Abrégé

The invention relates to drone-survey measurement based inundation probability forecast and flood hazard vulnerability measuring system (1) and method thereof. Location- specific elevation data are measured by drones (12) of the measuring system (11), wherein the measured location-specific elevation data are transmitted to an inundation engine (11 ) for forecasting flood hazard vulnerability zones and risk zones based on the said measured location-specific elevation data depending on return periods (21) or inundation heights (22) of a flood hazard (2).

Classes IPC  ?

• G01C 25/00 - Fabrication, étalonnage, nettoyage ou réparation des instruments ou des dispositifs mentionnés dans les autres groupes de la présente sous-classe
• G06Q 40/08 - Assurance
• G01C 21/00 - Navigation; Instruments de navigation non prévus dans les groupes

Abrégé

Proposed is an electronic, automotive accident risk measuring system (1) for accidentology-based measuring of accident risk-indexing score values for a motor vehicle (2) to be tested providing a measured accident probability value for an occurrence of an accident event having a physical impact to the tested motor vehicle (2), which comprises the processing unit (4) comprising a driving scenario module (40), a test setting module (42) and a scoring module (44). The driving scenario module (40) is configured for determining various driving scenarios (5) for the motor vehicle (2) by defining a set of measurable scenario characteristics (50, 51, 52,...), which include at least one ADAS variable. The test setting module (42) is configured for determining a test setting (6) in form of a multi-dimensional test matrix (60), which includes testing protocols (61, 62, 63,...) for each of the measurable scenario characteristics for providing measured values of measurable scenario characteristics of the various driving scenarios. The measured values are presented in a multi-dimensional test result signal (14) including test result data for each of the measured scenario characteristics. The scoring module (44) is configured for generating the risk-indexing score (70) by receiving the multi-dimensional test result signal (16) and a historical data information signal (16) from an accident database (8). The historical information data signal (16) indicates a probability of occurrence of an accident and/or a damage magnitude for one or more historic driving scenarios, which at least partially comprise the measured scenario characteristics of one or more of the various driving scenarios (5). The historical data provide a quantified measure of frequency of accidents (163, 165, 167,...) and/or severity of damage (164, 166, 168,...) associated to the various driving scenarios (5). The scoring module (44) comprises a scoring structure with a weighting structure (46) for weighting the multi-dimensional test result data (14) based on the historical data information signal (16) with respect to a contribution of each of the various driving scenarios (5) to the accident probability value and an aggregator (48) for aggregating the weighted multi-dimensional test result data of the various driving scenarios (5) to define the risk-indexing score (70) for the motor vehicle (2).

Classes IPC  ?

• G06Q 40/08 - Assurance
• B60W 60/00 - Systèmes d’aide à la conduite spécialement adaptés aux véhicules routiers autonomes

Abrégé

A digital health or life claim processing system (1) providing electronic integration of multiple digital automated claims channels, wherein a digital claims channel includes a claims data set (91), a policy data set (93) regarding a claim event (E) and/or a services data set (92), and processing one or more claims of a customer (A; B; C) based on at least one claims channel related to the customer (A; B; C). The system (1) comprising a cloud-based infrastructure platform (2) accessible via a digital network (3), which hosts a storage module (4), a data modelling module (5), a claims processing module (6), and a communication module (7), and at least one data transmission interface (81; 82; 83) for exchanging data and/or information provided by at least one user device (191; 192) with the infrastructure platform (2). At least the claims data set (91), the policy data set (93) and/or the services data set (92) includes claimants doctors and/or medical cause data at least comprising measuring data for physical characteristics values quantifying a claim event (E) and/or historic policy disclosures' parameter values and/or product rules' parameters and medical cause data and/or diagnostic measuring parameter values and/or laboratory measuring parameter values. The data modelling module (5) comprises a data validation structure (51) for validating data of characteristics values of the claims data sets (91), the policy data sets (93) and/or the services data sets (92), wherein validated data sets of multiple claims channels of a customer (A; B; C) are stored as structured data sets (302) in the data storage module (4). The claims processing module (6) comprises a processing and analyzing structure (61) designed for analyzing the structured data sets (302) according to claims requirements defined in the claims channels, and for defining a current claim processing status (305). The communication module (7) provides a digital communication signal (73; 74) representing the current claim processing status (305) to a user device (191; 192) within the digital network (3).

Classes IPC  ?

• G06Q 40/08 - Assurance

Abrégé

Proposed is a digital, state discrete system and platform and corresponding method thereof, for automated underwriting and pricing of individually predicted loss covers using a combination of a Markov Chain modelling structure and configurable elements at least comprising states and/or state transitions and/or cashflows specific to the product it instantiates. The digital system comprises a simulation engine using deterministic transition and interest rates of a discrete process to conduct calculations per policy, wherein parts of the process are used with stochastic transition and interest rates of a discrete process for conducting simulations on portfolio level. The calculations take place on a slice level and are aggregated on benefit and quote level, wherein a slice is created whenever a policy benefit is subject to an unscheduled sum assured increase, and wherein for new business each benefit starts with one slice, each slice being related to the specific product version, cover, and tariff relevant at that the respective point in time the slice is created for.

Classes IPC  ?

• G06Q 40/08 - Assurance

Abrégé

Proposed is a digital finite state system and platform and corresponding method thereof, for processing a digital object by object-state triggered processes. The object being capturable by a digital set of defined parameter values comprising at least structural parameter values or state parameter values associated with the object, wherein the digital set of defined parameter values define an initial state and/or set-up of the object, wherein the object is automatedly processed by the digital systems by processing the digital object by a sequence of process steps through which the digital object passes from an initial state to a final state. The digital system comprises a finite state machine engine, wherein the processing of each digital object is based on a finite state automaton comprised in or associated with the digital object, the finite state automaton comprising all possible states and associated transition rules for the digital object, the transition rules at least comprising the process steps and condition parameter values for the digital object to be processed form one finite state to a next finite state by the finite state machine engine. The possible states and their transition rules for the digital object are configurable within the digital object and are implicitly processed as part of an initial digital object configuration process, wherein the initial state and/or set-up of the object at least comprise the possible states and associated transition rules as digital object configuration.

Classes IPC  ?

• G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projets; Planification d’entreprise ou d’organisation; Modélisation d’entreprise ou d’organisation
• G06Q 40/08 - Assurance

Abrégé

Proposed is a parameter pattern-driven, data mining system and corresponding method with a knowledge extraction engine based on a customizable chain of machine-learning-structures providing an automated pipeline for data processing of complex data structures with a hidden pattern detection for triggering automated under-writing processes. A plurality of digital risk-transfer policies is assessed via a data interface and storable captured by a persistence repository unit of the parameter pattern-driven, data mining system. The digital policy at least comprises premium parameter values and/or deducible parameter values and/or risk-transfer type definition parameter values and/or policy limits parameter values and/or exclusion parameter values and/or riders/addit parameter values. The parameter pattern-driven, data mining system comprises a chained series of machine learning modeling structures automatically assessing and parsing digital risk-transfer policies of a policyholder, and automatically translating contractual language of the digital policy into actionable offers for the policyholder by generating appropriate new digital risk-transfer policies for automated under writing by the policyholder.

Classes IPC  ?

