine contract through an apparatus and method for providing insurance guarantee suitability according to the present invention.

Hereinafter, embodiments of the present invention will be described clearly and in detail to the extent that those skilled in the art can easily practice the present invention.

1 is a block diagram showing a system for providing insurance guarantee conformity according to an embodiment of the present invention.

Referring to FIG. 1 , a system for providing a guaranteed fitness level of insurance according to an example of the present invention includes an insurance guarantee fitness level providing apparatus 10 and a user terminal 15 .

The insurance suitability providing apparatus 10 according to the present invention may provide insurance suitability information and an optimal guarantee detail recommendation service to the user terminal 15 . Accordingly, the guarantee suitability providing device 10 allows the policyholder to quickly and accurately and intuitively grasp the insurance product he or she needs.

The guaranteed fitness providing system 1 is a system for providing insurance fitness service from the insurance guaranteed fitness providing device 10 to the user terminal 15, and is connected to the user terminal 15 through a communication network to provide the guaranteed fitness service. receive data for

The user terminal 15 is not limited to a device that receives an image from the guaranteed conformance providing device 10 and may include both a server and a device.

The user terminal 15 is configured to correspond to a terminal possessed by a customer, that is, an insurance subscriber. The user terminal 15 has applications installed through a communication network. The user terminal 15 may exchange various data and receive a guaranteed suitable service. Although the description of the user terminal 15 is limited to applications, it may further include miniaturized devices, that is, portable electronic devices capable of communication.

The guaranteed fitness providing device 10 and the user terminal 15 communicate through wireless communication.

In addition, wireless communication includes a WiFi module and a wireless broadband module, as well as global system for mobile communication (GSM), code division multiple access (CDMA), wideband code division multiple access (WCDMA), and universal mobile telecommunications (UMTS). system), time division multiple access (TDMA), and long term evolution (LTE).

With this configuration, the image and information received from the guaranteed fitness providing device 10 can be safely received by the user terminal 15 .

In addition, the guaranteed fitness providing apparatus 10 according to an embodiment of the present invention may further include a fitness detection device for deriving a guaranteed fitness result of insurance, in addition to the above-described configuration.

As described above, the insurance suitability providing apparatus 10 according to the present invention may provide insurance suitability information and optimal guarantee details recommendation service to the user terminal 15 . Accordingly, the correction suitability providing system 1 allows the policyholder to quickly and accurately and intuitively grasp the insurance product he or she needs.

FIG. 2 is a block diagram showing an example of an apparatus for providing guaranteed conformity of FIG. 1 .

Referring to FIG. 2 , the guaranteed fitness level providing device 10 of the insurance guaranteed fitness level providing system 1 according to the present invention includes an input unit 101, a communication unit 102, a storage unit 103, and an external management module. 100, a control unit 104, and an output unit 105, and the apparatus 10 for providing guaranteed conformity is configured to correspond to each part of the insurance company server 700.

The apparatus 10 for providing insurance guarantee conformity is configured to electrically connect and correspond to a plurality of insurance company servers 700 and/or a plurality of insurance company servers 700 managed by each user terminal 15 .

The external management module 100 may convert machine contract guarantee details from data sets of the plurality of insurance company servers 700 into unstructured data based on the subscription information, and may be configured to correspond thereto.

The external management module 100 may be configured to share or manage information related to machine learning models between geographically distributed systems and/or model aggregation processes.

In addition, it is clarified that the division of each constituent part is only a division by the main function in charge of each constituent part.

As described above, the external management module 100 configures the device unit of the guaranteed fitness providing device 10, but is not limited thereto, and may also be configured as a component of the control unit 104.

The insurance company server 700 is a computing device commonly used by insurance companies, and when it receives a request from users through a network, it can provide a web service in response to the request. Specifically, the insurance company server 700 may provide users with terms and conditions of all types of insurance products operated as web pages or other unconvertible files.

As described above, the guaranteed fitness providing apparatus 10 according to an embodiment of the present invention may be refined and output through the output unit 105 through several steps from the input unit 101 .

