SYSTEM AND METHOD FOR DETERMINING A VALUE OF PROPERTY REFURBISHMENTS TO A PROPERTY SALE PRICE

• US 20200134754A1
• Filed: 10/30/2019
• Published: 04/30/2020
• Est. Priority Date: 10/30/2018
• Status: Active Application

• Current Assignee: Stoa USA, Inc.
• Original Assignee: Stoa Fund, Ltd.
• Inventors: AGASSI, Or, SELLA, Tom, SARAGOSSI, Jonathan
• Application Number:
  US16/668,868
• Publication Number:
  US 20200134754A1
• Time in Patent Office: Days
• CPC Class Codes: G06Q 30/0283 Price estimation or determination
• CPC Class Codes: G06Q 50/163 Real estate management

Abstract

A system and method for determining a value of property refurbishments to a property sale price, including: receiving a first dataset of descriptive information associated with a first property; receiving a second dataset including information related to one or more objectives made to the first property throughout a first refurbishment process; receiving a sale price of the first property after the refurbishment process is completed; searching for a second property in which at least one of the one or more objectives was made; collecting a third dataset associated with the at least a second property, wherein the third dataset comprises descriptive information of the at least a second property; analyzing the first dataset and the second dataset with respect to the third dataset; and, determining, based on the analysis, a value contribution for each of the plurality of objectives to the sale price of the first property.

Claims

1. A method for determining a value of property refurbishments to a property sale price, comprising:

receiving a first dataset associated with a first property, wherein the first dataset comprises descriptive information about the first property;

receiving a second dataset associated with the first property, wherein the second dataset comprises information related to one or more objectives made to the first property throughout a first refurbishment process;

receiving a sale price of the first property after the refurbishment process is completed;

searching for at least a second property in which at least one of the one or more objectives was made to a second refurbishment process;

collecting a third dataset associated with the at least a second property, wherein the third dataset comprises descriptive information of the at least a second property;

analyzing the first dataset and the second dataset with respect to the third dataset, wherein the analysis includes measuring multiple parameters of a refurbishment; and

,

determining, based on the analysis, a value contribution for each of the plurality of objectives to the sale price of the first property.

2. The method of claim 1, wherein the first dataset comprises at least a purchase price of the first property and a location of the first property.

3. The method of claim 1, wherein the second dataset comprises a first set of metadata associated with each of the plurality of objectives, wherein the first set of metadata comprises at least a cost of each of the plurality of objectives.

4. The method of claim 1, wherein the one or more objectives includes at least one of:

rehabilitation, renovation, replacement, demolition, cleaning, painting, and installation of new appliances.

5. The method of claim 1, wherein the third dataset comprises at least a sale price of the at least a second property, a location of the at least a second property and a second set of metadata that is related to the one or more objectives that was made throughout the second refurbishment process.

6. The method of claim 1, further comprising:

storing the value contribution of each of the plurality of objectives in a database.

7. The method of claim 1, wherein the analysis is achieved using at least one machine learning model configured to calculate the contribution of the one or more objectives performed throughout the second refurbishment processes to the sale price of the second property.

8. The method of claim 7, wherein the machine learning model includes at least one of:

deep learning, neural networks, such as deep convolutional neural network, recurrent neural networks, decision tree learning, Bayesian networks, and clustering.

9. The method of claim 1, wherein the determination of the value contribution of the one or more objectives made to the first property is extracted from multiple comparable second properties within the third database sharing at least one similar objective, where the comparable property and similar objective match the first property and an objective, respectively, above a predetermined threshold.

10. A non-transitory computer readable medium having stored thereon instructions for causing a processing circuitry to perform a process, the process comprising:

receiving a first dataset associated with a first property, wherein the first dataset comprises descriptive information about the first property;

receiving a second dataset associated with a first property, wherein the second dataset comprises information related to one or more objectives made to the first property throughout a first refurbishment process;

receiving a sale price of the first property after the refurbishment process is completed;

searching for at least a second property in which at least one of the one or more objectives was made to a second refurbishment process;

collecting a third dataset associated with the at least a second property, wherein the third dataset comprises descriptive information of the at least a second property;

analyzing the first dataset and the second dataset with respect to the third dataset, wherein the analysis includes measuring multiple parameters of a refurbishment; and

,

determining, based on the analysis, a value contribution for each of the plurality of objectives to the sale price of the first property.