• G06Q 40/08 - Assurance

Abrégé

Proposed is an electronic vulnerability detection and measuring system (1) and method for susceptibility or vulnerability measurements of a truck fleet (2) to occurring accident events caused by a carriage vehicle (2.1 2.5) of the carriage vehicle fleet (2). At least one data interface (3.1) is associated with data access means to a carriage vehicle fleet database (50) for capturing carriage vehicle data as a fleet input signals (5) from the carriage vehicle fleet database (50). The carriage vehicle data comprises: vehicle data (5.11.... 5.31) comprising physical parameter measurements of carriage vehicle characteristics for the carriage vehicles (2.1.... 2.5), carriage vehicle driver data (5.12.... 5.32) comprising physical parameter measurements of driver characteristics and/or carriage vehicle usage data (5.13... 5.33) comprising physical parameter measurements of carriage vehicle usage characteristics. At least one data interface (3.2) is associated with data access means for capturing behavioral driving data (6.1.... 6.3) of an electronic driving monitoring system (10) of at least one carriage vehicle (2.1.... 2.5) as a driving data input signal (6). A processing unit (100) is designed for receiving the fleet input signal (5) and the driving data input signal (6) and comprises a machine learning module (110) for analyzing the data provided by the fleet input signal (5) and the driving data input signal (6) by using one or more machine learning structures (111, 112) and generating a risk index value for the carriage vehicles (2.1.... 2.5 ). An aggregating module (130) automatically generates an aggregated risk score measure for the truck fleet (2) based on the risk index values of the carriage vehicles (2.1.... 2.5). A signal generator (140) provides the aggregated risk score measure as output signal (150) indicating the risk score measure of the truck fleet (2).

Classes IPC  ?

• G06Q 40/08 - Assurance
• B60W 40/00 - Calcul ou estimation des paramètres de fonctionnement pour les systèmes d'aide à la conduite de véhicules routiers qui ne sont pas liés à la commande d'un sous-ensemble particulier
• G07C 5/00 - Enregistrement ou indication du fonctionnement de véhicules

Abrégé

A geospatial digital encoding, decoding, and mapping system (100) and method for processing and geospatial data to generate a unique geo identification (ID) code (212) for a geospatial object distinctively identifying the geospatial object and for decoding and mapping a unique geo identification (ID) code (212) to a digital representation. The system (100) comprises a geospatial data processing unit (112) for capturing geospatial data associated with a geospatial object, and for extracting a footprint (202) of the geospatial object based on the geospatial data. The system (100) comprises boundary determination unit (114) for identifying a centroid (206) of the footprint (202) and determining relevant boundary (206) for the footprint (202). The system (100) further comprises geo ID code generation unit (116) for determining an orientation of the boundary (206) and rotating the boundary (206) around the centroid (204) of the footprint (202). The geo ID code generation unit (116) computes directional extents (216) of the boundary (206), and generates the geo ID code (212) based on directional extents (216), centroid (204), and orientation of the boundary (206).

Classes IPC  ?

• G06F 16/29 - Bases de données d’informations géographiques
• G06F 16/909 - Recherche caractérisée par l’utilisation de métadonnées, p.ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement utilisant des informations géographiques ou spatiales, p.ex. la localisation

Abrégé

Proposed is a digital system (1) and a method for forecasting and/or allocating risk measures for an occurrence of an impact event causing a physical loss or damage impact on cargo and/or cargo logistics causing a negative impact (30) on the cargo (10) and/or the cargo logistics services. Sets (13) of measurable cargo logistics parameters (11) are captured by the system (1) as logistics input signals (400) from a cargo logistics services database (41) and are transmitted to an allocation structure (22). Each set (13) of measurable cargo logistics parameters (11) at least comprises cargo parameters (12) and/or logistics parameters (42). At least one risk factor (52) indicating a measured negative impact risk for the cargo (10) and/or the cargo logistics services is captured by the system (1) as risk input signals (500). Each of the risk factors (52) at least corresponds to a measured impact strength (31) or impact type (32) of a negative impact (30) on the cargo (10) and/or the cargo logistics services, and/or a quantified damage (33) at the cargo (10) and/or on the cargo logistics services. At least one measurable cargo logistics parameter (11) is assigned a risk factor (52) by the allocation structure (22) that corresponds to a measured value of the measurable cargo logistics parameters (11). An aggregated risk measure (60) for the cargo logistics services is automatically generated by an aggregating structure (25) of the processing unit (20) based on the at least one risk factors (52) allocated to measurable cargo logistics parameters (11) and is provided as output signal (600) by a signal generator (24) to predict an occurrence of a measurable negative impact (30).

Classes IPC  ?

• G06Q 10/08 - Logistique, p.ex. entreposage, chargement ou distribution; Gestion d’inventaires ou de stocks

Abrégé

Proposed is an electronic risk measuring and scoring system (100) and method (400) for an autonomous vehicle (101), comprising: an vehicle component valuation unit (1101) to valuate the autonomous vehicle (101); an automated ranking unit (1102) for determining ranking associated with forward-looking accident frequencies and severities for the autonomous vehicle (101) based on the valuation thereof, and at least on one of operational risk data, contextual risk data, technical performance of the autonomous vehicle (101), legal risk data and cyber risk data therefor; a benchmarking unit (1103) for benchmarking autonomous vehicle risks associated with the autonomous vehicle (101) based on testing and/or simulating an autonomous vehicle component modelling structure for the autonomous vehicle (101); a risk class unit (1104) for generating a risk space with one or more risk classes for the autonomous vehicle (101) based on the benchmarking; and a scoring unit (1105) for generating scores or indices, to calibrate and rate and/or price risk-transfers, and/or as input for risk-transfer modeling.

Classes IPC  ?

• G06Q 40/08 - Assurance
• B60W 60/00 - Systèmes d’aide à la conduite spécialement adaptés aux véhicules routiers autonomes

Abrégé

Proposed is a scalable, data-driven digital market place and system providing a standardized data aggregator by a central digital platform for interlinking sensitive risk-related data, the scalable data-driven digital market place providing controlled data-driven and/or process-driven cross-data interaction between different units of the scalable data-driven digital market place and the central digital platform. The digital market place platform is based on an automated digital process for users centered around six areas with modular core and premium add-on processes. The first area provides automated loss analytics and automated programme optimization facilitating the understanding of loss trends and automated deriving of an optimized risk-transfer structure and/or programme. The second area provides automated property exposure management and automated visualization of property portfolio and risk exposures. The third area provides employee health risk-transfer structures and/or programmes facilitating automated analysis of complex impact of risks on employee health programs and/or risk-transfer structures. The forth area provides automated policy and/or certificate and/or exposure and/or claims management, inter alia, providing automated capturing and automated managing of risk-relevant data and documents. The fifth area provides automated supply chain resilience by automatically creating digital twins of production and supplier networks to be covered and/or fenced by risk mitigation. The sixth area provides automated sustainability solutions and/or automated compiling of sustainability metrics and tracking against NetZero.

Classes IPC  ?

• G06F 16/84 - Mise en correspondance; Conversion
• G06Q 10/04 - Prévision ou optimisation spécialement adaptées à des fins administratives ou de gestion, p. ex. programmation linéaire ou "problème d’optimisation des stocks"
• G06Q 10/0635 - Analyse des risques liés aux activités d’entreprises ou d’organisations
• G06Q 10/20 - Administration de la réparation ou de la maintenance des produits
• H04W 4/38 - Services spécialement adaptés à des environnements, à des situations ou à des fins spécifiques pour la collecte d’informations de capteurs

Abrégé

Proposed is a digital system and robust expert method for accuracy-enhanced expert forecasting based on a digital audit-linked best-estimation framework, wherein the audit-based best-estimation framework comprises two or more execution member executing at least the steps of (i) determining a forecasted value for a definable future time window benchmarking the audit-based best-estimation framework to a starting point value based on one or more historical databases, (ii) determining a 90% confidence interval range for the determined starting point value by a lower bund value and an upper bond value of the interval range, wherein the starting point value is part of the confidence interval value range, and wherein an actually measured value of the forecasted value in the future time window is forecasted to measurably deviate with a 90% probability within the 90% confidence interval range, and (iii) selecting one or more possible scenarios each having a definable probability distribution and applying a sensitivity analysis by at least varying a time-based range of an observation window, wherein if the forecasted value deviates further from the starting point value as a predefined threshold value by the variation, the starting point value is adjusted. The forecasted values of the at least two execution member are transmitted and captured by a best-estimation engine determining a best-estimation forecasted value based on the captured forecasted values of the at least two execution member.

Classes IPC  ?

