EA038697B1 - Determining risk relating to real estate and reconstruction - Google Patents

Abstract

The invention relates to a computer-implemented method for determining a risk associated with a physical entity based on physical data, said physical entity relating to real estate, said risk relating to a probability of damage of said physical entity with respect to a physical parameter comprised in said physical data, said method comprising the following steps: receiving, from a user, a geographical address of said physical entity; receiving, from the user, an entity category relating to said physical entity, said entity category being one of a row house, a semi-detached house, a detached house or an apartment; automatically determining said risk based on at least on said entity category; automatically determining a set of geographical coordinates of said physical entity based on said geographical address; automatically retrieving at least one value of said physical parameter belonging to said physical data based on said geographical coordinates from a database.

Description

The technical field to which the invention relates

The invention relates to the field of determining the risk associated with a physical object based on physical characteristics, and the said physical object is real estate.

State of the art

Building owners often choose to minimize their risks of loss due to flooding, fire and other risks by taking out insurance to protect themselves against the costs of renovating their insured property. From the insurer's point of view, the ability to accurately estimate the cost of renovation of a building is necessary in order to establish an appropriate fee for such an insurance policy. In addition, it is vital for both the insurer and the building owner to determine the risk associated with the building.

Unfortunately, existing methods for estimating the cost of renovation are complex, ineffective and often inaccurate. Moreover, existing methods for assessing the risk associated with physical objects such as buildings are overly complex for the user or do not take into account the physical data available for risk assessment.

There remains a need for an improved system and a corresponding method for estimating the cost of renovating a building or apartment and automating the formation of a prospectus. However, there remains a need for an improved method and associated system for determining the risk associated with a physical item based on physical data, said physical item being real estate.

US 2003/0115163 describes systems and methods for estimating the cost of renovating a building, as well as the allocated area in a building. Data on prices for reconstruction, based on data supplied by the developer on the cost of a complete reconstruction, is stored in a database from which data is obtained depending on the geographic location, building category and type of built-up area. The selected data is used to obtain an estimate of the renovation costs. Price data for a given geographic location of an existing building is obtained from a database based on location data entered by the user. Data on the level of prices for the renovation of the building and the various areas within the building are also obtained from the database. The reconstruction cost estimate is calculated using the processor based on the price data for a given location and the renovation price data. As such, US 2003/0115163 is mainly aimed at improving the accuracy of estimates. Accordingly, a problem with US 2003/0115163 is that the number of parameters required to be able to estimate the cost of renovation is too large, which makes the system difficult and tedious to use. This is due to the valuation approach used in US 2003/0115163 based on traditional criteria such as the size of the living space. Moreover, the concept US 2003/0115163 lacks the means to take into account the number of floors in a building and, in the case of an apartment building, the presence of separate apartments in an apartment building. At the same time, the approach of US 2003/0115163 is too complex and, moreover, incomplete, when it is necessary to take into account physical data when determining the risk associated with a physical property related to real estate.

US 2013/0211790 describes a system and method for evaluating construction using aerial photographs. The system receives at least one aerial photograph of the building. The scoring engine processes the aerial photograph from multiple angles to automatically identify multiple lines (for example, perimeter and interior) in the image, corresponding to multiple building roof features. The scoring engine allows the user to create 2D and 3D roof models by automatically delineating various roof features, and generates a report that includes information about the roof of the building. The system contains computer systems for receiving aerial photographs of the building. An evaluation engine is implemented in an aerial photographic computer system to evaluate a plurality of features related to the roof of a building. An evaluation engine histogram is provided for processing aerial photographs at multiple angles to automatically identify multiple lines in an image corresponding to multiple roof features. A graphical user interface is provided for displaying an aerial photograph of the building. An issue with US 2013/0211790 is that this document only offers a partial means of estimating the cost of a building renovation. For example, it lacks a means of identifying apartments in a building, as well as a means to account for aspects that are critical to the cost of renovation, such as signs of the neighborhood where the building is located. Also, the approach of US 2013/0211790 is complex and inadequate when it is necessary to take into account physical data when determining the risk associated with a physical property related to real estate.

The object of the invention is to solve at least some of the problems mentioned above. The aim of the invention is to provide an adequate tool and appropriate system for determining the risk and / or estimating the cost of renovation.

The essence of the invention

In a first aspect of the invention, there is provided a computer-implemented method according to claim 1 of the claims.

- 1 038697

This method advantageously comprises said extraction of said value of said physical parameter, which may be decisive for the risk assessment. Said extraction is performed automatically and is based on a common knowledge of data such as a geographic address, which can be considered known to any user as a key feature of said physical object, thus contributing to a positive user experience. Moreover, the method advantageously uses said value of said physical parameter through selective execution, thereby reducing the effort on the part of the user to apply the method. Since the value of the physical parameter can be critical for the risk assessment, it can be considered that it will be more convenient for the user to add an additional step only if the mentioned predetermined value is reached or exceeded. In a preferred embodiment, reaching or exceeding said predetermined value refers to an increased risk and / or an increased likelihood that said risk is high, whereas the opposite may occur when said predetermined value is not reached or exceeded, the risk is reduced / low and / or the likelihood that said risk is high is low. Therefore, it is preferred that the method be as less complicated as possible when the risk is low / low, while adding an additional step when said predetermined value is reached or exceeded. This additional step may relate to obtaining additional physical value from the said user, which may allow for a more accurate calculation of the risk in this case and / or may provide the operator investigating the risk with more detailed information about the reasons and / or circumstances of reaching or exceeding the predetermined value. ... Additionally or alternatively, the additional step may relate to providing additional information to said user. For example, the user may be provided with information regarding the fact that, based on a geographic address, a physical entity is associated with said value of said physical parameter equal to or greater than said predetermined value.

Thus, said automatic determination of said risk, said automatic determination of said set of geographic coordinates, and said automatic extraction may be automatic in the sense that they relate to machine-to-machine operations or interactions between machines. In a preferred embodiment, said method implements a risk determination server, which may or may not be the server referred to herein. In such an embodiment, the risk determination server may be configured to determine said risk, preferably autonomously, based on at least said category of object received from a user and at least one value of said physical parameter. Thus, said geographic coordinates are preferably computed locally on said risk server, but alternatively they can be determined through an interaction associated with a location service with a remote location server, such as a remote geographic information system server. In addition, retrieving said at least one value of said physical parameter can be performed locally by means of said database stored on said risk determination server, but can also be performed through interaction associated with a physical parameter with a remote server associated with a physical parameter. , such as a remote server for determining a physical parameter, configured to receive said set of geographic coordinates as an input value and return said value of said physical parameter as an output value.

In a second aspect, the invention provides a system according to claim 12. In a third aspect, the invention proposes the use of the method according to claims 1-11 in the system according to claims 12-14 of the claims. The advantages of the system and use are similar to those of the method.

Additional preferred embodiments are discussed in the detailed description and dependent claims.

Description of drawings

The figure shows an example of a sequence of actions related to the invention.

