Apparatus, method, and program for assessing the rent of rental properties.

Abstract

To further facilitate the use of assessment of the rent for a rental property.SOLUTION: A device 100 acquires target property data representing a target property (S201). Subsequently, the device 100 extracts, from a plurality of comparative properties, ones with first similarity to the target property to a predetermined rank as a first set of comparative properties (S202). The device 100, for each comparative property included in the extracted first set of comparative properties, calculates a rent after correction obtained by correcting a rent for the comparative property with the amount of money according to the difference between the value of a first characteristic of a plurality of characteristics of the target property and the value of the first characteristic of the comparative property, and generates a first set of comparative properties after correction (S203). After that, the device extracts, from the generated first set of comparative properties after correction, ones with second similarity to the target property to a predetermined rank as a second set of comparative properties (S204). Finally, the device calculates, as an assessed rent, the average value or the approximate value of the rent after correction for the second set of comparative properties (S205).SELECTED DRAWING: Figure 2

Description

Technical Field

[0001] The present invention relates to an apparatus, a method, and a program for assessing the rent of rental properties.

Background Art

[0002] In real estate management companies that manage rental properties, rent assessment services for each property are generated. Conventionally, although the transaction case comparison method is known as an objective method, in order for a real estate management company to adopt a rent assessment based on the transaction case comparison method on its own, a large amount of calculation is involved. Therefore, it is necessary to develop a rent assessment system that automates these calculations.

Summary of the Invention

Problems to be Solved by the Invention

[0003] Although there are rent assessment systems provided for real estate management companies, they have not been sufficiently popularized, and improvements are required.

[0004] The present invention has been made in view of such points, and the problem is to improve an apparatus, a method, or a program for assessing the rent of rental properties so that its use becomes easier.

Means for Solving the Problems

[0005] To solve these problems, a first aspect of the present invention is a method for assessing the rent of a rental property, comprising the steps of: a server receiving from a device communicating with the server via an IP network, target property data representing a plurality of characteristics of the target property to be assessed, or input for identifying the target property data; the server extracting from a plurality of comparison properties stored accessible from the server, based on the target property data, at least some of the comparison properties whose first similarity to the target property is up to a first predetermined rank, or at least some of the comparison properties whose first similarity is equal to or greater than a first predetermined value, as a first set of comparison properties; and for each comparison property included in at least some of the first set of comparison properties, the server provides the following information about the target property. The process includes the steps of: generating a first set of corrected compared properties by storing a corrected rent associated with the compared property, obtained by adjusting the rent of the compared property by an amount corresponding to the difference, if there is a difference between the value of a first feature among multiple features and the value of the first feature of the compared property; the server extracting from at least a portion of the first set of corrected compared properties, based on the target property data, at least a portion of the compared properties whose second similarity to the target property is up to a second predetermined rank, or at least a portion of the compared properties whose second similarity is equal to or greater than a second predetermined value, as a second set of compared properties; and the server calculating the average value or an approximate value thereof of the corrected rents of the second set of compared properties as the assessed rent of the target property, and transmitting the assessed rent to the device.

[0006] Furthermore, a second aspect of the present invention is the method of the first aspect, wherein the first set of comparative items includes 500 to 1000 comparative items.

[0007] Furthermore, a third aspect of the present invention is the method of the first aspect, wherein the second set of comparative items includes 50 to 150 comparative items.

[0008] Furthermore, a fourth aspect of the present invention is the method of the first aspect, wherein at least a portion of the first set of adjusted comparison properties is a portion obtained by excluding at least the comparison properties from the first set of adjusted comparison properties in which the difference between the adjusted rent and the unadjusted rent is equal to or greater than a predetermined threshold from the average value or an approximation thereof.

[0009] Furthermore, a fifth aspect of the present invention is a method according to any of the first to fourth aspects, wherein the first similarity is calculated based on a predetermined first formula that uses at least one of the following: the difference in the occupied area with the subject property, the difference in the age of the building, and the distance between the subject property and the other property.

[0010] Furthermore, a sixth aspect of the present invention is a method according to any of the first to fourth aspects, wherein the second similarity is calculated based on a predetermined second formula that uses at least one of the distance between the property and the property and the difference in walking time.