• G06Q 40/08 - Assurance
• G06N 3/02 - Réseaux neuronaux

Abrégé

The invention relates to automated method (1) and flood measuring and trigger system (1)for providing a dynamic parametric flood impact cover (1031) for physical objects (3/31) being measurably impacted by an occurrence (41/42/43) of a flood event (4) by using an adaptive damage-cover structure (1041) of a damage-cover system (104) based on physical flood event measurements, wherein by flood detection devices and/or flood sensors (102), an occurrence of a flood event (2) is measured by measuring floodings within the grid cells (1003) of the spatial grid (1002), wherein flood measuring parameters (1021) of the flood detection devices and/or flood sensors (102) are transmitted to the central measuring engine (10) and wherein, based on the transmitted flood measuring parameters (1021), grid cells (1003) measured as flooded are contributing to the area measured as affected (21) while grid cells measured as not flooded are contributing to the area measured as not affected (22).

Classes IPC  ?

• G06Q 40/08 - Assurance

Abrégé

The invention relates to automated method (1) for providing a dynamic parametric cover to an individual in case of an occurrence of a flood event by using an adaptive risk-transfer structure based on physical flood event measurements. Using a predefined data structure, a geographic or topographic area to be covered is determined. Equally spaced network points are generated over said geographic and/or topographic area providing a meshed network of network points having a definable mesh size and covering the whole geographic and/or topographic area. After an occurrence of a flood event, for an affected area of said geographic and/or topographic area the total number of network points within the affected area is aggregated and the affected area of said geographic and/or topographic area is measured based on measuring a flooding at each network point of the meshed network within the affected area based on the flood map, wherein network points measured as flooded are contributing to the measured affected area while network points measured as not flooded are not contributing to the measured affected area.

Classes IPC  ?

• G06Q 40/08 - Assurance

Abrégé

The invention relates to automated airborne and/or spaceborne optical flood sensory and flood impact sensory method and system for measuring and/or forecasting a weightage-specific, quantitative flooding measure value and/or a weightage-specific, quantified flooding impact extent measure value, the weightage being based on an object density of a selected topographic and/or geographic area impacted by an occurrence of a flood event.

Classes IPC  ?

• G06Q 40/08 - Assurance

Abrégé

Proposed is a digital platform (1) and a method for automated risk analysis for a physical property asset are based on image data of a geographic area, geo location parameters for locations in the geographic area and measurement-based risk relevant data for locations in the geographic area. The digital platform (1) is used to generate a location digital twin based on image data of a geographic area, a sub- area including a physical property asset of interest, geo location parameters and the measurement-based risk relevant data of the property asset of interest in the sub area. A framework structure (3) maintains a plurality of location digital twins of a plurality of physical property assets providing a basis for the risk analysis.

Classes IPC  ?

• G06Q 10/0635 - Analyse des risques liés aux activités d’entreprises ou d’organisations
• G06Q 40/08 - Assurance
• G06Q 10/10 - Bureautique; Gestion du temps
• G06Q 50/16 - Immobilier

Abrégé

An aerial and/or satellite imagery-based, optical system and corresponding method for measuring physical impacts to land-based objects (3) by impact measurands (1113) in case of an occurrence of a natural catastrophe event (2), the natural catastrophe event (2) impacting the objects (3) causing a physical damage (32). The method and system comprise the steps of capturing by remote airborne and/or spaceborne sensors (121) digital aerial and/or satellite imagery and/or photography (122) of an area (4) affected by the natural catastrophe event (2), and generating a digital natural catastrophe event footprint (1111) with a topographical map (11111) of the natural catastrophe event (2) based on the captured digital satellite imagery (122). Finally, parametrizing, by an adaptive vulnerability curve structure (1112), impact measurands (1113) for selected objects (3) based on the measured topographical map (11111), and generating an impact measurand (1113) value for each of the land-based objects (3) based on an event intensity (23) measured by the natural catastrophe event footprint (1111) using the vulnerability curve structure (1112). In addition, the present invention leverages computer vision/ deep learning/ artificial intelligence on actual post catastrophe satellite and aerial imagery to detect and measure different types and/or damages of damage on properties/ roofs.

Classes IPC  ?

• G06Q 10/04 - Prévision ou optimisation spécialement adaptées à des fins administratives ou de gestion, p. ex. programmation linéaire ou "problème d’optimisation des stocks"
• G06Q 40/08 - Assurance
• G06Q 30/02 - Marketing; Estimation ou détermination des prix; Collecte de fonds
• G06Q 50/16 - Immobilier
• G06T 7/00 - Analyse d'image
• G06T 7/90 - Détermination de caractéristiques de couleur

Abrégé

Proposed is a measuring and control system (1) and method for individually measuring of a multitude of perils and/or safety scores of a property or smart home (3). The measuring and control system (1) comprises at least one hardware controller and a plurality of sensory devices, wherein the property or smart home (3) is populated with the sensory devices, the at least one hardware controller being in communication with the plurality of sensory devices, and the sensory devices transmitting sensory signals to the hardware controller.

Classes IPC  ?

• H04Q 9/00 - Dispositions dans les systèmes de commande à distance ou de télémétrie pour appeler sélectivement une sous-station à partir d'une station principale, sous-station dans laquelle un appareil recherché est choisi pour appliquer un signal de commande ou
• G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projets; Planification d’entreprise ou d’organisation; Modélisation d’entreprise ou d’organisation
• G08B 21/10 - Alarmes pour assurer la sécurité des personnes réagissant aux événements désastreux, p.ex. les tornades ou les tremblements de terre
• G06Q 40/08 - Assurance

Abrégé

Proposed is an automated maximum impact measurand forecasting system (1) for measuring an impact of an explosion of an explosive (3) in open steel and/or concrete and/or reinforced concrete structures (2), wherein at least loading (311) and/or resistance (211) measuring parameter (21/31) values are measured and/or captured by the automated forecasting system (1).

Classes IPC  ?

• G01M 7/08 - Test de résistance au choc
• A62C 3/06 - Prévention, limitation ou extinction des incendies spécialement adaptées pour des objets ou des endroits particuliers pour des matériaux très inflammables, p.ex. les métaux légers, les produits du pétrole
• G01N 3/313 - Recherche des propriétés mécaniques des matériaux solides par application d'une contrainte mécanique en appliquant une force unique et brève engendrée par des explosifs
• G06F 30/13 - Conception architecturale, p.ex. conception architecturale assistée par ordinateur [CAAO] relative à la conception de bâtiments, de ponts, de paysages, d’usines ou de routes
• G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projets; Planification d’entreprise ou d’organisation; Modélisation d’entreprise ou d’organisation

Abrégé

Proposed is an automated, fully integrated, and embedded measuring system and method for measuring a score-indexing parameter essentially based on directly measured connected motor vehicle sensory data and/or sensory data of a mobile device of a user of the motor vehicle. The sensory data stem from a change in status of the vehicle at any point in time, due to i) the actions/reaction of the driver, ii) the context in which the driver is driving or, the way the driver perceives and feels the surroundings, iii) the way the car adapts to internal and external conditions, including the driver. The measured score-indexing parameter captures (i) vehicle component impacts by which systems are present and activated/deactivated, (ii) driver component impact comprising at least measured harsh maneuvers and/or excess of speed and/or risky behaviors and/or distraction, and (iii) contextual component impacts where vehicle data are enriched with additional layers to measure location- based risks.

Classes IPC  ?

• G06Q 40/08 - Assurance
• G07C 5/00 - Enregistrement ou indication du fonctionnement de véhicules

Abrégé

Proposed is a vehicle embedded or mobile-phone-based, automated dynamic routing unit (100) associated with a vehicle (800) and/or a user (700) along a route (122) traveled and method thereof. The dynamic routing unit (100) provides an optimized route between a departure location (1221) and a destination location (1222), wherein the automated dynamic routing unit (100) comprises a routing interface (110) for receiving destination input parameters (112/1121) of a destination location (1221) and/or departure location input parameters (112/1122) of a departure location (1222), and wherein the automated dynamic routing unit (100) comprises a routing generator (120) for generating one or more routes (1201) between the departure location (1221) and the destination location (1222). Among the generated routes, an optimized route (1401) can be selected based on risk-exposure scores (1301) determined for each route, quantifying a probability of occurrences of impacting accident events along the route.