Detailed description of the invention

In this document, the term physical object refers to any physical structure or area that can be identified as a permanent or semi-permanent space in which people can reside and / or spend time. Consequently, the term physical entity is generally used interchangeably with the term building unless otherwise indicated. This covers the entire spectrum from private buildings such as houses or apartment buildings to library buildings, town halls, hotels or restaurants, sports stadiums, etc. This could involve a building constructed of common material such as brick, concrete, steel, or wood, but it could also be a cave dug into rock or soil. It can be a permanent structure, but it can also be semi-permanent, as in the case of a trailer, container, van or tent. In addition, the term flat is

- 2 038697 connects to any space in which people can live and / or spend time, while the apartment belongs to the said building. In the context of the present invention, the distinction between apartment and building is purely formal and simply defines the relationship between apartment and building in which the latter includes the former. Generally speaking, a building may contain an apartment, but itself may be contained in a second, larger building.

In this document, the term geographic address or address refers to the physical address of a building or apartment belonging to that building. An address refers to a set of information indicating the location of a building or apartment. Typically, this set includes a country / city / district and / or other political boundary, street name, and other identifiers such as house or apartment numbers. The address can also contain one or more special codes. One of these codes is the postal code to facilitate identification. Another special code is the longitude and latitude of a building or apartment. This can refer to the aforementioned set of coordinates and can be useful as a secondary or alternative means of locating a building or apartment, and can also be critical in the absence of a specific or accessible address.

This document discusses options for implementation that may apply to all aspects of the invention, ie, at least any method, system and use in accordance with the present invention.

In a first aspect, the invention relates to a method according to claim 1 of the claims.

In a preferred embodiment, said value of said physical parameter is based at least in part on automatic measurement of said physical parameter, preferably on automatic measurement of said physical parameter in real time. For example, there may be a network of sensors to measure the water level in an area in which a physical object is located. In another example, seismic activity is measured using sensors located in the soil or in buildings in the vicinity of a physical object. Measurements from such sensors can be collected offline and recorded in a database, but preferably can be recorded in a database in real time. Such an embodiment is advantageous as it automates the process of obtaining said physical parameter. This can lead to a more accurate picture of the actual risk.

In a preferred embodiment, said method comprises the additional step of providing said user with an output based on said risk, said output preferably comprising said risk and / or risk category. This is preferable as it informs the user directly about the risk. This may differ from the way in which said risk is calculated and used in calculating some additional measure without informing the user of the calculated risk.

In another preferred embodiment, said additional step, selectively triggered by said reaching or exceeding said predetermined value, relates at least to said obtaining said additional physical value; wherein said additional step comprises the following: receiving from the user said additional physical value, which is the value of a feature that is an indicator of the risk related to said physical object; and in which said definition of said risk is also based on said value of a feature that is an indicator of risk. This is beneficial because it can lead to a more accurate calculation of the risk associated with a limited set of one or more specific high relevance questions, without the user having to answer many general questions of potentially low relevance.

In a preferred embodiment, said method includes the additional step of providing the user with a first and a second risk value, wherein said first risk value is determined without taking into account said attribute value, which is a risk indicator, and wherein said second risk value is determined taking into account said the value of the attribute, which is a risk indicator, for quantitatively assessing the influence of the mentioned value of the attribute, which is the indicator of risk, and allowing the user to evaluate the said impact.

Such an embodiment can be advantageous as it allows the user to evaluate the effect of certain features of said physical object.

In another preferred embodiment, said additional step, selectively triggered by said reaching or exceeding said predetermined value, relates at least to said providing additional information to said user, said additional step comprising: providing the user with additional information containing a recommendation regarding said physical object, and said recommendation contains a technical measure; and wherein said technical measure refers to a modification of said physical object, which can be

- 3 038697 was carried out by the mentioned user to reduce the mentioned risk. Such an embodiment can advantageously provide the user with specific, highly relevant information on how he / she can take action to mitigate the risk. See the Examples section for an example.

In another embodiment, said recommendation further comprises first and second risk values, wherein said first risk value is determined provided that said technical measure is not implemented, and wherein said second risk value is determined provided that said technical measure has been implemented, to quantify the impact of the mentioned value of the attribute, which is an indicator of risk, and allowing the user to evaluate the said impact. This further enhances the relevance of the recommendations and the technical measures contained therein, leading to a better understanding of the user.

In accordance with another embodiment, said method also comprises the step of: obtaining from a user a characteristic value related to said physical object, said characteristic value relating to at least one physical surface or several floors characteristic of said physical object; and wherein said definition of said risk is also based on said characteristic value. Such an embodiment may be preferable because the risk of damage needs to be assessed in relation to the overall size of the physical object.

In another preferred embodiment, said method includes the additional step of: providing a user with a construction or renovation requirement related to said physical object based on said risk, category of said object, and preferably based on said characteristic value.

In one embodiment, a physical object refers to newly built real estate or real estate that has not yet been built and a building requirement is provided. In another embodiment, the physical object refers to existing immovable property, and in the event of damage or loss of the physical object, a reconstruction requirement is provided that relates to the reconstruction of said physical object. A refurbishment requirement can consist of one or more technical requirements that must be met in relation to a physical object or its refurbishment. For example, an object reconstruction requirement category may be provided, which in the preferred embodiment is equivalent to the object category. One or more specifications may also relate to instructions for reconstruction in relation to said physical object, preferably instructions in relation to foundation and / or fire protection and / or dam and / or seismic activity detection system. Such an embodiment is advantageous in that it facilitates the technical activity of enumerating the requirements associated with the construction or renovation of said physical object.

In another preferred embodiment, said method comprises additional steps comprising the following:

obtaining comparative data on a category of an object from a second database, said second database preferably being said database based on said category of objects, and preferably also based on said characteristic value;

retrieving geo-indexed data from a third database, said third database being said database and / or said second database based on said address and / or said category of objects and / or said property value; preferably based on said address and said category of objects and said characteristic value;

provide the user with information about the cost of construction or reconstruction and / or the complexity of construction or reconstruction in relation to said physical object based on at least the mentioned risk, said comparative data on categories of objects, said geo-indexed data, and preferably additionally based on said characteristic value and / or the mentioned renovation requirement.

Thus, comparative data for asset categories refers to the relative levels of risk and / or complexity and / or cost to construct or renovate each of the many different asset categories. In addition, the comparative data on the categories of buildings may preferably be an example of the said comparative data on the categories of objects. Geo-indexed data refers to data indexed by geographic location indicating the complexity of a building and / or its attributes, such as construction or renovation costs, based on price data for many different categories of properties in a given location. An example of such geo-indexed data is the aforementioned geo-indexed price data. In one embodiment, a physical object refers to newly built real estate or real estate that has not yet been built and provides construction costs. In another embodiment, the physical object refers to existing immovable property, and in the event of damage or loss of the physical object, reconstruction costs are provided.

- 4 038697, which relates to the reconstruction of the said physical object.

In another preferred embodiment, said risk related to said probability of damage refers to the likelihood of damage caused by flooding of said physical object; wherein said physical parameter and said at least one value of said physical parameter relate to the likelihood of flooding associated with a given physical location.

