JP4014401B2 - Risk diagnosis system, risk diagnosis method and risk diagnosis program - Google Patents

Description

[0001]
BACKGROUND OF THE INVENTION
The present invention relates to a system in which a user can diagnose his / her risk by inputting his / her schedule.
[0002]
[Prior art]
Conventionally, an insurance system that introduces risk diagnosis and optimal insurance based on risk diagnosis is known. In this system, users simply diagnosed a user's risk and introduced the optimal insurance by simply accessing the insurance system via the Internet and answering a questionnaire presented by the insurance system.
[0003]
[Problems to be solved by the invention]
However, since there are not a few users who dislike the questionnaire format, it cannot be said that the conventional insurance system has become widespread. In addition, in the method of inputting necessary answers to the questionnaire, it is necessary to input answers to a large number of items in order to realize more appropriate risk diagnosis and introduction of insurance, and input work takes time and effort.
An object of this invention is to provide the system which can implement | achieve an appropriate risk diagnosis, referring to the schedule input when the user desired, reducing the number of items of a questionnaire.
[0004]
[Means for Solving the Problems]
An object of the present invention is a database for generating question items that stores various information related to a user, the basic information including the number of logins of the user associated with an ID that uniquely identifies the user, and the user A question item generation database having a basic table for storing attribute information, a history table for storing answers and diagnosis results for past items of the user, and an item table for storing question items for the user, and a user A schedule database for storing a unique schedule book for each user, a user identification means for identifying a user based on an ID included in login information from the user, and the schedule database. Based on the schedule entered by the user In response to the login from the user and the schedule processing means for updating the schedule book, the question item for the user is selected from the item table, or the question item for the user is generated based on the item table Receiving the input item presenting means for presenting the item, the schedule in the user-specific schedule book stored in the schedule database, and the input data indicating the user's answer to the presented item, Classify the risk categories that have been set, quantify them in relation to each risk category, and compare these numbers with statistical data for each risk category to calculate the risk level associated with each risk category. And a risk diagnosis means for presenting a diagnosis result including the degree of risk to the user. Is achieved by the risk diagnostic system characterized and.
[0005]
According to the present invention, the risk is diagnosed by referring to the user's schedule and taking into account the user's actions and events. For example, if a user inputs a trip or going out in his / her schedule, the risk that may occur during the trip or outing time can be diagnosed based on this. Further, since the user can refer to his / her schedule book, he / she only has to input his / her schedule into the schedule book for his / her schedule management, not for risk diagnosis. This makes it possible to acquire information necessary for risk diagnosis while reducing the user's resistance.
In addition, since it is not necessary to include the question items including the user's behavior in the questionnaire items, the number of questionnaire items can be reduced, and the user's input operation can be reduced.
[0006]
In a preferred embodiment, a risk category that exceeds a predetermined risk level is further determined by referring to an insurance product database that stores information on insurance products and a diagnosis result obtained by the risk diagnosis means. Insurance diagnosis means for selecting and presenting insurance products from the insurance product database based on the determination result.
In a more preferred embodiment, the information about the insurance product is introduced in response to a request from the user regarding the presented insurance product, and the use is made to the insurance product seller handling the insurance product. Insurance product information introduction means for notifying the customer information of the person in charge.
[0007]
In another preferred embodiment, the schedule processing means presents a calendar-type schedule book from the schedule database to the user, and the user can input the schedule in the date / time field of the presented schedule book, The user can refer to the input schedule book when necessary.
[0008]
In still another preferred embodiment, life cycle information relating to a seasonal or short-term event related to the user's personal preference is further extracted from the input schedule, and the life cycle information is associated with the life cycle information. The risk diagnosis means executes diagnosis using the life cycle information and the associated item. In addition, a second search means for extracting life stage information related to an event related to the long-term life design of the user from the input schedule, and searching for an item associated with the life stage information, The risk diagnosis means may be configured to execute diagnosis using the life stage information and associated items.
As described above, a more appropriate diagnosis can be realized by performing a risk diagnosis using life cycle information, life stage information, and related items (such as associative words).
