Abstract: Apparatuses, systems and methods are provided for generating a base-line probable roof loss confidence score. More particularly, apparatuses, systems and methods are provided for generating a base-line probable roof loss confidence score based on hail data. The apparatuses, systems and methods may generate a probable roof loss confidence score. The apparatuses, systems and methods may generate verified probable roof loss confidence score data. The apparatuses, systems and methods may generate property insurance underwriting data based on probable roof loss confidence score data. The apparatuses, systems and methods may generate property insurance claims data based on probable roof loss confidence score data. The apparatuses, systems and methods may generate property insurance loss mitigation data based on probable roof loss confidence score data.

Abstract: Methods and systems for monitoring use, determining risk, and pricing insurance policies for a vehicle having one or more autonomous or semi-autonomous operation features are provided. According to certain aspects, the operating status of the features, the identity of a vehicle operator, risk levels for operation of the vehicle by the vehicle operator, or damage to the vehicle may be determined based upon sensor or other data. According to further aspects, decisions regarding transferring control between the features and the vehicle operator may be made based upon sensor data and information regarding the vehicle operator. Additional aspects may recommend or install updates to the autonomous operation features based upon determined risk levels. Some aspects may include monitoring transportation infrastructure and communicating information about the infrastructure to vehicles.

Abstract: Computer-implemented methods, mobile computing devices, and tangible, non-transitory computer-readable media storing instructions for creating one or more new insurance policy quotes for a customer associated with a customer vehicle may be described. The computer-implemented methods may include tracking, by a mobile computing device in conjunction with one or more sensors, a particular type of usage data of a customer vehicle based on a coverage type, of a plurality of coverage types, for the customer vehicle, wherein a first type of usage data is tracked for a first coverage type and a second type of usage data is tracked for a second coverage type, the first type of usage data being distinct from the second type of usage data; and transmitting, by the mobile computing device to a computing device, the particular type of usage data.

Abstract: Methods and systems for monitoring use, determining risk, and pricing insurance policies for a vehicle having one or more autonomous or semi-autonomous operation features are provided. According to certain aspects, the operating status of the features, the identity of a vehicle operator, risk levels for operation of the vehicle by the vehicle operator, or damage to the vehicle may be determined based upon sensor or other data. According to further aspects, decisions regarding transferring control between the features and the vehicle operator may be made based upon sensor data and information regarding the vehicle operator. Additional aspects may recommend or install updates to the autonomous operation features based upon determined risk levels. Some aspects may include monitoring transportation infrastructure and communicating information about the infrastructure to vehicles.

Abstract: According to certain aspects, a computer-implemented method for operating an autonomous or semi-autonomous vehicle may be provided. With the customer's permission, an identity of a vehicle operator may be identified and a vehicle operator profile may be retrieved. Operating data regarding autonomous operation features operating the vehicle may be received from vehicle-mounted sensors. When a request to disable an autonomous feature is received, a risk level for the autonomous feature is determined and compared with a driver behavior setting for the autonomous feature stored in the vehicle operator profile. Based upon the risk level comparison, the autonomous vehicle retains control of vehicle or the autonomous feature is disengaged depending upon which is the safer driver- the autonomous vehicle or the vehicle human occupant. As a result, unsafe disengagement of self-driving functionality for autonomous vehicles may be alleviated.

Abstract: Methods and systems for automatically mitigating risks of water damage to a property caused by insurance-related events are provided. A smart home controller and/or insurance provider remote processor may analyze data received from a smart device disposed on, within, or proximate to a property associated with monitoring water flow, as well as data received from an insurance provider. If it is determined that an actual or potential risk of water leakage exists, the smart home controller or remote processor may automatically issue commands to the smart device to take actions that mitigate the risk of water damage. The smart home controller may transmit information about the actual or potential water leakage risks and any mitigative actions to an insurance provider. The insurance provider remote processor may interpret the transmitted data and perform insurance activities, such as providing a discount or premium, and/or adjusting an insurance policy associated with the property.

Abstract: Apparatuses, systems and methods are provided for performing insurance property loss mitigation processes based on an event driven probable roof loss confidence score based on a particular weather event, the event driven probable roof loss confidence score associated with a roof of a building. An example method may include receiving a base-line probable roof loss confidence score for the building. The method may further include receiving weather data associated with the particular weather event, that occurred in the geographic area of the building, and hail data associated with the particular weather event. The method also may include estimating at least one attribute of the one or more attributes, and generating the event driven probable roof loss confidence score based on the base-line probable roof loss confidence score, the weather data, the hail data, and the at least one estimated attribute.

