JP7797446B2 - Financial product proposal device and financial product proposal method - Google Patents

Description

The present invention relates to a financial product proposal device and a financial product proposal method.

While various measures have been taken to address global environmental issues in recent years, there is an increasing need for companies to conduct business activities that take into account the risks of climate change.

Weather derivatives have been proposed as financial instruments that allow companies to hedge against the risks arising from such climate change. Weather derivatives are financial instruments that hedge (reduce) corporate losses (reduced sales or increased expenses) that may arise from abnormal or unseasonable weather.

As an example of technology related to the operation of weather derivatives, Patent Document 1 describes how, when ID information is received from a trading terminal or a customer terminal, the trading company server transmits the ID information to the power company server, and when the number of tradable lots is received from the power company server, the trading company server transmits the number of tradable lots to the trading terminal or customer terminal. As a result, the number of tradable lots is displayed on the display screen of the trading terminal or customer terminal, and when the selected number of tradable lots is received, the received number of tradable lots is set as the contracted number of tradable lots.

Patent Document 2 also describes a weather derivative product recommendation device as technology for selling weather derivative products, which includes an input unit that inputs customer product sales information related to customer product sales, weather information related to weather, and weather derivative product information related to weather derivative products in which a fee is paid depending on weather conditions; a risk hedge calculation unit that calculates an expected loss amount due to a predicted decrease in sales of the customer product based on the customer product sales information and weather information, and calculates the conditions of the weather derivative product to reduce the expected loss amount and hedge against risk based on the weather derivative product information; and an output unit that outputs the conditions of the weather derivative product.

Japanese Patent Application Laid-Open No. 2006-134116 Japanese Patent Application Laid-Open No. 2004-252569

However, weather derivatives are products based on uncertain factors such as climate change and can have complex structures. Therefore, companies looking to purchase weather derivatives often find it difficult to determine which weather derivative product to choose from the many available.

The present invention was made in light of this background, and its purpose is to provide a financial product proposal device and a financial product proposal method that are capable of proposing appropriate financial products that hedge against climate change risks.

One aspect of the present invention that solves the above problem is a financial product proposal device that includes a storage device that stores information on multiple financial products for which payment amounts are set according to predetermined conditions set for weather index values, and a control device that executes a data acquisition process that acquires energy usage information, a weather risk calculation process that identifies the correlation between the weather index value and the acquired energy usage, a product identification process that identifies financial products from the multiple financial products that meet predetermined criteria based on the financial product information, the identified correlation, and the predetermined conditions, and an information presentation process that outputs information about the identified financial products.

According to the present invention, it is possible to propose appropriate financial products that hedge against climate change risks.
Configurations and effects other than those described above will become apparent from the following description of the embodiments.

1 is a diagram illustrating an example of the configuration of a financial product proposal system according to an embodiment of the present invention. FIG. 2 is a diagram illustrating an example of hardware and functions of a financial product proposal device. FIG. 2 is a diagram illustrating an example of an energy usage amount DB. FIG. 2 is a diagram illustrating an example of a weather DB. FIG. 10 is a diagram illustrating an example of a weather derivative product DB. FIG. 1 is a flow chart outlining the processing performed in a financial product proposal system. FIG. 10 is a flow diagram illustrating a data accumulation process. FIG. 10 is a flow diagram illustrating a weather risk visualization report creation process. FIG. 10 is a diagram illustrating an example of a display screen of a weather risk visualization report. FIG. 10 is a flow diagram illustrating a weather derivative prescription creation process. FIG. 10 is a diagram showing an example of a weather derivative prescription display screen.

An embodiment of the present invention will be described with reference to the drawings.
1 is a diagram showing an example of the configuration of a financial product proposal system 1 according to this embodiment. The financial product proposal system 1 includes a user terminal 10 used by a user who is currently managing or intends to manage a financial product described below, one or more facilities 20 managed or used by the user, an energy management system 30, and a financial product proposal device 40. The user terminal 10, the facilities 20, the energy management system 30, and the financial product proposal device 40 are communicably connected to each other via a wired or wireless communication network 5 such as the Internet, a LAN (Local Area Network), a WAN, or a dedicated line.

The User is currently or intends to continue using weather derivatives as financial products. Weather derivatives are financial products used to hedge against losses (reduced sales or increased expenses) incurred due to weather fluctuations (weather fluctuations, climate change) such as abnormal weather or unfavorable weather.

