KR102641743B1 - Calculating method of loading premiums discount rate for insurance products - Google Patents

Abstract

The purpose of the present invention is to provide a method for calculating a discount rate of an additional insurance premium, which quantifies a disease occurrence probability by insurance coverage by using digital medical record information of an individual which can be collected through the internet, and calculates a discount rate of an additional insurance premium corresponding to a business cost of an insurance product among insurance premiums which an insurance company receives from an insurance policyholder by using the quantified disease occurrence probability. A method for calculating a discount rate of additional insurance premiums comprises: a URL requesting step; a URL providing step of generating a URL including a customized identification code and returning the URL to a customer terminal requesting the provision of the URL; a medical record information collecting step of collecting medical record information matched with personal authentication information; a health grade calculating step of selecting a participation group according to the gender and age of a customer by analyzing the application information, and calculating the health grade of the customer related to the participation group by analyzing the medical record information through a health grade program; a risk relative degree calculating step of generating risk relative degree information by calculating a risk relative degree for the health grade of the customer for each security of an insurance product; and a discount rate calculating step of calculating a discount rate of additional insurance premiums of the insurance product based on the risk relative degree information. According to the present invention, it is possible to provide reasonable benefits to both insurance companies and customers by analyzing individual digital medical record information and differentiating insurance premiums according to health conditions, to induce lifestyle improvement through risk relativeity according to health grades, and to encourage social health promotion and disease prevention by providing inexpensive insurance products to those with excellent health checkups.

Description

{CALCULATING METHOD OF LOADING PREMIUMS DISCOUNT RATE FOR INSURANCE PRODUCTS}

The present invention relates to a method of calculating the value-added insurance premium discount rate for calculating the value-added insurance premium discount rate of the insurance product selected by the customer using accumulated medical record information. More specifically, it relates to a method of calculating the value-added insurance premium discount rate using accumulated medical record information. It relates to a method of calculating the value-added insurance premium discount rate that can evaluate an individual's health level and calculate the value-added insurance premium discount rate for insurance products based on this evaluation.

In modern society, each individual's health programs such as diagnosis, exercise, and management are periodically managed by the individual's will or by surrounding conditions such as workplace health management programs or various social health management programs.

Through this, health information includes medical data such as consultations with doctors, examination records, surgery records, prescription records, and accident injury records, pharmacy dispensing records, constitutional classification data by Oriental medicine based on treatment at oriental medicine clinics, and physical strength improvement. Data such as consultation records at a sports center, exercise history, injury records during exercise, etc. for pregnant women, obstetrician/gynecologist records during pregnancy, health recovery records at a postpartum care center after childbirth, health status during the newborn period for babies, etc. Records and data are continuously created throughout each individual's life.

However, this information related to medical care is not managed in an integrated manner by the individual, and although it is the information that can best determine the individual's health status, the information is not directly used to calculate insurance premiums. Therefore, the information related to each individual's medical care, which is obtained at a very high cost, is used only for partial application and cannot be used to determine the insurance premium by determining the health status of the person eligible for medical insurance.

In addition, along with the recent trend of the general public's increasing awareness of their own health, and thanks to the rapid development of Internet technology, many Internet sites providing medical information have been opened, and medical and health-related Internet sites continue to exist. It is being opened.

These online sites provide health consulting and information services, and some sites provide medical information system solutions, electronic prescription delivery businesses linked to hospitals, pharmacies, and pharmaceutical companies, and medical device and drug distribution businesses. It is being promoted in conjunction with others.

However, in the case of Internet sites such as those mentioned above, it is difficult to obtain customized information suitable for determining insurance premiums because they provide general information. Although an individual's health level can be confirmed with the information provided from the Internet site, future health status can be predicted through this. It is difficult to do so.

In addition, the insurance industry has sometimes used the above-mentioned health information to discount a portion of insurance premiums when prospective insurance subscribers meet certain requirements (submission of health checkup results, achievement of number of steps within a certain period of time), but there is no method for calculating the insurance premium discount rate. There was a problem of uncertainty.

Therefore, the need for an evaluation index to understand the current level of health and for continuous health management is emerging, and the need to develop an evaluation system that can systematically discount insurance premiums according to the evaluation index is gradually increasing.

Republic of Korea Patent No. 10-2152827 (announced on 2020.09.07) Republic of Korea Patent Publication No. 10-2011-0032594 (published on March 30, 2011) Republic of Korea Patent Publication No. 10-2013-0030401 (published on March 27, 2013) Republic of Korea Patent No. 10-1970947 (announced on April 25, 2019)

Therefore, the purpose of the present invention is to quantify the probability of disease occurrence by insurance collateral by using personal digital medical record information that can be collected through the Internet, and to use the quantified probability of disease occurrence to collect insurance premiums from policyholders. The purpose is to provide a method for calculating the discount rate of additional insurance premiums that can calculate the discount rate of additional insurance premiums corresponding to the operating expenses of heavy insurance products.

In order to achieve the purpose of the present invention described above, in one embodiment of the present invention, an application reception step in which an operation server receives application information for calculating insurance premiums for insurance products from a customer terminal connected through a communication network, and the operation server A medical record information collection step of providing personal authentication information provided from a customer terminal to an institutional server and then collecting medical record information matching the personal authentication information from the institutional server, or receiving medical record information from the customer terminal; The operation server analyzes the application information and selects a participation group according to the customer's gender and age, and analyzes the medical record information through a health rating program based on a health evaluation model to calculate the health level of the customer related to the participation group. A health grade calculation step, a risk relativity calculation step in which the operation server generates risk relativity information by calculating a risk relativity for the customer's health grade for each collateral of the insurance product, and the risk relativity calculation step from the operation server. It provides a discount rate calculation method for the additional insurance premium of an insurance product, including a discount rate calculation step in which the insurance company server that has received the relativity information calculates the discount rate of the additional insurance premium of the insurance product based on the risk relativity information.

According to the present invention, customers can pay an insurance premium appropriate for their health status, and insurance companies can determine an insurance premium appropriate for the customer's health status. In other words, from the insurance company's perspective, the likelihood of insurance payment for people in good health is relatively lower than for people without health, so establishing a reasonable insurance product pricing system that matches the health status of the insured person benefits both policyholders and insurance companies. can be provided.