[0009]
Another object of the present invention is a question item generation database storing various information related to a user, the basic information including the number of logins of the user associated with an ID that uniquely identifies the user, and A database for question item generation having a basic table for storing user attribute information, a history table for accumulating answers and diagnosis results for past items of the user, an item table for storing question items for the user, and A risk diagnosis method for diagnosing a user's risk based on an answer from a user in a system including a schedule database that stores a schedule book unique to each user, including a user's schedule, A user identification step for identifying the user based on the ID included in the login information from the user; In response to login from the schedule processing step of presenting the schedule book to the user from the schedule database and updating the user's schedule book based on the schedule entered by the user, the item A question item for the user is selected from the table, or a question item for the user is generated based on the item table, and an input item presenting step for presenting the item, and a user-specific schedule stored in the schedule database It accepts input data indicating schedules in the book and user responses to the items presented, classifies them into preset risk categories, quantifies them in relation to each risk category, and Compare numbers with statistical data by risk category And it allows to calculate the degree of risk associated with each risk category also achieved by a risk diagnosing method characterized by and a risk diagnosing step of presenting a diagnosis result to the user including the risk.
[0010]
Furthermore, an object of the present invention is a question item generation database storing various pieces of information about a user, the basic information including the number of logins of the user associated with an ID that uniquely identifies the user, and A database for question item generation having a basic table for storing user attribute information, a history table for accumulating answers and diagnosis results for past items of the user, an item table for storing question items for the user, and A computer-readable program for operating a computer for diagnosing the risk of the user based on an answer from the user, the computer having a schedule database for storing the user's schedule, Identifies the user based on the ID included in the login information from the user A user identification step, a schedule processing step for presenting a schedule book to the user from the schedule database, and updating the user's schedule book based on the schedule input by the user, and In response to login, a question item for the user is selected from the item table, or a question item for the user is generated based on the item table, and the item is presented to the input item presenting step and the schedule database It accepts input data indicating the schedule in the stored user-specific schedule and the user's response to the presented items, classifies them into preset risk categories, and relates to each risk category. And digitize these numbers into risk categories. A risk diagnosis step of calculating a risk level related to each risk category and presenting a diagnosis result including the risk level to a user by comparing with the statistical data of It is also achieved by the risk diagnosis program.
[0011]
DETAILED DESCRIPTION OF THE INVENTION
Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings. FIG. 1 is a block diagram showing the configuration of an insurance diagnostic system 10 according to an embodiment of the present invention.
[0012]
As shown in FIG. 1, the insurance diagnosis system 10 presents a user identification unit 12 that identifies a user based on login information such as a user ID and a password from the user, and a schedule book in which the user inputs a schedule. It has a schedule book presentation unit 14. The insurance diagnosis system 10 selects a diagnosis input item according to the number of log-ins of the user and presents the diagnosis input item presentation unit 16, and presents the user input data to the presented schedule book and diagnosis input item. In addition to quantifying these values according to the risk categories that have been set in advance, the user risk is diagnosed by comparing these numbers with the average values and statistical data for each risk category stored in the user database. And a risk diagnosis unit 18 to be presented. Further, the insurance diagnosis system 10 determines the risk category to which the highest risk among the risks obtained by the risk diagnosis unit 18 belongs, and selects and presents insurance products from the insurance product database based on the determination results. When the diagnostic unit 20 and the user are interested in the presented insurance product, the information is received and information on the insurance product is introduced, and the customer information of the user is given to the insurance company that handles the insurance product. Data exchange between the user and the apparatus, and the insurance product information introduction unit 22 for notifying the user, the user database 26, the schedule database 28, the insurance product database 30 and the database 24 for storing various tables 32 to be described later. And an input / output unit 34. The user database 26 here functions to generate question items for the user, and also functions as a database for storing information identifying the user such as the user ID and password of the user. ing.
[0013]
Next, with reference to FIG. 2, a process for inputting a schedule into the user's schedule book will be described in detail.
As shown in FIG. 2, the user accesses the apparatus from the personal computer or the like via the Internet, or inputs the user ID and password using a dedicated terminal connected to the apparatus via a LAN or the like. By logging in to the insurance diagnosis system 10. The insurance diagnosis system 10 according to the present embodiment requires input of the user's age, residence, hobby, etc. in a questionnaire format, and diagnoses risks based on the input questionnaire, in addition to the user's schedule. It can function as a book. That is, the user can use the insurance diagnosis system 10 as a simple schedule book, but can know a risk that may occur based on the schedule of the user.
In the present embodiment, the user needs to register a user ID and a password in advance in order to receive the service provided by the system.
[0014]
Next, based on login information such as a user ID and password, the user identification unit 12 refers to the user database 26 and identifies a user (step 201).
