FIELD OF DISCLOSURE
[0001] The present disclosure relates to systems and methods that enable risk profiling of a location. More particularly, the present disclosure relates to risk management/profiling of a geo-location for strengthening underwriting by an insurance entity.

BACKGROUND
[0002] The background description includes information that may be useful in understanding the present invention. It is not an admission that any of the information provided herein is prior art or relevant to the presently claimed invention, or that any publication specifically or implicitly referenced is prior art.
[0003] Non-life Insurance industry has been suffering immense losses due to unprecedented Natural (Nat) Catastrophe (Cat) events. As per industry, it has been seeing sustained underwriting losses over the last 5-6 years. This is majorly because of the insurance companies/entities following a pricing regime that is not risk based, and because they are not utilizing Nat Cat models to their full potential. Traditionally, in India, Nat Cat models have been used as a means to validate reinsurance cover. However, dependency on models should not be only for postmortem of what has already been underwritten but rather they should also be used during underwriting to get a better understanding of Nat Cat risk associated to the policy under consideration and use that information for premium pricing. In addition, a holistic view of total exposure to Natural Catastrophes is also important, which currently is not being offered. This can only be accomplished by conducting exposure accumulation monitoring in Nat Cat Risk zones, which is currently not being implemented.
[0004] There is therefore a need in the art for a system and method that enables risk profiling of a location, and further enables strengthening of underwriting by an insurance entity based on risk assessment of a geo-location.

OBJECTS OF THE INVENTION
[0005] It is an object of the present invention to provide a system and method that enables risk profiling of a location.
[0006] It is an object of the present invention to provide a system and method that enables strengthening of underwriting by an insurance entity based on risk assessment of a geo-location.

SUMMARY
[0007] The present disclosure relates to systems and methods that enable risk profiling of a location. More particularly, the present disclosure relates to risk management/profiling of a geo-location for strengthening underwriting by an insurance entity.
[0008] In an aspect, the present disclosure relates to a system for risk profiling a location, wherein the system comprises a non-transitory storage device having embodied therein one or more routines operable to generate risk profile of said location; and one or more processors coupled to the non-transitory storage device and operable to execute the one or more routines, wherein the one or more routines include: an earthquake based risk score receive module, which when executed by the one or more processors, receives, for said location, an earthquake based risk score, said earthquake based risk score being generated based on any or a combination of data pertaining to one or more past earthquake events for historical and pre-historical periods, soil condition, soil modification over a defined period, height/floor at which said location is configured, and grid cell based attenuation patterns of seismic energy with respect to distance; a flood based risk score receive module, which when executed by the one or more processors, receives, for said location, a flood based risk score, said flood based risk score being generated based on any or a combination of rainfall data for a historical time duration, soil type, land use, slope, structural distribution of buildings, height/floor at which said location is configured, and attributes defining propensity of flooding; a cyclone based risk score receive module, which when executed by the one or more processors, receives, for said location, a cyclone based risk score, said cyclone based risk score being generated based on any or a combination of historical cyclone data, historical data pertaining to wind speed data at said location, impact of previous cyclones on land of said location, historical gust values at said location, height/floor at which said location is configured, and structural distribution of buildings; and a location specific risk profile generation module, which when executed by the one or more processors, generates said risk profile for said location based on a combination of earthquake based risk score, flood based risk score, and cyclone based risk score.
[0009] In an aspect, the location can be received by the proposed system in the form of any or a combination of Pin code of said location, latitude/longitude of the location, landmark near the location, geo-location parameters of the location, and address of the location.
[00010] In another aspect, the location specific risk profile generation module can combine said earthquake based risk score, flood based risk score, and cyclone based risk score based on weights associated with respective earthquake based risk score, flood based risk score, and cyclone based risk score.
[00011] In another aspect, the location specific risk profile generation module further refines said generated risk profile based on real-time data from any or a combination of a user, or a census based structural type distribution.
[00012] In another aspect, the proposed system can be configured to develop behavioral patterns for one or more types of structures based on historical performance of said one or more types of structures against varying wind speeds induced by incoming cyclones, based on which behavioral patterns, risk load for at least one structure type at various wind speeds is computed. Such risk load can, in an aspect, be factored in during generation of said cyclone based risk score.