In addition, the present invention predicts the risk of developing future diseases by collecting and analyzing an individual's accumulated digital medical record information through the Internet, and can provide differentiated prices for insurance products based on the results.

In addition, the present invention can inform customers of the possibility of occurrence of a disease covered by an insurance product within a certain period of time in the future with a risk relative degree according to health grade, thereby providing incentives for improving lifestyle habits and raising social awareness of health promotion. Compensation for this is provided in the form of discounts on additional insurance premiums, providing economic benefits for health care to the insured.

Furthermore, the present invention can provide customers with excellent health checkup results with the opportunity to sign up for cheaper insurance products than before, thereby increasing the national health checkup rate and promoting active health such as early detection, treatment, and prevention of diseases. Management activities can be encouraged.

1 is a flowchart illustrating a method of calculating a discount rate for additional insurance premiums according to the present invention.
2 to 4 are flow charts for explaining the method of calculating the additional insurance premium discount rate according to the present invention.
Figure 5 is a configuration diagram showing a system for calculating the additional insurance premium discount rate according to the present invention.
Figure 6 is a block diagram showing an embodiment of the additional insurance premium discount rate calculation system according to the present invention.
Figure 7 is a block diagram showing another embodiment of the system for calculating the discount rate of additional insurance premiums according to the present invention.
Figure 8 is a block diagram for explaining the operation server according to the present invention.

Hereinafter, a method for calculating the value-added insurance premium discount rate for insurance products according to preferred embodiments of the present invention (hereinafter abbreviated as 'method for calculating value-added insurance premium discount rate') will be described in detail with reference to the accompanying drawings.

Figure 1 is a flow chart for explaining the method for calculating the additional insurance premium discount rate according to the present invention, and Figures 2 to 4 are flow charts for explaining the method for calculating the additional insurance premium discount rate according to the present invention.

Referring to Figures 1 to 4, the method for calculating the discount rate for additional insurance premiums according to the present invention includes an application reception step (S100) of receiving application information for calculating insurance premiums for insurance products from the customer terminal (200), and the customer terminal (200). ) A medical record information collection step (S200) of receiving medical record information from or collecting medical record information from the institutional server 100, analyzing the application information to select a participating group, and applying the medical record information to a health evaluation model. A health grade calculation step (S300) in which the health grade of the customer related to the participating group is calculated by analyzing through a health grade program based on the health grade, and the risk relativity for the customer's health grade is calculated for each collateral of the insurance product. It includes a risk relativity calculation step (S400) that generates information, and a discount rate calculation step (S500) in which the insurance company server 400 calculates the discount rate of the additional insurance premium of the insurance product based on the risk relativity information.

Figure 5 is a configuration diagram showing a system for calculating the additional insurance premium discount rate according to the present invention. The method of calculating the above-described additional insurance premium discount rate can be provided through the additional insurance premium discount rate calculation system shown in FIG. 5. More specifically, the system for calculating the value-added insurance premium discount rate includes an institutional server 100 that stores medical record information, a customer terminal 200 that transmits insurance premium calculation application information and personal authentication information requesting calculation of the value-added insurance premium discount rate of an insurance product, and , is connected to the customer terminal 200 through a wired or wireless communication network (hereinafter abbreviated as 'communication network'), analyzes the application information received from the customer terminal 200, extracts the customer's gender and age, and extracts the gender and age of the customer. Participating groups are selected according to age, and the medical record information is analyzed through a health rating program based on a health evaluation model to calculate the health level of the customer associated with the participating group. The health level of the customer is calculated for each collateral of the insurance product. An operation server 300 that calculates risk relativity and generates risk relativity information, and an insurance company server 400 that calculates the discount rate of additional insurance premiums for insurance products based on the risk relativity information provided by the operation server 300. It consists of:

The operation server 300 is connected to the customer terminal 200 and the insurance company server 400 through a communication network, and can optionally be connected to the institutional server 100 through a communication network.

Hereinafter, each component will be described in more detail with reference to the drawings.

The method of calculating the additional insurance premium discount rate according to the present invention may further include a URL request step before the application reception step (S100).

The URL request step is a step in which the customer terminal 200 connects to the operation server 300 through a communication network and then requests the operation server 300 to provide a URL. The customer terminal 200 sends a URL request signal to the user. It receives input from and transmits it to the operation server 300 through a communication network.

If necessary, in the URL request step, the customer terminal 200 may provide member information including personal information and insurance product selection information to the operation server 300.

The method of calculating the additional insurance premium discount rate according to the present invention may further include a URL provision step between the URL request step and the application reception step (S100).

The URL provision step is a step in which the operation server 300 creates a URL and replies to the customer terminal 200 that provided the application information. At this time, the URL is a URL that can access the first web page provided by the operation server 300, or a URL that can download the installation file of the insurance application management app 210 so that the insurance application management app 210 can be installed. One of the URLs of a web page.

As an embodiment, in the URL provision step according to the present invention, the operation server 300 generates an identification code with a unique key value, generates a URL including the identification code, and sends the URL to the customer terminal 200. can be provided. In other words, the operation server 300 extracts the customer's individual identifier from the personal information provided by the customer, extracts the insurance company and insurance product identification code from the insurance product selection information, and generates a customized identification code for each customer.

In another embodiment, in the URL provision step according to the present invention, the operation server 300 generates an encrypted non-identification code that cannot be decrypted through the process of encrypting the unique key value using a hash function, and deep link (deep link) ) can be used to generate a URL containing a non-identification code and provide it to the customer terminal 200.

Referring to Figures 3 and 4, the method of calculating the value-added insurance premium discount rate according to the present invention may further include an app installation step (S50) between the URL request step and the application reception step (S100).

The app installation step (S50) is a step in which the customer terminal 200 downloads the installation file of the insurance application management app 210 through the URL provided by the operation server 300 and then installs the insurance application management app 210. . This insurance application management app 210 is equipped with a scraper and can use client base scraping to collect medical use information extracted from the institutional server 100 through the scraper to the customer terminal 200.

