JP2005182587A - Insurance model creation system - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an insurance model creation system for reducing resale risks of a property of which the reasonable price is unknown at the time of resale, such as immovables. <P>SOLUTION: Data 3 peculiar to a house which a house owner owns, such as a purchase time, a price, and the location of the house is inputted as individual risks by a terminal 15a or the like. Data relating to market risks such as entire immovables data 4, financial market data 5, and macro data 6 are always updated and stored in a system 1 besides the individual risks, and one or more insurance models for the house are created from the individual risks and market risks, the income and expenditure of insurance premiums and insurance money payment, risk management data 9, etc. by an arithmetic means 12 and are displayed on the terminal 15a or the like, and the house owner makes an insurance contract when finding an appropriate model. <P>COPYRIGHT: (C)2005,JPO&NCIPI

Description

  The present invention relates to a system for creating an insurance product that compensates for the price fluctuation risk at the time of resale for a property that does not actually have an open market, such as real estate or intellectual property rights.

  Because there is virtually no open market for certain properties such as real estate and intellectual property rights, the objective price of these properties is unknown at the time of resale. In addition, there is a possibility that a large price risk such as a drop in price may occur when reselling.

Hereinafter, the above points will be described by taking real estate as an example.
Real estate is an expensive property, and for most individuals it is the biggest purchase in their lifetime. On the other hand, due to changes in the family structure, changes in work locations, changes in the living environment of individuals who own real estate, such as retirement, there are not a few reasons for replacing real estate.

  Real estate prices fluctuate significantly due to changes in the characteristics of each real estate, such as changes in the general society such as changes in the economic situation, deterioration in sunlight, noise in the neighborhood, changes in convenience such as shopping, etc. Since there is no open market, objective market prices are unknown. Therefore, real estate owners are actually investing in very risky assets, even though they have little awareness that they are investing in the real estate. In addition, since it is often purchased with a relatively small down payment, leverage (insulator) becomes a more dangerous speculation that acts strongly. In addition, because buying and selling is not easy, there is also a problem that once it is purchased, risk control cannot be performed even if it wants to respond to changes in the market.

As a result, the purchase of real estate incurs a great risk without being conscious of general individuals, and a situation in which an individual's daily life base is influenced by fluctuations in real estate prices.
In other words, possessing property with a very high risk, such as real estate, has many harsh situations for real estate owners such as seizure of real estate due to a significant drop in the price of real estate purchased during the bubble period, personal bankruptcy, etc. We know that it is happening.

  On the other hand, from a social point of view, social burdens such as loan delinquency and auction procedures for seized property increase. As a result, personal property purchases mean that a completely amateur in real estate transactions is investing in a very high-risk investment without any risk hedging, for example, without a license. It is like wearing a helmet and riding a motorcycle without a helmet, and considering society from the viewpoint of real estate ownership as an investment, it is extremely dangerous and abnormal that most real estate owners are such unlicensed drivers In other words, it is necessary to say that accidents such as personal bankruptcy have occurred as much as possible.

  Actually, in order to hedge the risks related to real estate, real estate prices are expensive and require huge expenses and organizations, and amateur individuals own, for example, a large number of real estate and risk them as a portfolio. Hedging is virtually impossible. In such an environment, it is harsh for an individual to bear all the risks, and when an accident occurs, not only the individual but also a social loss occurs. Therefore, it is necessary to construct a system that separates at least a part of this risk from individuals and places it on a specialized system that can risk hedge. For the first time, individuals can live a safe life that is separated from risks. From a social perspective, the increase in the number of individuals living such a stable life means an increase in consumption, a decrease in social anxiety, etc. It will include many positive factors.

Although there is no prior art related to a system constructed from the viewpoint of responding to the above request, the following techniques can be cited as references for some of the elements constituting the system.
JP 2003-022314 A JP 2002-366628 A

Each of the above technologies is a program or system for estimating the price fluctuation of real estate, and nothing is shown regarding the hedge of the real estate risk resulting from the price fluctuation.
For this real estate risk hedging, an insurance system called “housing asset insurance” has been considered on the desk, but it has not been commercialized due to the following difficulties.