[00013] In an aspect, the present disclosure further relates to a method for profile risk of a location, wherein the method comprises the steps of: receiving, at a computing device, for said location, an earthquake based risk score, said earthquake based risk score being generated based on any or a combination of data pertaining to one or more past earthquake events for historical and pre-historical periods, soil condition, soil modification over a defined period, height/floor at which said location is configured, and grid cell based attenuation patterns of seismic energy with respect to distance; receiving, at said computing device, for said location, a flood based risk score, said flood based risk score being generated based on any or a combination of rainfall data for a historical time duration, soil type, land use, slope, structural distribution of buildings, height/floor at which said location is configured, and attributes defining propensity of flooding; receiving, at said computing device, for said location, a cyclone based risk score, said cyclone based risk score being generated based on any or a combination of historical cyclone data, historical data pertaining to wind speed data at said location, impact of previous cyclones on land of said location, historical gust values at said location, height/floor at which said location is configured, and structural distribution of buildings; and generating, at said computing device, said risk profile for said location based on a combination of earthquake based risk score, flood based risk score, and cyclone based risk score.

BRIEF DESCRIPTION OF DRAWINGS
[00014] FIG. 1 illustrates an exemplary functional module architecture diagram of the proposed system for risk profiling a location in accordance with an embodiment of the present disclosure.
[00015] FIG. 2 illustrates an exemplary flow diagram of the proposed invention in accordance with an embodiment.

DETAILED DESCRIPTION
[00016] All publications herein are incorporated by reference to the same extent as if each individual publication or patent application were specifically and individually indicated to be incorporated by reference. Where a definition or use of a term in an incorporated reference is inconsistent or contrary to the definition of that term provided herein, the definition of that term provided herein applies and the definition of that term in the reference does not apply.
[00017] As used in the description herein and throughout the claims that follow, the meaning of “a,” “an,” and “the” includes plural reference unless the context clearly dictates otherwise. Also, as used in the description herein, the meaning of “in” includes “in” and “on” unless the context clearly dictates otherwise.
[00018] The following is a detailed description of embodiments of the disclosure depicted in the accompanying drawings. The embodiments are in such detail as to clearly communicate the disclosure. However, the amount of detail offered is not intended to limit the anticipated variations of embodiments; on the contrary, the intention is to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the present disclosure as defined by the appended claims.
[00019] Each of the appended claims defines a separate invention, which for infringement purposes is recognized as including equivalents to the various elements or limitations specified in the claims. Depending on the context, all references below to the "invention" may in some cases refer to certain specific embodiments only. In other cases it will be recognized that references to the "invention" will refer to subject matter recited in one or more, but not necessarily all, of the claims.
[00020] All methods described herein can be performed in any suitable order unless otherwise indicated herein or otherwise clearly contradicted by context. The use of any and all examples, or exemplary language (e.g. “such as”) provided with respect to certain embodiments herein is intended merely to better illuminate the invention and does not pose a limitation on the scope of the invention otherwise claimed. No language in the specification should be construed as indicating any non-claimed element essential to the practice of the invention.
[00021] Various terms are used herein. To the extent a term used in a claim is not defined below, it should be given the broadest definition persons in the pertinent art have given that term as reflected in printed publications and issued patents at the time of filing.
[00022] In the following description, numerous details are set forth. It will be apparent, however, to one skilled in the art, that the present invention may be practiced without these specific details. In other instances, well-known structures and devices are shown in block diagram form, rather than in detail, in order to avoid obscuring the present invention.
[00023] Reference throughout this specification to "one embodiment" or "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the present invention. Thus, the appearance of the phrases "in one embodiment" or "in an embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
[00024] Throughout the following discussion, numerous references will be made regarding servers, services, interfaces, engines, modules, clients, peers, portals, platforms, or other systems formed from computing devices. It should be appreciated that the use of such terms is deemed to represent one or more computing devices having at least one processor (e.g., ASIC, FPGA, DSP, x86, ARM, ColdFire, GPU, multi-core processors, etc.) configured to execute software instructions stored on a computer readable tangible, non- transitory medium (e.g., hard drive, solid state drive, RAM, flash, ROM, etc.). For example, a server can include one or more computers operating as a web server, database server, or other type of computer server in a manner to fulfill described roles, responsibilities, or functions. One should further appreciate the disclosed computer-based algorithms, processes, methods, or other types of instruction sets can be embodied as a computer program product comprising a non-transitory, tangible computer readable media storing the instructions that cause a processor to execute the disclosed steps. The various servers, systems, databases, or interfaces can exchange data using standardized protocols or algorithms, possibly based on HTTP, HTTPS, AES, public-private key exchanges, web service APIs, known financial transaction protocols, or other electronic information exchanging methods. Data exchanges can be conducted over a packet-switched network, a circuit- switched network, the Internet, LAN, WAN, VPN, or other type of network.