Weather derivatives are set with weather-related indicators such as temperature, precipitation, or wind speed (hereinafter referred to as weather parameters), a target location (hereinafter referred to as the product target location), and a specified index value of the weather parameter (deductible value). Users who purchase weather derivatives can receive an amount based on the difference between the deductible value and the actual observed value of the weather parameter at the product target location.

In the weather derivative of this embodiment, if the average temperature exceeds the exclusion value, the user will be paid an amount proportional to the difference (temperature difference).

The equipment 20 is equipment that can operate using energy such as electricity or gas. The equipment 20 is equipped with a specified sensor or measuring device, and transmits information about energy usage to the energy management system 30. In this embodiment, the energy usage is assumed to be the amount of electricity usage.

The energy management system 30 acquires and stores energy usage data from the equipment 20 at predetermined times (e.g., at predetermined times or predetermined time intervals).

The financial product proposal device 40 stores information on multiple weather derivatives (weather derivative product data). Based on the energy usage managed by the energy management system 30 and the weather derivative product data, the financial product proposal device 40 identifies the weather derivative that meets specified criteria and is optimal for the user (for example, the one with the highest risk hedging effect), and provides information on the identified weather derivative to the user.

Figure 2 is a diagram illustrating an example of the hardware and functions of the financial product proposal device 40.

The financial product proposal device 40 stores data from an energy usage DB 100, a weather DB 200, a weather derivative product DB 300, a weather risk visualization report 400, and a weather derivative prescription 500.

The energy usage DB 100 contains energy usage data obtained from the energy management system 30.

Weather DB 200 is data that accumulates observation values related to weather parameters at each observation point. In this embodiment, the weather parameters are assumed to be data on the average temperature for each day.

Weather derivative product DB300 is data that stores details of multiple weather derivative products. For example, weather derivative product DB300 includes information on payment amounts according to specified thresholds (deductible values) of weather parameters at specified locations (product target locations).

The weather risk visualization report 400 is data that stores the correlation between weather parameter values and energy usage.

Weather derivative prescription 500 is data that stores information about weather derivatives that meet specified criteria and are optimal for the user.

Next, the financial product proposal device 40 has the following functional units: a data acquisition unit 111, a weather risk calculation unit 112, a product identification unit 113, and an information presentation unit 114.

The weather risk calculation unit 112 identifies the correlation between the value of the weather parameter and the amount of energy usage. The weather risk calculation unit 112 stores information on the identified correlation in the weather risk visualization report 400.

Specifically, the weather risk calculation unit 112 acquires the observed values of the weather data at the observation point corresponding to the product target point and identifies the correlation between the acquired observed values of the weather data and energy consumption. The weather risk calculation unit 112 outputs information about the identified correlation to the user terminal 10, etc., as a weather risk visualization report 400.

The product identification unit 113 identifies weather derivatives that meet specified criteria from the weather derivatives registered in the weather derivative product DB 300 based on the correlations identified by the weather risk calculation unit 112 and the information in the weather derivative product DB 300.

The information presentation unit 114 outputs information about the weather derivative identified by the product identification unit 113 as a weather derivative prescription 500 to the user terminal 10, etc.

In addition, the information presentation unit 114 calculates (predicts) the purchase amount of the financial product identified by the product identification unit 113 and the payment amount (amount the user will receive) if the financial product identified by the product identification unit 113 is purchased, and outputs information on the calculated (predicted) purchase amount and payment amount as a weather derivative prescription 500.

(Energy consumption data)
3 is a diagram showing an example of the energy usage DB 100. The energy usage DB 100 has the following data items: measurement point 101, in which the location of the equipment 20 (hereinafter referred to as the energy measurement point) is set; date 102, in which the date and time of measurement of the energy usage is set; and energy usage 103, in which the amount of energy usage at the measurement date and time at the energy measurement point of the equipment 20 is set.

(Weather DB)
4 is a diagram showing an example of the weather DB 200. The weather DB 200 has the following data items: observation point 201, which sets the observation point of the weather parameters; date 202, which sets the observation date and time of the weather parameters; and average daily temperature 203, which sets the weather parameter at the observation date and time at the observation point (here, the average temperature on the observation date).