In yet another embodiment, said additional step, selectively triggered by said reaching or exceeding said predetermined value, relates at least to said obtaining said additional physical value; moreover, said additional step comprises the following: receiving from the user said additional physical value, which is the value of a feature that is an indicator of the risk related to said physical object; wherein said definition of said risk is also based on said value of a feature that is an indicator of risk; moreover, the mentioned value of the attribute, which is an indicator of risk, refers to any of the following: the presence and / or physical area of underground space, preferably a basement, of the said physical object; the floor of the mentioned physical object in case the mentioned category of the object is an apartment.

In another further embodiment, said additional step, selectively triggered by said reaching or exceeding said predetermined value, refers to at least said providing said additional information to said user, said additional step comprising: providing the user with additional information containing a recommendation in with respect to the said physical object, and the said recommendation contains a technical measure; wherein said technical measure relates to a modification of said physical object that can be carried out by said user to reduce said risk, said technical measure preferably relates to an underground space, preferably a basement, of said physical object and / or the lowest level of said physical object.

Such an embodiment and each of said additional embodiments may be advantageous as it adequately addresses the problem of determining the risk of flooding. The benefits are discussed in more detail in the Examples section.

In a second aspect, the invention provides a system according to claim 12.

In a preferred embodiment, said determination of said set of geographic coordinates based on said geographic address is performed by a remote location server other than said server. In a corresponding preferred embodiment, said machine storage medium containing said database is contained on a remote server associated with physical parameters other than said server. This is advantageous in that it provides modularity, allowing you to create a system that is easier to administer and / or that is more predictable in its operation and / or more adequate for delegating certain steps of the method to third parties. In another preferred embodiment, said remote location server is equivalent to said remote server associated with physical parameters.

In a preferred embodiment, one or more of the method steps may be performed via a dedicated graphical interface on a user device, but may also be performed using a plug-in or internal functionality of some larger application or web service with a website, which may be a native application. or a web service or third party application or web service. In some embodiments, such an application may only apply to apartments, for example. In such a case, the use of the application may entail that the user is viewing the physical object, which is an apartment, and therefore the second step does not need to be explicitly performed, but this follows from the context and the fact that the user is using the application.

In a preferred embodiment, the user is prompted for a geographic address and a site category for a variety of purposes, of which risk determination is only one goal. For example, an application or web service that provides a context for the present invention may relate to the estimation of the cost of renovating said physical object, for example, through the system and the brochure in accordance with claims 1-15. For such an assessment, it may be important to define the mentioned risk. For example, it can be helpful to determine if a physical object is, for example, in a flooded area to determine the type of foundations needed. In another example, a physical object in an area of increased fire hazard may indicate that appropriate building materials are required, such as refractory building materials.

In accordance with another aspect, which in no way limits the invention, the invention relates to the technical field of estimating the cost of renovating a building or apartment and creating

- 5 038697 Danish of the prospectus associated with the said building or apartment, and may or may not refer to the following items 1-15.

1) A computing system for estimating reconstruction costs, the computing system comprising a server, the server comprising a processor, nonvolatile material memory, program code located in said memory for instructing said processor;

at least one computer-readable medium, wherein at least one computer-readable medium comprises a database, said database comprising renovation price data containing a plurality of price index data indexed by a respective geographic location and representing renovation price data for a plurality of different building types and many different types of floor space in a building, comparative data by category of buildings, representing the relative price levels for renovation of each of many different categories of buildings, and alternatively, comparative data on apartments, representing the relative price levels for renovation of each of the many different types of apartments in the building ;

said computing system is configured to perform a method for said estimating said renovation costs of a building and / or apartment belonging to said building, said method comprising the following steps:

(a) receive a set of key parameters entered by the user belonging to the user input on the said server; wherein said key user input relates to said building and / or said apartment belonging to said building;

(b) retrieving building data related to said user input from said database;

(c) determining data defining a category for said building based on said building data;

(d) optionally determining type data for said apartment belonging to said building, the type of apartment data being selected from a plurality of different types of apartments;

(e) retrieving price index data related to said user input from said database;

(f) retrieving relevant comparative building category data from the database for said building based on the building category defining data identified in step (c);

(g) if necessary, obtain relevant comparative data on apartments from the database based on the data on the types of apartments identified in step (d);

(h) determine whether sufficient information is available to estimate the cost of renovating a building and / or apartment belonging to said building:

(h.1) if yes, then go to step (i);

(h.2) if not, then obtain additional user input parameters belonging to said user input from said user and return to step (b);

(i) generating said estimate of renovation costs for a building and / or apartment belonging to said building based on at least the price index data obtained in step (e), corresponding comparative building category data obtained in step (f ), and, optionally, the corresponding comparative apartment data in step (g);

characterized in that said set of key parameters entered by the user consists only of (A) the address of said building and / or an apartment belonging to said building, (B) in the case of an apartment, an area of said apartment and, as an option, from (C) said type of said building and / or possibly (D) the number of levels of said building, and in that said type of said building is one of the following types: townhouse, semi-detached house, detached house or apartment building.

2) A computing system according to claim 1, characterized in that said set of key parameters entered by the user consists only of (A) the address of said building and / or an apartment belonging to said building, (B) in the case of an apartment, the area of said apartment, and (C) the type of building mentioned.

3) A computing system according to claim 1, characterized in that said set of key parameters entered by the user consists only of (A) the address of said building and / or an apartment belonging to said building, (B) in the case of an apartment, the area of said apartment, and (D) the number of floors of said building.

4) A computing system according to claim 1, characterized in that said set of key parameters entered by the user consists only of (A) the address of said building and / or an apartment belonging to said building, (B) in the case of an apartment, the area of said apartment, (C) the type of said building; and (D) the number of floors of said building.

5) A computing system according to any of the previous clauses 3, 4, characterized in that said

- 6,038697 database contains comparative data on apartments, representing the relative price levels for renovation of each of the many different types of apartments; wherein said method comprises step (d), which determines type data of said apartment belonging to said building, wherein the type of apartment data is selected from a plurality of different types of apartments, and step (g), which retrieves corresponding comparative apartment data from databases based on the type of apartment identified in step (d); and in that said apartment type data determined in step (d) is determined based at least in part on said number of floors.

6) A computing system according to any of the previous claims 1-5, characterized in that said additional parameters entered by the user contain an indication relating to any or any combination of the following parameters: the current commercial purpose of the said building, the former commercial purpose of the said building, the second house, houseboat, chalet, mobile home, listed building, thatched roof, mentioned building under construction, mentioned building to be demolished, mentioned building in disrepair, land area, building located in the river floodplain, presence of solar panels , a building located in a foreign country, a user with items of high value.

7) A computing system according to any of the previous claims 1-6, characterized in that step (h) further comprises the following: generate a variance related to said estimate of reconstruction costs to be obtained in step (h), said variance characterizes the accuracy of the mentioned estimate of reconstruction costs.