In the present embodiment, as shown in FIG. 6, the user database 26 includes a user basic table 600 that stores various types of user information associated with user IDs. Further, as shown in FIG. 7A, the user basic table 600 includes user basic information 702 associated with the user ID 701 including, for example, the user's sex, age, family structure, and address, and the user. User attribute information 703 including hobbies, personalities, and the like.
[0015]
When the user is specified in the user database 26, the schedule book presenting unit 14 reads the schedule book unique to the user from the schedule database 28. As a result, a calendar-type schedule book 301 as shown in FIG. 3 is presented on the screen of the display device of the user's personal computer or dedicated terminal (step 202). The user inputs his / her schedule in the presented schedule book 301 (step 203). The schedule book to which the schedule is input by the user is stored in the schedule database 28 (step 204). Thereby, the schedule input ends.
The user can check his / her schedule by referring to the schedule book in which the schedule is input when desired.
[0016]
Next, a process using the input schedule will be described in detail with reference to FIGS. These may be executed in response to a schedule input by the user, or may be executed when the user inputs other necessary items and instructs risk diagnosis, as will be described later. good.
As shown in FIG. 3 and FIG. 4, the schedule input by the user in the schedule book 301 is a life cycle related to an event occurring in a shorter period of time (for example, golf, baseball, tennis, etc.) unique to the user. Information can be divided into life stage information related to longer-term and general events (for example, marriage, childbirth, etc.) that can occur in consideration of the age of the user. Therefore, in the present embodiment, life cycle information and life stage information are extracted from the user's schedule, and the risk considering each can be diagnosed.
[0017]
In the present embodiment, as shown in FIG. 6, the risk diagnosis unit 18 includes a life cycle search table 302 for searching a schedule stored in the schedule database 28 and a life stage search table 402. Further, a search engine 303 and a search engine 403 are further provided for further searching for words (associative words) associated with the words searched in the life cycle search table 302 and the life stage search table 402.
As shown in FIG. 3, the search engine 303 in the risk diagnosis unit 18 searches the life cycle search table 302 based on the schedule input in the schedule book 301, and the corresponding word / phrase is specified. Further, based on the words searched from the life cycle search table 302, the search engine 303 further searches for words and phrases associated with the searched words and phrases. For example, regarding the word “golf” in the schedule, the same word “golf” is found from the life cycle search table 302, and the word “golf” is used as the key and the associated word is used. Words such as “injury”, “hole-in-one”, “accident”, and “club damage” may be extracted. The words and phrases searched by the life cycle search table 302 and the search engine 303 are used for diagnosis by the risk diagnosis unit 18.
[0018]
As shown in FIG. 4, the search engine 403 in the risk diagnosis unit 18 searches the life stage search table 402 based on the schedule input to the schedule book 301, thereby identifying the corresponding word / phrase. Further, based on the words and phrases searched from the life stage search table 402, the search engine 403 further searches for words and phrases associated with the searched words and phrases. The words and phrases searched by the life stage search table 402 and the search engine 403 are used for diagnosis by the risk diagnosis unit 18.
[0019]
Next, the insurance diagnosis processing procedure will be described in detail with reference to FIG.
When the user inputs the user ID and password, the user identifying unit 12 refers to the user basic table 600 to identify the user (step 501), whereby the user logs into the insurance diagnostic system 10. can do. As the user ID and password, those registered in advance similarly to the schedule input may be used.
Next, when the user is specified, a predetermined one is selected from the conditions stored in the fixed condition table 601 and the diagnostic item table 602 in the user database 26 and presented to the user (step 502). . In the present embodiment, the standard condition table 601 shown in FIG. 6 is for presenting basic input items according to the number of logins by the user. In the present embodiment, more detailed input items are presented as the number of logins increases.
[0020]
As shown in FIG. 7B, in the first login, only the condition “A” and the condition “B” were obtained (see reference numeral 712). In the second login, the condition “C” "Is added (see reference numeral 713). Further, in the third login, conditions “D” and “E” are added to the above conditions “A” to “C” (see reference numeral 714). More specifically, “sex” and “age” are presented as the first login, and in the second login, in addition to the above conditions, “family structure”, “address (location)”, and “hobby” Can be presented. Furthermore, “annual income” and “occupation” may be added at the third login, and “history” and “personality” may be added at the fourth login. Thus, it is desirable that more private items be presented as the number of logins increases. As a result, more detailed risk diagnosis is possible as the number of logins increases.