(Weather derivative product database)
5 is a diagram showing an example of a weather derivative product DB 300. The weather derivative product DB 300 has the following data items: product type 301, which sets the type of weather derivative product; observation point 302, which sets the product target point for that product; period 303, which sets the period covered by the product (product target period); index 304, which sets the type of weather parameter covered by the product (product target index); exemption value 305, which sets the exemption value for that product; unit payment amount 306, which sets the unit payment amount that is the unit of the purchase amount for that product; and estimated price 307, which sets the estimated price for that product.

The expected price may be a price determined by the company selling the weather derivative product, or it may be automatically calculated using weather data and other factors in accordance with a predetermined algorithm (pricing method), or it may be based on both. Pricing methods are disclosed, for example, in Japanese Patent Application Laid-Open Nos. 2002-288437 and 2003-122918.

The weather derivative product DB300 is configured in advance, for example, by an administrator of the financial product proposal device 40.

If the product conditions differ for each weather derivative (for example, for each financial institution), data with unified conditions is set in the weather derivative product DB 300. For example, if there are financial institutions whose exemption figures are in 0.1°C units and financial institutions whose exemption figures are in 0.5°C units, the data will be unified to the coarser granularity of 0.5°C. Also, if there are financial institutions whose unit payment amounts are in 100,000 yen units and financial institutions whose unit payment amounts are in 1 million yen units, the data will be unified to the coarser granularity of 1 million yen.

Next, as shown in FIG. 2, the financial product proposal device 40 includes a control device 21 (arithmetic device, etc.) such as a CPU (Central Processing Unit), a memory 22 such as RAM (Random Access Memory) or ROM (Read Only Memory), a storage device 23 such as an HDD (Hard Disk Drive) or SSD (Solid State Drive), an input device 24 such as a keyboard, mouse, or touch panel, an output device 25 such as a display or touch panel, and a communication device 26 consisting of a NIC (Network Interface Card), a wireless communication module, a USB (Universal Serial Interface) module, a serial communication module, etc. The energy management system 30 and the user terminal 10 also have a similar hardware configuration.

The functions of the functional units of each information processing device in the financial product proposal system 1 described above are realized by the control device reading a program from a memory or storage device. Each program can be recorded on, for example, a portable or fixed recording medium and distributed. All or part of these programs may be realized using virtual information processing resources provided using virtualization technology, process space separation technology, or the like, such as a virtual server provided by a cloud system. All or part of these programs may also be realized by a service provided by a cloud system via an API (Application Programming Interface), for example.
Next, FIG. 6 is a flowchart illustrating an outline of the processing performed by the financial product proposal system 1.

First, the financial product proposal device 40 executes a data accumulation process s100 to acquire energy usage data and weather data.

Then, the financial product proposal device 40 executes the weather risk visualization report creation process s200, which creates a weather risk visualization report 400 based on the data acquired in the data accumulation process s100.

The financial product proposal device 40 also executes a weather derivative prescription creation process s300 for creating a weather derivative prescription 500 based on the data acquired in the data accumulation process s100.
Each process will be described in detail below.

<Data accumulation processing>
7 is a flow diagram illustrating the data accumulation process s100. The data accumulation process s100 is executed repeatedly at predetermined timing (for example, at predetermined times or predetermined time intervals).

The data acquisition unit 111 receives energy usage data from the energy management system 30 (s101). Specifically, the data acquisition unit 111 receives from the energy management system 30 the amount of power usage stored in the energy management system 30.

The data acquisition unit 111 stores the energy usage data received in s101 in the energy usage DB 100 (s102).

The data acquisition unit 111 also receives weather parameters (average temperature data for each day) from the energy management system 30 (s103). For example, the data acquisition unit 111 receives the weather parameters from a predetermined weather database (for example, weather data provided by a predetermined organization such as the Japan Meteorological Agency).

The data acquisition unit 111 stores the weather parameter values received in s101 in the weather DB 200 (s104).

<Weather risk visualization report creation process>
8 is a flow diagram illustrating the weather risk visualization report creation process s200. The weather risk visualization report creation process s200 is executed, for example, when a predetermined instruction is received from the user terminal 10.

The weather risk calculation unit 112 sets the energy measurement points and periods for power usage that will be the subject of the weather risk visualization report to be created (s201). For example, the weather risk calculation unit 112 receives input specifying the energy measurement points and periods from the user terminal 10.