Abstract: Computer-implemented methods, mobile computing devices, and tangible, non-transitory computer-readable media storing instructions for creating one or more new insurance policy quotes for a customer associated with a customer vehicle may be described. The computer-implemented methods may include tracking, in conjunction with one or more sensors, a particular type of usage data of the customer vehicle based on a coverage type, of a plurality of coverage types, for the customer vehicle; transmitting, to a computing device, the particular type of usage data; receiving, from the computing device, one or more insurance policy quotes corresponding to the coverage type for the customer vehicle; and displaying the one or more insurance policy quotes in a user interface of the mobile computing device.

Abstract: According to certain aspects, a computer-implemented method for operating an autonomous or semi-autonomous vehicle may be provided. With the customer's permission, an identity of a vehicle operator may be identified and a vehicle operator profile may be retrieved. Operating data regarding autonomous operation features operating the vehicle may be received from vehicle-mounted sensors. When a request to disable an autonomous feature is received, a risk level for the autonomous feature is determined and compared with a driver behavior setting for the autonomous feature stored in the vehicle operator profile. Based upon the risk level comparison, the autonomous vehicle retains control of vehicle or the autonomous feature is disengaged depending upon which is the safer driver—the autonomous vehicle or the vehicle human occupant. As a result, unsafe disengagement of self-driving functionality for autonomous vehicles may be alleviated.

Abstract: Methods and systems for automatically mitigating risks of water damage to a property caused by insurance-related events are provided. A smart home controller and/or insurance provider remote processor may analyze data received from a smart device disposed on, within, or proximate to a property associated with monitoring water flow, as well as data received from an insurance provider. If it is determined that an actual or potential risk of water leakage exists, the smart home controller or remote processor may automatically issue commands to the smart device to take actions that mitigate the risk of water damage. The smart home controller may transmit information about the actual or potential water leakage risks and any mitigative actions to an insurance provider. The insurance provider remote processor may interpret the transmitted data and perform insurance activities, such as providing a discount or premium, and/or adjusting an insurance policy associated with the property.

Abstract: Methods and systems for predictively generating an insurance claim in response to detecting an imminent insurance-related event are provided. According to certain aspects, a smart home controller or insurance provider remote processor may store a first set of data received from smart devices disposed on, or proximate to, a property. This data may be analyzed to detect that an insurance-related event is imminent and calculate a likelihood that a property owner will file an insurance claim in response to damage caused by the imminent insurance-related event. If there is a sufficient likelihood that an insurance claim will be filed, the smart home controller or remote processor may store a second set of data received from the smart devices. Subsequently, according to certain aspects, the second set of data may be analyzed to prepopulate an automatically generated insurance claim with information detailing damage to the property caused by the insurance-related event.

Abstract: Methods and systems for automatically mitigating risks of insurance-related events to a property are provided. According to certain aspects, a smart home controller or insurance provider remote processor may analyze data received from a plurality of smart devices disposed on, within, or proximate to a property, as well as data received from an insurance provider. If it is determined that an actual or potential risk of property damage exists, the smart home controller or insurance provider remote processor may automatically issue commands to one or more smart devices to take actions that mitigate the risk. The smart home controller may also transmit information about the actual or potential risks and any mitigative actions to an insurance provider. The insurance provider remote processor may interpret the transmitted data to perform insurance activities, such as providing a discount and/or adjusting an insurance premium or policy associated with the property.

Abstract: A computer-implemented method includes receiving a vehicle condition query via a computer network and retrieving condition data corresponding to a vehicle from a vehicle condition database. Further, the method includes determining a condition of the vehicle based on a collective analysis of the condition data, where the condition of the vehicle includes a market value of the vehicle and an overall quality level of the vehicle, and receiving a geographic location of a computing device. Still further, the method includes generating a vehicle condition report, where the vehicle condition report includes an interactive image of a first set of one or more visual condition descriptors indicative of the condition of the vehicle. Moreover, the method includes customizing the vehicle condition report according to the climate associated with the geographic location for the computing device, and communicating the vehicle condition report to the second computing device.