[00025] The terms "configured to" and "programmed to" in the context of a processor refer to being programmed by a set of software instructions to perform a function or set of functions.
[00026] The following discussion provides many example embodiments. Although each embodiment represents a single combination of components, this disclosure contemplates combinations of the disclosed components. Thus, for example, if one embodiment comprises components A, B, and C, and a second embodiment comprises components B and D, then the other remaining combinations of A, B, C, or D are included in this disclosure, even if not explicitly disclosed.
[00027] As used herein, and unless the context dictates otherwise, the term "coupled to" is intended to include both direct coupling (in which two elements that are coupled to each other contact each other) and indirect coupling (in which at least one additional element is located between the two elements). Therefore, the terms "coupled to" and "coupled with" are used synonymously.
[00028] In some embodiments, numerical parameters expressing quantities are used. It is to be understood that such numerical parameters may not be exact, and are instead to be understood as being modified in some instances by the term "about." Accordingly, in some embodiments, a numerical parameter is an approximation that can vary depending upon the desired properties sought to be obtained by a particular embodiment.
[00029] Unless the context dictates the contrary, ranges set forth herein should be interpreted as being inclusive of their endpoints and open-ended ranges should be interpreted to include only commercially practical values. The recitation of ranges of values herein is merely intended to serve as a shorthand method of referring individually to each separate value falling within the range. Unless otherwise indicated herein, each individual value within a range is incorporated into the specification as if it were individually recited herein. Similarly, all lists of values should be considered as inclusive of intermediate values unless the context indicates the contrary.
[00030] Groupings of alternative elements or embodiments of the inventive subject matter disclosed herein are not to be construed as limitations. Each group member can be referred to and claimed individually or in any combination with other members of the group or other elements found herein. One or more members of a group can be included in, or deleted from, a group for reasons of convenience and/or patentability. When any such inclusion or deletion occurs, the specification is herein deemed to contain the group as modified thus fulfilling the written description of all groups used in the appended claims.
[00031] The present disclosure relates to systems and methods that enable risk profiling of a location. More particularly, the present disclosure relates to risk management/profiling of a geo-location for strengthening underwriting by an insurance entity.
[00032] In an exemplary aspect, risk assessment (also interchangeably referred to as risk evaluation, or risk management, or risk profiling) can be performed for a given location based on Pin code of the location, wherein in order to risk profile a location, Earthquake, Flood, and Cyclone risk scores can be computed and evaluated at a higher resolution, for instance at 1 sq. km resolution across one or more regions (which could be a city, tehsil, district, state, or country). Hazard risk scores for Earthquake, Flood, and Cyclone can then be evaluated individually and/or in any combination (or weighted combination) in order to compute a Composite Hazard Risk score.
[00033] It should be appreciated that although illustrative examples of India and regions therein have been given in the instant disclosure, the subject matter relates to any other region/country as the parameters/method computation remains the same, and hence all such variations are well within the scope of the present disclosure.
[00034] In an exemplary aspect, the present disclosure can be configured to combine one or more traditional approaches with live data from user or census based structural type distribution in order to refine risk score for a specific insurance policy, and then combine (with equal or different weights) these risk scores for earthquake, flood, and cyclone to create a composite risk score.
[00035] The present disclosure relates to systems and methods that enable risk profiling of a location. More particularly, the present disclosure relates to risk management/profiling of a geo-location for strengthening underwriting by an insurance entity.
[00036] In an aspect, the present disclosure relates to a system for risk profiling a location, wherein the system comprises a non-transitory storage device having embodied therein one or more routines operable to generate risk profile of said location; and one or more processors coupled to the non-transitory storage device and operable to execute the one or more routines, wherein the one or more routines include: an earthquake based risk score receive module, which when executed by the one or more processors, receives, for said location, an earthquake based risk score, said earthquake based risk score being generated based on any or a combination of data pertaining to one or more past earthquake events for historical and pre-historical periods, soil condition, soil modification over a defined period, height/floor at which said location is configured, and grid cell based attenuation patterns of seismic energy with respect to distance; a flood based risk score receive module, which when executed by the one or more processors, receives, for said location, a flood based risk score, said flood based risk score being generated based on any or a combination of rainfall data for a historical time duration, soil type, land use, slope, structural distribution of buildings, height/floor at which said location is configured, and attributes defining propensity of flooding; a cyclone based risk score receive module, which when executed by the one or more processors, receives, for said location, a cyclone based risk score, said cyclone based risk score being generated based on any or a combination of historical cyclone data, historical data pertaining to wind speed data at said location, impact of previous cyclones on land of said location, historical gust values at said location, height/floor at which said location is configured, and structural distribution of buildings; and a location specific risk profile generation module, which when executed by the one or more processors, generates said risk profile for said location based on a combination of earthquake based risk score, flood based risk score, and cyclone based risk score.