The weather risk calculation unit 112 identifies the observation point corresponding to the energy measurement point set in s201 (s202).

For example, the weather risk calculation unit 112 acquires the measurement point 101 of the record related to the energy measurement point set in s201 in the energy usage DB 100. The weather risk calculation unit 112 identifies all records in the weather DB 200 in which data for a location closest to the location indicated by the acquired measurement point 101 is set as the observation point 201.

Note that the method of identifying the observation point described here is just one example. For example, rather than identifying the observation point closest to the energy measurement point, the weather risk calculation unit 112 may identify the observation point corresponding to the energy measurement point by referencing a specified database that associates energy measurement points with observation points.

The weather risk calculation unit 112 acquires energy usage data from the energy measurement points set in s201 and the weather parameter values from the observation points identified in s202 for the period identified in s201 (s203).

For example, the weather risk calculation unit 112 acquires the contents of the energy usage 103 of records in the energy usage DB 100 that relate to the energy measurement point set in s201 and in which the date 102 is set to a date within the period set in s201. Furthermore, the weather risk calculation unit 112 acquires the contents of the average daily temperature 203 of records in the weather DB 200 that relate to the observation point identified in s202 and in which the date 202 is set to a date within the period set in s201.

The weather risk calculation unit 112 corrects the energy usage data acquired in s203 to include only the portion of energy usage data linked to the weather (specifically, the average daily temperature) (s204).

For example, the weather risk calculation unit 112 multiplies the energy usage by the availability rate of the equipment 20. Furthermore, for example, the weather risk calculation unit 112 extracts only the energy usage associated with the equipment 20 that operates in conjunction with the weather.

The energy management system 30 may also perform processing similar to step s204 in advance. Furthermore, the energy management system 30 may, for example, separately manage data on fluctuations in power usage linked to weather and data on fluctuations in power usage not linked to weather.

The weather risk calculation unit 112 analyzes the fluctuation trend of the energy usage value corrected in s204 relative to the weather parameter value acquired in s203. Then, the weather risk calculation unit 112 identifies the change point (combination of weather parameter value and energy usage value) where the rate of fluctuation of the energy usage value relative to the change in the weather parameter value becomes large (s205).

For example, first, the weather risk calculation unit 112 divides the range of possible values for the weather parameter into multiple ranges (classes). For each divided range (class), the weather risk calculation unit 112 identifies all weather parameter values (weather data acquired in s203) that belong to that range. The weather risk calculation unit 112 acquires all energy usage data corresponding to each identified weather data value (i.e., for the same date and time). The weather risk calculation unit 112 calculates the average value of each acquired energy usage. Then, the weather risk calculation unit 112 identifies the range of the weather data where the average energy usage rises sharply (the rate of increase exceeds a predetermined threshold), and stores the combination of the identified range of weather data values and the average energy usage value corresponding to that range as a change point.

The weather risk calculation unit 112 creates a weather risk visualization report 400 that includes information about the change points identified in s205, and displays the created weather risk visualization report 400 on the screen of the user terminal 10.

(Weather Risk Visualization Report)
9 is a diagram showing an example of the display screen of the weather risk visualization report 400. This display screen 800 displays the measurement point 801 set in s201, the observation point 802 identified in s202, the type of weather parameter 803, and the period 804 set in s201.

This display screen 800 also displays a list of each range 805 (class) of weather parameter values and the average energy usage value 806 for each range. This display screen 800 also displays information 807 about the calculated change points.

<Weather derivative prescription creation process>
10 is a flow diagram illustrating the weather derivative prescription creation process s300. The weather derivative prescription creation process s300 is executed, for example, when a predetermined instruction is received from the user terminal 10.

First, the information presentation unit 114 sets the planned period (contract period) for purchasing and holding the weather derivative (s301). For example, the information presentation unit 114 may automatically set the contract period randomly, or may accept input of the contract period from the user terminal 10.

In addition, based on the change points identified in the weather risk visualization report creation process s200, the information presentation unit 114 identifies the weather derivative with the optimal payment amount over the contract period from the weather derivatives registered in the weather derivative product DB300 (s302).

Specifically, the information presentation unit 114 references the weather derivative product DB 300 and identifies the weather derivative (and the weather derivative whose period 303 includes the contract period) that has the exemption value closest to the value of the weather parameter related to the change point identified in the weather risk visualization report creation process s200. For example, if the average temperature at the change point is 27.0°C, the information presentation unit 114 identifies the weather derivative whose exemption threshold is closest to 27.0°C and is a product within the contract period.