The above input unit 101, the communication unit 102, the storage unit 103, the control unit 104, the external management module 100, and the output unit 105 according to the present invention including the insurance coverage suitability In the provision system 1 , all or at least some of the components of the guaranteed conformity providing apparatus 10 may be implemented in the form of hardware modules, software modules, or a combination of hardware modules and software modules.

Here, the software module may be understood as, for example, a command executed by a processor for controlling an operation within the guaranteed fitness providing device 10, and such a command may be loaded into a memory within the guaranteed fitness providing device 10. can have

In addition, it is clarified that the division of each constituent part is only a division by the main function in charge of each constituent part.

Two or more components to be described below may be combined into one component, or one component may be divided into two or more for each more subdivided function.

This will be described later in more detail with reference to FIGS. 4 and 5 .

3 is a block diagram for explaining a storage unit in an apparatus for providing a guaranteed fitness level of insurance in an apparatus and method for providing a guaranteed fitness level of insurance according to an embodiment.

Referring to FIG. 3 , the storage unit 103 of the apparatus 10 for providing guaranteed conformity of insurance according to the present invention includes a local unit 200, a data storage unit 50, a model storage unit 20, and a learning unit 200. It includes a unit 30, a pre-processing unit 40, a processor 400, and an interface 300, and the storage unit 103 receives information from the external management module 100 and analyzes new data. It can be implemented in the form of transmitting / receiving with the client 500 capable of extracting and refining.

The client 500 may be connected to a machine learning service such as a convolutional neural network or a recursive neural network through the interface 300 .

The client 500 may install software or access the service through an Internet browser.

The configuration including the data storage unit 50, the model storage unit 20, the learning unit 30, and the pre-processing unit 40 of FIG. 3 shows the relationship between the local unit 200 and the processor 400. It is only urbanized for easy explanation.

The external management module 100 may convert the guarantee details of the contract from the data sets of the plurality of insurance company servers 700 into unstructured data based on the subscription information, and may be configured to correspond thereto.

The model storage unit 20 collects insurance subscription information of a user through a dataset of a plurality of insurance company servers 700, identifies machine contract insurance based on the collected insurance subscription information, and provides machine contract guarantee details corresponding thereto It can be implemented in the form of configuring to store a machine learning model that extracts by channel from insurance terms and compares and analyzes it through a model integration process.

When subscription information is received from the new insurance company server 700, the data storage unit 50 updates and stores machine contract guarantee details from insurance terms and conditions and insurance information.

In addition, when the user's insurance subscription information is collected based on the user information, the data storage unit 50 receives information from the user or/or the insurance company server 700 and uses the information received from the insurance company server 700 to form a neural network. The model is trained, and the acquired learning information is divided into layered channels according to a predetermined assurance diagnosis.

The processor 400 may update another model to the machine learning model when it is determined that at least one new data of new insurance information or insurance terms and conditions is based on the machine contract guarantee details based on the machine learning model.

The data storage unit 50 , the model storage unit 20 , the learning unit 30 , and the pre-processing unit 40 may configure the storage unit 103 .

The storage unit 103 further includes an interface 300 that compares and analyzes guarantee details based on the processor 400 and the machine learning model and provides them.

The interface 300 may be connected to the processor 400 and may store various information related to the operation of the processor 400 . For example, the interface 300 functions to perform or extract some or all of the processes controlled by the processor 400, and instructions for performing the descriptions, suggestions, methods, and/or flowcharts of the present disclosure. It may store and/or execute software codes including them.

The processor 400 controls all or part of the interface 300 and the storage unit 103, and executes instructions stored in the interface 300 to obtain descriptions, functions, procedures, suggestions, methods, and/or operational flowcharts of the present disclosure. can be configured to implement For example, the processor 400 may receive a signal through the interface 300 and store information included in the signal in the storage unit 103 . Also, the processor 130 may provide a service based on instructions stored in the storage unit 103 . In addition, the processor 400 may process information stored in the storage unit 103 to generate a signal, and transmit the generated radio signal.

In other words, the interface 300 provides a learning-based service capable of communicating with the processor 130 .

The model storage unit 20 and the data storage unit 10 recently use a neural network to obtain highly accurate judgment results through image processing.