8) A computing system according to claim 7, characterized in that said variance obtained in step (h) is used to decide whether there is sufficient information to generate said estimate of the reconstruction costs, and preferably to decide whether what parameters, supplied by the user, to receive at stage (h.2).

9) A computing system according to any of the previous claims 1-8, characterized in that step (c) comprises the following: determining the estimate of the number of floors of said building based on the height and / or area of the land plot and / or the number of rooms and / or the size of the building itself. a large room of the said building obtained in step (b).

10) A computing system according to any one of the preceding claims 1 to 9, characterized in that step (h) comprises the following: it is checked whether the area of the plot of land exceeds the threshold value of the area of the plot of land.

11) A computing system according to any of the previous claims 1-10, characterized in that said database contains one or more data sets, of which at least one data set is located at a remote location relative to said server.

12) A computing system according to any of the previous claims 1-11, characterized in that said database contains data about the surroundings surrounding said address, and said data about the surroundings contains any information or any combination of the following information: median income, type of urbanization , socio-economic data about the area, such as statistics on income or living conditions, general population density, population density by age.

13) A computing system according to any of the previous claims 1-12, characterized in that said computing system is also configured to carry out a method for generating a prospectus, said method comprising the following steps:

(01) receive input on the legal capacity of a user belonging to said input about the user and related to the legal capacity of the user, wherein said legal capacity relates to a tenant and / or home owner and / or tenant;

(02) obtaining brochure-related user inputs related to said user inputs, said prospect-related user inputs comprising the presence and area of a swimming pool, and / or the presence and area of a garden, and / or the presence of a fuel tank, and / or the year of construction of the building, and / or the availability of a parking space;

(03) generate a prospectus containing a premium based at least in part on said estimate of renovation costs, and further comprising one or more additional insurances determined at least in part on said user input relating to said related the prospectus of the sign obtained in step (02).

14) A computing system according to the previous claim 13, characterized in that said step (03) comprises the following: determining whether said prospectus can be accepted by said system, wherein said determination takes into account the risk associated with said user input data and / or additional available information concerning the mentioned user.

15) A prospectus generated by the system according to claim 14, wherein said prospectus contains a visualization either on the screen of the device of said user, or on a printout of data obtained on said device of said user; wherein said prospectus contains said premium and a list of said optional insurances, each of said optional insurances is visualized with a corresponding premium to the premium determined by said system.

In accordance with the mentioned additional aspect and regarding the mentioned paragraphs 1-15, in on

- 7 038697 The standing invention provides a computing system for estimating renovation costs, comprising the following:

a server, and the server contains a processor, non-volatile material memory, program code located in said memory for instructing said processor;

at least one computer-readable medium, and at least one computer-readable medium contains a database, and said database contains data on prices for reconstruction, containing:

a plurality of price index data indexed by a respective geographic location and representing renovation price data for many different types of buildings and many different types of floor space in a building, comparative data by building category representing the relative price levels for renovation of each of many different types of buildings, and alternatively, comparative apartment data, representing the relative price levels for the renovation of each of the many different types of apartments in the building;

said computing system is configured to perform a method for said estimating said renovation costs of a building and / or apartment belonging to said building, said method comprising the following steps:

(a) receive a set of key parameters entered by the user, belonging to the user input, on the said server; wherein said key user input relates to said building and / or said apartment belonging to said building;

(b) retrieving building data related to said user input from said database;

(c) determining data defining a category for said building based on said building data;

(d) optionally determining type data for said apartment belonging to said building, the type of apartment data being selected from a plurality of different types of apartments;

(e) retrieving price index data related to said user input from said database;

(f) retrieving relevant comparative building category data from the database for said building based on the building category defining data identified in step (c);

(g) if necessary, obtain relevant comparative data on apartments from the database based on the data on the types of apartments identified in step (d);

(h) determine whether sufficient information is available to estimate the cost of renovating a building and / or apartment belonging to said building:

(h.1) if yes, then go to step (i);

(h.2) if not, then receive additional user input parameters belonging to said user input from said user and return to step (b);

(i) generating said estimate of renovation costs for a building and / or apartment belonging to said building based on at least the price index data obtained in step (e), corresponding comparative building category data obtained in step (f ), and, optionally, corresponding comparative data on apartments in step (g), wherein said set of key parameters entered by the user consists only of (A) the address of said building and / or an apartment belonging to said building, (B) in the case apartment, district of said apartment and, as an option, from (C) said type of said building and / or possibly (D) the number of levels of said building, and the fact that said type of said building is one of the following types: townhouse, semi-detached house , detached house or apartment building.

The advantage of such a system is the ease of use offered to the user of the system. Instead of going through an extensive list of questions before obtaining a prospectus, as is the case in prior art systems, the user is simply required to enter a very limited number of key user inputs, of which the address is the primary one, optionally supplemented by the building type and the number of building levels. ... If it is supposed to estimate the mentioned reconstruction costs for an apartment belonging to the said building, then the area of the said apartment is also requested. Thus, this user input, and in particular the address, is used to retrieve data from the database. While it is possible that additional user input parameters will be requested in the second step, there is a significant likelihood that the user will be assisted without the need to obtain these additional user input parameters, resulting in a quick estimate of the cost of renovation and, in a preferred embodiment, prospectus.

In addition, it should be noted that the selection of key parameters entered by the user is beneficial in itself. Indeed, in the current context of the information society, the address itself provides access to a lot of information about a building or apartment, including aerial photographs and 3D views such as Google Street View. The number of floors is especially important for complementing

- 8 038697 knowledge available in the database, for example to check the correctness of the height value present in the database. This can facilitate the output of the average area per floor (in m ² ). In turn, knowing the average floor area per floor allows the unit cost per floor unit, preferably obtained in step (e), to be used to obtain an estimate of the renovation costs for a floor, apartment, or the entire building. This is advantageous because usually the number of floors can be reliably obtained from the user, whereas for the living area (in m ² ), the estimate given by the user is error prone. The type of building is significant because it can indicate the total value of the property.

Also, the present invention provides advantages for the system administrator who manages the system. Due to the very limited amount of user input required to obtain an estimate of the renovation costs, the user interface can be simplified. In a preferred embodiment, the database contains one or more datasets, of which at least one dataset is located at a remote location relative to said server. This part of the remote dataset can be managed by a third party. The remote dataset may be freely available or available under certain terms and conditions associated with service agreements. Its advantage lies in the fact that access to external information, which is kept up to date by a third party, reduces the burden on the system administrator.

Another advantage relates to improved estimation accuracy over prior art systems. While prior art systems typically collect a lot of information using an extensive list of questions to be answered by the user, the relationship between responses and cost estimates is usually based on some generalization and is error prone. For example, relying on the number of rooms to estimate renovation costs is not always appropriate due to the large differences between building styles and current trends in construction. Indeed, over the past decades, the number of rooms in each house as a whole has declined, while the area of a room has increased on average. Therefore, the use of an extensive list of questions and the subsequent accounting for historical correlations is far from accurate. On the contrary, the present invention uses a data-driven approach in which, in particular, the address forms the key to electronically and automatically retrieving a large amount of information that until recently was not available electronically.