Then, the information presentation unit 114 sets the purchase quantity of the weather derivative identified in s302 (hereinafter referred to as the selected weather derivative) (s303). For example, the information presentation unit 114 may automatically set the purchase quantity randomly, or may accept input of the purchase quantity from the user terminal 10.

The information presentation unit 114 calculates the purchase price of the selected weather derivative based on the purchase quantity set in s303. The information presentation unit 114 also predicts the total amount (hereinafter referred to as expenditure amount) of the purchase price if the selected weather derivative is purchased and the cost required for energy usage (energy charges, e.g., electricity charges) for a period of the same length as the contract period, based on actual data on past energy usage (s304).

For example, first, the information presentation unit 114 calculates the purchase price of the selected weather derivative by multiplying the purchase quantity set in s303 by the expected price of the selected weather derivative identified by the weather derivative product DB300.

The information presentation unit 114 also obtains from the energy usage DB 100 the energy usage amounts for each past period corresponding to the purchase period set in s301 (for example, periods one year ago, two years ago, ... X years ago in the same month as the purchase period; hereinafter referred to as the reference period). The information presentation unit 114 calculates the energy fee by multiplying the total amount of energy usage obtained by multiplying it by a specified energy unit price. The information presentation unit 114 then adds up the calculated purchase amount and energy fee.

Furthermore, the information presentation unit 114 predicts the amount of receivables (payment amount) based on the selected weather derivatives based on past weather data (s305). The information presentation unit 114 also predicts the total balance (post-hedged energy-related expenses) if the selected weather derivatives are purchased.

For example, the information presentation unit 114 first obtains weather data (average temperature) for each reference period set in s304 from the weather DB 200. The information presentation unit 114 compares the weather data for each reference period with the exemption value of the selected weather derivative, and calculates the difference between the weather data for each day in each reference period on which the weather data exceeds the exemption value (application day). The information presentation unit 114 multiplies the calculated difference by the unit payment amount for each application day, and calculates the payment amount by summing up the calculated multiplication values.

Furthermore, the information presentation unit 114 calculates the hedged energy-related expenses by subtracting the payment amount calculated in s305 from the expense amount calculated in s304.

The information presentation unit 114 determines (s306) whether receiving the payment amount will result in an overall profit exceeding a predetermined amount (whether purchasing the selected weather derivative will result in an excessive profit; here, the predetermined amount may be set to 0 or a negative value) based on the expense amount for each reference period calculated in s304, the payment amount for each reference period calculated in s305, and the hedged energy-related expenses. In other words, the information presentation unit 114 determines whether the profit amount in the overall balance sheet if the selected weather derivative is purchased will exceed a certain amount.

If the profit earned does not exceed the predetermined amount (s305: NO), the information presentation unit 114 executes the process of s307. If the profit earned exceeds the predetermined amount (s305: YES), the information presentation unit 114 repeats the process of s303 to set a new purchase amount.

In s307, the information presentation unit 114 outputs the results of the above processing to the weather derivative prescription 500. The information presentation unit 114 displays the contents of the output weather derivative prescription 500 on the screen of the user terminal 10.

In step S306 above, the information presentation unit 114 selected weather derivatives that meet the criterion that the profit amount is equal to or less than a predetermined amount as the subject of prescription data, but any other criterion may be set. For example, the information presentation unit 114 may select only weather derivatives that result in expenses or energy charges that are equal to or less than a predetermined amount as the subject of prescription data. Also, for example, the information presentation unit 114 may select only weather derivatives that have a predetermined attribute (for example, a predetermined attribute obtained from the weather derivative product DB 300) as the subject of prescription data.

(Weather Derivative Prescription)
11 is a diagram showing an example of the display screen of the weather derivative prescription 500. This display screen 1000 displays a selected weather derivative information display field 1010 that displays information about the selected weather derivative, and a reference data display field 1020.

The selected weather derivative information display field 1010 displays the product type 1011, product target location 1012, product target period 1013, product target index 1014, exemption value 1015, unit payment amount 1016, expected price 1017, and purchase quantity 108 of the selected weather derivative.