[0021]
FIG. 8A is a flowchart showing the processing executed when extracting the standard input items. As shown in FIG. 8A, the diagnostic input item presentation unit 16 refers to the user ID, specifies the user basic information associated with the user ID (step 801), and includes the specified user basic information. (Step 802). Next, the diagnostic input item presentation unit 16 refers to the fixed condition table 601 associated with the user ID, and extracts items corresponding to the acquired number of logins (step 803). Further, with reference to the user history associated with the user ID in the user history database 605, unanswered items are identified among the standard input items (step 804), and the items corresponding to the number of logins are specified. Then, an item list in which unanswered items are added is generated (step 805). In this way, a predetermined fixed input item is presented to the user for each login.
[0022]
As shown in FIG. 7C, the diagnostic item table 602 contains items to be presented in stages for each risk category. This is for presenting input items based on the user's past diagnosis results. The purpose of this table is to recognize how the risk surrounding the user has changed based on the current diagnosis result by reflecting the past diagnosis result on the current input. For example, if the previous diagnosis result is considered as the previous diagnosis result, and the compensation risk is the highest, input items related to compensation risk are increased this time, and input items related to more specialized compensation risk are added. can do.
[0023]
FIG. 8B is a flowchart illustrating processing executed when extracting input items related to the diagnostic item table 602. Here, the diagnostic input item presentation unit 16 refers to the user history database 605, identifies the risk category with the highest risk level in the history associated with the user ID (step 811), and items in the category. And an answer is specified (step 812). Next, the diagnostic input item presentation unit 16 refers to the diagnostic item table and determines items to be presented in consideration of items that have already been answered by the user in the identified risk category (step 813). .
For example, referring to the user's history, if the risk of compensation is the highest, present the user with more detailed items related to compensation (eg, accidents caused in the past, whether or not the personality is sober). Can do.
[0024]
The user inputs an answer to the item selected and presented by the diagnostic input item presentation unit 16 described above (step 503).
Information input to the input items is stored in the user basic table 600 and / or the user history database 605 in association with the user ID. For example, items extracted from the standard condition table are stored as user attribute information in the user basic table 600, and other items are stored in the user history database 605.
[0025]
Next, the risk diagnosis unit 18 acquires the user's past answers from the user history database 605 (step 504), and acquires the user's schedule from the schedule database 28 (step 505). The acquired information is digitized together with the answer input this time (step 506).
In the present embodiment, the answers are classified for each preset risk category and digitized. Risk categories include “body” related to illness and injury, “income” related to annual income, household income, salary, etc., “property” related to homes, cars, household goods, etc., “hobbies” related to sports, travel, etc., personality, lifestyle, occupation, etc. "Compensation" is used. For each of these, an index indicating the degree of risk or the like is digitized.
[0026]
When the above index is digitized, the system operator can set it as desired. For example, consider “medical history” and “previous disease” which are input items of the risk category “body”. Here, even with the same medical history, the index indicating the risk varies greatly depending on the type of disease (for example, “cecalitis” and “gastric ulcer”). Therefore, the risk level can be set to “30%” for “cecalitis”, while the risk level can be set to “70%” for “gastric ulcer”.
[0027]
Alternatively, the amount of risk category “income” and “property” can be quantified as they are. Although income and property do not directly lead to risks, they can be used to calculate the necessary compensation amount (insurance amount) for insurance diagnosis, which will be described later. In addition, regarding the risk category “compensation”, the numerical value of the index indicating the degree of risk can be set according to occupation, address, accuracy, and the like. For example, for a profession that needs to drive a car on a regular basis, a predetermined value (20%) can be added to the values for other professions. The risk categories are not limited to those described above, and can be set as desired by the operator of this system.
[0028]
After quantification for each risk category, the risk diagnosis unit 18 compares each numerical value with the average value for each risk category stored in the average value / trend value table 606 of the user database 26. Further, the risk diagnosis unit 18 obtains statistical values in the reference value table 607 (for example, compensation accident rate, average life span, disease incidence, income by age, etc.) based on the values of the above items and the values for each risk category. To do. Based on the comparison and the acquired information, the risk diagnosis unit 18 makes a determination for each risk category according to the difference from the average value by comparison. This determination can be presented in the form of “plus or minus OO percent” from the average value or statistical data.