Housing asset insurance is roughly divided into two categories.
The first is insurance paid to compensate for the difference (decrease) between the sale price when the real estate is actually sold and the purchase price when the real estate was purchased once. This insurance has a problem that if the buyer and seller are informed, the difference can be increased to obtain a larger amount of insurance (fraud).

  The second is insurance that creates a real estate index or pricing model that shows standard real estate prices, uses these as the basis for real estate valuation, and pays insurance money regularly or when the real estate is sold. However, in real estate with a strong individuality, the error in the price determined artificially by such an index is large, and as a result, it is difficult to obtain high confidence from the insurance subscriber, and the insurance amount presented by the insurance company It is also conceivable that the real estate owner who is the insurance subscriber is not convinced about the insurance premiums.

  Real estate prices are not risks that can be estimated to some extent by past probabilities, such as deaths that are covered by life insurance and accidents that are covered by non-life insurance. It is a hedged insurance, and it is necessary to perform detailed evaluation for each individual case and set insurance conditions such as insurance premiums according to the risk of the target asset and contract conditions (insurance amount, etc.). In addition, there may be market risks that cannot be eliminated, such as fluctuations in real estate prices nationwide. Moreover, because individual real estate is not homogeneous, it is not possible to decide on insurance content as easily as life insurance. For this reason, continuous risk management and data correction are required, so the processing amount is enormous and management by a computer is required.

  The present invention is configured in view of the above requirements, and is a system for setting insurance conditions for individual assets to be insured, such as individual real estate, and data for managing the risk of the insured And means for calculating the risk for the specific insurance object from these risk data, and means for individually setting insurance conditions for the specific insurance object based on the risk for the specific insurance object. It is an insurance system.

  For example, with regard to a specific real estate property consisting of land and houses, the specific real estate risk, the price trend of the real estate market as a whole, and the data such as financial market data are constantly updated, so that the latest data can be used for the specific real estate. Highly accurate risk management is possible. By setting insurance contract details for each specific property based on the risk of this specific property, the property owner can hedge the risk of property price fluctuations, and the insurance system manages the overall risk It becomes possible.

  Real estate owners who have exercised their insurance content by comparing the purchase price of real estate preset as the contract details with the market price of the real estate that the real estate owner has inferred (appraised) at the expiration of the preset deadline If it is deemed advantageous, it is sufficient to exercise the right, and if it is considered unfavorable, it is sufficient to continue possessing the property without exercising the right.

  Various risk information data that changes from moment to moment is input in near real time, and the data is updated, so when setting insurance for a specific property, it is possible to instantly propose multiple insurance contract models specified for that property Thus, it is possible to conclude an insurance contract specified for the real estate at the time of the real estate purchase contract.

  Individuals are vague with respect to the future because most of the price fluctuation risk when buying and selling real estate, which had previously been accepted by individuals and other homeowners, can be entrusted to specialized organizations that implement insurance, such as insurance companies. Anxiety is reduced and there is no suspicion related to the wisdom and claims of real estate sellers and buyers as in the case of traditional housing asset insurance.

  Computer terminals are installed at banks and other places where loans are handled, and these terminals are operated by an insurance company that operates and sets up an insurance system (hereinafter referred to as “insurer”) and the Internet. Etc. are connected via communication means such as.

For real estate that the individual owns or has decided to purchase, data specific to the real estate property, such as the location, size of the real estate, and the building year of the house, is input in advance to a predetermined terminal by an expert.
The data of these specific real estate is input to the insurance operator's calculation system, and the insurance operator will set one or more insurance conditions such as insurance period (maturity), insurance amount (exercise price), insurance premium, etc. corresponding to this real estate. And presented to the terminal. From these presented insurance conditions, the homeowner selects an insurance condition that suits him and makes an insurance contract. Hereinafter, the contract conditions similar to the individual insurance presented by the insurance practitioner including the examples are referred to as “insurance model”.

FIG. 1 shows an embodiment of the present invention, and shows an insurance setting system relating to a residential land and a house provided in the residential land (hereinafter referred to as “house” including these land and house).
Reference numeral 1 denotes an insurance model creation system for an insurance operator. To this system 1, terminals 15a, 15b, 15c... Such as personal computers are connected via communication means 16 such as the Internet. . This terminal may be, for example, a terminal of a homeowner who owns a house in addition to being placed at a bank loan counter or a business that operates real estate.