A neural network is a network structure having a structure similar to that of a human neural network, and is also referred to as a deep neural network.

The neural network may include Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Deep Belief Networks, Restricted Boltzman Machines, Generative Adversarial Network (GAN), and Recurrent Deep Learning Network, but is not limited to the above example.

Collected data obtained by collecting user's insurance subscription information into the data storage unit 50 is unidirectionally transmitted by the local unit 200 .

The local unit 200 receives information learned from the neural network model according to criteria predetermined in the external management module 100 .

In other words, information received by the local unit 200 is information learned through a classification and prediction algorithm, and the received local model result is transmitted to the data storage unit 50 .

That is, the information learned by the local unit 200 is transmitted to the data storage unit 50 through the local model weight parameter, but information that is not directly reflected in the update of the neural network model may be transmitted in a method, but is not limited thereto.

The pre-processing unit 40 divides the contract guarantee details collected for comparative analysis from the data storage unit 50 into numerical data and categorical data to resolve data imbalance, and the numerical data and/or the category Type data can be scaled.

The learning unit 30 performs data analysis to detect whether or not the distribution of numerical data and/or categorical data is imbalanced from the preprocessing unit 40, and samples of the numerical data and categorical data are obtained based on a sampling technique. It is possible to provide a feature of controlling a sample by extracting for each channel.

The sampling technique is unsupervised learning, which is a technique of learning a statistical structure of a model input pattern, that is, a technique of learning to classify a specific input pattern. Unlike Supervised Learning and Reinforcement Learning, it does not receive a reward for the predicted value or the correct answer to the problem as input. Therefore, unsupervised learning is used to find structural characteristics of inputs or relationships between different inputs rather than finding answers to inputs.

This will be described later in more detail with reference to FIGS. 4 and 5 .

4 is a structural diagram of a model storage system existing in a data storage unit in an insurance guarantee conformity providing apparatus according to an embodiment, and FIG. It is a block diagram illustrating the device.

Referring to FIG. 4, the model storage unit 20 constituting the storage unit 103 in the apparatus 10 for providing insurance guarantee conformity according to the present invention is a data input unit 201 and a data preprocessing unit 40' and dimensions It includes a reduction unit 203, a clustering unit 204, a pattern device unit 205, and a pattern result unit 206.

In the model storage unit 20 of the storage unit 103, a model integration process is performed. When the machine contracted insurance subscriber's data is extracted from the pre-processing unit 40', it moves to the dimension reduction unit 203 that compares and analyzes the insurance subscriber's information according to characteristics.

Based on the output result of the dimension reduction unit 203, a clustering unit 204 is performed to classify and group groups of similar insurance subscribers. A pattern detection unit 205 that detects patterns of insurance subscribers based on groups of similar insurance subscribers clustered in the clustering unit 204 and a pattern result unit 206 that displays the results of the pattern detection unit 205 in color and/or saturation. ) may be included.

The clustering unit 204 is a process of finding similarities between each input value and grouping the input values into groups based on the similarities. Representative features of the clustering unit 204 include k-nearest neighbors (k-NN) and neural networks Network), SVM (Support Vector Machine), etc., which are intended to explain an example, but are not limited thereto.

The data pre-processing unit 40' constituting the model storage unit 20 and the pre-processing unit 40 constituting the storage unit 103 will be understood as a detailed description by way of an example of the same function in which the technical features of the present disclosure are reflected. can

Referring to FIG. 5, when the local model weight parameters transmitted from the local unit 200 are transmitted to the data storage unit 50, the data storage unit 50 performs a weight parameter aggregation algorithm 501 and initial global data generation 502. ), implemented by the global data update/validation/evaluation 504 via the validation dataset 503.

The weight parameter data transmitted from the local unit 200 is stored inside the data storage unit 50 so that the initial global data generation 502, verification data set 503, and global data update/verification/evaluation 504 can be used by itself. and can be configured by adding a detection device.

6 is a flow chart showing the entire flow of the method for providing insurance coverage conformity according to the present invention.

FIG. 7 is a flow chart showing in detail the flow of generating image information in the method for providing guaranteed conformity of insurance illustrated in FIG. 6 .