[0029]
In the present embodiment, as illustrated in FIG. 9A, information in each risk category is related to each other. It is possible for the operator of this model to set which risk category and which risk category are linked to each other and how to influence the quantification as desired. For example, in FIG. 9B, the item “previous disease” in the risk category “body” affects the item “salary” in the risk category “income”, and the items “personality” and “occupation” in the risk category “compensation”. ”And the risk category“ hobby ”item“ hobby ”affect the risk category“ body ”item“ injury ”. In addition, the operator can set a desired prediction as to how much the numerical value changes due to the association. For example, when the item “skiing” is listed as “hobby”, the numerical values related to the risk category “body” and “compensation” may be set to increase by a predetermined percentage.
[0030]
As described above, in this embodiment, the determination is performed not only by comparing items in a single category and referring to statistical values, but also by taking into account the values of items in other related categories. be able to.
When the determination regarding all risk categories is completed, the risk diagnosis unit 18 outputs a diagnosis result (step 508).
[0031]
In this embodiment, both (1) numerical values (scores) and comments regarding each risk category in the current diagnosis, and (2) numerical values (scores) and comments regarding each risk category in the previous diagnosis are presented simultaneously. The This is to allow the user to recognize how the risk has changed from the past to the present and what risk category should be noted this time. (3) It is desirable to visually present the above results (previous / current) in a diagram (for example, a bar graph, a pie chart, etc.) In order to convince the diagnosis result, it is also desirable to display (4) the average value and statistical value of the entire model user for each risk category. This diagnosis result is stored in the user history database 605 in association with the user ID.
In the present embodiment, the processes from step 504 to step 508 are executed by the risk diagnosis unit 18 (see step 511 in FIG. 5).
[0032]
The insurance diagnosis unit 20 proposes an insurance product according to the result of the risk diagnosis in steps 504 to 508 (step 509). An insurance product that is particularly related to a risk category that has a risk level that is greater than or equal to a predetermined value according to the result of the risk diagnosis. Is selected from the insurance product table in the insurance product database 30. Many insurance products are stored in the insurance product table, and the operator of this model can freely set which insurance product is set for which risk category. The insurance product table stores insurance products related to the risk category for each risk category. A plurality of insurance products can be stored in one risk category. In the present embodiment, the number of proposed insurance products is not necessarily one. Since there are many similar insurance products, a plurality of insurance products may be proposed (see step 512).
[0033]
As a result of the insurance product proposal by the insurance diagnosis unit 20, when the user plans to purchase the insurance product, the user selects the product by clicking an input device such as a mouse. Thereby, the insurance product information introduction unit 20 is activated, and, for example, by linking to a server of an insurance company or an agency that handles the insurance product, the content for introducing or purchasing the insurance product from the server is as follows. Can be communicated to the system. In this way, the user can receive a detailed product description, a guide email or telephone contact from an insurance company.
The insurance product selected in step 509 and the information related to access in step 510 are stored in the user history database 605 of the user database 26.
[0034]
According to the embodiment of the present invention, inputting a schedule in a schedule book can be used for diagnosis of a risk that may occur to a user, and an optimal insurance product can be introduced based on the risk diagnosis. The user can also use his / her own schedule management such as referring to the schedule book. In addition, it is possible to expect an increase in users to access by using a technique of less resistance and easier input compared to a questionnaire, which is input to a schedule book. Further, according to the present embodiment, it is possible to appropriately select a question item for the user according to the past diagnosis result, and by inputting the schedule in the schedule book, excessive input to the user is possible. It is possible to ask the user for appropriate input necessary for diagnosis without imposing a burden.
[0035]
Furthermore, according to the present embodiment, an appropriate input item is selected according to the user's age, hobby, season, etc., and the answer is requested. Therefore, it is possible to select a more detailed risk diagnosis and insurance product for the diagnosis.
The present invention is not limited to the above embodiments, and various modifications can be made within the scope of the invention described in the claims, and these are also included in the scope of the present invention. Needless to say.
[0036]
For example, in the embodiment described above, the schedule book presented to the user uses a calendar format, but is not limited to this, and may be a memo pad input format. Further, in this embodiment, the schedule is classified into life stages and life cycles, and associative words are extracted by searching and used for risk diagnosis, but such classification may not be performed. . Alternatively, it goes without saying that the schedule may be classified by other scales.
In the present specification, the function of one means may be realized by two or more physical means, or the function of two or more means may be realized by one physical means.
[0037]
【The invention's effect】
According to the present invention, the user's input items are quantified based on the risk category, the risk is diagnosed, and the optimal insurance product is presented, so that the user inputs predetermined items to the presented items, and By entering the schedule in the schedule book, you can receive an introduction of the best insurance products for you.