[00037] In an aspect, the location can be received by the proposed system in the form of any or a combination of Pin code of said location, latitude/longitude of the location, landmark near the location, geo-location parameters of the location, and address of the location.
[00038] In another aspect, the location specific risk profile generation module can combine said earthquake based risk score, flood based risk score, and cyclone based risk score based on weights associated with respective earthquake based risk score, flood based risk score, and cyclone based risk score.
[00039] In another aspect, the location specific risk profile generation module further refines said generated risk profile based on real-time data from any or a combination of a user, or a census based structural type distribution.
[00040] In another aspect, the proposed system can be configured to develop behavioral patterns for one or more types of structures based on historical performance of said one or more types of structures against varying wind speeds induced by incoming cyclones, based on which behavioral patterns, risk load for at least one structure type at various wind speeds is computed. Such risk load can, in an aspect, be factored in during generation of said cyclone based risk score.
[00041] In an aspect, the present disclosure further relates to a method for profile risk of a location, wherein the method comprises the steps of: receiving, at a computing device, for said location, an earthquake based risk score, said earthquake based risk score being generated based on any or a combination of data pertaining to one or more past earthquake events for historical and pre-historical periods, soil condition, soil modification over a defined period, height/floor at which said location is configured, and grid cell based attenuation patterns of seismic energy with respect to distance; receiving, at said computing device, for said location, a flood based risk score, said flood based risk score being generated based on any or a combination of rainfall data for a historical time duration, soil type, land use, slope, structural distribution of buildings, height/floor at which said location is configured, and attributes defining propensity of flooding; receiving, at said computing device, for said location, a cyclone based risk score, said cyclone based risk score being generated based on any or a combination of historical cyclone data, historical data pertaining to wind speed data at said location, impact of previous cyclones on land of said location, historical gust values at said location, height/floor at which said location is configured, and structural distribution of buildings; and generating, at said computing device, said risk profile for said location based on a combination of earthquake based risk score, flood based risk score, and cyclone based risk score.

Earthquake based risk assessment
[00042] In an exemplary implementation for computing Earthquake based risk score, literature on compiled Earthquake events for historical and pre-historical periods can be considered as large damaging earthquakes have long return periods. In an aspect, one exemplary component of earthquake hazard can be analyzed using standard earthquake engineering methodologies, wherein, in order to accurately model the effects of an earthquake at a specific site (say 1 sq km grid cell), one or more geological hazard characteristics can be identified at grid level. For a given event on a specific earthquake source, a model can be designed to analyze attenuation of seismic energy with distance in order to determine level of ground shaking at a grid cell. In another aspect, empirical relationships can be developed for different regions based on recording of seismic waves of past earthquakes, wherein such relationships can express the amount of ground shaking at a specific location as a function of size of earthquake, distance (various distance definition, such distance from epicenter/ hypocenter/ closest distance from the fault etc.), and local soil conditions. Maximum magnitudes can be an exemplary variable in calculating seismic hazard as such magnitudes help determine expected peak ground acceleration and energy released in an earthquake.
[00043] In another aspect, soil conditions over which a structure’s foundation stands can also impact seismic ground shaking, wherein soil top layers can act as filters that can modify ground motion as a function of their dynamic characteristics. Soft, weak soils tend to amplify long-period seismic motions and thus generally impart large ground displacements to structures. Conversely, stiff and more competent soil conditions tend to amplify short period seismic motions and impart high amplitude ground accelerations to structures. Soil type can be, in an embodiment, classified in terms of their shear wave velocity (Vs30, shear wave velocity in top 30 meters), stiffest soils having highest Vs30. Relationship between Vs30 and local soil index can be used to derive soil modification factors. State-of-art next generation attenuation of ground motion prediction equations (NGA-GMPEs), single or in combination with different weights through validation with the recent historical earthquakes ground motion intensity can be used.