[0011] Furthermore, a seventh aspect of the present invention is a method according to any of the first to fourth aspects, wherein the first feature is any of the following: square footage, year of construction, walking distance from the station, whether or not the bathroom and toilet are separate, and whether or not there is a delivery box.

[0012] Furthermore, an eighth aspect of the present invention is a method of the seventh aspect, further comprising the step of, for each corrected comparative property included in the first set of corrected comparative properties, if there is a difference between the value of a second characteristic of the subject property that is different from the first characteristic of the plurality of characteristics of the subject property and the value of the second characteristic of the corrected comparative property, the rent of the corrected comparative property is further corrected by an amount corresponding to the difference and stored in association with the corrected comparative property.

[0013] Furthermore, a ninth aspect of the present invention is a program for causing a server to execute a method for assessing the rent of a rental property, the method comprising: receiving from a device communicating with the server via an IP network, target property data representing a plurality of characteristics of a target property to be assessed, or input for identifying the target property data; extracting from a plurality of comparison properties stored accessible from the server, based on the target property data, at least some of the comparison properties whose first similarity to the target property is up to a first predetermined rank, or at least some of the comparison properties whose first similarity is equal to or greater than a first predetermined value, as a first set of comparison properties; and for each comparison property included in at least some of the first set of comparison properties, the target property If there is a difference between the value of the first of the multiple features of the subject and the value of the first feature of the comparison property, the adjusted rent of the comparison property is adjusted by an amount corresponding to the difference and stored in association with the comparison property to generate a first set of adjusted comparison properties; at least a portion of the adjusted comparison properties of the first set of adjusted comparison properties are extracted from at least a portion of the comparison properties whose second similarity to the subject property is up to a second predetermined rank, or at least a portion of the comparison properties whose second similarity is equal to or greater than a second predetermined value, based on the subject property data, as a second set of comparison properties; the average value or an approximate value thereof of the adjusted rents of the second set of comparison properties is calculated as the assessed rent of the subject property, and the assessed rent is transmitted to the device.

[0014] Furthermore, a tenth aspect of the present invention is a server for assessing the rent of a rental property, which receives from a device communicating with the server via an IP network, target property data representing a plurality of characteristics of the target property to be assessed or input for identifying the target property data, and extracts from a plurality of comparison properties stored accessible from the server, based on the target property data, at least some of the comparison properties whose first similarity to the target property is up to a first predetermined rank or at least some of the comparison properties whose first similarity is equal to or greater than a first predetermined value, as a first set of comparison properties, and for each comparison property included in at least some of the first set of comparison properties, the plurality of characteristics of the target property If there is a difference between the value of the first feature of the property and the value of the first feature of the comparison property, the adjusted rent of the comparison property is adjusted by an amount corresponding to the difference and stored in association with the comparison property to generate a first set of adjusted comparison properties. From at least a portion of the first set of adjusted comparison properties, at least a portion of the comparison properties whose second similarity to the target property is up to a second predetermined rank, or at least a portion of the comparison properties whose second similarity is equal to or greater than a second predetermined value, are extracted as a second set of comparison properties based on the target property data. The average value or an approximate value thereof of the adjusted rents of the second set of comparison properties is calculated as the assessed rent of the target property, and the assessed rent is transmitted to the device. [Effects of the Invention]

[0015] According to one aspect of the present invention, the rent of each of the extracted comparative properties is adjusted by an amount corresponding to the difference with the target property, and then some of the comparative properties are selected and the rent of the target property is assessed using the adjusted rent of each comparative property, thereby making it easier to use devices and the like for assessing the rent of rental properties. [Brief explanation of the drawing]

[0016] [Figure 1] This figure shows an apparatus according to one embodiment of the present invention. [Figure 2]This diagram shows the flow of a method for calculating rent related to one embodiment of the present invention. [Figure 3] This figure shows an example of a property data input screen according to one embodiment of the present invention. [Figure 4] This is a distribution chart of pre-adjustment and post-adjustment rents for comparable properties according to one embodiment of the present invention. [Modes for carrying out the invention]

[0017] Embodiments of the present invention will be described in detail below with reference to the drawings.

[0018] (First Embodiment) Figure 1 shows a device according to one embodiment of the present invention. Device 100 is a device for assessing the rent of rental properties and communicates with a company terminal 110 used by a real estate management company via an IP network such as the Internet.

