Abstract: An automated system, phone distraction detector and method for automatically detecting phone distraction events in a moving vehicle, caused by a driver of the moving vehicle by using a smartphone. An Internet of Things (IoT) server is communicatively coupled to the smartphone. The smartphone (comprises one or more sensors built into the smartphone, wherein sensory data of the one or more sensors, are captured by the sensors of the smartphone during a vehicle trip and are transmitted to the Internet of Things (IoT) server, and wherein the sensor data comprises one or more chunks of data streams associated with an IoT service from the smartphone. The sensory data are processed and analyzed by the server to identify one or more phone handling events associated with the smartphone during the vehicle trip. One or more phone handling events associated with the smartphone are aggregated into one or more macro events by the processing means of the server.

Abstract: A fully or semi-automated, integrated learning, labeling and classification system and method have closed, self-sustaining pattern recognition, labeling and classification operation, wherein unclassified data sets are selected and converted to an assembly of graphic and text data forming compound data sets that are to be classified. By means of feature vectors, which can be automatically generated, a machine learning classifier is trained for improving the classification operation of the automated system during training as a measure of the classification performance if the automated labeling and classification system is applied to unlabeled and unclassified data sets, and wherein unclassified data sets are classified automatically by applying the machine learning classifier of the system to the compound data set of the unclassified data sets.

Abstract: A digital platform and system that provides an automated, multi-channel, end-to-end risk-transfer configuration and/or parametrization process for configuring, launching, and processing of customized second-tier transfer structures, wherein an automated risk-transfer placement for objects or property assets each having a geographic location related to occurrence of physical impacting risk-events, the objects or property assets impacting events, is provided by the digital platform and system as a first online channel comprising an electronic, parameter-driven, rule-based underwriting process for automatically creating a portfolio or composition of customized second-tier structures. An automated claim handling is provided by the digital platform and system as a second online channel, and automated accounting is provided by the digital platform and system as a third online channel.

Abstract: An electronic logging and track detection system for mobile telematics devices and method are provided. In particular, an electronic logging and track detection system and system for mobile telematics devices, as smart phones and/or mobile cellular phones is proposed, which tend to change their sensing and measuring orientation and direction in respect to the main direction of movement/motion or moving sense, as for example given by a person with proper motion holding a mobile phone within a moving vehicle. Instantaneous movement telematics data are measured by and logged from sensors of the mobile telematics devices and trips and/or trip-segments based on the instantaneous movement sensory telematics data are automatically identified and detected at least by the telematics sensors comprising an accelerometer sensor and a gyroscope sensor and a Global Positioning System sensor.

Abstract: A risk parsing device provides risk splitting and loss event diversification for a multi-risk forecast systems capturing multiple loss aggregation under complex environmental conditions based on the occurrence of defined loss events. The loss events are triggered by one or more involved causing units and affected units, wherein the loss events evolve from one or multiple risk accumulating sources. Risk events related loss measures can be scattered over multiple causing units or multiple related clash events. The multi-risk forecast system provides loss-generating processes and events, wherein the inventive risk splitter is a technical core element to generate an event-related loss distribution mirroring cause-effect chains induced by the risk events which extend over space and time. The risk splitter module allows automated splitting of the risk based on risk exposed, causing unit characteristics and risk exposed affected units' characteristics.

Abstract: A method and automated flight trajectory prediction and flight trajectory-borne automated delay risk-transfer system related to airspace risks for risk sharing of a variable number of risk-exposed units by pooling resources of the risk-exposed units and by providing the risk-transfer system as a self-sufficient operatable risk-transfer system based on the pooled resources for the risk-exposed units by a resource-pooling system associated with the risk-transfer system. The risk-exposed units are connected to the risk-transfer system by a plurality of payment-transfer devices configured to receive and store payments from the risk-exposed units for the pooling of their risks and resources, and an automated transfer of risk exposure associated with the risk-exposed units is provided by the risk-transfer system.