[00044] In yet another aspect, soil modification due to historical earthquake events for each grid cell can yield earthquake ground motion intensity at surface level for that grid cell. Categorizing earthquake ground motion intensity at 475-year return period (i.e. a probability of 10% in 50 years) can, for instance, provide hazard risk score for earthquake. Such earthquake risk scores can be modified by taking into consideration structural distribution of buildings in an administrative unit or structural type of building at that location, if provided by the user.
[00045] In an aspect, risk scores can be modified based on building level taking into account if there is a basement that is involved in underwritten insurance policy or the floor level at which the insurance policy in defined. As the floor level increases, earthquake risk increases.

Flood based risk assessment
[00046] In an exemplary implementation for computing Flood based risk score, data sets pertaining to, for instance, daily rainfall data for 35 years (1971-2011) across India at 0.5° X 0.5° grid resolution and/or Geo-spatial information like soil type, slope and land use can be utilized. Any other relevant data set can also be considered/ factored, and therefore all such inputs are completely within the scope of the present disclosure. In an exemplary implementation, three-day moving sum of rainfall can be estimated for all grid points. In an example, 35 maximum rainfall events can be short-listed for each grid point. Generalized extreme value distribution can then be fitted on this dataset and 3-day cumulative rainfall for 20-year return period can be considered. The 3-day 20-year rainfall can then be categorized into 10 categories from negligible to extreme based on IMD’s definition. Resolution of severity scores can be downscaled from 0.5° X 0.5° at grid points to 10m X 10m resolution using GIS tools (Since the soil type, slope, and land use information is available at 30m X 30m resolution). Soil type, slope, and land use can also be categorized based on their propensity to flooding as these play a crucial role in deciding susceptibility of an area for flooding. A weighted average of scores of the 4 parameters, 3-day cumulative rainfall, slope, soil type, and land use can be used/configured to provide hazard value of flood at a 30m X 30m resolution across the country, which scores at this resolution can be aggregated to 1 sq km grid resolution in order to obtain hazard values at grid level. Categorizing this weighted average yields the modeled hazard risk score for flood.
[00047] In an aspect, flood risk scores can be modified by taking into consideration structural distribution of buildings in an administrative unit or structural type of building at that location, if provided by the user. Risk scores can further be modified based on building level taking into account if there is a basement that is involved in underwritten insurance policy or floor level at which the insurance policy in defined. As the floor level increases, flood risk decreases.
[00048] One should appreciate that the values mentioned above for computation of flood risk score are completely exemplary and only illustrative of a sample situation. Any other manner/value/parameter that uses the above-mentioned technique for flood risk computation is therefore completely within the scope of the present disclosure.

Cyclone based risk assessment
[00049] In an exemplary implementation for computing cyclone based risk score, data used to develop the hazard risk score can be of a defined period, say for 124 years from 1891 to 2014. Such data can be configured to give latitude, longitude, and observed wind speed at 6 hourly intervals (for instance) for all historical storms from 1891 to 2014. In an implementation, such data set can be used to analyze one or more historical cyclone tracks and develop a model that maps the path followed and wind speed at regular intervals for each event. The model can accordingly analyze impact of each cyclone after it makes a landfall. As soon as the cyclone makes landfall over a large mass of land, it begins to lose strength, which can be attributed to the following two factors, namely, barometric pressure at the center of the storm that increases due to a loss of the cyclone's source of energy (the warm ocean waters), and surface friction from man-made and natural barriers that reduces wind speeds as the cyclone moves inland. Both these factors, directionally dependent on roughness and topographic modifiers can be incorporated into the wind speed of each storm. As a cyclone progresses over land, wind speed changes can be modeled during the lifecycle of the cyclone, wherein the maximum wind speed of a storm in a certain location can be referred to as peak gust wind speed at a specific location. The proposed model can then process each historical event as a deterministic event and the peak gust can be estimated at, for instance, a 1 sq. km grid level. At the end of the analysis of all the events in the dataset, each grid cell can include peak gust values corresponding to each of the historical events with an associated rate of occurrence of the corresponding cyclone. Many location Pincodes may have a zero peak gust value since cyclones only have a local impact and do not affect large sections of India. Ranking these values in decreasing order helps in calculating probability of exceedance of any particular peak gust using a Poisson model of occurrence. Peak gust can then be categorized at a 200-year return period in order to yield hazard risk score for cyclone. In an exemplary embodiment, the cyclone risk scores can be modified by taking into consideration structural distribution of buildings in an administrative unit or structural type of building at that location, if provided by the user. Next, risk scores can be modified based on building level taking into account if there is a basement that is involved in the underwritten insurance policy or floor level at which the insurance policy is defined. As the floor level height increases cyclone wind risk increases.