Next, the configuration of the insurance model creation system 1 will be described in detail.
Reference numeral 2 is various data that is constantly accumulated and updated as risk management information, and reference numeral 3 is data relating to a specific house for which an insurance model is created (hereinafter referred to as “target property data”). This is pre-input data when buying and selling real estate. If more detailed data is required, it is input to the system 1 using the terminal 15a or the like when considering the insurance.

  The data to be input indirectly through a bank clerk, etc. includes the purchase price (assessment) 3a of the house, the location 3b of the house, presence / absence 3c of administrative regulations such as building coverage ratio, height regulation, reinforced concrete, wooden structures, etc. It is 3d etc., such as a building structure and the scale of a structure. Reference numeral 3e is a negative factor for the house such as avoidance factors related to the house, such as noise problems and poor sunlight. This avoidance factor 3d is included in the assessment of the house price at the time of setting the loan, and is input as the target real estate data 3, so there is no need to input a new one. In principle, this avoidance factor 3d is not disclosed to homeowners. The target real estate data 3 is used as an individual risk for the house when creating an insurance model for the house.

  Reference numeral 4 is real estate market data, 5 is financial market data, and 6 is macro data, both of which are market risks as a large economic flow involving the individual house, with respect to individual risks specific to the individual house. It is about. In other words, the evaluation of an individual house is evaluated based on two risks: the inherent risk of the house and the market risk that encompasses the individual house.

  Among the market risks, first, the real estate market data 4 indicating the trend of the entire real estate market will be described. Note that the real estate market here does not mean the market as a place where individual properties are directly traded as described in the section of the conventional example, but rather the general trend of real estate transactions as seen from individual real estate transactions. is there.

  First, the overall price trend 4a is, for example, rough price trend data indicating whether the domestic real estate price fluctuates, that is, whether the price is on an uptrend or a downtrend. This data is configured so that the latest data is input by constantly storing or changing information such as various economic reports in real time.

  Next, the regional price trend 4b may be, for example, a price trend in a clearer area such as the Tokyo metropolitan area or Nagano city, in addition to a price trend in a somewhat vague area such as an urban area or a suburb. . In this case, the line price 4c, which is an evaluation as a taxable object, may be converted into data. These data are also configured to update the data in real time as much as possible.

  In the financial market data 5, for example, market prices such as fluctuations 5a of government bonds, TOPIX, real estate investment trusts (REITs, etc.) 5b, fluctuations 5c of real estate company stocks, etc. are input. Since these data are published as accurate numbers from time to time, it is preferable to automatically drop these data into a database forming the financial market data 5 using an online system or the like. This financial market data 5 is used not only as a market risk when evaluating individual houses, for example, but also as a risk hedging means in an insurance system constructed by an insurer with a large number of insurance subscribers. Of course, it can also be used as derivative data.

  The macro data 6 is the most macro information as the risk management information, and is data that is considered to have an influence on the market risk, which is one of the risks that influence the house price and the like. Reference numeral 6a indicates economic trends forecasts announced by various think tanks or the Bank of Japan, etc., data 6b such as forecasts of the current and future gender, demographic composition by age, etc., political stability, etc. Data 6c on changes in political situation, changes in the regional industrial population, changes in government policies, etc. that are said to be given, but not shown in the figure, changes in taxation, housing starts, capital investment indices, GDP, and other market risks It is desirable to input more data that seems to give It is desirable that the data is updated so that these data are also automatically dropped into the database.

  Reference numeral 7 is premium income data, which is data of the total amount of premium income based on an insurance contract, which will be described later, and income from the resale of purchased houses, etc., and is an important source of funds for configuring the insurance system. It will become one. Reference numeral 8 denotes a total amount of money (insurance money) spent when purchasing the target house based on the insurance contract, and is an amount deducted from the insurance resources.