11. A system for determining a value of property refurbishments to a property sale price, comprising:

a processing circuitry; and

a memory, the memory containing instructions that, when executed by the processing circuitry, configure the system to;

receive a first dataset associated with a first property, wherein the first dataset comprises descriptive information about the first property;

receive a second dataset associated with a first property, wherein the second dataset comprises information related to one or more objectives made to the first property throughout a first refurbishment process;

receive a sale price of the first property after the refurbishment process is completed;

search for at least a second property in which at least one of the one or more objectives was made to a second refurbishment process;

collect a third dataset associated with the at least a second property, wherein the third dataset comprises descriptive information of the at least a second property;

analyze the first dataset and the second dataset with respect to the third dataset, wherein the analysis includes measuring multiple parameters of a refurbishment; and

,

determine, based on the analysis, a value contribution for each of the plurality of objectives to the sale price of the first property.

12. A method of predicting a projected value contribution of at least one objective to a projected sale price of a property, comprising:

receiving a request to determine the projected value contribution of at least one objective to a projected sale price of a first property;

receiving a first dataset associated with the first property, wherein the first dataset comprises descriptive information about the first property;

searching for at least a second property in which the at least one objective was performed throughout a second refurbishment process;

collecting a second dataset that is associated with the at least a second property, wherein the second dataset comprises information related to one or more objectives made to the second property throughout a refurbishment process;

determining, based on an analysis of the second dataset, an average value contribution of the at least one objective to a second property sale price; and

,

determining the projected value contribution of the at least one objective to the projected sale price of the first property based on the determination of the average value contribution of the at least one objective to the at least a second property sale price.

13. The method of claim 12, wherein the first dataset comprises at least a purchase price of the first property and a location of the first property.

14. The method of claim 12, wherein the second dataset comprises at least a purchase price of the at least a second property, a sale price, a location of the at least a second property and a set of metadata that is related to the at least one objective that was performed throughout the refurbishment of the at least a second property.

15. A non-transitory computer readable medium having stored thereon instructions for causing a processing circuitry to perform a process, the process comprising:

receiving a request to determine the projected value contribution of at least one objective to a projected sale price of a first property;

receiving a first dataset associated with the first property, wherein the first dataset comprises descriptive information about the first property;

searching for at least a second property in which the at least one objective was performed throughout a second refurbishment process;

collecting a second dataset that is associated with the at least a second property, wherein the second dataset comprises information related to one or more objectives made to the second property throughout a refurbishment process;

determining, based on an analysis of the second dataset, an average value contribution of the at least one objective to a second property sale price; and

,

determining the projected value contribution of the at least one objective to the projected sale price of the first property based on the determination of the average value contribution of the at least one objective to the at least a second property sale price.

16. A system for predicting a projected value contribution of at least one objective to a projected sale price of a property, comprising:

a processing circuitry; and

a memory, the memory containing instructions that, when executed by the processing circuitry, configure the system to;

receive a request to determine the projected value contribution of at least one objective to a projected sale price of a first property;

receive a first dataset associated with the first property, wherein the first dataset comprises descriptive information about the first property;

search for at least a second property in which the at least one objective was performed throughout a second refurbishment process;

collect a second dataset that is associated with the at least a second property, wherein the second dataset comprises information related to one or more objectives made to the second property throughout a refurbishment process;

determine, based on an analysis of the second dataset, an average value contribution of the at least one objective to a second property sale price; and

,

determine the projected value contribution of the at least one objective to the projected sale price of the first property based on the determination of the average value contribution of the at least one objective to the at least a second property sale price.