In a preferred embodiment of the present invention, the system in accordance with the present invention is also configured to carry out a method for creating a prospectus, said method comprising the following steps:

(01) receive input on the legal capacity of a user belonging to said input about the user and related to the legal capacity of the user, wherein said legal capacity relates to a tenant and / or home owner and / or tenant;

(02) obtaining prospect-related user inputs related to said prospect-related user inputs, said prospect-related user inputs comprising the presence and area of a swimming pool, and / or the presence and area of a garden, and / or the presence of a fuel tank, and / or the year of construction of the building, and / or the availability of a parking space;

(03) generate a prospectus containing a premium based at least in part on said estimate of renovation costs, and further comprising one or more additional insurances determined at least in part on said user input relating to said related the prospectus of the sign obtained in step (02).

Here, the term prospectus refers to a commercial offer for insurance of a building or apartment belonging to said building and is at least in part based on renovation costs or an estimate thereof. Moreover, the term legal capacity covers any person / party responsible for the said building or said apartment belonging to the said building, regardless of the exact context connecting that person / party with the people actually living or spending time there. This context can be captured in a regular contract, but it can also be a hotel service like Airbnb.

The advantage is that the user can get the complete brochure after entering only a limited number of key parameters entered by the user. This is beneficial as it meets the requirements of the user who is looking not only for an estimate of the cost of renovation, but also for the entire brochure around the house on the Internet, while wanting to keep the process simple and fast and involve as few steps as possible. In another preferred embodiment, said step (03) comprises the following: determining whether said prospectus can be accepted by said system, said determination taking into account the risk associated with said user input and / or additional available information regarding said building or apartment and, optionally, related to said user. From the point of view of the policyholder associated with the aforementioned prospectus, this is preferable, since it leads to early filtering of users, thus, only those prospectuses that cannot be generated automatically require personal attention of the insurer's employee.

- 9 038697

In another aspect, preferably related to the aforementioned claims 1 to 15, the present invention provides a brochure generated by a system in accordance with the invention, said brochure comprising a visualization either on the screen of said user's device or on a printout of data received on said device of said user ; wherein said prospectus contains said premium and a list of said optional insurances, each of said optional insurances is visualized with a corresponding premium to the premium determined by said system.

In yet another aspect concerning the above-mentioned claims 1-15, the invention provides a system according to any one of claims 11-14 of the claims and at the same time according to any of claims 1-14, for example, a system according to claim 1 of the claims and claim 1 or the system according to claim 2 of the claims and claim 2.

In a preferred embodiment, said set of key parameters entered by the user consists only of (A) the address of said building and / or apartment belonging to said building, (B) in the case of an apartment, the area of said apartment, and (C) the type of said building. In a corresponding preferred embodiment, said set of key parameters entered by the user consists only of (A) the address of said building and / or apartment belonging to said building, (B) in the case of an apartment, the area of said apartment, and (D) the number of levels of said building. Both embodiments have the advantage that only two key parameters from the user are required from the user, which leads to an improved user experience. In another preferred embodiment, said set of key parameters entered by the user consists only of (A) the address of said building and / or apartment belonging to said building, (B) in the case of an apartment, the area of said apartment, (C) the type of said building, and ( D) the number of levels of the said building. From a usability point of view, this embodiment is also preferred since only three key parameters are required from the user.

In a preferred embodiment, said database comprises apartment comparative data representing the relative level of renovation prices for each of a plurality of different apartment types; wherein said method comprises step (d), which determines type data of said apartment belonging to said building, wherein the type of apartment data is selected from a plurality of different types of apartments, and step (g), which retrieves corresponding comparative apartment data from databases based on the type of apartment identified in step (d); wherein said apartment type data determined in step (d) is determined at least in part on the basis of said number of floors. The advantage of accounting for different types of apartments is beneficial in itself, as it gives a higher accuracy in estimating renovation costs. Since the apartment type data is based at least in part on the number of levels, the minimum amount of information provided by the user is maximized.

In accordance with another preferred embodiment of the present invention, said additional parameters entered by the user comprise an indication relating to any or any combination of the following parameters: current commercial purpose of said building, former commercial purpose of said building, second home, houseboat, chalet, house on wheels, listed building, thatched roof, said building under construction, said building to be demolished, said building in disrepair, land area, building located in a river floodplain, presence of solar panels, building located in a foreign country, user possessing items of high value. Thus, the reason for requesting additional parameters from the user is that the set of key parameters entered by the user is not detailed enough to calculate an accurate estimate of the reconstruction costs. According to a preferred embodiment, another reason may be that there is not enough information to decide whether said prospectus should be accepted. Requesting additional user input parameters only later, rather than from the very beginning, is advantageous, since it allows in many cases to obtain an estimate of the cost of construction and / or a prospectus without the need for the user to enter additional input parameters.

According to another preferred embodiment, step (h) further comprises the following: generating a variance related to said estimate of renovation costs to be obtained in step (h), said variance characterizing the accuracy of said estimate of renovation costs. As a statistical measure, this variance indicates the deviation that can be expected when comparing the obtained estimate of reconstruction costs with another value of reconstruction costs, for example, the amount of reconstruction costs obtained by manual intervention and detailed manual analysis, and subsequently, the actual cost of reconstruction. Variance can also be associated with a specific interval around the estimate, which interval indicates the range in which the actual cost of reconstruction is likely to be. Thus, in a preferred embodiment, the probability that the actual cost of reconstruction is within the described range can be expressed as

- 10 038697 wife in percentage, for example, 95%, indicating that the actual cost of reconstruction can be in this interval, for example, with a probability of 95%. In a preferred embodiment, the variance may preferably be used to trigger certain decisions, wherein a certain threshold value may be used to determine if the variance is, for example, low enough or too high. The first decision of this kind is whether the prospectus related to the calculation of the renovation costs can be adopted. This is also discussed below. Thus, high variance may indicate too much uncertainty, leading to a decision not to accept the prospectus and to recommend that the user go through a face-to-face interview at the branch / agent. On the other hand, low variance may indicate a good quality estimate, indicating that a prospectus can be generated at least if all other conditions associated with this decision are met. The second decision of this kind is the decision in step (h) about the presence or absence of sufficient information. Thus, if the variance turns out to be too high, it may be advisable to prompt the user for additional inputs in accordance with step (h.2). On the other hand, if the variance is low enough, then it may also be necessary to ask the user for additional input parameters in accordance with step (h.1).

In another preferred embodiment, said variance obtained in step (h) is used to decide whether there is sufficient information to generate said estimate of the renovation costs, and preferably to decide which user input parameters to retrieve on step (h.2). As discussed above, variance can be used to initiate certain decisions. In another preferred embodiment, the resulting variance not only determines whether additional input parameters should be received from the user, but also, if additional input parameters are required from the user, determines the number and type of user parameters required. For example, a variance that is only slightly overestimated may require only a small number of additional questions to be presented to the user, while an excessively large variance may require more additional questions.