Classes IPC  ?

• G01C 21/34 - Recherche d'itinéraire; Guidage en matière d'itinéraire

Abrégé

Proposed is an automated system and method for measuring and/or allocating risk measures of loss for a replacement cost of an electric vehicle and/or parts of the electric vehicle. The system based on a forward looking model structure for electric vehicles (FLM-EV) returns rating modification factors for MTPL and MOD for electric vehicles. The input consists of either car make, model year or rating parameters like model year, maximum power etc. The output are modification factors that are applied on MOD or MTPL frequency, severity or expected loss for non-electric cars.

Classes IPC  ?

• G06F 21/55 - Détection d’intrusion locale ou mise en œuvre de contre-mesures

Abrégé

Proposed is an automated automobile claims fraud detector and method for automatically evaluating validity and extent of at least one damaged object from image data and detect possible fraud, the automated automobile claims fraud detector comprising the processing steps of: (a) receiving image data comprising one or more images of at least one damaged object; (b) processing said one or more images for existing image alteration using unusual pattern identification and providing a first fraud detection; ( c) processing said one or more images for fraud detection using RGB image input, wherein the RGB values are used for (i) CNN-based pre-existing damage detection, (ii) parallel CNN-based color matching, and (iii) double JPEG compression (DJCD) detection using custom CNN; (d) processing output of (i) CNN- based pre-existing damage detection, (ii) parallel CNN-based color matching, and (iii) double JPEG compression detection using custom CNN as input for ML-based fraud identifier providing a second fraud detection; and (e) generating fraud signaling output, if the first or second fraud detection indicates fraud.

Classes IPC  ?

• G06V 10/764 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant la classification, p.ex. des objets vidéo
• G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
• G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques
• G06V 10/44 - Extraction de caractéristiques locales par analyse des parties du motif, p.ex. par détection d’arêtes, de contours, de boucles, d’angles, de barres ou d’intersections; Analyse de connectivité, p.ex. de composantes connectées
• G06V 10/56 - Extraction de caractéristiques d’images ou de vidéos relative à la couleur

Abrégé

Proposed is a ML-based, predictive, digital underwriting system (1) and corresponding method providing an automated parameter-driven predictive underwriting process (9) based on measured probability values (22) associated with individuals (2) of a cohort (21) or portfolio (1011), the individuals (2) being exposed to a probability of occurrence of one or more predefined medical and/or health and/or life events (4) having the probability value (22) with a predefined severity (41) within a future measuring time-window (42).

Classes IPC  ?

• G06Q 40/08 - Assurance

Abrégé

Proposed is a system (16) and method for measuring relative risk measurands of living individuals (2). The relative risk measurands provides a measure for the frequency of occurrences of specific medical events having impacting consequences in specified ranges to the living individual (2) within a defined cohort of living individuals (2) relative to a randomized cohort of living individuals (2). The system provides automation of the risk assessment and measuring process with a high efficiency and accuracy.

Classes IPC  ?

• G06Q 40/08 - Assurance

Abrégé

Proposed is a digital multi-channel platform (1) based on a multi-channel, high-layer data-transfer structure (1113) accessible by means of web-client applications (121) running on front-end network-enabled devices (12) providing discrete high-layer data-flow and capturing of structured (1121) and unstructured (1122) data content transferred from the front-end network-enabled devices (12) over a data transmission network (13) to a digital multi-channel back-end system (11).

Classes IPC  ?

• G06F 16/21 - Conception, administration ou maintenance des bases de données
• G06F 16/25 - Systèmes d’intégration ou d’interfaçage impliquant les systèmes de gestion de bases de données

Abrégé

Proposed is a digital and automated underwriting system 1 and method with fast point of sale decision-making and intelligent data processing engine (11) for the coverage of possible damage impacted by the occurrence of health events to users. The automated system 1 captures user-specific medical parameter data sets. The captured medical parameter data sets are processed by the electronic signal processing engine (11), wherein the electronic signal processing engine (11) transmits an output signal generated upon processing the medical parameter data set, the output signal automatically triggering or blocking an automated underwriting process by an electronic underwriting unit (13).

Classes IPC  ?

• G06Q 40/08 - Assurance

Abrégé

Proposed is a cloud-based, scalable, advanced analytics platform and/or anomaly detection system 1 for analyzing complex medical risk data and providing dedicated electronic trigger signals, inter alia, applicable for triggering risk-related activities or providing expert-system-based insights for medical risk-transfer. The digital- based system can, inter alia, be based on measurements based on evolving real-world measuring parameters associated with complex medical or clinical risk-related measuring parameter values and data. The present invention further relates to pattern anomaly detection and more specifically to a method and apparatus for performing a multi-domain anomaly pattern definition and detection, in particular in the filed bio- surveillance.

Classes IPC  ?

• G16H 40/20 - TIC spécialement adaptées à la gestion ou à l’administration de ressources ou d’établissements de santé; TIC spécialement adaptées à la gestion ou au fonctionnement d’équipement ou de dispositifs médicaux pour la gestion ou l’administration de ressources ou d’établissements de soins de santé, p.ex. pour la gestion du personnel hospitalier ou de salles d’opération
• G16H 10/60 - TIC spécialement adaptées au maniement ou au traitement des données médicales ou de soins de santé relatives aux patients pour des données spécifiques de patients, p.ex. pour des dossiers électroniques de patients
• G06N 20/00 - Apprentissage automatique
• G06Q 40/08 - Assurance

Abrégé

Proposed are an automated real-time fraud monitoring and detection system (1) for detecting unusual and/or suspicious activities within a network of nodes (41) interconnected by edges (42) triggered by captured synthetic forms of social data, in particular social networking and/or linkage and/or relationship data) and social metadata comprising at least data from microblogging services and/or social networking services by means of pattern recognition and matching.

Classes IPC  ?

• G06Q 40/08 - Assurance

Abrégé

Proposed is an automated system (1000), phone distraction detector and method for automatically detecting phone distraction events in a moving vehicle (202), caused by a driver of the moving vehicle (202) by using a smartphone (102). An Internet of Things (IoT) server (104) is communicatively coupled to the smartphone (102). The smartphone (102) comprises one or more sensors (118, 120) built into the smartphone (102), wherein sensory data of the one or more sensors (118, 120) are captured by the sensors (118, 120) of the smartphone (102) during a vehicle trip and are transmitted to the Internet of Things (IoT) server (104), and wherein the sensor data comprises one or more chunks of data streams associated with an IoT service from the smartphone (l02). The sensory data are processed and analyzed by the server (104) to identify one or more phone handling events associated with the smartphone (102) during the vehicle trip (202). One or more phone handling events associated with the smartphone (102) are aggregated into one or more macro events by the processing means of the server (104). The aggregated one or more macro events are processes by the server (104) based on a set of preconfigured rules to determine a phone distraction event, wherein the set of preconfigured rules are based on predefined thresholds to determine the phone distraction event.

Classes IPC  ?

• H04L 29/08 - Procédure de commande de la transmission, p.ex. procédure de commande du niveau de la liaison

Abrégé

Proposed is an automated measuring system (1) for progress monitoring and steering of impacts of a complex system (2) to world environment and ecosystem (3) induced by environmental-human linkages (21) and for quantitative measuring of effects of applied risk-transfer structures (4) to said environmental-human linkages (21) induced by risk-transfer–SDG linkages (41/411,…41x) measuring quantifying distances (11/111, 112, …, 11x) of progresses toward at least one of a predefined sustainable development goal (SDG/12) with and without applying said risk-transfer structures (4).

Classes IPC  ?