The reference data display field 1020 displays the energy usage data for the reference period used to determine the purchase quantity of the selected weather derivative and to predict expenses and payments, as well as information regarding the payment and cost amounts for the selected weather derivative estimated based on the energy usage data.

Specifically, the reference data display field 1020 displays information on each reference period 1021, energy usage during that reference period 1022, energy-related expenses during that reference period (energy charges 1023), estimated prices 1024, weather parameter values during that reference period (index values 1025), amount received during that reference period 1026, and hedged energy-related expenses 1027.

If the user decides to purchase the selected weather derivative by referring to this display screen 1000, they present the weather derivative prescription 500 to the financial institution related to the selected weather derivative and inquire about the price of the selected weather derivative. If the user agrees with the price, they purchase the selected weather derivative.

As described above, the financial product proposal device 40 of this embodiment acquires information on energy usage (electricity usage), identifies the correlation between the value of a weather parameter (average temperature) and energy usage, identifies weather derivatives that meet specified criteria based on information on each weather derivative, the correlation, and the conditions set for the weather parameter (exemption value), and outputs information about the identified weather derivatives.

In other words, energy usage generally has a certain correlation with weather (climate) fluctuations. Therefore, by identifying the correlation between weather parameters and energy usage, it is possible to identify weather derivatives that meet certain criteria (e.g., optimal payouts and hedging risks) based on that correlation.

In this way, the financial product proposal device 40 of this embodiment can propose appropriate financial products that hedge against climate change risks.

In addition, the financial product proposal device 40 of this embodiment acquires the values of weather parameters at an observation point corresponding to the product target location, and identifies the correlation between the acquired weather parameter values and energy usage.

This allows for appropriate assessment of the risks of weather derivatives based on the correlation between weather parameters and energy usage.

In addition, the financial product proposal device 40 of this embodiment predicts and outputs the payment amount (received amount) if the selected weather derivative is purchased based on past weather parameter values.

In this way, by predicting the payout amount for weather derivatives based on past weather parameter values, users can determine whether it is economically appropriate to purchase selected weather derivatives.

In addition, the financial product proposal device 40 of this embodiment acquires information on the sales price of each weather derivative and information on energy charges, and predicts and outputs the total balance (post-hedged energy-related expenses) for the purchase of the selected weather derivative based on the sales price information, energy charge information, and the payment amount information.

In this way, by outputting the total balance of income and expenditure when purchasing the selected weather derivative, the user can make a comprehensive judgment as to whether purchasing the selected weather derivative is economically appropriate.

In addition, the financial product proposal device 40 of this embodiment identifies the value or range (change point) of the weather parameter when the value of energy usage changes by more than a specified percentage in response to a change in the value of the weather parameter, and identifies weather derivatives that meet specified criteria based on the weather derivative information, change point, and weather derivative conditions (exemption value).

In this way, by identifying weather derivatives that meet specified criteria based on the change points of weather parameters relative to energy usage, it is possible to identify the optimal weather derivatives based on the characteristics of the weather derivative product.

In addition, the financial product proposal device 40 of this embodiment outputs information on change points.

This allows users to estimate the conditions that will be the turning points for the risks of weather derivatives and provides information to help them select the most appropriate weather derivatives.

In addition, the financial product proposal device 40 of this embodiment predicts the payment amount when each weather derivative is purchased based on the weather derivative product DB 300, the correlation between the value of the weather parameter (average temperature) and energy consumption, the deductible value, and past weather parameter values, predicts the overall balance when each weather derivative is purchased based on the predicted payment amount and the purchase price of each weather derivative, and identifies weather derivatives from the weather derivative product DB 300 that will result in a profit amount in the overall balance that is less than a predetermined amount.

In this way, by predicting the total profit and loss when purchasing each weather derivative and identifying weather derivatives with low total profit and loss, it is possible to prevent excessive profits from being obtained by purchasing weather derivatives, which would go against the purpose of the weather derivative product.

The present invention is not limited to the above-described embodiments, and can be implemented using any components within the scope of the gist of the invention. The embodiments and modifications described above are merely examples, and the present invention is not limited to these contents as long as the characteristics of the invention are not impaired. Furthermore, while various embodiments and modifications have been described above, the present invention is not limited to these contents. Other aspects conceivable within the technical spirit of the present invention are also included within the scope of the present invention.