  On the other hand, it is necessary to manage the risks of the above resources by operating them appropriately. Reference numeral 9 is a database for stochastically accumulating data (hereinafter referred to as risk management data) such as balance and prediction, risk reserve for operating the system soundly, and risk reserve data (hereinafter referred to as risk management data). Normally, purchased properties are sold immediately and do not need to be managed. However, if the negotiation with the seller is not established or the seller does not appear, it is necessary to manage the purchased property for a certain period (reference 9a). Market risk that cannot be eliminated by a portfolio based on the law of large numbers is hedged by reinsurance (reference 9b).

  In addition, market risks such as price movements of the entire real estate, such as a significant drop in the entire real estate price due to the collapse of the bubble economy, cannot be eliminated by diversified investment. In this case, in addition to reinsurance, methods such as hedging by combining various financial products and securitizing insurance income to transfer risk are implemented (reference 9b).

The above point will be described in more detail as follows.
Unlike normal fires, accidents, or individual deaths, property prices fluctuate in the same direction to some extent all at once. Therefore, if the price falls significantly, it is expected that the insurance system cannot be maintained with premiums and profits from the investment (earthquake insurance is an insurance that deals with the same nature).
To hedge some of these market risks, for example, short (sell) financial products moving in the same direction, long (buy) financial products moving in the opposite direction of the real estate market, reinsurance, joint insurance, Contingency reserve is considered.

  In addition, the development of financial technology (securitization) and marketization has made it possible to cover such market risks in the capital market. In other words, the pooling stabilization effect is small as in the above insurance system, so the “Law of Large Numbers” is not effective, and even if the insurance market capacity is insufficient for risk hedging, it is correlated with this insurance market. It is possible to cover the capital market with a low nature. For example, a system is constructed in which the risk pool is transferred to a special purpose company (SPC), and this SPC issues bonds and buys the investors to pass the insurance payment risk to the investors.

Figure 2 shows this bond issuance system based on deposits and withdrawals as seen from the investor side.
For example, SPC issues a bond of A yen (for example, 1 million yen). When an investor purchases A yen (in the case of one unit), a huge amount of money enters the SPC at a time, thereby preparing for a large market fluctuation.

  When there is no loss due to market risk by the maturity, A yen, which is the purchase price of bonds, is redeemed at maturity. On the other hand, in the event of damage, the (A-N) yen, which is deducted N yen in proportion to the amount of damage, will be redeemed to investors. In some cases, the contract is not redeemed at all.

  The assessment of the reduction is carried out by calculating with a computer using a mathematical formula determined in advance based on a numerical value obtained by a third party such as an official land price, not an actual insurance payment amount. These ingenuity stems from the fact that the exact price of an asset is not known, and is used to make the insurance system objective, clarified and expedited.

  In this way, bonds issued by SPC have a relatively high risk for investors, so in return, a portion of insurance premiums (option fees) is added, and coupons paid from SPC to investors in each fiscal year until maturity (C1, C2,...) Is set higher than the interest of ordinary investment, and is set as a so-called high risk / high return product. In this way, market risk has been transferred to investors. Incidentally, the insurance system and SPC are legally separated.

  Next, reference numeral 10 is a database that stores data for configuring an insurance model, which is a contract content presented to the homeowner when the insurance provider concludes an insurance contract with the homeowner. Reference numeral 10a is data on the timing of the exercise of the insurance, that is, the time when the individual decides whether or not to request the insurance operator to purchase the housing for the insurance target. It is converted into data as ten years, 20 years or 30 years, or as a term or period that can be exercised at any time.

  The purchase price indicated by reference numeral 10b is the purchase price of the house by the insurance operator at the insurance exercise period 10a. The homeowner corresponds to the price of the house at that time, as will be described in detail later. It is possible to decide whether to request the purchase of a house (exercise of option) or to continue to own the house without making a claim.

  The partial compensation indicated by reference numeral 10c means that when the option is exercised, if the house price is significantly lower than that at the time of purchase and the amount falls below a predetermined amount (minimum compensation amount), insurance This is price data for setting the content of an option that the implementer refuses to purchase or a contract for reducing the purchase amount.

  The calculating means 11 calculates one or more insurance models for the specific house by calculating the risk evaluation of the above data for each specific house using a probabilistic statistical method. On the other hand, it is presented through the terminal 15a.