• G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projets; Planification d’entreprise ou d’organisation; Modélisation d’entreprise ou d’organisation

Abrégé

Proposed is an automated system (1) providing an automatable long-term care risk mitigation structure associated with immediate care needs of risk-exposed individuals in case of becoming a long-term care-receiver. The system (1) provides an automated multi-step trigger and defection cycle (9/91, 92, 93, 94, 95, 96, 97) based on sensory measuring data for risk-exposed individuals (4) thereby mitigating possibly occurring long-term care needs by means of the automated system based on a defected sufficient state of disability (2), possibly predetermined up-front amount parameters (8211) and an assigned care equity ratio associated with an asset (3). The state of disability (2) of the risk-exposed individual (4) is measurable by a definable set of risk-exposed individual measuring parameters (10).

Classes IPC  ?

• G06Q 30/06 - Transactions d’achat, de vente ou de crédit-bail
• G06Q 40/08 - Assurance

Abrégé

Proposed is an automated risk assessment and underwriting platform and corresponding method. The platform providing an automated underwriting process comprising the processing steps of: (i) identifying, for each line of business or industry, risk classes with similarity risk characteristics, comprising industry classes and/or sub-classes, (ii) analyzing risk classes for typical risk features, (ill) turning features info a small set of risk focused questions and pre-defined responses from which the underwriting return (UWR) picks the answers, (iv) weighting questions and feeding responses info a structure generating a default risk assessment allocating the actual risk info a risk qualify quintile, (v) benchmarking by the underwriter, based on experience and knowledge the actual risk against other bound risks belonging to the same risk class, the underwriter further modifying the default risk assessment leading to a different risk opinion, (vi) justifying with a rationale the modification of the default risk assessment, and (vii) using the final risk assessment as the basis for risk related base rate modifications in the pricing process. Further, the platform provides automated management of risk-driven portfolios.

Classes IPC  ?

• G06Q 40/08 - Assurance

Abrégé

Proposed is an electronic risk measuring and scoring system (100), in particular for mobile telematics devices (10) and method thereof. In particular, an electronic risk measuring and scoring system (100) which measures an ADAS risk score measure measuring the impact of ADAS features (200) to the accident risk associated with a motor vehicles (10), and which rates and calibrates a risk-transfer user-specifically thereby capturing the impact of ADAS features (200) in measures of risk-transfer claims frequency and severity.

Classes IPC  ?

• G06Q 40/08 - Assurance

Abrégé

Proposed is a digital marketplace platform (1) providing an automated, multi-channel, end-to-end, digital marketplace platform (1) providing fully automated, end-to-end risk-assessment and risk-transfer processes (2) 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 (1).

Classes IPC  ?

• G06Q 40/08 - Assurance
• G06Q 30/06 - Transactions d’achat, de vente ou de crédit-bail

Abrégé

Proposed is a digital platform (1) for automated predicting and quantified rating of exposure measures associated with occurring construction and erection risks (31) of an engineering or construction project (20-26) and for automated prediction and measuring of future occurring loss patterns (1511,…,151i) induced by the occurring construction/erection risks (31) to the project (20-26) exposed to said construction/erection risks (31), wherein an engineering risk profile (101i2) of a project (20-26) associated with and exposed to construction and/or erection risks (31/CAR/EAR) is assembled, and wherein, based on the predicted and measured future occurring losses patterns (1511,…,151i), risk-tailored expert advices for underwriting parameters are provided.

Classes IPC  ?

• G06Q 40/08 - Assurance
• G06Q 10/04 - Prévision ou optimisation spécialement adaptées à des fins administratives ou de gestion, p. ex. programmation linéaire ou "problème d’optimisation des stocks"
• G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projets; Planification d’entreprise ou d’organisation; Modélisation d’entreprise ou d’organisation

Abrégé

The invention relates to an intermediary, digital, data-driven platform (1) and a method for heterogeneous industry ecosystems for the standardised identification and automated management of risk transfers and associated product- and company-specific capabilities as a standardised digital channel between risk-exposed entities of the industry ecosystem and the systems of a heterogeneous risk transfer ecosystem.

Classes IPC  ?

• G06Q 40/08 - Assurance

Abrégé

A measuring and monitoring system is proposed, comprising a plurality of measurement sensors and measurement devices by means of which geographically cellularly limited measurement parameters are detected. The measurement parameters are aggregated to form a BES measurement index, with the measurement parameters being selected in respect of the desired measurement accuracy of the biodiversity and ecosystem services (BES) measurement index. The measurement and monitoring system comprises selectable, different biodiversity and ecosystem services at least comprising measurement parameters for measuring the intactness of the habitat and/or pollination and/or air quality and local climate and/or water security and/or water quality and/or soil fertility and/or erosion control and/or coastal defences and/or supply with food and/or wood provision. The measuring and monitoring system additionally allows the quantitative detection/measurement of risk indices on the basis of the measured ecosystem services depending on sector-based economic performances.

Classes IPC  ?

• G06Q 40/08 - Assurance

Abrégé

Proposed is a method and system for automated transportation mode recognition based on sensory data measured by a plurality of sensors (102) of a cellular mobile device (10) of a user (6/61 /62), the plurality of sensors (102) at least comprising an accelerometer (1025) and a gyroscope (1026), the plurality of sensors (102) being connected to a monitoring mobile node application (101) of the mobile device (10), wherein the mobile device (10) measures time series of sensory parameter values based on measuring parameters obtained from the sensors (102), the measuring parameters comprise time series of sensory parameter values of a 3-axis accelerometer as sensor (102) and time series of sensory parameter values of GPS-based speed measurements of a GPS receiver as sensor (102), and wherein the measured time series of sensory parameter values trigger the automated transportation mode recognition as input feature values to a gradient boosting machine-learning classifier, the transportation modes at least comprising the modes public transportation and/or motorcycle and/or cycling and/or train and/or tram and/or plane and/or car and/or skiing and/or boat, and the transportation mode recognition generating a transport mode label for a transport mode movement pattern of a trip.

Classes IPC  ?

• G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales

Abrégé

Proposed is a method and system for identifying and/or classifying an occupant of a vehicle based on sensory data measured by a plurality of sensors of a cellular mobile device of the occupant, the plurality of sensors at least comprising an accelerometer and a gyroscope. The mobile device measures gravitational acceleration movement sensory data by means of the accelerometer based on measuring parameters obtained from the accelerometer, wherein vehicle entering or exiting movement patterns of the user are 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.

Classes IPC  ?

• G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales

Abrégé

Proposed is a method and system for electronic trip familiarity detection (114) based on sensory data (3) measured by a plurality of sensors (102) of a mobile telematics device (10) associated with a user (6) and/or a vehicle, the plurality of sensors (102) at least comprising a GPS sensor (1024) and/or an accelerometer (1025), the mobile device (10) comprising one or more wireless connections (105), wherein by at least one of the wireless connection (105) the mobile device (10) acts as a wireless node (221, …, 225) within a cellular data transmission network (2) by means of antenna connections of the mobile device (10) to the cellular data transmission network (2), and the plurality of sensors (102) being connected to a monitoring mobile node application (101) of the mobile device (10), wherein the monitoring mobile node application (101) captures usage-based (3) and/or user-based sensory data (3) of the plurality of sensors (102) of mobile device (10).

Classes IPC  ?

• G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales

Abrégé

Proposed is a digital platform (1) and method for providing controlled data- and process-driven cross-network interaction and program (41, 42, …, 4i) development between heterogeneous units (2/3) with network-enabled devices on a secured cloud- based network (5/51, 52, …, 5i). Each unit has a unit or user (2/3) account in the digital cross-network platform (1) with assigned authentication and authorization credentials for authentication and authorization controlled network access (5) to the digital cross- network platform (1) and the secured cloud-based network (5). Each unit (2/3) further has an assigned relationship with one or more other units (2/3) comprised in a persistent storage (12) of the digital networking platform (1), each assigned relationship providing a defined relationship between the one or more other units (2/3) or a subgroup of the one or more other units (2/3) and an associated program (41, 42,…,4i), the digital cross- network platform (1), enabling the controlled process-driven cross-network development of the international programs (41, 42, …, 4i).

Classes IPC  ?