Abstract: Methods and systems for processing insurance policies associated with properties may be provided. A property may be populated with a plurality of smart devices or devices that are connected to a central controller, such as via wired or wireless communication, whereby the plurality of devices are covered by an insurance policy, such as a homeowners, renters, or personal articles insurance policy. The central controller may receive identifications for the devices, and may update an inventory list to include the plurality of devices. A total market value of the devices may be calculated, and the central controller may estimate any modification to the insurance policy based upon the total market value. The controller may facilitate the modification to the insurance policy with a customer and an insurance provider. The smart devices may be, or be associated with, appliances, electronics, computers, televisions, jewelry, vehicles, furniture, or other equipment or personal belongings.

Abstract: Methods and systems for predictively generating an insurance claim in response to detecting an imminent insurance-related event are provided. According to certain aspects, a smart home controller or insurance provider remote processor may store a first set of data received from smart devices disposed on, or proximate to, a property. This data may be analyzed to detect that an insurance-related event is imminent and calculate a likelihood that a property owner will file an insurance claim in response to damage caused by the imminent insurance-related event. If there is a sufficient likelihood that an insurance claim will be filed, the smart home controller or remote processor may store a second set of data received from the smart devices. Subsequently, according to certain aspects, the second set of data may be analyzed to prepopulate an automatically generated insurance claim with information detailing damage to the property caused by the insurance-related event.

Abstract: Systems and methods are provided for automating property assessment using probable roof loss confidence scores. More particularly, the systems and methods may generate a base-line probable roof loss confidence score based upon buildings, roof, weather, hail, and climate data. The systems and methods may predict a specific event and a set of characteristics of the specific event. The systems and methods may predict a level of roof damage and a cost of roof damage based upon the predicted level of roof damage. The systems and methods may adjust a risk-related factor, and may further adjust policy parameters based upon the risk-related factor. A probable roof loss confidence score may be generated, as well as property insurance claims data or property insurance loss mitigation data based upon probable roof loss confidence score data.

Abstract: Systems and methods for analyzing image data to identify cabinet products are disclosed. A computer-implemented method may include receiving, from an electronic device via a network connection, at least one digital image depicting a cabinet. The method also may include analyzing, by one or more processors, the at least one digital image to determine a first set of characteristics of the cabinet. Additionally, the method may include accessing, by the one or more processors from memory, a second set of characteristics corresponding to a plurality of cabinet products and comparing the first set of characteristics to the second set of characteristics to identify a cabinet product of the plurality of cabinet products that matches the cabinet. Further, the method may include transmitting, to the electronic device via the network connection, an indication of the cabinet product.

Abstract: Methods and systems for assigning damage to a property to causes of loss are provided. A smart home controller and/or an insurance provider remote processor (or server) may generate a time sequence of events for damage associated with an insure-related event. The time-sequence of events may be analyzed to identify causes of loss associated with damage to the property. The smart home controller or insurance provider remote processor may further analyze the time-sequence of event to determine a portion of the overall damage associated with each cause of loss. Subsequently, according to certain aspects, the smart home controller or insurance provider remote processor may automatically generate a prepopulated insurance claim for damage associated with the insurance-related event, and/or transmit the automatically prepared insurance claim to an insured for their review, approval, and/or modification, such as via wireless communication to a mobile device associated with the insured.

Abstract: Systems and methods are provided for automating property assessment using probable roof loss confidence scores. More particularly, the systems and methods may generate a base-line probable roof loss confidence score based upon buildings, roof, weather, hail, and climate data. The systems and methods may predict a specific event and a set of characteristics of the specific event. The systems and methods may predict a level of roof damage and a cost of roof damage based upon the predicted level of roof damage. The systems and methods may adjust a risk-related factor, and may further adjust policy parameters based upon the risk-related factor. A probable roof loss confidence score may be generated, as well as property insurance claims data or property insurance loss mitigation data based upon probable roof loss confidence score data.

Abstract: Systems and methods for analyzing image data to identify cabinet products are disclosed. A computer-implemented method may include receiving, from an electronic device via a network connection, at least one digital image depicting a cabinet. The method also may include analyzing, by one or more processors, the at least one digital image to determine a first set of characteristics of the cabinet. Additionally, the method may include accessing, by the one or more processors from memory, a second set of characteristics corresponding to a plurality of cabinet products and comparing the first set of characteristics to the second set of characteristics to identify a cabinet product of the plurality of cabinet products that matches the cabinet. Further, the method may include transmitting, to the electronic device via the network connection, an indication of the cabinet product.