[0019] The device 100 comprises a communication unit 101 such as a communication interface, a processing unit 102 such as a processor or CPU, and a storage unit 103 including a storage device or storage medium such as memory or a hard disk. The device can be configured by executing a program for performing each process or operation in the processing unit 102. The device 100 may include one or more devices, computers, or servers. The program may also include one or more programs and can be recorded on a computer-readable storage medium to form a non-transient program product. The program is stored in the storage unit 103 or in a storage device or storage medium such as a database 104 accessible via an IP network from the device 100, and instructions included in the program can be executed by at least one processor in the processing unit 102. The data described below as being stored in the storage unit 103 may be stored in the database 104, and vice versa.

[0020] First, the device 100 acquires target property data representing a plurality of features of a target property to be appraised (S201). The target property data can be acquired, for example, by a person in charge of a real estate management company inputting it using the company terminal 110 and the device 100 receiving the input.

[0021] The input by the company terminal 110 can be performed from an input screen (see FIG. 3) displayed on the display screen of the company terminal 110 on a web browser by transmitting property data input screen display information as, for example, a file in HTML format, or by operating an application (hereinafter also referred to as an "app") installed on the company terminal 110 and performing the input from an input screen displayed on the app. Note that the "input screen" can adopt various forms such as a web page, a modal window, a pop-up window, etc. when displayed on a web browser, and can be one screen of the app when displayed on the app. In any case, as long as it is a screen including an area having an input field for inputting target property data, it corresponds to the property data input screen.

[0022] The target property data may be indirectly acquired as data identified by an input received by the device 100 by performing a search from a search screen displayed on the company terminal 110 and selecting a target property from the search results. In this case, the device 100 may identify and acquire the target property data stored in the storage unit 103 based on the input.

[0023] In addition, the target property data can be obtained from various devices rather than from the company terminal 110 of the real estate management company. As an example, the target property data may be received by the device 100 from a system storing rental property data representing a plurality of features of rental properties managed by the real estate management company. For example, in the system, when the rental status of a rental property becomes vacant or is scheduled to be vacant, the target property data is automatically transmitted to the device 100 with the rental property as the target property, and from the device 100, the appraised rent for the rental property may be transmitted to the system. By doing so, the latest appraised rent can be stored in the system. Also, when the device 100 provides an API for rent appraisal, the required target property data may be obtained by the device 100 as a parameter for calling the API.

[0024] The target property data includes the address or the nearest station of the target property as its feature. When including the nearest station, it may further include the line along which it is located and the walking time (hereinafter also referred to as "walking time") from the nearest station to the target property. Also, the target property data may further include, as its features, the property type such as condominium, apartment, detached house, etc., the sale designation of whether it is for sale only, excluding sale, or including sale, the structure such as RC construction, lightweight steel frame construction, etc., the floor plan such as 1R, 1LDK, etc., the value or range of the floor area, the value or range of the number of years since construction, etc.

[0025] Next, the device 100 extracts at least some of the comparison properties from a plurality of comparison properties, based on the target property data, that have a first similarity to the target property up to a first predetermined rank, as a first set of comparison properties (S202). The comparison property data representing the plurality of comparison properties can be stored in the storage unit 103. The first similarity is calculated, for example, based on a predetermined first formula for comparison properties that have the same nearest station included in the target property data or the nearest station inferred from the address included in the target property data. More specifically, the predetermined first formula can calculate a value corresponding to the difference between each of the plurality of features of the comparison property and the target property, and calculate a first score based on the plurality of calculated values. It is preferable that the extraction is performed automatically based on the first similarity, rather than the user using the rent assessment service provided by the device 100 specifying conditions for extracting the first set of comparison properties from the terminal 110.

[0026] If the target property data includes address, floor area, walking distance, and year of construction, the first score can be calculated using the following formula as an example. When using this formula, a smaller first score indicates greater similarity, so the reciprocal of the first score can be used to represent the similarity. First score = |Difference in floor area| × 3 / 1 + |Difference in walking time| × 3 / 1 +|Difference in building age|×2 / 1+|Distance between properties|×1 / 100 Differences in floor area and walking distance are evaluated as having a similar impact on similarity, while differences in building age are evaluated as having a smaller impact. Furthermore, since the distance between properties is large (e.g., 100m, 200m), it is adjusted by dividing by 100. If walking distance is not included as a feature in the target property data, it may be calculated using the nearest station included in the target property data or the nearest station inferred from the address included in the target property data, along with the address included in the target property data. Here, an example formula using all of the differences in floor area, walking distance, building age, and distance between properties is provided, but a formula using any one of these may also be used.