• H04L 29/06 - Commande de la communication; Traitement de la communication caractérisés par un protocole
• H04L 29/08 - Procédure de commande de la transmission, p.ex. procédure de commande du niveau de la liaison
• G06Q 10/10 - Bureautique; Gestion du temps

Abrégé

Proposed is a digital channel for automated risk-transfer underwriting in fragmented, unstructured data environments covering heterogenous risk sources (1142) and risk-exposure classes (1141) associated with assets (2i1) of small and/or medium size enterprises (21,22,…,2i). The digital channel is provided by a digital platform (1) for the risk-exposed units (2, 21,22,…,2i) assessing the digital platform (1) by means of network- enabled devices (2i2) via a data transmission network (4). Risk-transfer portfolio data (101, 102, …, 10i) are held in a persistence storage (10) of the digital platform (1). The digital platform (1) comprises a risk advisory module (11) for automated asset classification (1262), risk scoring (1263) and interactive risk-transfer and risk-exposure steering (1264), wherein asset characteristics parameters (1121) of a unit (21,22,…,2i) are assigned to a risk profile (112) of the unit (21,22,…,2i), and wherein the assets (2i1) of the unit (21,22,…,2i) are classified into predefined asset classes (11211,…,1121i). The digital platform (1) comprises an automated underwriting and pricing module (13), wherein base rates (13412) for applicable risk-transfer covers (13411) are provided and corresponding pricings (13414) are generated based on the base rates (13412), associated rate factors (13413) and value parameters of the asset characteristics parameters (1121), wherein different applicable risk-transfer covers (13411) are generated and are assigned to a profile section (1123) of the risk-exposed unit (21,22,…,2i). A risk score (1124) is generated and assigned to each profile section (1123) of the risk profile (112), wherein the interactive portfolio steering is provided by inter- actively assigning and adjusting risk-transfer covers associated with said portfolio (101, 02, …, 10i).

Classes IPC  ?

• G06Q 40/08 - Assurance

Abrégé

Proposed is an automated digital channel to place and manage risk- transfers in the reinsurance industry. The digital channel is based on a metric simulation engine for automated prediction of forward- and backward-looking impact measures based on measured event parameter values of time-dependent series of occurrences of physical impact events. The occurrence of the physical risk events are measured based on predefined threshold-values of event characteristic parameters and the impact of the physical risk events to a specific physical or intangible real-world asset or living object is measured based on impact characteristic parameters. The characteristics of the risk-transfer are captured at least partially by means of a parameter-driven bifurcation process dynamically capturing characteristics parameter values and dynamically mapping the values to structured characteristics parameters.

Classes IPC  ?

• G06Q 40/08 - Assurance
• G06Q 10/04 - Prévision ou optimisation spécialement adaptées à des fins administratives ou de gestion, p. ex. programmation linéaire ou "problème d’optimisation des stocks"

Abrégé

Proposed is a digital platform (1) providing an automated, multi-channel, end-to-end risk-transfer product configuration process (2) for configuring, launching and processing of customized reinsurance risk-transfer structures, wherein an automated risk-transfer product placement is provided by the system (1) as a first online channel comprising a parameter-driven, rule-based underwriting process (21) for creating a portfolio of customized second-tier structures, wherein an automated claim handling (22) is provided by the system (1) as a second online channel, and wherein an automated accounting (23) is provided by the system (1) as a third online channel. For capturing of risk information parameters (2144), a product configurator (214) comprises a machine-based exposure data intelligence (215) enabled to automatically identify unique risks of objects (12) based on a precise location of the objects (12). The system (1) further comprises a graphical user interface of a portfolio analytics framework (6) providing a dynamic representation (61) of a portfolio structure (14). By means of the metric simulation engine (10), the dynamic representation of the portfolio structure (14) provides forward- and backward-looking insights to the user thereby enabling portfolio steering by identification of critical areas of the portfolio (14) and impacts of possible changes to the underwriting before going to launch it in the market.

Classes IPC  ?

• G06Q 40/08 - Assurance
• G06Q 10/04 - Prévision ou optimisation spécialement adaptées à des fins administratives ou de gestion, p. ex. programmation linéaire ou "problème d’optimisation des stocks"

Abrégé

Proposed is a system (1) and method for avatar measurements of temporally evolving real-world measuring parameters. The digital platform (1) comprising measuring sensors (2) and IoT sensory associated with a specific physical or intangible real-world asset (3) or living object (33) to be monitored. A digital twin representation (4) is generated of the physical or intangible real-world asset (3) or living object (33) from data structures of a data store (10) based on captured structural (421), operational (422) and/or environmental (423) property parameters (42). Data structures (44) for the digital twin representation (4) representing future states (441) of each of the plurality of subsystems (41) of the real-world asset or object (3) are generated as value time series over a future time period based on an application of simulations using cumulative damage modelling processing, the cumulative damage modelling generating the effect of the operational and/or environmental asset or object parameters on the twinned real-world asset or object (3) of the future time period. By means of the digital platform (1), the digital twin representation (4) is analyzed providing a measure for a future state or operation of the twinned real-world asset or object (3) based on the generated value time series of values over said future time period, the measure being related to the probability of the occurrence of a predefined event to the real-world asset or object (3).

Classes IPC  ?

• G06Q 10/00 - Administration; Gestion
• G05B 17/02 - Systèmes impliquant l'usage de modèles ou de simulateurs desdits systèmes électriques
• G06Q 10/04 - Prévision ou optimisation spécialement adaptées à des fins administratives ou de gestion, p. ex. programmation linéaire ou "problème d’optimisation des stocks"

Abrégé

Proposed is a digital platform (1) and method for avatar measurements of temporally evolving risk-based real-world measuring parameters. The digital platform (1) comprising measuring sensors (2) and loT sensory associated with a specific physical or intangible real-world asset (3) or living object (33) to be monitored. A digital twin representation (4) is generated of the physical or intangible real-world asset (3) or living object (33) from data structures of a data store (10) based on captured structural (421), operational (422) and/or environmental (423) property parameters (42). Data structures (44) for the digital twin representation (4) representing future states (441) of each of the plurality of subsystems (41) of the real-world asset or object (3) are generated as value time series over a future time period based on an application of simulations using cumulative damage models, the cumulative damage models generating the effect of the operational and/or environmental asset or object parameters on the twinned real-world asset or object (3) of the future time period. By means of the digital platform (1), the digital twin representation (4) is analyzed providing a measure for a future state or operation of the twinned real-world asset or object (3) based on the generated value time series of values over said future time period, the measure being related to the probability of the occurrence of a predefined even to the real-world asset or object (3).

Classes IPC  ?

• G06Q 10/00 - Administration; Gestion
• G05B 17/02 - Systèmes impliquant l'usage de modèles ou de simulateurs desdits systèmes électriques
• G06Q 10/04 - Prévision ou optimisation spécialement adaptées à des fins administratives ou de gestion, p. ex. programmation linéaire ou "problème d’optimisation des stocks"

Abrégé

Proposed is a system (10) providing a liability temperature measure (31) for liability systems (1) based on a time-dependent, composite indexing parameter (17). Measurement parameters assigned to parameterized liability risk drivers (311-313) are measured for generating the measured time-dependent, composite indexing parameter (17). The used liability risk drivers (311-313) are selected based on their impact to the measured variable composite index parameter and dynamically normalized to each other. The normalization is based on a defined transformation (151) applied to the final time series of the parameters providing individual set weights (1511,…,1513), wherein based on the weighted liability risk drivers (311-313) and sets of liability risk drivers (311-313), a minimum number (192) of liability risk drivers (311-313) in relation to maximized statistical significance is selected by applying an index assembly and validation unit (19), and wherein the index assembly and validation unit (19) provides the minimum number (192) of liability risk drivers (311-313) as a reduced set (161) of liability risk drivers out of all available liability risk drivers (16) using best fit characteristics (191). The driver selector (15) dynamically adapts the minimum number (192) of liability risk drivers (311-313) varying the liability risk drivers (311-313) in relation to the measured liability exposure signal (31) by periodic time response, wherein the time-dependent composite index parameter (17) is generated based on the adapted reduced set (161) of liability risk drivers (311-313).