[00050] In an aspect, as every structural type has a behavioral pattern with respect to the wind load it is subjected to, the proposed system is configured to develop behavioral patterns for one or more types of structures based on historical performance of these structural types against varying wind speeds induced by incoming cyclones. Based on these patterns, the proposed system can compute a risk load for every structure type at various wind speeds. These loads, when added to the base Wind Hazard Risk Score, can help compute Wind Vulnerability Risk Score for a specific structure. Just as different structures behave differently at different wind speeds, similarly a single structure behaves differently to the same wind load at various levels along the height of the structure. The proposed system is configured to develop factors that modify structure behavior based on height at which wind load is being considered. Application of these factors on the Wind Vulnerability Risk Scores can yield a more refined Wind Vulnerability Risk Score that changes with the height of the structure.

Composite Risk Score Assessment
[00051] In an exemplary embodiment, system of the present disclosure can be configured to compute a Composite Risk Score (CRS) based on risk values associated with earthquake, flood, and cyclone, and possibly other natural hazards. In an exemplary embodiment, CRS can vary from Extreme (5/10) to Negligible(0), wherein the risk score classes can be Extreme, High, Medium, Low and Negligible. In an exemplary implementation, CRS of any location or any administrative unit can be defined based on any or a combination of risk scores for all the perils in that area, structural type of the building for which the policy is underwritten i.e. RCC or Masonry or Steel, and height band of that building along with floor level of the building where the insurance policy was/is to be issued.
[00052] In an exemplary implementation, CRS can use individual risk scores as a weight to arrive at the CRS, wherein combination of weights can be defined either based on judgment of one or more experts having long years of experience or through weighted Logic Tree Approach. In an exemplary implementation, CRS for a given location can be computed based on individual risk scores associated with earthquake, flood, and cyclone and combined through weighted scores for the given location. Earthquake and cyclone are independent events; however, flood could be an independent event and or dependent event due to earthquake or cyclone. For example, flood can happen due dam-break or breach of a levee which resulted due to high earthquake ground motion. Similarly, flood may happen due to storm surge effect from a cyclone and or due to cyclone induced rainfall. So, CRS of these perils could be computed through Logic Tree Approach by combining the scores of dependent peril based on dependent event frequency. Once the combined risk score of dependent events is estimated then apply the logic tree approach again to combine the risk scores of independent events to arrive is at a CRS for a location.
[00053] FIG. 1 illustrates an exemplary functional module architecture diagram of the proposed system for risk profiling a location in accordance with an embodiment of the present disclosure.
[00054] In an aspect, proposed system 100 may include one or more processor(s) 102. The one or more processor(s) 102 may be implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, logic circuitries, and/or any devices that manipulate data based on operational instructions. Among other capabilities, the one or more processor(s) 102 are configured to fetch and execute computer-readable instructions stored in a memory 104 of the system 100. The memory 104 may store one or more computer-readable instructions or routines, which may be fetched and executed to create or share the data units over a network service. The memory 104 may include any non-transitory storage device including, for example, volatile memory such as RAM, or non-volatile memory such as EPROM, flash memory, and the like.
[00055] In another aspect, system 100 may also include an interface(s) 106 that can be enabled, for instance, on display of computing device 102. The interface(s) 106 may include a variety of interfaces, for example, interfaces for data input and output devices, referred to as I/O devices, storage devices, and the like. The interface(s) 106 may facilitate communication of the system 100 with various devices coupled to the system 100. The interface(s) 106 may also provide a communication pathway for one or more components of the system 100. Examples of such components include, but are not limited to, processing engine(s) 108 and data 120.
[00056] The processing engine(s) 108 may be implemented as a combination of hardware and programming (for example, programmable instructions) to implement one or more functionalities of the processing engine(s) 108. In examples described herein, such combinations of hardware and programming may be implemented in several different ways. For example, the programming for the processing engine(s) 108 may be processor executable instructions stored on a non-transitory machine-readable storage medium and the hardware for the processing engine(s) 108 may include a processing resource (for example, one or more processors), to execute such instructions. In the present examples, the machine-readable storage medium may store instructions that, when executed by the processing resource, implement the processing engine(s) 108. In such examples, the system 100 may include the machine-readable storage medium storing the instructions and the processing resource to execute the instructions, or the machine-readable storage medium may be separate but accessible to system 100 and the processing resource. In other examples, the processing engine(s) 108 may be implemented by electronic circuitry.