In a preferred embodiment, step (c) comprises the following: determining an estimate of the number of floors of said building based on the height and / or area of the plot of land and / or the number of rooms and / or the size of the largest room of said building obtained in step (b) ... This is especially beneficial when the height and / or area of the plot of land and / or the number of rooms and / or the size of the largest room of said building are readily available parameters in a database, for example in an external dataset collected by a third party and / or the government. As mentioned above, if the height and area of the parcel is available, then this information can be combined with the number of floors to get the average area per floor. This, in turn, can be used, at least in part, to obtain an estimate of the renovation costs using unit costs per unit area, preferably obtained in step (e). The number of rooms and / or the size of the largest room can additionally be used to improve the accuracy of the calculation and / or to check / improve the estimate of the average floor area.

In a preferred embodiment, step (h) comprises the following: checking if the land area exceeds the land area threshold. This is preferable as it allows for a situation where a building has many annexes at the ground floor level that do not extend above the ground floor. This may be evidenced by the excessive importance of the area of the land plot. In this case, the calculation should not take into account the area of the plot of land, as this leads to an inaccurate estimate of the average area per floor. Thus, it is preferable to trim the land area value to a certain maximum value and use this maximum value instead of the original land area value in further calculations.

In a preferred embodiment, the database contains one or more datasets, of which at least one dataset is located at a remote location relative to said server. This part of the remote dataset can be managed by a third party. The remote dataset may be freely available or available under certain terms and conditions associated with service agreements. Its advantage is that access to external information that is kept up to date by a third party can reduce the burden on the system administrator (s) administering the system in accordance with the present invention.

In yet another embodiment, said database contains data about neighborhoods surrounding said address, said neighborhood data containing any information or any combination of the following information: median income, type of urbanization, socio-economic data about the area, such as income statistics or living conditions , general population density, population density by age. This is beneficial as it provides sufficient input to the statistical model underlying the costing. From experiments carried out on the available datasets, it is clear that renovation-related characteristics of the house, such as types, are used.

- 11 038697 materials and degree of finishing, can indicate not only the type of house, but also data about the surroundings.

In accordance with a preferred embodiment, said additional user-entered parameters comprise an indication relating to any or any combination of the following parameters: current commercial purpose of said building, former commercial purpose of said building, second home, houseboat, chalet, mobile home, said listed building, thatched roof, said building under construction, said building to be demolished, said building in disrepair, land area, building located in a river floodplain, presence of solar panels, building located in a foreign country, a user with items of high value. This has the advantage that such additional user input can be used in step (i) to obtain a more accurate estimate of the renovation costs. Thus, the said building is an architectural monument if it is subject to restrictions related to cultural heritage.

In a preferred embodiment, additional information about the property, such as aerial photographs, is also taken into account when determining the cost of the renovation and / or when generating the prospectus.

In another preferred embodiment, additional information about the property, such as aerial photographs, is also taken into account in determining the risk.

In another preferred embodiment, said set of key parameters entered by the user consists only of (A) the address of said building and / or apartment belonging to said building and, optionally, (C) the type of said building and / or, optionally, ( D) the number of levels of the said building.

The invention is further described in the following non-limiting examples, which further illustrate the invention, although they are not intended to limit the scope of the invention, and should not be interpreted as limiting.

Examples of

Example 1. An example of a flowchart for steps (1) to (9).

This example is illustrated by the flowchart shown in the figure containing steps (1) to (9). This example relates to the estimation of renovation costs for a building or apartment belonging to that building in the context of a home insurance offer using a system presented to the user as an online platform. The building type can be one of the following: apartment building, townhouse, semi-detached house, or detached house, and the allocated area can be for an apartment belonging to a multi-family building or for an entire building.

A key advantage of the system is that it allows you to estimate renovation costs based on (very) limited user input. User input concerns a (very) limited set of user-definable parameters. This meets the requirements of a user looking for a brochure around the house on the Internet, while wanting to keep the process simple and fast and involve as few steps as possible. The system goes through a series of steps to estimate costs.

Step (1) concerns the user making the first user input, i. E. input of key parameters entered by the user, in this case the address of the property. The set of key parameters entered by the user is received by the server, which has the task of forming a prospect around the house, which entails determining an estimate of the cost of restoration.

In step (2), the server retrieves data from the database to obtain an estimate of the cost of the renovation. This data contains data about the property itself (type of building, area, height), as well as data about the surrounding area (median income, type of urbanization, socio-economic data about the neighborhood, such as income statistics or living conditions, population). Preferably, the database contains a plurality of data sets that are external to the insurance company issuing the prospectuses.

At stage (3), based on the quality of the data obtained, the algorithm decides whether there is enough information for the model or not: if yes, then the system goes to stage (5), otherwise the system goes to stage (4).

At step (4), if necessary, additional information is requested from the user. It is also called optional user-supplied parameters.

In step (5), the system runs one or more statistical models on all information from the prospectus, along with information obtained from the database.

At step (6), the possibility of acceptance is calculated, the needs and the value of the property are determined as the output of said one or more statistical models. Here, the acceptability refers to the willingness of the insurance company to accept the said property and, alternatively, the said user for online insurance, based on internal risk and / or specific criteria associated with the online process. In addition, the definition of needs refers to

- 12 038697 on the one hand, to determine the needs of a specific user of the said property (for example, whether he needs insurance for the owner-owner, landowner or tenant). On the other hand, identifying needs involves answering the question of whether the property in question needs some additional insurance, such as swimming pool insurance, garden insurance or fuel tank insurance. Value estimation refers to the use of a combination of prospectus input data (primarily only the address of said property) and available internal and / or external data, processing said input data and additional data using a statistical model (s) and issuing a correct reconstruction estimate for said property. If there is no readiness to accept the mentioned prospectus (which implies the acceptance, among other things, of the mentioned user and the mentioned property), then the system proceeds to step (9). If there is a willingness to accept the aforementioned prospectus, then the system proceeds to step (7).

At step (7), a pricing model is applied to the output of the statistical model.

In step (8), the premium is calculated.

In step (9), the user is referred to the standard checkout process at the branch / agent location. Example 2. An example of implementation with flooding.

In this example, said method according to claim 1 of the claims is applied in the case where the risk is associated with flooding. Thus, the risk related to said probability of damage refers to the likelihood of damage caused by flooding of said physical object. Said physical parameter and said at least one value of said physical parameter relate to the likelihood of flooding associated with a given physical location.

More preferably, the physical parameter refers to a flood flood map in which said physical entity is located, identifying areas of low and / or high likelihood of flooding based on measurements in recent years. In one embodiment, for each location characterized by, for example, a set of geographic coordinates, the flood map may indicate any of the following variables, or any combination of them:

a boolean value for a given time window indicating whether the given location was flooded or not;

a numerical value of p, 0 <p <1, representing the probability of a potential risk of flooding for a given period of time, for example, over the next ten years;

the intensity of flooding in a given time window, taking into account the number of times a given location was flooded and / or the water level at the time of flooding at a given location.

A physical parameter can be any of these variables, or it can be obtained as a combination of these variables, for example, in the form of a linear combination of them with weights that can be selected based on experience and / or adjusted so as to optimally correspond to some available data set, according to some criterion such as the least squares test.