Classes IPC  ?

• G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projets; Planification d’entreprise ou d’organisation; Modélisation d’entreprise ou d’organisation
• G06Q 40/08 - Assurance
• G06Q 40/02 - Opérations bancaires, p.ex. calcul d'intérêts ou tenue de compte

Abrégé

Proposed is a passage-based risk splitter (11) providing risk splitting and loss event diversification for multi-risk forecast systems (1) capturing multiple loss aggregation under complex environmental conditions based on the occurrence of defined loss events (44). The loss events (44) are triggered by one or more involved causing units (4) and affected units (3), wherein the loss events (44) evolve from one or multiple risk accumulating sources. Risk events (44) related loss measures can be scattered over multiple causing units (4) and/or multiple related clash events (44). The multi-risk forecast system (1) provides loss-generating processes and events (44), wherein the inventive risk splitter (11) is a technical core element to generate an event-related loss distribution (112) mirroring cause-effect chains (100) induced by the risk events (44) which extend over space and time. The risk splitter module (11) allows automated splitting of the risk based on risk exposed, causing unit characteristics (111) and risk exposed affected units' characteristics (112). The causing unit characteristics (111) comprise, for each causing unit (4), assigned activity characteristic parameters (1110) and participation characteristic parameters (1111) of said causing unit (4) defining, for a specific causing unit (4), a specific set of executable activity link members (1112) and market share driving participation probabilities (1113). The causing unit characteristics (112) comprises quota parameters defining affected populations of affected units (3) with incidence (1121) and defining refined effect types (1122).

Classes IPC  ?

• G06Q 40/08 - Assurance

Abrégé

Proposed is an event generator (10) generating risk events (2) for clash-quantifying, multi-risk assessment systems (1) with automated assessment of multi-risk exposures induced by the generated risk events (2), liability catastrophes (21) and casualty accumulations (22). A plurality of affected units (3) are subject to the risk exposure of the occurring risk events (2) caused by one or a plurality of causing liability risk exposed units (4). The event generator performs a scenario selection by means of a scenario selector (104) selecting relevant LLC/ULC/ELC scenarios (1001) from the scenarios (1001) of a data structure (101). Based on the selected scenarios (10001), concrete events (1002) are generated by means of the event generator (10).

Classes IPC  ?

• G06Q 40/08 - Assurance

Abrégé

Proposed is an electronic logging and track detection system (1) for mobile telematics devices (41,...,45) and method thereof. In particular, an electronic logging and track detection system (1) and system for mobile telematics devices (41,...,45), 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 (3) are measured by and logged from sensors (401,...,405) of the mobile telematics devices (41,...,45) and trips and/or trip-segments based on the instantaneous movement sensory telematics data (3) are automatically identified and detected at least by the telematics sensors comprising an accelerometer sensor (4011) and a gyroscope sensor (4012) and a Global Positioning System (GPS) sensor (4013). The telematics devices (41,...,45) comprise one or more wireless connections (421,..., 425) acting as a wireless node (221,..., 225) within a corresponding data transmission network (2) by means of antenna connections of the telematics device (41,...,45).

Classes IPC  ?

• G07C 5/00 - Enregistrement ou indication du fonctionnement de véhicules
• G07C 5/08 - Enregistrement ou indication de données de marche autres que le temps de circulation, de fonctionnement, d'arrêt ou d'attente, avec ou sans enregistrement des temps de circulation, de fonctionnement, d'arrêt ou d'attente
• B60W 40/02 - Calcul ou estimation des paramètres de fonctionnement pour les systèmes d'aide à la conduite de véhicules routiers qui ne sont pas liés à la commande d'un sous-ensemble particulier liés aux conditions ambiantes
• B60W 40/09 - Style ou comportement de conduite
• B60W 40/10 - Calcul ou estimation des paramètres de fonctionnement pour les systèmes d'aide à la conduite de véhicules routiers qui ne sont pas liés à la commande d'un sous-ensemble particulier liés au mouvement du véhicule
• G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projets; Planification d’entreprise ou d’organisation; Modélisation d’entreprise ou d’organisation

Abrégé

Proposed is an electronic, real-time maneuver detection system(1) for maneuver recognition of vehicles(41,...,45) based on dynamically measured telematics data (3), particularly based solely on the sensory data of smartphone (471,...,475) sensors, and more particularly based solely on measuring data from the accelerometer sensor (4011) and the global positioning system (GPS) sensor (4013) and/or the gyroscope sensor (4012) of a smartphone (471,...,475),and a method thereof. The axes of the smartphone (471,...,475) may be moving independently relative to the axes of the vehicle (41,...,45) and thus do not need to be aligned with the axes of the vehicle (41,...,45).Driver behaviors and operational parameters are automatically measured and discriminated by means of the system (1), based on automatically individuated and measured driver maneuvers (91) within various measured vehicle trajectories (9),and wherein an output signal is generated based upon derived risk measure parameters and/or crash attitude measure parameters. In particular, the telematics-based system (1) can be implemented as a system with score-driven, especially risk-score driven,operations associated with motor vehicles (41,...,45) or transportation means for passengers or goods,and reliant on a dynamic, telematics-based data aggregation and dynamically measured driving maneuvers (91), respectively.

Classes IPC  ?

• G07C 5/08 - Enregistrement ou indication de données de marche autres que le temps de circulation, de fonctionnement, d'arrêt ou d'attente, avec ou sans enregistrement des temps de circulation, de fonctionnement, d'arrêt ou d'attente
• G07C 5/00 - Enregistrement ou indication du fonctionnement de véhicules
• B60W 40/09 - Style ou comportement de conduite
• G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projets; Planification d’entreprise ou d’organisation; Modélisation d’entreprise ou d’organisation
• B60W 40/10 - Calcul ou estimation des paramètres de fonctionnement pour les systèmes d'aide à la conduite de véhicules routiers qui ne sont pas liés à la commande d'un sous-ensemble particulier liés au mouvement du véhicule
• B60W 40/02 - Calcul ou estimation des paramètres de fonctionnement pour les systèmes d'aide à la conduite de véhicules routiers qui ne sont pas liés à la commande d'un sous-ensemble particulier liés aux conditions ambiantes

Abrégé

Proposed is an adaptive, layered, automated risk-transfer system (1) and method thereof, with a self-optimizing, increased leveraged capacity and enhanced drop-down cover structure with a plurality of adjustable risk-transfer layers (721,...,72t). If a triggered risk-event (52) is assignable to either of the top risk-transfer layer (72t) or the bottom risk-transfer layer (721) of the drop-down cover structure, a shared exhaustion factor (54) is generated based on the assigned risk-transfer layer (721,72t) and based on a cover of the loss (53) associated with the triggered risk event (52). The shared exhaustion factor (54) is applied mutually to both layers by the system (1) eroding both layers by the same exhaustion factor (54). The top layer (72t) and the bottom layer (72t) are reinstatable by a corresponding generated normalized reinstatement parameter values normalized over both layers (721,72t) and based on a thus provided shared limit (75) and the erosion of the top layer (72t) and the bottom layer (72t).

Classes IPC  ?

• G06Q 40/08 - Assurance

Abrégé

Proposed is an adaptive capacity-based system (1) with an adaptable layered share-capacity structure and method thereof. The capacity-based systems (1) are based on adaptive layered shared-capacities structures with a shared multiple-unit basis performing automated counterbalancing of exposure related to actual occurences of measured trigger events. The system (1) provides further an event-driven trigger device with an optimized switching performance of the applied capacity layers allowing an optimized leveraging of the operated capacities increasing the leveraged capacity by means of a plurality of adjustable transfer layers (721,…,72t). If a measured trigger-event (52) is assignable to either of the top transfer layer (72t) or the bottom transfer layer (721) of a drop-down impact cover structure, a shared exhaustion factor (54) is generated based on the assigned transfer layer (721,72t) and based on a cover of the impact(53) associated with the measured trigger event (52). The shared exhaustion factor (54) is applied mutually to both layers by the system (1) eroding both layers by the same exhaustion factor (54). The top layer (72t) and the bottom layer (72t) are reinstatable by a corresponding generated normalized reinstatement parameter values normalized over both layers (721, 72t) and based on a thus provided shared limit (75) and the erosion of the top layer (72t) and the bottom layer (72t).