[00057] The data 120 may include data that is either stored or generated as a result of functionalities implemented by any of the components of the processing engine(s) 108. For instance, data 120 may store various stencils that can be made available to various users on demand, images acquired by various users, registration/authentication data of various users etc.
[00058] Modules as described hereunder can interface with such systems as and when required. Appropriate user interfaces can be deployed using system proposed onto such devices that can be operatively connected to the proposed system so as to enable its operation as described hereunder. In another aspect, relevant modules of the proposed system can be configured to be operatively connected to a website using Internet, or be part of a mobile application that can be downloaded on a mobile device that can connect to the Internet. In such fashion, the proposed system can be available 24*7 to its users. Any other manner of implementation of the proposed system or a part thereof is well within the scope of the present disclosure/invention.
[00059] In an aspect, the processing engine(s) 108 can include a stencil reception module 210 and a stencil based actual vehicle image acquisition module 112.Besides, there could be other modules shown as 118 that may implement functionalities that supplement applications or functions performed by the system 100 or the processing engine(s) 108. It would be appreciated that these are only exemplary modules and any other module or sub-module can be included as part of the proposed system. These modules too can be merged or divided into super-modules or sub-modules as may be configured and can be spread across one or more computing devices operatively connected to each other using appropriate communication technologies.
[00060] In an aspect, modules of the present system can include an earthquake based risk score receive module 110, which when executed by the one or more processors, receives, for a given location, an earthquake based risk score, said earthquake based risk score being generated based on any or a combination of data pertaining to one or more past earthquake events for historical and pre-historical periods, soil condition, soil modification over a defined period, height/floor at which said location is configured, and grid cell based attenuation patterns of seismic energy with respect to distance;
[00061] In another aspect, the proposed set of modules can include a flood based risk score receive module 112, which when executed by the one or more processors, receives, for said location, a flood based risk score, said flood based risk score being generated based on any or a combination of rainfall data for a historical time duration, soil type, land use, slope, structural distribution of buildings, height/floor at which said location is configured, and attributes defining propensity of flooding;
[00062] In yet another aspect, the proposed set of modules can include a cyclone based risk score receive module 114, which when executed by the one or more processors, receives, for said location, a cyclone based risk score, said cyclone based risk score being generated based on any or a combination of historical cyclone data, historical data pertaining to wind speed data at said location, impact of previous cyclones on land of said location, historical gust values at said location, height/floor at which said location is configured, and structural distribution of buildings; and
[00063] Modules of the present disclosure can further include, but not limited to, a location specific risk profile generation module 116, which when executed by the one or more processors, generates said risk profile for said location based on a combination of earthquake based risk score, flood based risk score, and cyclone based risk score.
[00064] FIG. 2 illustrates an exemplary flow diagram of the proposed invention in accordance with an embodiment. At step 202, the method can include receiving, at a computing device, for a location, an earthquake based risk score, said earthquake based risk score being generated based on any or a combination of data pertaining to one or more past earthquake events for historical and pre-historical periods, soil condition, soil modification over a defined period, height/floor at which said location is configured, and grid cell based attenuation patterns of seismic energy with respect to distance; and at step 204, the method can include the step of receiving, at said computing device, for said location, a flood based risk score, said flood based risk score being generated based on any or a combination of rainfall data for a historical time duration, soil type, land use, slope, structural distribution of buildings, height/floor at which said location is configured, and attributes defining propensity of flooding. The proposed method, at step 206, can further include the step of receiving, at said computing device, for said location, a cyclone based risk score, said cyclone based risk score being generated based on any or a combination of historical cyclone data, historical data pertaining to wind speed data at said location, impact of previous cyclones on land of said location, historical gust values at said location, height/floor at which said location is configured, and structural distribution of buildings. At step 208, the method can include the step of generating, at said computing device, said risk profile for said location based on a combination of earthquake based risk score, flood based risk score, and cyclone based risk score.
[00065] While the foregoing describes various embodiments of the invention, other and further embodiments of the invention may be devised without departing from the basic scope thereof. The scope of the invention is determined by the claims that follow. The invention is not limited to the described embodiments, versions or examples, which are included to enable a person having ordinary skill in the art to make and use the invention when combined with information and knowledge available to the person having ordinary skill in the art.