[0038]
In addition, risk management information is acquired by using a method that is less resistant to the user and that is convenient for the user, such as inputting his own schedule into the schedule book. Thereby, it can be expected that a larger number of users use the system.
[Brief description of the drawings]
FIG. 1 is a block diagram showing a configuration of an insurance diagnostic system according to an embodiment of the present invention.
FIG. 2 is a flowchart showing a processing procedure of a schedule according to the embodiment of the present invention.
FIG. 3 is a diagram showing a processing procedure of a schedule according to the present embodiment.
FIG. 4 is a diagram showing a processing procedure of a schedule according to the present embodiment.
FIG. 5 is a flowchart showing a processing procedure of insurance diagnosis according to the present embodiment.
FIG. 6 is a diagram for explaining a user database according to the embodiment;
FIG. 7 is a diagram for explaining a table in the user database according to the embodiment;
FIG. 8 is a flowchart showing processing executed when extracting input items according to the embodiment.
FIG. 9 is a diagram showing an example of the correlation between category risks according to the present embodiment.
[Explanation of symbols]
10 Insurance diagnostic system
12 User Identification Department
14 Schedule book presentation part
16 Diagnosis input item presentation section
18 Risk diagnosis department
20 Insurance diagnosis department
22 Insurance Product Information Introduction Department
24 database
26 User database
28 Schedule database
30 Insurance product database
32 Various tables
34 I / O section

Claims (4)

A database for generating question items that stores various information related to a user, and stores basic information including a user's login count associated with an ID that uniquely identifies the user and attribute information of the user A question table generation database having a basic table, a history table that accumulates answers and diagnosis results for past question items of the user, and an item table that stores question items for the user;
A schedule database that is unique to each user and includes a schedule book that stores the daily schedule of the user ;
User identification means for identifying a user based on an ID included in login information from the user;
A schedule processing means for presenting a schedule book to the user from the schedule database and updating the user's schedule book based on the schedule input by the user;
In response to the login information , the number of logins in the basic table associated with the user ID specified by the user specifying unit is acquired, and a new question item determined according to the number of logins is obtained. Obtained from the item table of the question item generation database, input item presenting means for presenting the question item,
The schedule database stored in the user's inherent of the day for each of the schedule in the schedule book, and, presented to accept the input data showing the answer of the user for the item, the schedule in the schedule book, the user And answers to past question items accumulated in the history table are risk categories set in advance, such as “body” related to illness and injury, “income” related to annual income, household, salary, house, car, Categorized into risk categories that include “property” related to household goods and “compensation” related to personality, lifestyle, and occupation ;
For the “income” and “property” risk categories, the amount included in the answer is quantified, and in the “body” risk category, based on the “medical history” and “previous disease” included in the answer in advance. In the risk category of “compensation”, a numerical value indicating the risk of a specific occupation according to the “occupation” included in the answer In addition to being quantified by increasing the number of occupations by a predetermined amount from a predetermined value ,
The numerical value in the reference value table storing the statistical value for each risk category is compared with the numerical value obtained by the quantification, and the numerical value in the reference value table and the numerical value obtained by the quantification are obtained for each category. A risk diagnosis system comprising: a risk diagnosis unit that calculates a difference from a numerical value and presents the difference to a user. Further, an insurance product database for storing information on insurance products, for each risk category, an insurance product database in which information on insurance products related to the risk category is stored ;
Referring to the numerical value obtained by the quantification for each category obtained by the risk diagnosis means, identify the risk category in which the numerical value is a predetermined value or more ,
2. The risk diagnosis system according to claim 1 , further comprising insurance diagnosis means for selecting and presenting information on the insurance product relating to the identified risk category from the insurance product database. In addition, in response to a request from the user about the insurance products that the presented, from the server of insurance products seller dealing with the insurance products, the information in order to purchase the information and the insurance products to introduce the previous year insurance products The risk diagnosis system according to claim 2, wherein the risk diagnosis system is configured to acquire the risk diagnosis system. Further, from the input schedule, a search table corresponding to the search word corresponding to the schedule, and an association word associated with the search word,
Based on the keyword, and a search means for searching for associated words from the search table,
The risk diagnosis system according to any one of claims 1 to 3 , wherein the risk diagnosis unit performs diagnosis using the search word and the associative word .

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