  First, an insurance provider such as an insurance company inputs specific data related to a home owned by the homeowner or to be purchased after conducting a survey. This unique data is the data to be recorded in the target real estate data 3 of the risk management information 2 in the insurance model creation system 1, that is, the purchase price (assessment) 3a of the house, the location 3b of the house, various administrative regulations 3c, The structure, scale, etc., of the house, and the presence / absence of an avoidance factor 3e for the house.

In the insurance model creation system 1, insurance revenue data 7, purchase expense expenditure data 8 and risk management data 9 are input to the calculation means 11, and the financial status of the entire insurance system is calculated.
Also, the latest risk management information 2 including individual data as the target real estate data 3 and market risks such as real estate market data 4, financial market data 5, macro data 6 and the like is input to the calculation means 11.

  Based on the insurance contracts that have been concluded and currently contracted, the housing of a specific individual that is based on the current and future forecasted income and expenditure status of the entire insurance system and the income and expenditure forecast and output from the risk management information 2 above Based on the risk management information 2 for the contract, the predetermined data is drawn from the data of the contract content database 10, the insurance premium 12 is set, the other contract content 13 is set, and the individual who owns the house operates through the server 14. Presents the insurance model set for the terminal.

FIG. 3 is a diagram (payoff diagram) showing a basic system of insurance contents to be presented.
This insurance is sold as a “put option” in terms of finance, where the individual owning the house can claim that the insurer buys the insured house at a pre-determined price at a specific time in the future. This is a “buy” of the right, and the insurance has a special agreement that the homeowner purchases the right of “buy” at the time of the insurance contract.

Hereinafter, a specific example will be described.
The description will be made on the assumption that the home owner contracts the following insurance presented by the insurance model creation system 1 shown in FIG.
In other words, a special contract that allows an insurer to make a purchase request for 30 million yen (exercise price) for a house purchased by a homeowner who is an insurance subscriber for 40 million yen, with a maturity of 30 years. (Option fee) Suppose you pay 200,000 yen and make a contract.

  In the payoff diagram of FIG. 3, the vertical axis shows the payoff (loss / loss, that is, the profit and loss of the insurance subscriber and the insurer), and the horizontal axis shows the house price at the maturity (30 years after the insurance contract in the above insurance). . At maturity, the house price is 0 to 30 million yen, or a solid line portion of 30 million yen or more.

  If it is determined that the price of the insured house has fallen to 25 million yen, for example, at a maturity of 30 years after the contract, if the homeowner exercises his / her rights, the insurance provider such as an insurance company will It will be purchased for 30 million yen based on the insurance contract. As a result, the homeowner can obtain a gain of 5 million yen with respect to the current price of the home.

  Conversely, if it is determined that the price has risen to 45 million yen, for example, the homeowner can abandon the option and own the home at this price. Homeowners assess (appraise) the price of their homes at the expiration of the insurance contract. This evaluation is performed by the individual homeowner. In any case, in this insurance, there is no price determination work by the insurance operator, and the property is that the home owner who is the insurance subscriber determines the price and decides whether or not to exercise the option.

  The homeowner can exercise the so-called “good right to take advantage of” that can decide whether or not to exercise the option in consideration of whether the exercise of the option is advantageous to himself or herself according to the above valuation It becomes. For this reason, even if it becomes necessary to sell the house before it reaches maturity, it can be expected that the sale price will be increased if it is sold with this insurance. If this insurance is attached, the collateral value of the house will increase, so it is expected that the loan interest rate and the guarantor-set price can be reduced.

On the other hand, for insurance providers, if the homeowner does not exercise the option, the insurance premium (option fee) at the time of contract is directly used as income.
In other words, the insurance money of the insurer varies from 30 million yen for the house price of 0 yen to 0 yen for the house price of 30 million yen or more (thin solid line), while the homeowner (contractor) is 30 million as shown in the bold line in the figure Up to the yen, 30 million yen will be compensated by the transfer of houses (horizontal part of the thick line), and if you evaluate it as 30 million yen or more, you can continue to own the house that has increased the price without exercising options (the diagonal of the thick line) portion). In other words, in any situation, insurance subscribers will be compensated for a value of 30 million yen.