Here, scraping is a technology in which a computer program automatically extracts data from a web page or program screen. Screen scraping extracts data by reading the screen output of another program using image processing techniques, and the source code and data that make up the web page. Includes web scraping to extract.

Referring to Figure 1, the method of calculating the value-added insurance premium discount rate according to the present invention includes an application reception step (S100).

The application reception step (S100) is a step in which the operation server 300 receives application information for calculating insurance premiums for insurance products from the customer terminal 200 connected through a communication network, as shown in Figures 1 to 3, and the customer When the terminal 200 receives application information for calculating insurance premiums containing customer information from the user to request confirmation of the discount rate for additional insurance premiums and transmits it to the operation server 300 through a communication network, the operation server 300 The application information is received and stored.

The application information may include customer information and insurance product information. Such customer information includes one or more of the customer's name, date of birth or resident registration number, address, phone number, ID and password for login, etc. And the insurance product information may include the insurance company and insurance product name or the insurance company and insurance product classification code.

If necessary, in the application reception step (S100), the operation server 300 may receive approval information consenting to the use of the customer's medical record information from the customer terminal 200. At this time, the approval information includes prior consent to use the health examination information and medical use information in the institutional server 100 to confirm the insured person's health status, past medical history, and medical history.

In the application reception step (S100), the operation server 300 can analyze the application information and determine whether the applicant customer is eligible for health rating calculation.

As a first embodiment, the customer terminal 200 according to the present invention accesses the website provided by the operation server 300 through the URL provided by the insurance company server 400 as shown in FIG. 2 and operates the operation server through the website. Application information and personal authentication information are sent to (300), and approval information can also be optionally sent. At this time, the personal authentication information may include one or more simple authentication information, mobile phone authentication information, and joint certificate authentication information. If necessary, the customer terminal 200 may provide encrypted personal authentication information to the operation server 300.

As a second embodiment, the customer terminal 200 according to the present invention connects to the operation server 300 through the insurance application management app 210 according to the user's request as shown in FIG. 3 and provides application information. At this time, the customer terminal 200 does not provide personal authentication information to the operation server 300.

As a third embodiment, the customer terminal 200 according to the present invention connects to the operation server 300 through the insurance application management app 210 according to the user's request as shown in FIG. 4 and operates application information and identity authentication information. Provided by server 300.

In the application reception step (S100), when the customer terminal 200 accesses the operation server 300 through a URL containing a customized identification code, the operation server 300 analyzes the URL and extracts insurance product selection information.

If the personal authentication information provided from the customer terminal 200 is encrypted to prevent hacking, the operation server 300 decrypts the personal authentication information.

This customer terminal 200 is an operation server 300 that provides an additional insurance premium discount rate calculation service through a wireless communication network including multiple base stations, base station controllers, mobile communication exchanges, and WAP gateways, and a wired communication network such as the Internet. It refers to a means of applying for insurance premium confirmation, and wireless terminals and wired terminals can be used. At this time, a smartphone, tablet PC, laptop computer, etc. can be used as a wireless terminal, and a desktop computer, smart TV, landline phone, etc. with Internet access can be used as a wired terminal.

Figure 6 is a block diagram showing an embodiment of the additional insurance premium discount rate calculation system according to the present invention, Figure 7 is a block diagram showing another embodiment of the additional insurance premium discount rate calculation system according to the present invention, and Figure 8 is a block diagram of the present invention This is a block diagram to explain the operation server 300 according to.

Referring to Figures 6 to 8, the operation server 300 of the present invention includes a communication unit 310, a medical record information collection unit 320, a participation group management unit 330, a health grade management unit 340, and a risk partner management unit. It also includes a management unit 350, and may optionally further include a storage unit 360.

The communication unit 310 is connected to the customer terminal 200, the institution server 100, and the insurance company server 400 through a communication network, and processes data transmission and reception by the operation server 300. At this time, the communication unit 310 may store various information received from the outside through a communication network in the storage unit 360.

In one embodiment, the communication unit 310 according to the present invention can receive membership registration information and personal authentication information from the customer terminal 200 connected through a communication network, and can optionally also receive approval information.

In another embodiment, the communication unit 310 according to the present invention can receive membership registration information and medical record information from the customer terminal 200 connected through a communication network, and can optionally receive approval information.

The storage unit 360 stores various data received through the communication unit 310 and includes a medical record information collection unit 320, a participation group management unit 330, a health grade management unit 340, and a relative risk management unit 350. It stores the results derived from the communication unit 310, medical record information collection unit 320, participation group management unit 330, health grade management unit 340, and risk relative management unit 350. .

Referring to FIG. 1, the method for calculating the additional insurance premium discount rate according to the present invention includes a medical record information collection step (S200).

In the medical record information collection step (S200), the operation server 300 receives medical record information from the customer terminal 200 or provides the identity authentication information provided from the customer terminal 200 to the institutional server 100. In the step of collecting medical record information matched to personal authentication information from the institutional server 100, when the customer terminal 200 collects medical record information from the institutional server 100, the operation server 300 collects the medical record information from the institutional server 100. Receives medical record information from, and if the customer terminal 200 does not collect medical record information from the institutional server 100, the operation server 300 directly collects the medical record information from the institutional server 100. At this time, the collection of medical record information through the institutional server 100 may target medical record information within the past 10 years based on the time of collection.

The institutional server 100 is equipped with a medical record information database (DB, 110) in which medical record information is stored, and the medical record information includes health examination information from the National Health Insurance Corporation and medical utilization information from the Health Insurance Review and Assessment Service (HIRA). Information is included.

The health checkup information includes information on height, weight, waist circumference, body mass index, vision, hearing, and blood pressure (systolic/diastolic) as measurement information, urine protein information as urinalysis information, and blood test information. Information on hemoglobin, fasting blood sugar, cholesterol (HDL/LDL), neutral fat, serum creatinine, glomerular filtration rate (GFP), AST (SGOT), ALT (SGPT), and gamma TP are included, and imaging test information for pulmonary tuberculosis chest Information about the disease may be included.