In this example, a method in accordance with the invention comprises the following steps, which may be performed by a local server or a cloud computing service running remotely.

The first step is to obtain from the user the geographic address of the said physical object. The second stage consists in obtaining from the user the category of the object related to the said physical object, and the mentioned category is one of the following: townhouse, semi-detached house, detached house or apartment.

Then, the third step is to automatically determine a set of geographic coordinates of said physical object based on said geographic address. This is preferably done by referring to its own geographic database, which is regularly updated. Such a native database, for example, can be stored on a server, or it can be privately stored / accessed and maintained in the context of said cloud computing. In an alternative step, said third step is performed by sending a geographic address to a third-party service that, upon receiving the geographic address, searches for and returns a set of geographic coordinates.

The fourth step is to automatically retrieve from the database at least one value of said physical parameter belonging to said physical data, based on said geographic coordinates. In particular, for a given set of geographic coordinates, the risk of flooding is extracted from the database. This risk of flooding is compared with a predetermined value, wherein said at least one value of said physical parameter equal to or greater than said predetermined value selectively triggers an additional step of the method, i.e. fifth optional stage.

The fifth stage is optional and is selectively triggered in the fourth stage. This step is carried out only if a high risk of flooding is detected. The fifth stage is as follows: an additional physical value is obtained from the user, which is the value of a feature that is an indicator of the risk associated with the said physical object. In particular, the meaning of a feature that is an indicator of risk refers to any of the following: the presence and / or physical surface of an underground space, preferably a basement, of said physical object

- 13 038697 ta; the floor of the mentioned physical object in case the mentioned category of the object is an apartment. In one embodiment, the physical object is an apartment with a high risk of flooding, and the value of the risk indicator is a floor. Thus, a floor of 0 may indicate a higher risk of damage due to flooding than, for example, a floor of 1, 2, 3, 4, 5, 6, or 7. In another example, the physical object is a semi-detached house, and the value of a feature that is a risk indicator is the presence of a basement. Thus, the presence of a basement may indicate an increased risk of damage from flooding.

The sixth stage consists in determining the mentioned risk based on at least the category of the mentioned object and the value of the attribute, which is the indicator of the risk.

In this example, these steps are performed through a dedicated graphical interface on a user device running a web service with a web application, i.e. web service with website. The physical object can belong to any category, and, therefore, the selection in the second stage is made unambiguously by means of a drop-down menu or a list with a radio button. The application prompts the user for the geographic address and category of the facility for a variety of purposes, of which risk identification is only one goal. The application is associated with an estimate of the costs of the reconstruction of the said physical object, for example, using the system and the prospectus according to paragraphs 1-15. The assessment includes the following: determine the risk, thereby determining whether the physical object is in the flooded area, for example, to determine the type of foundations required for reconstruction.

In an alternative embodiment, the fifth step also and / or additionally comprises the following: giving a recommendation regarding a technical object, said recommendation comprising a technical measure. A technical measure, for example, can relate to reducing the risk of flooding, for example by eliminating the basement by filling it with fill material.

Example 3. An example of implementation with a different physical parameter.

In this third example, the attributes are the same as in the second example, except that the physical parameter refers to a different card. For example, it may refer to a fire risk map, which may refer to an area with a risk of wildfires. In another embodiment, the physical entity is located in an area of increased seismic activity, such as natural seismic activity or seismic activity due to hydraulic fracturing or mining, and the physical parameter refers to a seismic or earthquake map. In this example, a combination of physical parameters is preferably considered, for example a combination of flooding risk, fire risk and seismic risk.

Claims (15)