ADVANTAGES OF THE INVENTION
[00066] The present disclosure provides a system and method that enables risk profiling of a location.
[00067] The present disclosure provides a system and method that enables strengthening of underwriting by an insurance entity based on risk assessment of a geo-location.

CLAIMS:
1. A system for risk profiling a location, said system comprising:
a non-transitory storage device having embodied therein one or more routines operable to generate risk profile of said location; and
one or more processors coupled to the non-transitory storage device and operable to execute the one or more routines, wherein the one or more routines include:
an earthquake based risk score receive module, which when executed by the one or more processors, receives, for said location, an earthquake based risk score, said earthquake based risk score being generated based on any or a combination of data pertaining to one or more past earthquake events for historical and pre-historical periods, soil condition, soil modification over a defined period, height/floor at which said location is configured, and grid cell based attenuation patterns of seismic energy with respect to distance;
a flood based risk score receive module, which when executed by the one or more processors, receives, for said location, a flood based risk score, said flood based risk score being generated based on any or a combination of rainfall data for a historical time duration, soil type, land use, slope, structural distribution of buildings, height/floor at which said location is configured, and attributes defining propensity of flooding;
a cyclone based risk score receive module, which when executed by the one or more processors, receives, for said location, a cyclone based risk score, said cyclone based risk score being generated based on any or a combination of historical cyclone data, historical data pertaining to wind speed data at said location, impact of previous cyclones on land of said location, historical gust values at said location, height/floor at which said location is configured, and structural distribution of buildings; and
location specific risk profile generation module, which when executed by the one or more processors, generates said risk profile for said location based on a combination of earthquake based risk score, flood based risk score, and cyclone based risk score.
2. The system of claim 1, wherein said location is received by said system in the form of any or a combination of Pin code of said location, latitude/longitude of said location, landmark near said location, geo-location parameters of said location, and address of said location.
3. The system of claim 1, wherein said location specific risk profile generation module combines said earthquake based risk score, flood based risk score, and cyclone based risk score based on weights associated with respective earthquake based risk score, flood based risk score, and cyclone based risk score.
4. The system of claim 1, wherein said location specific risk profile generation module refines said generated risk profile based on real-time data from any or a combination of a user, or a census based structural type distribution.
5. The system of claim 1, wherein said system is configured to develop behavioral patterns for one or more types of structures based on historical performance of said one or more types of structures against varying wind speeds induced by incoming cyclones, based on which behavioral patterns, risk load for at least one structure type at various wind speeds is computed.
6. The system of claim 5, wherein the risk load is factored in during generation of said cyclone based risk score.
7. A method for profile risk of a location, said method comprising the steps of:
receiving, at a computing device, for said location, an earthquake based risk score, said earthquake based risk score being generated based on any or a combination of data pertaining to one or more past earthquake events for historical and pre-historical periods, soil condition, soil modification over a defined period, height/floor at which said location is configured, and grid cell based attenuation patterns of seismic energy with respect to distance;
receiving, at said computing device, for said location, a flood based risk score, said flood based risk score being generated based on any or a combination of rainfall data for a historical time duration, soil type, land use, slope, structural distribution of buildings, height/floor at which said location is configured, and attributes defining propensity of flooding;
receiving, at said computing device, for said location, a cyclone based risk score, said cyclone based risk score being generated based on any or a combination of historical cyclone data, historical data pertaining to wind speed data at said location, impact of previous cyclones on land of said location, historical gust values at said location, height/floor at which said location is configured, and structural distribution of buildings; and
generating, at said computing device, said risk profile for said location based on a combination of earthquake based risk score, flood based risk score, and cyclone based risk score.
8. The method of claim 7, wherein said location is received in the form of any or a combination of Pin code of said location, latitude/longitude of said location, landmark near said location, geo-location parameters of said location, and address of said location.
9. The method of claim 7, wherein the step of generating combines said earthquake based risk score, flood based risk score, and cyclone based risk score based on weights associated with respective earthquake based risk score, flood based risk score, and cyclone based risk score.
10. The method of claim 7, wherein the method further comprises the step of developing behavioral patterns for one or more types of structures based on historical performance of said one or more types of structures against varying wind speeds induced by incoming cyclones, based on which behavioral patterns, risk load for at least one structure type at various wind speeds is computed, and wherein the risk load is factored in during generation of said cyclone based risk score.