The above medical use information includes personal medical information summary information [name of hospital and pharmacy], number of hospitalization [outpatient] days, total medical expenses [health insurance coverage], amount of benefits received from health insurance, etc., medical expenses [medical treatment expenses], basic medical treatment details [treatment start date, Name of hospital and pharmacy, diagnosis department, inpatient/outpatient classification, number of days of visit, total medical expenses (health insurance coverage), amount received from health insurance, etc., medical expenses incurred (medical expenses)], detailed treatment information [treatment start date, name of hospital and pharmacy, Medical treatment details, code name, 1 dose, 1 dose number, 1 dose number, total number of medication days], prescription dispensing information [treatment start date, hospital and pharmacy name, prescription/dispensing category, drug name, ingredient name, 1 dose, 1 dose number, total Number of days of administration] may be included.

This institutional server 100 is a server operated by an organization designated by the government to collect and manage medical information generated in hospitals and clinics, such as the Health Insurance Review and Assessment Service and the National Health Insurance Service. Register and manage usage information and health checkup information.

More specifically, the institutional server 100 stores general health examination information including the results of health examination examinees performed by the National Health Insurance Corporation, health examination questionnaire data, and medical use information including statement and medical record data. I'm doing it. For example, the institutional server 100 may store information on subscribers enrolled in the National Health Insurance Corporation in the form of a general examination database, questionnaire database, statement database, and medical record database.

When the operation server 300 requests medical record information while providing personal authentication information or personal authentication information changed based on personal authentication information, the institutional server 100 provides the medical record information in the form of a web page to the operating server ( 300). Additionally, when the customer terminal 200 requests medical record information while providing identity authentication information, the institutional server 100 may provide the medical record information to the customer terminal 200 in the form of a web page.

As a first embodiment, in the medical record information collection step (S200) according to the present invention, the operation server 300 provides identity authentication information or personal authentication information to the institutional server 100 where the medical record information is stored, as shown in FIG. And (S210), medical record information matching the identity authentication information is collected from the institutional server (100) (S220). At this time, the operation server 300 provides the identity authentication information provided by the customer terminal 200 to the web page accessed through the URL in the application reception step (S100) to the institutional server 100.

More specifically, in the medical record information collection step (S200), when personal authentication information is provided instead of medical record information from the customer terminal 200, the medical record information collection unit 320 of the operation server 300 collects the personal authentication information from the organization. It is provided to the server 100 to collect medical record information matched to personal authentication information. And when the institutional server 100 provides medical record information matched to the user authentication information or personal authentication information to a web page, the medical record information collection unit 320 of the operation server 300 collects the medical records disclosed through the web page. Record information is collected and stored through scraping. At this time, the medical record information collection unit 320 can store the medical record information collected from the institutional server 100 itself or in the medical information DB of the storage unit 360. This medical record information collection unit 320 may be connected to the communication unit 310 and the storage unit 360. For this purpose, the medical record information collection unit 320 of the operation server 300 is installed with a scraper and performs server base scraping to collect medical record information extracted from the institutional server 100 through the scraper to the server. can be used.

If necessary, the operation server 300 processes the personal authentication information provided from the customer terminal 200 into a form requested by the institutional server 100 to generate personal authentication information, and sends the personal authentication information to the institutional server 100. ), and the matched medical record information can be collected from the institutional server (100). In addition, the operation server 300 generates encrypted personal authentication information requested by the institutional server 100 based on the personal authentication information and transmits the encrypted personal authentication information to the institutional server 100.

As a second embodiment, in the medical record information collection step (S200) according to the present invention, as shown in FIG. 3, the customer terminal 200 connects to the institutional server 100 through the insurance application management app 210 according to the user's request. Personal authentication information is provided (S250), and medical record information matching the personal authentication information is collected from the institutional server (100) through the insurance application management app (210) (S260), and then the medical record information is operated. Register on the server 300 (S270).

When the institutional server 100 provides medical record information matched to personal authentication information to a web page, the insurance application management app 210 can collect and store the medical record information disclosed through the web page through scraping. .

The insurance application management app 210 can combine each medical record information collected through different web pages, and classify and refine them to delete unnecessary or redundant information.

In addition, the customer terminal 200 connects to the operation server 300 through the insurance application management app 210 and transmits the classified and refined medical record information to the operation server 300. At this time, the insurance application management app 210 may provide the medical record information to the operation server 300 after receiving the final consent for providing the medical record information to the operation server 300.

In this way, when medical record information is received from the customer terminal 200, the operation server 300 does not collect the customer's medical record information from the institutional server 100, but uses the medical record information provided from the customer terminal 200 to Health level can be calculated.

As a third embodiment, in the medical record information collection step (S200) according to the present invention, the operation server 300 provides identity authentication information or personal authentication information to the institutional server 100 where the medical record information is stored, as shown in FIG. (S210), medical record information matching the identity authentication information is collected from the institutional server 100 (S220). At this time, the operation server 300 provides the identity authentication information provided by the customer terminal 200 through the insurance application management app 210 in the application reception step (S100) to the institutional server 100.

Referring to Figure 1, the method for calculating the discount rate for additional insurance premiums according to the present invention includes a health grade calculation step (S300).

In the health grade calculation step (S300), the operation server 300 analyzes the application information, selects a participation group according to the customer's gender and age, and analyzes the medical record information through a program based on a health evaluation model to participate in the participation. A step of calculating the health level of a customer associated with a group, a participation group selection process (S310) in which the operation server 300 analyzes application information and selects a participation group according to the customer's gender and age, and the operation server 300 ) includes a health grade calculation process (S320) in which the collected medical record information is analyzed through a health grade program based on a health assessment model to calculate the health grade of the customer associated with the participating group. Here, medical record information includes health examination information and medical use information.

Specifically, in the participation group selection process (S310), the participation group management unit 330 of the operation server 300 extracts the customer's gender and age from the application information received by the communication unit 310, and then extracts the customer's gender and age into multiple numbers according to the customer's gender and age. Among the participation groups, the participation group that matches gender and age is selected as the customer's participation group. For this purpose, the participation group management unit 330 may be connected to the communication unit 310.