Referring to FIG. 6 , the overall flow of the method for providing insurance coverage conformity according to the present invention may include eight steps.

Such a method for providing guaranteed fitness for insurance includes an input unit 101, a communication unit 102, a storage unit 103, a control unit 104, and an output unit 105. It is implemented by the system 1 for providing guaranteed conformity of insurance including the user terminal 15 .

In step S110, the method for providing insurance coverage suitability analyzes a subscription pattern of an already subscribed insurance based on big data.

In step S120 , the method for providing insurance coverage fitness extracts insurance subscription information.

In step S130, the method of providing insurance coverage suitability determines the amount and coverage of general insurance or/or special contract insurance.

In step S140, the method for providing insurance coverage suitability analyzes the guarantee diagnosis to set a guarantee amount and criteria according to the subscription pattern.

In step S150, a method for providing insurance coverage suitability is prioritized through a pattern analysis result.

In step S160, the method of providing insurance coverage suitability divides groups according to insurance companies and sets a range of disparity rates based on the groups.

In step S170, the method for providing insurance coverage suitability assigns color and saturation appropriately to the range and difference of the gap ratio.

In step S180, the method for providing insurance coverage fitness outputs the result value.

A method for providing insurance coverage according to the present invention will be described later in detail.

The insurance subscription pattern analysis step (S110) of analyzing the insurance subscription pattern from user information based on a machine learning model in the insurance coverage suitability providing method can compare and explain by dividing special contract insurance and general insurance. can be divided into unstructured data collection unit, unstructured data verification unit, block data collection unit, and block chain recording unit for analysis.

It may be performed by a disparity rate range setting step of setting a disparity rate range based on clustered groups of similar insurance subscribers and an image information generating step of imaging the result of the disparity rate range setting step.

In addition, the step of generating image information may further include a superiority and inferiority chroma matching process and an output process of visualizing and outputting a result value of the matching process.

As a result of the result of the output process in the method of providing insurance coverage conformity, a contract capable of providing the optimal guarantee can be visualized in comparison to the machine contract guarantee diagnosis based on chroma and color.

8 is a schematic diagram of the result of performing the sixth and seventh steps showing a method of extracting an image from insurance coverage details using a standard gap ratio in the method for providing coverage conformity according to the present invention, and FIG. Through the apparatus and method for providing insurance guarantee suitability according to the invention, details of guarantee according to the machine contract are actual result values displayed on the screen of the user terminal.

According to the present invention, even if you do not directly visit an insurance company, you can be introduced to an insurance product that provides optimal coverage based on product data obtained through integrated subscription design and contract analysis.

According to the present invention, there is an effect that guarantee comparison can be grasped at a glance even if the content of the guarantee is not properly understood.

According to the present invention, there is an effect of comparing and analyzing insurance recommendation products compared to mechanical drugs.

In the above, various preferred embodiments of the present invention have been described with some examples, but the description of various embodiments described in the "Specific Contents for Carrying Out the Invention" section is only exemplary, and the present invention Those skilled in the art will understand from the above description that the present invention can be practiced with various modifications or equivalent implementations of the present invention can be performed.

In addition, since the present invention can be implemented in various other forms, the present invention is not limited by the above description, and the above description is intended to complete the disclosure of the present invention and is common in the technical field to which the present invention belongs. It is only provided to completely inform those skilled in the art of the scope of the present invention, and it should be noted that the present invention is only defined by each claim of the claims.

Terms used in this application are only used to describe specific embodiments, and are not intended to limit the present invention. In this application, the terms "include" or "have" are intended to designate that there is a feature, number, step, operation, component, part, or combination thereof described in the specification, but one or more other features It should be understood that it does not preclude the presence or addition of numbers, steps, operations, components, parts, or combinations thereof.