Abstract: A system for risk sharing of a variable number of objects includes circuitry that receives transmitted air data parameters of aircraft controllers and/or ground-based flight controllers of air-ports or flight control systems and filters the transmitted air data parameters to detect flight indicators indicating predicted or actual flight time parameters assigned to a specific flight trajectory of an aircraft. The circuitry also dynamically triggers the flight time parameters via data flow pathway of the aircraft controllers and/or the ground-based flight controllers based on a predefined time-delay threshold value. For each triggered occurrence of a time delay associated with the specific flight trajectory, the circuitry sets a corresponding trigger-flag to all the objects assignable to that flight, and allocates a parametric transfer of payments to each trigger-flag.

Abstract: A digital marketplace platform providing an automated, multi-channel, end-to-end, digital marketplace platform providing fully automated, end-to-end risk-assessment and risk-transfer processes by configuring, launching and processing of customized insurance and/or reinsurance products and services offered for B2B and B2C users. Each individual and service provided on the Marketplace is automatically rated on its contribution to a resilience score of the consumers that purchase products on the Marketplace and benefits from the marketplace's services. In L&H risk-transfer, the resilience score, inter alia, measures and rates the current health status of individuals, and their likelihood to purchase insurance protection or start/keep behaviors that improve their health status, dynamically reassessed throughout the term of the risk-transfer, i.e. its lifetime, by the digital platform.

Abstract: A digital platform for automated prediction and quantified measuring of exposure-measures measuring occurring construction and erection risks of an engineering or construction project and for automated forecast and measuring of future occurring loss patterns induced by occurring construction/erection risk events to the project measurably exposed to construction/erection risks. An engineering risk profile of a project associated with and exposed to construction and/or erection risks is assembled, and, based on the predicted and measured future occurring losses patterns, risk-tailored expert advices for underwriting parameters are provided.

Abstract: A system and a method, the method including assigning a payment parameter to each variable risk transfer segment of a top-down table and accumulating payment parameters to a total payment sum, capturing payment transfer parameters from a first payment-transfer device to a second payment-transfer device, and when the total payment sum at the second payment-transfer device has been triggered, transferring the risk exposure of a first insurance system associated with the variable risk transfer segments of the top-down table to a second insurance system.

Abstract: A method and system for identifying and/or classifying a user of a vehicle based on sensory data measured by sensors of a cellular mobile device, the sensors at least comprising an accelerometer and a gyroscope. The mobile device measures gravitational acceleration movement sensory data by the accelerometer based on measuring parameters obtained from the accelerometer, vehicle entering or exiting movement patterns of the user being detected from the acceleration movement sensory data at least comprising pattern for base axis and degree of rotation associated with a vehicle entrance or exit of the user. The detected vehicle entering or exiting movement patterns of the user trigger as input features the recognition of a vehicle entering or exiting movement of the user by performing a decision-tree classification on the input features to rule out whether the user entered or exited from a left or right side of the vehicle.

Abstract: A method and system, the method including capturing country-specific parameters of a risk-exposed country relating to stored predefined criteria, assigning one or more disaster event types to a disaster history table, capturing and storing mapping parameters for a geographic risk map, assigning each of a plurality of selectable disaster financing types to a definable cost factor capturing the capital cost of the disaster financing type in relation to its application for disaster mitigation, determining expected catastrophe losses by a loss frequency function and the geographic risk map for various scenarios of occurring natural disaster event types, and preparing a forecast of an effect of the disaster financing type to cover the catastrophe losses based on the coverage structure, the assigned cost factors, and the determined expected catastrophe losses

Abstract: An electronic, real-time system performs maneuver recognition of vehicles based on dynamically measured telematics data, particularly the sensory data of smartphone sensors, and more particularly data from the accelerometer sensor and the global positioning system (GPS) sensor and/or the gyroscope sensor of a smartphone. The axes of the smartphone may be moving independently relative to the axes of the vehicle and thus do not need to be aligned with the axes of the vehicle. Driver behaviors and operational parameters are automatically measured and discriminated, based on automatically individuated and measured driver maneuvers within various measured vehicle trajectories, and an output signal is generated based upon derived risk measure parameters and/or crash attitude measure parameters.