  Fig. 3 shows the basic structure of the insurance system. Actually, it is difficult to compensate for the housing price of 0 yen based on the risks associated with changes in social and economic conditions and the income and expenditure of the insurance system. Yes, various maturity models, compensation price ranges, insurance premiums corresponding to this, etc. are set, and homeowners respond to insurance models that they consider advantageous from the various insurance models presented You will make an insurance contract. Below are some examples of insurance models.

FIG. 4 shows a second insurance model following FIG.
The model shown in this figure is as follows. That is, this model, like the first insurance model, has the same exercise price of 30 million yen for insurance subscribers, but it is possible for an insurance implementer to refuse purchase when the price is below a certain price. Contract model.
In other words, for the housing with a purchase price of 40 million yen that is the target of the insurance model in Fig. 2, the purchase price (K ₁ ) of 30 million yen can be exercised with a maturity of 30 years as in the first model. . Next, in the case of an insurance provider, 15 million yen is set as the purchase refusal price (second option price) (K ₂ ), and if the insurance provider evaluates that the target house is 15 million yen or less, the insurance operator The purchase is refused as an option (second option) on the side, and an amount of 15 million yen is paid.

In this case, if the insurance subscriber evaluates the target house as less than 30 million yen and exercises the purchase price (K ₁ ) 30 million yen (exercises the first option), If it is evaluated as 15 million yen or less (exercising the second option), the second option is executed, and 15 million yen will be paid to the insurance subscriber by refusal to purchase as described above. Here, since the insurance proponent assessed it as 15 million yen or less, the loss when owning a house that was paid 30 million yen and evaluated it as 15 million yen or less (assess that the loss amount is 15 million yen or more It is estimated that a gain of the difference can be obtained by paying 15 million yen.

  On the other hand, although the homeowner refuses to purchase for 30 million yen, he can get 15 million yen insurance money and has the ownership of the house as it is. Expected.

  In addition, if the homeowner evaluates it as 30 million yen or more, the option can be continued without owning the option as in the case of FIG. In addition, the ellipse part of the thick line in a figure shows the case where a homeowner owns a house, and the ellipse part of a dotted line shows the case where an insurance implementer owns a house by purchase. In this case, the insurance means is reduced from 200,000 yen in the case of FIG. 2 to 150,000 yen, for example, so that the attractiveness of the insurance is not reduced. Set.

FIG. 5 is a flowchart showing the above flow.
That is, when the insurance contract expires, the insurance subscriber who is the home owner evaluates his / her own house and determines whether the evaluation value of the house is less than 30 million yen or more than 30 million yen (S1). . If it is evaluated as 30 million yen or more, the ownership of the house is continued and the insurance contract is terminated (S2).

  On the other hand, when it is determined that the price is less than 30 million yen, the option (first option) is exercised and the purchaser is requested to purchase the insurance (S3). In response to the first option by the insurance subscriber, the insurance operator evaluates the house (S4), and if the evaluation is 15 million yen or more, purchases it at 30 million yen (S5).

  On the contrary, if the value is less than 15 million yen, the insurer exercises the option (second option) (S6), refuses to purchase the house, and pays 15 million yen to the insurance subscriber ( S7).

  Even in the case of the above insurance contract, individual risks themselves are eliminated, which is advantageous for insurance subscribers, and real estate prices change (for example, decrease) in a certain direction as a whole due to market risks. When a homeowner who is an insurance subscriber replaces another home, the replacement risk can be hedged because the prices of other real estate properties are also decreasing.

FIG. 6 shows a third insurance model.
In this model, the second option price K ₂ of the put option is set to 5 million yen, and K ₁ -K _{2 is set} to 25 million yen, so that compensation for fluctuations in the house price is set wider (thicker compensation) than the second model. . In this case, the insurance money at the time of contract is set higher than that of the second model corresponding to the compensation. Alternatively, the insurance model is set so as to balance the payoff with a maturity of, for example, 10 years. As in the case of FIG. 3, the bold oval portion indicates the case where the homeowner owns the home, and the dotted oval portion indicates the case where the insurance operator owns the home by purchase.