For example, some of the hardware provided in each device in this embodiment may be provided in another device.

Furthermore, each program of each device may be provided on another device, a program may consist of multiple programs, or multiple programs may be integrated into a single program.

Furthermore, the configuration of each database described in this embodiment is an example, and information on each item related to equipment and components may be added or some of it may be omitted.

In addition, in this embodiment, the condition for determining the weather derivative payment amount is a predetermined value (deductible value), but a value range, conditional expression, function, etc. may also be set. Furthermore, multiple conditions may also be set. For example, if a function is set as the above condition, the financial product proposal device 40 identifies the point (maximum value, minimum value, etc.) where the value of energy usage changes by a predetermined rate or more in response to changes in the value of the weather parameter.

In addition, in this embodiment, the climate parameter related to the weather derivative is temperature, but it may also be other weather parameters such as precipitation, wind direction, wind speed, etc.

30 Energy Management System, 40 Financial Product Proposal Device, 400 Weather Risk Visualization Report, 500 Weather Derivative Prescription

Claims (6)

a storage device that stores information on a plurality of financial products for which payout amounts are set according to predetermined conditions set with respect to the value of a weather index; and
a data acquisition process for acquiring information on energy usage;
a weather risk calculation process for identifying a correlation between the value of the weather index and the acquired energy usage;
a product identification process for identifying financial products that satisfy predetermined criteria from the plurality of financial products based on the information on the financial products, the identified correlations, and the predetermined conditions;
an information presentation process for outputting information about the identified financial product ;
a control device that executes the
the control device, in the information presentation process, predicts a payment amount in the case of purchasing the specified financial product based on past values of the weather index, and outputs information on the predicted payment amount;
In the product identification process, the financial product proposal device acquires information on the purchase amount of each financial product and information on costs related to energy usage, predicts the total balance amount for purchasing the identified financial product based on the acquired purchase amount information, cost information, and information on the predicted payment amount, and outputs information on the predicted total balance amount . the storage device stores information on a financial product in which a payout amount according to a predetermined condition set with respect to a weather index value is associated with a predetermined location;
In the weather risk calculation process, the control device acquires a value of the weather index at a location corresponding to the predetermined location, and identifies a correlation between the acquired value of the weather index and the acquired amount of energy usage.
The financial product proposal device according to claim 1. The control device
In the weather risk calculation process, in the correlation between the value of the energy usage and the value of the weather index, a value or range of the weather index when the value of the energy usage changes at a predetermined rate or more with respect to a change in the value of the weather index is identified;
In the product identification process, a financial product that satisfies the predetermined criteria is identified from the plurality of financial products based on the information on the financial product, the identified value or range, and the predetermined conditions.
The financial product proposal device according to claim 1. The control device outputs information on the specified value or range in the weather risk calculation process.
The financial product proposal device according to claim 3. the storage device stores information on financial products for which a purchase amount and a payment amount are set according to predetermined conditions set with respect to the value of a weather index;
The control device
In the product identification process, the payment amount when each of the financial products is purchased is predicted based on the information of each of the financial products, the identified correlation, the predetermined conditions, and the past values of the weather index, and the total balance amount when each of the financial products is purchased is predicted based on each predicted payment amount and the purchase amount of each of the financial products, and financial products whose profit amount in the total balance amount is less than a predetermined amount are identified from the plurality of financial products.
The financial product proposal device according to claim 1. A financial product proposal method using an information processing device including a control device and a storage device that stores information on a plurality of financial products for which payment amounts are set according to predetermined conditions set with respect to weather index values, the method comprising:
The control device
a data acquisition process for acquiring information on energy usage;
a weather risk calculation process for identifying a correlation between the value of the weather index and the acquired energy usage;
a product identification process for identifying financial products that satisfy predetermined criteria from the plurality of financial products based on the information on the financial products, the identified correlations, and the predetermined conditions;
an information presentation process for outputting information about the identified financial product;
Run
In the information presentation process, a payment amount in the case of purchasing the specified financial product is predicted based on past values of the weather index, and information on the predicted payment amount is output;
A financial product proposal method in which, in the product identification process, information on the purchase amount of each financial product and information on costs related to energy usage are obtained, and based on the obtained purchase amount information, cost information, and information on the predicted payment amount, the total balance amount related to the purchase of the identified financial product is predicted, and information on the predicted total balance amount is output.