These participating groups are divided into categories using statistical methods of individual test items and medical use information that have a high statistical correlation with the occurrence of health accidents, which are dependent variables, and then use health accident and explanatory variables such as IV (Information Value) and K-S (Kolmogorov-Smirnov) statistics. Explanatory variables are selected and divided based on the discriminability and reliability between the variables.

More specifically, the statistical method of dividing explanatory variables into sections uses the classification tree of the decision tree model to classify health accidents into certain sections to minimize cross-entropy. After separating the nodes so that the information gain satisfies a certain level, a small number of people showing homogeneity through health accident incidence rate, odds, WOE (Weight Of Evidence), etc. for the section that satisfies the sufficiency of data. This is a method of reclassifying into sections.

In addition, the classification tree of the decision tree model is selected to maximize homogeneity within nodes (groups) and heterogeneity between nodes at child nodes branching from the parent node, and the size of the model is adjusted to avoid overfitting (or underfitting). It is regulated by reasonable standards.

In a specific embodiment, the participating groups include a first group of men and under 35 years of age, a second group of men and ages 35 to 49, a third group of men and ages 50 to 59, a fourth group of men and over 60 years of age, and a fourth group of men and older than 60 years of age. Group 5 is women aged under 30 years, Group 6 is women aged 30 to 44 years, Group 7 is women aged 45 to 54 years, Group 8 is women aged 55 to 64 years, and Group 9 is women aged 65 years or older. The customer's participation group may be selected as one of the nine groups mentioned above depending on gender and age.

For example, if the participation group management unit 330 analyzes the medical record information and determines that the analysis target is a 45-year-old male, it classifies the participation group as the second group. Then, the participation group management unit 330 analyzes the medical record information and, if the analysis target is determined to be a 45-year-old woman, it classifies the participation group as the 7th group.

In the health grade calculation process (S320), the health grade management unit 340 analyzes medical record information through a health grade program based on a health assessment model to select the health grade of the customer associated with the participating group, and 9 according to pre-designed criteria. Among the classified health grades, the health grade of the customer for whom medical record information is collected is selected.

Specifically, the health grade calculation process (S320) is a numerical extraction process in which the health grade management unit 340 extracts the values of test items and medical use information matched to the participation group of the health grade user from medical record information, and the health grade management unit 340 A numerical grading process in which (340) determines the grade of each object by classifying the extracted numerical value according to the grade of each object, and the health grade management unit (340) adds up the scores of the grades matched with the numerical value to create an individual score. It includes a scoring process that calculates the user's health grade, and a score grading process in which the health grade management unit 340 compares the individual score with the health grade scorecard of the user's participation group to calculate the user's health grade. At this time, about 4 to 10 individual test items may be selected from information confirmed through health examination information and medical use information, but are not limited to this.

For example, the test items matched to the second group are body mass index, blood pressure (systolic/diastolic), hemoglobin, fasting blood sugar, cholesterol (HDL/LDL), triglycerides, serum creatinine, number of days of medication in the past year, and prescriptions in the past year. If the number of days is the number of days, the health grade management unit 340 extracts the values of the 9 test items from the medical record information and calculates the individual score by adding up the scores previously assigned to the grade matched with each value. For example, the level for body mass index is level 2 (18 points), the level for blood pressure (systolic/diastolic) is level 3 (16 points), and the level for hemoglobin is level 4 (14 points). ), the level of fasting blood sugar level is grade 5 (12 points), the level of cholesterol (HDL/LDL) is level 6 (10 points), and the level of triglyceride level is level 7 ( 8 points), the level of the serum creatinine level is level 8 (6 points), the level of the number of days of medication administration over the past year is level 9 (4 points), and the level of level of the level of prescription days over the past year is level 9 (4 points). If the score is 10 (2 points), the health grade management unit 340 calculates the customer's personal score as 90 points.

If necessary, the health grade management unit 340 may calculate an individual score by adding a basic score to the total score from several test items matched to the customer's participation group. At this time, the basic score is not limited as it may change depending on the number of test items and scores for each grade.

In addition, the health grade management unit 340 assigns weights to each test item and medical use information matched to the customer's participation group, and applies the weight of the test items and medical use information to the score of the grade matched to each numerical value. The individual score can be calculated by adding up the weighted scores. This is to apply weight to highly important test items and medical use information to distinguish them from other test items and medical use information.

In addition, if some of the test items and medical use information matched to the customer's participation group in the medical record information are missing from the medical record information, the health grade management unit 340 sends the missing target test to the customer terminal 200. You can request numerical correction of items and medical use information. At this time, because the health grade may be lowered due to the missing test items and medical use information, the customer who provided the insurance premium calculation application information must confirm the values of the missing test items and medical use information through the medical institution and then submit the relevant data. It can be provided through the operation server (300).

Referring to Figure 1, the method for calculating the additional insurance premium discount rate according to the present invention includes a risk relativity calculation step (S400).

The risk relativity calculation step (S400) is a step in which the operation server 300 generates risk relativity information by calculating the risk relativity for the customer's health grade for each collateral of the insurance product. A risk relativity calculation process that generates risk relativity information by calculating the risk relativity of the customer's health grade for each collateral of the insurance product, and the operation server 300 provides the risk relativity information to the insurance company server 400. The risky counterpart also includes the transmission process.

In this step (S400), when the risk relativity is provided to the customer terminal 200 from the operation server 300, the customer terminal 200 can output the risk relativity on the screen.

In this risk relativity calculation step (S400), the risk relativity management department 350 calculates the health accident incidence rate, which is the probability of a customer's health accident occurring within a pre-specified period, by health grade, and based on the health accident incidence rate by health grade. Calculate risk relativity. Here, the pre-designated period can be set to within 1 to 10 years. However, the pre-designated period may be changed according to the basic principles of national health examination.