CLAIM 1. A computer-executed method for determining the risk associated with a physical object based on physical data, said physical object being real estate, said risk associated with the likelihood of damage to said physical object in relation to a physical parameter contained in said physical data, said method contains the following steps: obtain on the server from the user the geographic address of the said physical object; receive on the server from the user the category of the object related to the said physical object, and the mentioned category is one of the following: townhouse, semi-detached house, detached house or apartment; said risk is automatically determined by the server based on at least the category of said object, characterized in that said method also comprises the following steps: automatically determining a set of geographic coordinates of said physical object based on said geographic address; automatically retrieve from the database at least one value of said physical parameter belonging to said physical data, based on said geographic coordinates; and in that said determination of said risk is also based on said at least one value of said physical parameter, and in that said at least one value of said physical parameter is compared with a predetermined value, wherein said at least one value of said physical parameter equal to or greater than said predetermined value, selectively triggers an additional step in said method, said triggering being selectively performed in order to reduce the required mental and physical efforts of the user in determining said risk, and wherein said additional step relates to obtaining an additional physical value from said user and / or to provide additional information to said user, additionally characterized in that said - 14 038697 the value of said physical parameter is at least partially based on automatic real-time measurement of said physical parameter through a network of sensors in the area where the physical object is located, in which automatic sensor measurements are recorded in a database in real time, while said at least one value of said physical parameter refers to the likelihood of flooding and / or seismic activity associated with a given physical location, in which said determination of said set of geographic coordinates of said physical object based on said geographic address is performed by a remote location server other than said server, and in which said database is contained on a remote server associated with physical parameters other than said server. 2. A method according to claim 1, wherein said method comprises the additional step of providing said user with an output based on said risk, said output preferably comprising said risk and / or risk category. 3. A method according to claim 1 or 2, characterized in that said additional step, selectively initiated by said reaching or exceeding said predetermined value, relates at least to said obtaining said additional physical value and in that said additional step comprises the following: receive from the user said additional physical value, which is the value of a feature that is a risk indicator related to said physical object, and that said definition of said risk is also based on said value of a feature that is a risk indicator. 4. The method according to claim 3, characterized in that said method also comprises the following steps: providing the user with the first and second risk values, wherein said first risk value is determined without taking into account the said attribute value, which is a risk indicator, and wherein said second value The risk is determined taking into account the mentioned value of the attribute, which is a risk indicator, to quantitatively assess the influence of the mentioned value of the attribute, which is a risk indicator, and provide the user with the opportunity to evaluate the mentioned impact. 5. A method according to claims 1-4, characterized in that said additional step, selectively triggered by said reaching or exceeding said predetermined value, relates at least to said providing additional information to said user and in that said additional step comprises the following: provide the user with additional information containing a recommendation regarding said physical object, wherein said recommendation contains a technical measure, and that said technical measure refers to a modification of said physical object that can be carried out by said user to reduce said risk. 6. The method according to claim 5, characterized in that said recommendation further comprises first and second risk values, wherein said first risk value is determined provided that said technical measure is not implemented, and wherein said second risk value is determined provided that said technical measure is implemented to quantify the impact of said value of the attribute, which is a risk indicator, and to enable the user to evaluate said impact. 7. A method according to claims 1-6, characterized in that said method also comprises the following steps: obtain from a user a value of a characteristic related to said physical object, wherein said value of a characteristic refers to at least one of the following: a physical surface or a number floors characteristic of said physical object, and wherein said definition of said risk is also based on said characteristic value. 8. A method according to claims 1-7, characterized in that said method also comprises the following steps: provide the user with a construction or reconstruction requirement related to said physical object based on said risk, category of said object, and preferably based on said characteristic value ... 9. A method according to claims 1-8, characterized in that said method also comprises the following steps: obtaining comparative data on an object category from a second database, said second database preferably being said database based on said object category, and preferably also based on said characteristic value; retrieving geo-indexed data from a third database, said third database being said database and / or said second database based on said address and / or said category of objects and / or said property value; preferably based on said address and said category of objects and said characteristic value; provide the user with the cost of construction or renovation in relation to the mentioned - 15,038697th physical object based on at least said risk, said comparative data about categories of objects, said geo-indexed data, and preferably additionally based on said characteristic value and / or said reconstruction requirement. 10. A method according to claims 1-9, characterized in that said risk related to said probability of damage refers to the likelihood of damage caused by flooding of said physical object. 11. The method according to claim 10, characterized in that said additional step, selectively initiated by said reaching or exceeding said predetermined value, relates at least to said obtaining said additional physical value; wherein said additional step comprises the following: receiving from a user said additional physical value representing the value of a feature that is a risk indicator related to said physical object, wherein said definition of said risk is also based on said value of a feature that is a risk indicator; moreover, the mentioned value of the attribute, which is an indicator of risk, refers to any of the following: the presence and / or physical surface of an underground space, preferably a basement, of said physical object; the floor of the said physical object if the mentioned category of the object is an apartment; and / or in that said additional step, selectively triggered by said reaching or exceeding said predetermined value, relates at least to said providing additional information to said user, said additional step comprising: providing the user with additional information containing a recommendation in with respect to the said physical object, and the said recommendation contains a technical measure; wherein said technical measure relates to a modification of said physical object that can be performed by said user to reduce said risk, said technical measure preferably relates to an underground space, preferably a basement, of said physical object and / or the lowest level of said physical object. 12. A computing system for determining the risk associated with a physical object based on physical data, said physical object being real estate, said risk is associated with the probability of damage to said physical object in relation to a physical parameter contained in said physical data, and the computing system contains following: a server, and the server contains a processor, non-volatile material memory, program code located in said memory for instructing said processor; a user device, the user device comprising a processor, non-volatile non-volatile memory, program code located in said memory for supplying commands to said processor, a screen for displaying information to said user, input means for receiving user input from a user, communication means for connecting to said server; at least one computer-readable medium, wherein at least one computer-readable medium comprises a database, wherein said database contains said physical data, wherein said computer-readable medium containing said database is contained on a remote server associated with physical parameters other than said server, wherein said physical data contains a plurality of values of said physical parameter, indexed by corresponding geographic coordinates, said computing system being configured to determine the risk associated with a physical object based on physical data, said method comprising the following steps: obtain by said server the geographic address of said physical object from said user using said input means; receive, by said server, from said user by said input means, an object category related to said physical object, said category being one of the following: townhouse, semi-detached house, detached house or apartment; said risk is automatically determined by said server based on at least the category of said object, characterized in that said method also comprises the following steps: automatically determining, preferably by said server, a set of geographic coordinates of said physical object based on said geographic address, in which said determination of said set of geographic coordinates of said physical object based on said geographic address is performed by a remote location server other than said server; automatically retrieved, preferably by means of said server, from said database 16,038697 data at least one value of said physical parameter belonging to said physical data, based on said geographic coordinates; and in that said determination of said risk is also based on said at least one value of said physical parameter; and and in that said at least one value of said physical parameter is compared to a predetermined value, wherein said at least one value of said physical parameter equal to or greater than said predetermined predetermined value selectively triggers an additional step in said method, said triggering is performed selectively in order to reduce the required mental and physical efforts of the user in determining the said risk, and wherein said additional step relates to obtaining additional physical value from said user and / or to providing additional information to said user; and in that preferably said value of said physical parameter is at least partly based on automatic measurement of said physical parameter, preferably on automatic measurement of said physical parameter in real time via a network of sensors in the area in which the physical object is located, in which automatic measurements sensors are recorded in a database in real time, wherein said at least one value of said physical parameter relates to the likelihood of flooding and / or seismic activity associated with a given physical location; and in that preferably said method comprises the additional step of providing said user with an output based on said risk, said output preferably comprising said risk and / or a risk category; and in that, preferably, said additional step, selectively initiated by said reaching or exceeding said predetermined value, relates at least to said obtaining said additional physical value; and in that said additional step comprises the following: receiving from a user said additional physical value, which is the value of a feature that is an indicator of risk related to said physical object; and in that said definition of said risk is also based on said value of a feature that is an indicator of risk; and in that preferably, said method includes the additional step of providing the user with a first and a second risk value, wherein said first risk value is determined without taking into account said attribute value, which is a risk indicator, and wherein said second risk value is determined taking into account the mentioned value of the attribute, which is a risk indicator, for quantitatively assessing the impact of the mentioned value of the attribute, which is the indicator of risk, and allowing the user to evaluate the mentioned impact; and in that preferably, said additional step, selectively triggered by said reaching or exceeding said predetermined value, relates at least to said providing said additional information to said user; and in that said additional step comprises the following: provide the user with additional information containing a recommendation regarding said physical object, said recommendation comprising a technical measure; and in that said technical measure relates to a modification of said physical object that can be performed by said user to reduce said risk; and in that preferably said recommendation further comprises first and second risk values, wherein said first risk value is determined provided that said technical measure has not been implemented, and wherein said second risk value is determined provided that said technical measure is implemented, for quantitative assessing the impact of said value of the attribute, which is a risk indicator, and allowing the user to evaluate the said impact; and in that preferably said method also comprises the following step: obtaining from a user a characteristic value related to said physical object, said characteristic value relating to at least one physical surface or number of floors characteristic of said physical object; and wherein preferably said definition of said risk is also based on said characteristic value; and in that preferably said risk related to said probability of damage refers to the likelihood of damage caused by flooding of said physical object; wherein said physical parameter and said at least one value - 17,038697 physical parameters refer to the likelihood of flooding associated with a given physical location; and wherein said value of a feature that is a risk indicator refers to any of the following: the presence and / or physical surface of an underground space, preferably a basement, of said physical object; the floor of the said physical object if the mentioned category of the object is an apartment; and in that preferably said risk is determined in the context of a recommendation for reconstruction in relation to said physical object, and in that said method also comprises the following step: providing a user with said recommendation for reconstruction in relation to said physical object, wherein said recommendation for reconstruction contains a technical requirement ; and in that the said technical requirement relates to a refurbishment instruction for said building, preferably an instruction regarding a foundation and / or fire protection and / or a dam and / or a seismic activity detection system. 13. The system of claim 12, wherein said machine medium containing said database is contained in a remote server associated with physical parameters other than said server. 14. The system of claim 13, wherein said remote location server is equivalent to said remote server associated with physical parameters. 15. Use of the method according to claims 1-11 in the system according to claims 12-14 of the claims.