1: System for providing insurance coverage conformity
10: Device for providing insurance coverage
15: user terminal
101: input unit
102: communication department
103: storage unit
104: control unit
105: output unit
100: external management module
300: interface
400: processor
500: client
700: Insurance company server
501: weight parameter aggregation algorithm
502: Create initial global data
503: Validation dataset
504: Global data update/verification/evaluation
200: local part
20: model storage unit
201: data input unit
40': data pre-processing unit
203: dimension reduction unit
204: clustering department
205: pattern device
206: pattern result unit
30: learning unit
40: pre-processing unit
50: data storage unit

Claims (10)

Collect insurance subscription information of users through datasets from multiple insurance company servers, identify machine contract insurance based on the collected insurance subscription information, extract corresponding machine contract guarantee details from insurance terms by channel, and integrate the model a model storage unit configured to store a machine learning model to be compared and analyzed through a process;
a data storage unit for updating and storing machine contract guarantee details from insurance terms and insurance information when subscription information is received from the new insurance company server;
a processor for controlling to update another model to the machine learning model when it is determined that at least one new data of new insurance information or insurance terms and conditions is determined based on machine contract guarantee details based on the machine learning model; and
An interface that interworks with the processor to compare and analyze guarantee details based on the machine learning model and provides them to the user,
A device that provides insurance coverage.
According to claim 1,
An external management module is further included so that machine contract guarantee details from the plurality of insurance company datasets are converted into unstructured data based on the subscription information and corresponded to,
The data storage unit,
When the user's insurance subscription information is collected based on the user information, information is received from the user or the insurance company, a neural network model is trained according to the information from the insurance company, and the acquired learning information is layered according to a predetermined coverage diagnosis. divided into channels,
A device that provides insurance coverage.
According to claim 2,
The user's insurance subscription information collection data of the data storage unit,
Further comprising a local unit for receiving information learned by the neural network model according to a predetermined criterion in the external management module;
The learning information generated in the local unit,
Characterized in that it is not directly reflected in the update of the neural network model,
A device that provides insurance coverage.
According to claim 2,
The machine contract guarantee details collected for comparative analysis from the data storage unit,
A pre-processor configured to resolve data imbalance by classifying category sizes into numerical data and categorical data and to scale the numerical data and the categorical data;
The pre-processing unit performs data analysis to detect imbalance in the distribution of the numerical data and the categorical data, and samples of the numerical data and the categorical data are extracted for each channel based on a sampling technique to obtain samples. Learning unit to control; further comprising,
A device that provides insurance coverage.
According to claim 1,
The model integration process of the model storage unit,
a dimension reduction unit extracting the machine contract insurance subscriber data preprocessed based on the machine contract insurance subscription information from the preprocessing unit and comparing and analyzing characteristics of the insurance subscription information by applying the insurance subscriber characteristics;
a clustering unit that clusters groups of similar insurance subscribers based on the output result of the dimension reduction unit;
a pattern detection unit for detecting a pattern of insurance subscribers based on the group of similar insurance subscribers clustered in the clustering unit; and
A pattern result unit representing the result of the pattern detection unit in color or saturation; further comprising
A device that provides insurance coverage.
According to claim 3,
The local part represents a result through a classification and prediction algorithm,
Characterized in that the classification and prediction algorithm local model result is transmitted to the data storage unit as a local model weight parameter state.
A device that provides insurance coverage.
According to claim 1,
The interface is
Characterized in that it provides a learning-based service capable of communicating with the processor,
A device that provides insurance coverage.

In the method of providing insurance coverage,
Analyzing insurance subscription patterns from user information based on machine learning models;
an insurance subscription information extraction step of extracting insurance subscription information by analyzing a subscription pattern of the user information;
a pattern analysis step of setting a criterion according to a result of extracting the insurance subscription information and setting a criterion guaranteed amount;
a disparity rate range setting step of setting a disparity rate range based on a clustered similar insurance subscriber group after going through a superior/inferior judgment process from the pattern analysis step; and
Image information generation step of imaging the result of the disparity rate range setting step; comprising
How Insurance Provides Coverage Fit
According to claim 7
The image information generating step,
Dominance and inferiority saturation matching process;
Further comprising an output process of visualizing the result of the superiority and inferiority saturation matching
How insurance provides coverage fit.
According to claim 9,
Characterized in that the result value of the output process is visualized to provide the optimal guarantee compared to the guarantee guarantee diagnosis based on saturation and color,
How insurance provides coverage fit.

Images