In addition, health accidents include cardiovascular disease, diabetes, chronic respiratory disease, heart disease, cancer, and death due to disease, which are designated as major chronic diseases with a high disease burden by the World Health Organization (WHO) or equivalent organizations. and, in accordance with the Medical Services Act, includes any one or more selected from the group consisting of hospitalization at a general hospital or higher. At this time, the major chronic diseases designated by WHO are not particularly limited as they may change over time. If necessary, the Korean Standard Classification of Diseases (KCD) may be applied to health accidents. This KCD is applied to define the above-mentioned major chronic diseases with KCD codes, for example, cancer is defined as (C00-C97), and cerebrovascular disease is defined as (I60-I69).

The risk relativity management department 350 analyzes cohorts of more than 1 million people stored in the Health Insurance Review and Assessment Service, and among the samples representing the characteristics of the entire population (extracted using the stratified sampling method), there are health checkup results for a specified period in the past. The population is used as the analysis target, and the number of health accidents that are mainly covered by insurance is collected by health grade, and the health accident incidence rate is classified by health grade for each health accident to create a database of health accident incidence rates.

In a specific aspect, in the risk relativity calculation step (S400) according to the present invention, the risk relativity management unit 350 calculates the incidence rate for each health grade of each collateral in the participating group to which the customer belongs, and each collateral included in the insurance product. The overall incidence rate is calculated, and the incidence rate for each health grade of collateral is divided by the total incidence rate for the same collateral to calculate the risk relative to the customer's health grade for each collateral of the insurance product.

At this time, the incidence rate by health class of insurance coverage can be calculated as a percentage value divided by the number of health accidents corresponding to insurance coverage in the same health class based on the number of subjects classified by health class. For example, if the total number of subjects is 38,891, the number of subjects with a health grade of 1 is 3,889, and the number of people with heart disease is 99, the incidence of insurance coverage corresponding to heart disease in a health grade of 1 is 2.55%. It is calculated as And if the overall incidence of heart disease is 8.31%, the incidence of heart disease for subjects in class 1 (2.55%) is divided by the total incidence of heart disease (8.31%) to calculate the rate of heart disease in subjects in class 1. The risk relativity (30.7%) can be calculated.

In addition, in the risk relativity calculation step (S400), the risk relativity management unit 350 generates risk relativity information by extracting the risk relativity for each collateral matched to the customer's health grade from the risk relativity for each collateral's health grade. , the risk relative information can be provided to the insurance company server 400 through the communication unit 310.

If necessary, the risk relativity management department 350 uses a smoothing method using a statistical model such as a local regression model to calculate the incidence rate for each health grade of each collateral so that the health accident incidence rate and collateral incidence rate for each health grade can be maintained consistently. It is possible to calculate the risk relativity for each health grade of collateral based on the corrected incidence rate for each health grade of each collateral.

For example, the risk relative management department 350 can analyze data from the Health Insurance Review and Assessment Service to calculate the incidence rate by health class for heart disease (coverage) as shown in [Table 1] below, and localize the incidence rate by health class. Using a smoothing method using a regression model, corrections can be made as shown in [Table 2] below, and the adjusted incidence rate for each health grade is divided by the total incidence rate for the same collateral, as shown in [Table 3] below. Relativity can be calculated.

[Table 1] Incidence rate by health level for heart disease in group 3

[Table 2] Incidence rate by health grade corrected using the smoothing method

[Table 3] Relative risk by health level

Meanwhile, the risk relativity calculation step (S400) includes a risk relativity calculation process and a risk relativity mapping process, and may optionally further include an age-specific correction process.

In the risk relativity calculation process, the risk relativity management unit 350 of the operation server 300 designates reference diseases that can be matched to the collateral of the insurance product, and calculates the national health from the institutional server 100 where the national health checkup database is stored. By collecting examination results and medical use records, we detect the number of subjects and number of cases by health grade for standard diseases during a pre-designated period in the same participation group as the customer, and the incidence rate by health grade for each standard disease (number of cases by health grade/ number of subjects), extract the health grade incidence rate with the same health grade as the customer, calculate the total incidence rate (number of cases/number of subjects) of each standard disease, and divide the health grade incidence rate with the same standard disease by the total incidence rate for each standard disease. Calculate the relative risk for the reference disease.

The age-specific correction process is a process in which the risk relativity management unit 350 of the operation server 300 differentiates the risk relativity calculated for each health grade by age, and is performed through conventional corrections such as Greville correction, Beers correction, and Gompertz-Mecham correction. Apply the phosphorus correction method to calculate the corrected risk relativity of the target age. For example, in the age-specific correction process, the risk relativity management unit 350 sets the representative age of the participating group, maps the risk relativity of the participating group to the risk relativity of the representative age, and matches the highest age of the representative age of the participating group. The risk relativity of age groups outside the lowest age is extrapolated, the risk relativity of the target age and the risk relativity of surrounding ages in a pre-specified range are multiplied by the Greville correction coefficient and added to calculate the corrected risk relativity of the target age. do.

For example, if the customer is male, the collateral is a heart disease diagnosis, and the health grade is level 1, in the risk relativity calculation process, the operation server calculates the risk relativity of the first group (under 35 years old) as 49.595482%, and the risk relativity of the second group (under 35 years old) is calculated as 49.595482%. The risk relativity of the group (35-49 years old) is calculated as 27.052523%, the risk relativity of the 3rd group (50-59 years old) is calculated as 27.609818%, and the risk relativity of the 4th group (60 years old and older) is calculated as 27.609818%. can be calculated as 33.765550%.

In addition, the minimum age for national health checkups according to the Framework Act on Health Checkups is 20 years old, and people are eligible for geriatric physical examinations until the age of 80. There are no separate restrictions on national health checkups for ages after that, so the actual age for health checkups is 20 years old. From now on, it is designated as 80 years old.

Accordingly, the representative age of the first group is 27 years [(20+34)/2], the representative age of the second group is 42 years [(35+49)/2], and the representative age of the third group is The representative age of the 4th group is 54.5 years [(50+59)/2], the representative age of the 4th group is 70 years [(60+80)/2], and the representative age of the 5th group is 24.5 years [(20+29)/2 ], the representative age of the 6th group is 37 years [(30+44)/2], the representative age of the 7th group is 49.5 years [(45+54)/2], and the representative age of the 8th group is It is 59.5 years old [(55+64)/2], and the representative age of the 9th group is 72.5 years old [(65+80)/2].