[0027] As another example, if the property data includes address, floor area, and year of construction, the first score can be calculated using the following formula. First score = |Difference in floor area| × 3 / 1 + |Difference in age of building| × 2 / 1 +|Distance between properties| × 1 / 100

[0028] For example, the first set of comparable items may consist of the top 700 items with the highest similarity, or at least a portion of them. Alternatively, instead of ranking, the first set of comparable items may consist of comparable items with a first similarity of 0.01 or greater than or equal to a predetermined value (hereinafter also referred to as the "first predetermined value"). The first set of comparable items preferably contains between 500 and 1000 comparable items.

[0029] Then, for each comparative property included in the extracted first set of comparative properties, if there is a difference between the value of the first of the multiple features of the target property and the value of the first of the features of the comparative property, the device 100 adjusts the rent of the comparative property by an amount corresponding to the difference, stores the adjusted rent associated with the comparative property, and generates the first set of adjusted comparative properties (S203).

[0030] Rent adjustments can be made using a predetermined adjustment coefficient, obtained by referring to the correspondence between the predetermined characteristic and the adjustment coefficient, if the first characteristic is the number of floors or orientation. For example, if the comparable property has one fewer floor, since rents are generally higher for properties with more floors, an adjustment of 0.7% may be added to the rent.

[0031] Rent adjustments can be made by referring to the above-mentioned correspondence, or in addition to that, by performing a multiple regression analysis on the first set of comparison properties extracted, with rent as the dependent variable and multiple features as independent variables, to obtain the coefficient for each feature, and then calculating the estimated rent or an approximate value thereof for each comparison property, assuming that the value of each feature is the value of the target property. If the multiple features include qualitative variables such as whether the bathroom and toilet are separate or whether there is a delivery box, they are converted into dummy variables. If any of the coefficients obtained as a result of the multiple regression analysis are outside the predetermined range, the upper or lower limit of that predetermined range or an approximate value thereof may be used as the coefficient.

[0032] Next, if necessary, one or more comparison properties whose difference between the adjusted rent and the unadjusted rent is relatively far from the mean or an approximation thereof may be excluded. Specifically, at least one or more comparison properties whose difference is more than or equal to a predetermined threshold (hereinafter sometimes referred to as the "first predetermined threshold"), such as one standard deviation from the mean or an approximation thereof, may be excluded. Then, the one or more comparison properties may be excluded from the first set of comparison properties, and the first set of adjusted comparison properties may be regenerated using multiple regression analysis again. Alternatively, without performing multiple regression analysis again, one or more comparison properties whose difference between the rent before and after adjustment is significantly far from the mean or an approximation thereof may be excluded from the first set of adjusted comparison properties, and the process may proceed to the next step.

[0033] Subsequently, from at least a portion of the corrected comparison properties of the first set generated, at least a portion of the comparison properties whose second similarity to the target property is up to a second predetermined rank is extracted as the comparison properties of the second set (S204). The second similarity is calculated, for example, for each of the at least portion of the corrected comparison properties of the first set based on a predetermined second formula. Specifically, the predetermined second formula may calculate a value corresponding to the difference between each of the multiple features of the comparison property and the target property, and calculate a second score based on the multiple values ​​calculated. It is preferable that the extraction is performed automatically based on the second similarity, rather than the user using the rent assessment service provided by the device 100 specifying conditions for extracting the comparison properties of the second set from the terminal 110.

[0034] For example, the second score can be calculated based on at least one of the distance between properties and the difference in walking time. If a larger difference in distance or walking time between properties results in a larger second score, then a smaller second score indicates greater similarity, and therefore the second similarity can be taken as the reciprocal of the second score.