FIG. 7 shows a fourth insurance model.
In this model, the second option price K ₂ of the put option is set to 25 million yen, and K ₁ -K ₂ is reduced to 5 million yen. Since this model has the narrowest compensation range including the above model, the insurance money is reduced to, for example, 100,000 yen correspondingly. Alternatively, the content is set so that it is balanced as a long-term contract.

  In the above embodiment, the real estate that is covered by the insurance has been described as an example. However, since there is no open market for various rights including receivables, intellectual property rights, so-called branded goods, there is an objective price at the time of resale. Set insurance model for assets that are unknown. Reduce risk of price fluctuations through appropriate and fair insurance-like contracts corresponding to insurance models.

  A system is constructed so that information can be exchanged between the insurance practitioner and those who are considering insurance. In other words, the insurer sets up his / her own website on the Internet, and the homeowner who wants to join the insurance enters his / her own terminal, and the insurer enters one or more insurance models for the home by entering various patterns of conditions. Present. If the homeowner has a model that suits them, the homeowner will fill in a predetermined file on the website and will make a formal insurance contract at a later date.

  In addition, a network is formed between a large number of real estate brokerage agents and insurance providers, and individuals confirm the insurance model related to the real estate using a terminal placed in the real estate brokerage agent at the time of real estate acquisition contract, and insurance It can also be configured to make a contract.

It is a block diagram of an insurance model creation system showing an example of the present invention. It is a diagram which shows the payment / receipt state seen from the investor side in issue / purchase of bonds. It is a diagram (payoff diagram) showing a first model which is a basic configuration of an insurance model. It is a diagram which shows the 2nd model of an insurance model. It is a flowchart which shows the implementation state of the 2nd model of FIG. It is a diagram which shows the 3rd model of an insurance model. It is a diagram which shows the 4th model of an insurance model.

Explanation of symbols

1 Insurance model creation system 2 Risk management information 3 Target real estate data (individual risk)
4 Real estate data (market risk)
5 Financial market data (market risk)
6 Macro data (market risk)
7 Insurance premium revenue data 8 Purchase cost expenditure (insurance expenditure) data 9 Risk management data 10 Contract content database 11 Calculation means 12 Insurance premium 13 Contract content 14 Servers 15a to 15c Terminals (personal computers)
16 Communication means

Claims (7)

A model with a function similar to insurance that reduces the risk of price fluctuation when reselling an asset whose objective price at the time of resale is unknown due to the absence of an open market or a market that is extremely inadequate, such as real estate A system to be configured, data accumulated as risk management information, risk management implementation data as an insurance system, and balance data of an insurance system including at least premium income data and expenditure data such as insurance money, It has a contract content database that stores the details of insurance contracts, and a calculation means for calculating and creating a predetermined insurance model from each of these data. The calculation means is obtained from each data based on the risk of individual assets to be insured. It is configured to create and present one or more insurance models corresponding to the specific asset by calculating the calculated data Insurance model creation system that characterized the door. 2. The insurance model according to claim 1, wherein the data as the risk management information includes individual data specific to a specific asset and market data that affects evaluation of the entire asset including the specific asset. Creation system. The asset is real estate, and individual data is data specific to the real estate such as purchase amount, location, administrative regulations for the real estate, structure and size of the building, or avoidance factors, and market data is the overall real estate The insurance model creation system according to claim 2, wherein the insurance model creation system is overall real estate data indicating price trends and the like, financial market data, and macro data such as economic trends. The insurance model creation system according to any one of claims 1 to 3, wherein each risk in the risk management data is risk management data based on a portfolio composed of a plurality of assets. The insurance model creation system according to any one of claims 1 to 4, wherein, among the risk management data, market risk is risk management data based on derivatives and asset securitization. The contract content database stores at least the maturity of the contract, the purchase price of the target asset as insurance money, and the evaluation value of the asset that can be purchased. 6. The insurance model creation system according to claim 1, wherein one or more insurance models including an insurance premium corresponding to a specific asset are created and presented from the data. The system is connected to a large number of terminals via communication means such as the Internet, and the input of data specific to a specific asset and the display of the insurance model in the insurance model creation are performed via this terminal. The insurance model creation system according to claim 1, wherein the insurance model creation system is configured.

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