Therefore, in the age-specific correction process, the operation server calculates the relative risk for heart disease for a 27-year-old as 49.595482%, the relative risk for heart disease for a 42-year-old as 27.052523%, and the relative risk for heart disease for a 54.5-year-old. The risk relativity can be calculated as 27.609818%, and the risk relativity for heart disease at age 70 can be calculated as 33.765550%.

Next, in the age-specific correction process, the operation server performs linear interpolation and extrapolation based on the relative risk of heart disease by representative age group (interpolation processing for the 27-70 age range, extrapolation processing for the 20-26 age range and 71-80 age range). ) Process.

Subsequently, in the age-specific correction process, when the target age of the operation server is 40, Greville corrects the risk relativity for heart disease shown in [Table 4] below and the risk relativity of surrounding ages in a pre-specified range (± 4 years). Multiply by the coefficient and then sum to calculate the corrected risk relativity of the target age.

[Table 4]

As a result, in the age-specific correction process, the operation server can calculate the corrected relative risk of heart disease for a 40-year-old man as 29.916968% as shown below.

(0.360697*-0.040724)+(0.345668*-0.009872)+(0.330640*0.118470)+(0.315611*0.266557)+(0.300583*0.331139)+(0.285554*0.266557)+(0 .270525*0.118470)+(0.270971*-0.009872) +(0.271417*-0.040724) = 0.29916968

Meanwhile, in the risk relativity mapping process, the risk relativity management unit 350 of the operation server 300 compares the collateral guaranteed under the terms and conditions of the insurance product with the reference disease, and adds the risk relativity of the collateral to the risk relativity of the reference disease. can be mapped. For example, the risk relativity management unit 350 can analyze data from the Health Insurance Review and Assessment Service and map the risk relativity of the standard disease to the collateral of the insurance product as shown in [Table 5] below.

[Table 5] Relative risk of reference diseases mapped to collateral

This risk relative management unit 350 classifies the reference diseases based on the KCD code in the Korean Standard Classification of Diseases and Causes of Statistics of the National Statistical Office, and categorizes the collateral guaranteed under the terms and conditions of the insurance product based on the KCD code, and If the KCD code of the matched reference disease includes all KCD codes of the collateral, the risk relativity of the reference disease is mapped to the risk relativity of the collateral.

For example, if the KCD code guaranteed under the terms and conditions of the collateral cancer diagnosis is C00~C96, and the KCD code of cancer occurrence, which is the reference disease matched to the cancer diagnosis, is C00~C96, in the risk relative mapping process, the operation server The relative risk of cancer occurrence is mapped onto the diagnosis. In addition, if the KCD code guaranteed under the terms and conditions of cancer diagnosis is C00~C90, and the KCD code for cancer occurrence is C00~C96, in the risk relativity mapping process, the operation server maps the risk relativity of cancer occurrence to the cancer diagnosis as is. .

In addition, if the KCD code of the reference disease matched to the collateral does not include all of the KCD codes of the collateral, the risk relativity management unit 350 maps the risk relativity of the reference disease limited to the KCD code of the collateral or uses the standard as follows: The risk relativity of disease is mapped to the risk relativity of collateral.

Risk relativity of collateral = Risk relativity of the reference disease with a KCD code overlapping with the collateral Risk relativity of a reference disease with a KCD code that deviates from the KCD code of

At this time, the pre-designated period may be designated as the last 1 to 10 years.

Referring to Figure 1, the method for calculating the discount rate of additional insurance premiums according to the present invention includes a discount rate calculation step (S500).

The discount rate calculation step (S500) is a step in which the insurance company server 400, which has received the risk relativity information from the operation server 300, calculates the discount rate of the additional insurance premium of the insurance product based on the risk relativity information. The additional insurance premium discount rate can be provided by the operation server 300.

Specifically, in the discount rate calculation step (S500), the insurance company server 400 calculates the net premium difference for each collateral of the insurance product based on the risk relativity provided by the operation server 300, and calculates the net premium difference for each collateral and the insurance premium. The total net insurance premium difference of the insurance product is calculated based on the product's existing subscriber information, and the additional insurance premium discount rate reflecting the total net insurance premium difference is calculated. Here, the existing subscriber information of the insurance product includes the gender distribution, age distribution, subscription rate by insurance collateral, and insurance collateral of subscribers who have previously subscribed to the insurance product by the time the premium calculation application information is received by the insurance company server 400. It includes one or more of the insurance amount, coverage period, and payment period.

At this time, the net insurance premium difference for each collateral of the insurance product can be calculated using [Equation 1] below.

[Equation 1]

Net insurance premium difference by collateral =

×

×

×

이고, 는 ()세의 보험담보별 평균 연간 위험발생률이고, 는 건강등급이 (등급)인 ()세의 보험담보별 연간 위험발생률이고, 는 ()세 중 보험사고 미발생자수이고, 는 건강등급이 (등급)인 ()세 중 보험사고 미발생자수이고, 는 ()세 중 보험료 납입자수이고, 는 건강등급이 (등급)인 ()세 중 보험료 납입자수이다.At this time, is the net insurance premium by insurance coverage, is the insurance subscription age, is the insurance premium payment period (years), is the number of years elapsed from the time of insurance subscription to the period of health grade recalculation, is the number of years (years) elapsed since signing up for insurance, Is

ego, Is ( ) is the average annual risk occurrence rate by insurance coverage, is the health level ( grade)in ( ) is the annual risk occurrence rate by insurance coverage, Is ( ) is the number of people who did not experience an insurance accident among the three, is the health level ( grade)in ( ) is the number of people who did not experience an insurance accident among the three, Is ( ) is the number of insurance premium payers, is the health level ( grade)in ( ) This is the number of insurance premium payers.

Additionally, the total net insurance premium difference for an insurance product can be calculated using [Equation 2] below.

[Equation 2]

At this time, is the insurance subscription amount by insurance collateral of the customer (age x) who sent the insurance premium calculation application information, is the average subscription rate by insurance coverage for the same gender and age (x years) as the customer (x years), is the net insurance premium difference per insurance amount for each insurance collateral of a customer (x age) with class k.