Abstract: A digital cross-network platform and method for providing controlled data- and process-driven cross-network interaction and program development between heterogeneous units with network-enabled devices on a secured cloud-based network, each unit having a unit or user account in the digital cross-network platform with assigned authentication and authorization credentials for authentication and authorization controlled network access to the digital cross-network platform and the secured cloud-based network, and each unit having an assigned relationship with one or more other units stored in a persistent storage of the digital networking platform, each assigned relationship providing a defined relationship between the one or more other units or a subgroup of the one or more other units and an associated program.

Abstract: A system and method for real-time risk-assessment and adjustment, risks associated with a plurality of risk exposed individuals being at least partially transferable from a risk exposed individual to a first insurance system and/or from the first insurance system to an associated second insurance system. The system including a table with retrievable stored risk classes each comprising assigned risk class criteria, individual-specific parameters of the risk exposed individuals being captured relating to criteria of the stored risk classes by the system and stored in a memory, and a specific risk class associated with the risk of the exposed individual being identified out and selected of the stored risk classes by the system based on the captured parameters.

Abstract: A digital device is provided for automated risk-transfer underwriting in fragmented, unstructured data environment. The digital device includes a plurality of sensors, a storage configured to store transfer portfolio data, and circuitry configured to measure characteristics parameters of a plurality of objects, assign the measured characteristics parameters to a profile associated with the plurality of objects, classify the plurality of objects into a plurality of classes based on the measured characteristics parameters, generate a transfer cover value based on (i) the measured characteristics parameters and (ii) a relationship between a risk source, a risk exposure measure, and a risk exposed object of the transfer portfolio data, assign the generated transfer cover value to the corresponding section of the profile for the risk exposed object, and generate a risk score value to the corresponding section of the profile based on the assigned transfer cover value.

Abstract: Proposed is an adaptive, layered, automated risk-transfer system and method thereof, with a self-optimizing, increased leveraged capacity and enhanced drop-down cover structure with a plurality of adjustable risk-transfer layers. If a triggered risk-event is assignable to either of the top risk-transfer layer or the bottom risk-transfer layer of the drop-down cover structure, a shared exhaustion factor is generated based on the assigned risk-transfer layer and based on a cover of the loss associated with the triggered risk event. The shared exhaustion factor is applied mutually to both layers by the system eroding both layers by the same exhaustion factor. The top layer and the bottom layer are reinstatable by a corresponding generated normalized reinstatement parameter values normalized over both layers and based on a thus provided shared limit and the erosion of the top layer and the bottom layer.

Abstract: A simulation device is provided for automated prediction of impact measures based on occurrences of physical events. The simulation device includes a plurality of sensors and circuitry configured to detect the occurrences of the physical events based on predefined event parameters, measure impacts of the physical events on a physical object based on impact parameters, dynamically capture characteristics of the physical object and generate characteristics parameters based on the captured characteristics, identify a plurality of records associated with predefined events impacting the physical object and transfer the records to a portfolio, generate a rate value based on the predefined event parameters and the characteristics parameters, and estimate a cost for transferring a record, and dynamically provide forward- and backward-looking impact measures based on at least one of (i) a variation of the rate value and (ii) the portfolio including the plurality of records.

Abstract: A digital device is provided with circuitry configured to select object elements stored in a storage of the digital device, and assemble the selected object elements, a plurality of sensors configured to measure at least one parameter of structural parameter, operational parameter, and environmental status parameter, the at least one parameter being associated with a physical object represented by the assembled object elements, wherein the assembled object elements include data structure representing states of subsystems of the physical object, and the data structure holds a value of the at least one parameter.

Abstract: A fully or semi-automated, integrated learning, labeling and classification system and method have closed, self-sustaining pattern recognition, labeling and classification operation, wherein unclassified data sets are selected and converted to an assembly of graphic and text data forming compound data sets that are to be classified. By means of feature vectors, which can be automatically generated, a machine learning classifier is trained for improving the classification operation of the automated system during training as a measure of the classification performance if the automated labeling and classification system is applied to unlabeled and unclassified data sets, and wherein unclassified data sets are classified automatically by applying the machine learning classifier of the system to the compound data set of the unclassified data sets.