[0035] If necessary, one or more comparable properties whose adjusted rents deviate significantly from the average or approximate average adjusted rent of the comparable properties in the second set may be omitted from the comparable properties in the second set. Specifically, one or more comparable properties whose adjusted rents deviate by a predetermined threshold (hereinafter sometimes referred to as the "second predetermined threshold"), such as four times the standard deviation, from the average or approximate average rent may be omitted from the comparable properties in the second set. Since the comparable properties in the second set have been extracted through multiple processing steps to obtain properties similar to the target property, when excluding properties from the adjusted comparable properties in the first set using the first predetermined threshold, it is preferable to set the second predetermined threshold used for excluding properties from the comparable properties in the second set to be larger than the first predetermined threshold.

[0036] For example, the second set of comparable items may consist of the top 100 items with the highest second similarity, or at least a portion of them. Alternatively, instead of ranking, the second set of comparable items may consist of comparable items with a second similarity equal to or greater than a predetermined value (hereinafter sometimes referred to as the "second predetermined value"), or at least a portion of them. The second set of comparable items preferably contains between 50 and 150 comparable items.

[0037] Finally, the average or approximate value of the adjusted rents of the second set of comparable properties is calculated as the assessed rent for the property in question, and this assessed rent is transmitted to the company terminal 110 (S205).

[0038] Figure 4 schematically shows the distribution of unadjusted and adjusted rents for comparative properties according to an embodiment of the present invention. This is an example using a 2LDK property in Tokyo as the target property, and the distributions of the unadjusted rent for the first group of comparative properties, the adjusted rent for the first group of comparative properties, and the adjusted rent for the second group of comparative properties are shown by dotted lines, dashed lines, and solid lines, respectively. The distribution shifts due to the adjustment using multiple regression analysis, and the standard deviation of the distribution is reduced by extracting properties with high similarity to the target property.

[0039] (Second embodiment) In the first embodiment, a large number of comparison properties are stored in the storage unit 103, and a first set of comparison properties is extracted from them. Preferably, the multiple comparison properties stored in the storage unit 103 are obtained by the device 100 by scraping from one or more websites that contain information on multiple rental properties. This is because the assessment accuracy decreases if the comparison properties used become outdated.

[0040] Furthermore, in the embodiments described above, unless the word "only" is used, such as "based only on XX," "according only to XX," or "in the case of XX only," it is assumed in this specification that additional information may also be considered. Also, as an example, the statement "if a, then b" does not necessarily mean "always b in the case of a" or "b immediately after a," unless explicitly stated otherwise. In addition, the statement "each a constituting A" does not necessarily mean that A is composed of multiple components, but includes the possibility that the component is singular.

[0041] Furthermore, for the sake of clarity, even if there are aspects of operation in some method, program, terminal, device, server, or system (hereinafter referred to as "method, etc.") that differ from the operation described herein, each aspect of the present invention is intended to cover the same operation as any of the operations described herein, and the existence of operation different from the operation described herein does not mean that such method, etc. is outside the scope of each aspect of the present invention.

[0042] Furthermore, the "start" and "end" shown in Figure 2 are merely examples, and do not necessarily mean that the method according to this embodiment will always start or end in the illustrated procedure. [Explanation of symbols]

[0043] 100 devices 101 Communications Department 102 Processing Unit 103 Storage section 104 Databases 110 terminals 300 Property Data Entry Screen

Claims

[Claim 1] A method for assessing the rent of a rental property, The server receives, from a device communicating with the server via an IP network, target property data representing multiple characteristics of the property subject to assessment, or input for identifying the target property data. The server extracts, from a plurality of comparison properties stored accessible from the server, at least some of the comparison properties whose first similarity to the target property is up to a first predetermined rank, or at least some of the comparison properties whose first similarity is equal to or greater than a first predetermined value, as a first set of comparison properties, based on the target property data. The server, for each comparative property included in at least a portion of the first set of comparative properties, if there is a difference between the value of the first of the multiple features of the target property and the value of the first feature of the comparative property, stores the adjusted rent of the comparative property, adjusted by an amount corresponding to the difference, and associates it with the comparative property, thereby generating the first set of adjusted comparative properties. The server extracts, from at least a portion of the corrected comparison items of the first set, at least a portion of the comparison items whose second similarity to the target item is up to a second predetermined rank, or at least a portion of the comparison items whose second similarity is equal to or greater than a second predetermined value, as comparison items of the second set, based on the target item data. The server calculates the average or approximate value of the corrected rents of the second set of comparison properties as the assessed rent for the target property, and transmits the assessed rent to the device. Includes.

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