In addition, the additional insurance premium discount rate reflecting the total net insurance premium difference can be calculated using [Equation 3] below.

[Equation 3]

At this time, is the total net insurance premium difference for the relevant insurance product of the customer (age x, class k), is the business insurance premium charged to age X under the same conditions as the customer for the relevant insurance product.

Although the present invention has been described above with reference to preferred embodiments, those skilled in the art can make various modifications and changes to the present invention without departing from the spirit and scope of the present invention as set forth in the claims below. You will understand that it is possible.

100: Institutional server 110: Medical record information database
200: Customer terminal 210: Insurance application management app
300: Operation server 310: Communication department
320: Medical record information collection department 330: Participation group management department
340: Health grade management department 350: Risk relative management department
360: Storage unit 400: Insurance server

Claims (10)

A URL request step in which the customer terminal connects to the operation server through a communication network, provides member information including personal information and insurance product selection information, and requests provision of a URL;
The operation server extracts the customer's individual identifier from the personal information, extracts the insurance company and insurance product identification code from the insurance product selection information, generates a customized identification code, and generates a URL containing the customized identification code to create a URL. A step of providing a URL in response to a customer terminal requesting provision of a URL;
When the customer terminal accesses the website provided by the operation server through the URL containing the customized identification code and provides application information and personal authentication information for calculating insurance premiums for insurance products, the operation server analyzes the URL and provides insurance product information. An application reception step for extracting optional information;
A medical record information collection step in which the operation server provides personal authentication information provided from a customer terminal to an institutional server and then collects medical record information matched to the personal authentication information from the institutional server;
The operation server analyzes the application information and selects a participation group according to the customer's gender and age, and analyzes the medical record information through a health rating program based on a health evaluation model to determine the health rating of the customer associated with the participation group. Calculating health grade calculation step;
A risk relativity calculation step in which the operation server generates risk relativity information by calculating a risk relativity for the customer's health grade for each collateral of the insurance product; and
It includes a discount rate calculation step in which the insurance company server, which has received the risk relativity information from the operation server, calculates the discount rate of the additional insurance premium of the insurance product based on the risk relativity information,
In the risk relativity calculation step, the operation server calculates the number of health accidents corresponding to insurance coverage in the same health grade based on the number of subjects classified by health grade in the participating group to which the customer belongs, divided by the number of subjects as a percentage value. Calculate the incidence rate by health grade of each collateral for the insurance product, calculate the total incidence rate of each collateral in the above participating group, and divide the incidence rate by health grade of collateral by the total incidence rate of the same collateral to obtain the risk relative degree by health grade of each collateral. Calculate, generate risk relativity information by extracting the risk relativity matched to the customer's health grade from the risk relativity for each health grade of each collateral, and provide the risk relativity information to the insurance company server.
In the discount rate calculation step, the insurance company server calculates the net insurance premium difference for each collateral of the insurance product based on the risk relativity provided by the operation server, and calculates the net insurance premium difference for each collateral and the existing subscriber information of the insurance product. A method for calculating the discount rate of additional insurance premiums, characterized by calculating the total net insurance premium difference of the product and calculating the additional insurance premium discount rate reflecting the total net insurance premium difference. delete According to claim 1, the existing subscriber information is
Any of the gender distribution, age distribution, subscription rate by insurance coverage, insurance subscription amount by insurance coverage, coverage period, or payment period of subscribers who have previously subscribed to the insurance product by the time the application information for calculating the premium is received by the insurance company server. A method of calculating the discount rate of additional insurance premiums, characterized in that one or more are included.
delete According to claim 1,
The discount rate of additional insurance premiums, characterized in that the operation server corrects the incidence rate for each health grade of each collateral using a smoothing method using a statistical model, and calculates the risk relativity for each health grade of the collateral based on the corrected incidence rate for each health grade of each collateral. Calculation method. The method of claim 1, wherein the risk relativity calculation step is
The operation server specifies standard diseases that can be matched to the collateral of the insurance product, collects national health checkup results and medical use records from the institutional server where the national health checkup database is stored, and collects national health checkup results and medical use records for a pre-designated period in the same participating group as the customer. Detect the number of subjects and number of patients by health grade for standard diseases, calculate the incidence rate by health grade for each standard disease, extract the incidence rate of the health grade with the same health grade as the customer, and calculate the overall incidence rate of each standard disease. , a risk relativity calculation process that calculates the risk relativity for each reference disease by dividing the health class incidence rate of the same reference disease by the total incidence rate, and
Discount rate of additional insurance premiums, wherein the operation server compares the collateral guaranteed under the terms and conditions of the insurance product with the standard disease and maps the risk relativity of the standard disease to the risk relativity of the collateral. Calculation method. The method of claim 6, wherein the risk relativity calculation step is
The operation server sets the representative age of the participating group, maps the risk relativity of the participating group to the risk relativity of the representative age, and extrapolates the risk relativity of age groups outside the highest and lowest ages of the representative age of the participating group. And, the risk relativity of the target age and the risk relativity of surrounding ages in a pre-specified range are multiplied by the Greville correction coefficient and then added to calculate the corrected risk relativity of the target age. Characterized in that it further includes an age-specific correction process. How to calculate the discount rate of additional insurance premiums. The method of claim 6, wherein the risk relativity mapping process is
The operation server classifies the reference diseases based on the KCD code in the Korean Standard Classification of Diseases and Causes of Death by Statistics Korea, and the collateral guaranteed under the terms and conditions of the insurance product is classified based on the KCD code, and the KCD of the reference disease matched to the collateral. If the code includes all of the KCD codes of the collateral, the risk relativity of the reference disease is mapped to the risk relativity of the collateral. If the KCD code of the reference disease matched to the collateral does not include all of the KCD codes of the collateral, the math below is used. A method for calculating the discount rate of additional insurance premiums, characterized by mapping the risk relativity of the reference disease to the risk relativity of collateral through Equation 1.
[Equation 1]
Risk relativity of collateral = Risk relativity of the reference disease with a KCD code overlapping with the collateral Risk relativity of a reference disease with a KCD code that deviates from the KCD code of delete delete