Classes IPC  ?

• G06Q 40/08 - Assurance

Abrégé

Proposed are a measuring apparatus(1) and a measuring method for automated traffic and driving pattern recognition and location-dependent measurement and forecast of absolute and relative risks for car accidents based on exclusively non-insurance related measuring data and based on automated traffic pattern recognition and associated with the traffic and driving pattern providing a high degree of temporal and spatial resolution. The proposed apparatus(1) provides a grid- based (2121, 2122, 2123, 2124), technically new way of automation of automated traffic and driving pattern recognition and risk-prediction related to motor accidents using environment based factors (elevation, road network, traffic data, weather conditions including socio-economic factors)that are impacting motor traffic and are location dependent received from appropriate measuring devices (41,…,45). In this way, predictions of the accident risk for arbitrary areas can be provided. The measuring apparatus(1) is calibrated by comparing features of areas or road segments with the number and type of accidents that have measured or registered there, linking the features and accident data e.g. using the disclosed machine learning techniques.

Classes IPC  ?

• G06Q 40/08 - Assurance

Abrégé

Proposed are a system (1) and a method for the determination and forecast of absolute and relative risks for car accidents based on exclusively non-insurance related measuring data and based on automated traffic pattern recognition, wherein data records of accident events are generated and location-dependent probability values for specific accident conditions associated with the risk of car accident are determined. Thus, the proposed system (1) provides a grid-based (2121, 2122, 2123, 2124), technically new way of automation of risk-prediction related to motor accidents using environment based factors (elevation, road network, traffic data, weather conditions) including socio-economic factors that are impacting motor traffic and are location dependent received from appropriate measuring devices and systems (41,...,45). In this way, predictions of the accident risk for arbitrary areas can be provided. The system is calibrated by comparing features of areas or road segments with the number and type of accidents that have measured or registered there, linking the features and accident data e.g. using the below discussed machine learning techniques.

Classes IPC  ?

• G06Q 40/08 - Assurance

Abrégé

Proposed are a fully or semi-automated, integrated learning,labeling and classification system (1) and method with closed, self-sustaining pattern recognition (111), labeling (101) and classification (121) operation, wherein unclassified data sets (21) are selected and converted to an assembly of graphic and text data forming compound data sets (22) that are to be classified. By means of feature vectors (53), which can be automatically generated,a machine learning classifier (12) is trained for improving the classification operation (121) of the automated system (1) during training as a measure of the classification performance (122) if the automated labeling and classification system (1) is applied to unlabeled and unclassified data sets (2), and wherein unclassified data sets (2) are classified (121) automatically by applying the machine learning classifier (12) of the system (1) to the compound data set (22) of the unclassified data sets (2).

Classes IPC  ?

• G06N 99/00 - Matière non prévue dans les autres groupes de la présente sous-classe

Abrégé

Proposed is a measuring and forecasting system providing early inter-arrival time identification and self-adaptive time interval measurements of emerging hazards having an occurrence rate with a complex clustering structure. The measuring system (1) comprises measuring stations or sensors (90, 91, 92,…/401,402,…,411,412) for measuring occurring risk-events (311,…,313) by measured sensory data (4011, 4012…). Further,the system (1) comprises a data transmission network (2) for transmitting the measured sensory data (911, 912, 913,…/4011, 4012,…) of the measuring devices (90, 91, 92,… / 401, 402,…,411, 412) to a central core circuit (10), the measured sensory data (911, 912, 913,…/4011, 4012,…) being assigned to a historic hazard set (31) comprising event parameters for each assigned risk-event. An event loss set (32) is generated by means of the system (1) based on the measured frequencies with associated severities (341,…,343) or as alternative measure with losses (321,…,323) of said risk-events (311,…,313) of the hazard set (31), each of said catastrophic events (311,…,313) creating a set specific severity(321,…,323/341,…,343). The system (1) uses constructed time-stamps (331,…,333) based on an automatically and/or dynamically estimated distribution (1011) of corresponding generated inter-arrival times parameters (1012/IAT). An inter-arrival times parameter (1012) captures a waiting time between consecutive events (311,…,313) of the period severity or loss set (35/33). The waiting times measure the time intervals between two successive measured occurrences of catastrophic events (311,…,313), the occurrence of catastrophic events (311,…,313) being trackable over time by means of the time intervals and the system (1), and automatically capturing peril specific temporal clustering (1031) and/or seasonal occurrence patterns (1032).

Classes IPC  ?

• G06Q 40/08 - Assurance
• G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projets; Planification d’entreprise ou d’organisation; Modélisation d’entreprise ou d’organisation

Abrégé

Proposed is an automated, inter-arrival-time-based system (1) for automated prediction and exposure-signaling of associated, catastrophic risk-event driven or triggered risk-transfer systems (11/12), and method thereof, for low frequency catastrophic or operational risk events (311,..., 313) and related automated risk-transfer. Occurring risk-events (311,..., 313) are measured and assigned to a historic hazard set (31) comprising event parameters for each assigned risk-event. Risk-exposed units (40, 41, 42,...) and/or the automated risk-transfer systems (11/12) are provided with corresponding risk-transfer parameters (501,..., 505/511,..., 515) for automated risk-transfer and/or automated risk-event cover by signal transfer of a central, core circuit (10). An event loss set (32) is generated by means of the system (1) based on the measured frequencies with associated losses (321,..., 323) of said risk-events (311,..., 313) of the hazard set (31), each of said risk-events (311,..., 313) creating a set specific loss (321,..., 323). The system (1) uses constructed time-stamps (331,..., 333) based on an automatically and/or dynamically estimated distribution (1011) of corresponding generated inter-arrival times parameters (1012/IAT). An inter-arrival times parameter (1012) captures a waiting time between consecutive events (311,..., 313) of the period loss set (33). The waiting times measure the time intervals between two successive measured occurrences of risk-events (311,..., 313), the occurrence of risk-events (311,..., 313) being trackable over time by means of the time intervals, and automatically capturing peril specific temporal clustering (1031) and/or seasonal occurrence patterns (1032).

Classes IPC  ?

• G06Q 40/08 - Assurance
• G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projets; Planification d’entreprise ou d’organisation; Modélisation d’entreprise ou d’organisation

Abrégé

Proposed is an automated telematics-based system (1) for score-driven operations associated with motor vehicles (41,..., 45) or transportation means of passengers or goods and based on a dynamic, telematics-based data aggregation, and method thereof, for automated risk-transfer related to complex peer-to-peer lending schemes, especially related to vehicles and car sharing schemes and sharing economy transportation schemes related to risks associated with damages to third parties. The telematics-based system (1) comprises telematics devices (411,..., 415) associated with the plurality of motor vehicles (41,..., 45), wherein the telematics devices (411,..., 415) comprise a wireless connection (42101-42108) to a central, expert-system- based circuit (11). The telematics devices (411,..., 415) are connected via interfaces (421,..., 425) to the sensors and/or measuring devices (401,..., 405) and/or an on-board diagnostic system (431,..., 435) and/or an in-car interactive device (441,..., 445), wherein the telematics devices (411,..., 415) capture usage-based (31) and/or user-based (32) and/or operational (33) telematics data (3) of the motor vehicle (41,..., 45) and/or user (321, 322, 323). In response to an emitted shadow request (109) individualized risk-transfer profiles (114) based upon the dynamically generated variable scoring parameters (1011,..., 1013) are transmitted from a first risk-transfer systems (11) to the corresponding motor vehicle (41,..., 45) and issued by means of a user unit (461,..., 465) of the motor vehicle (41,..., 45) for selection by the driver of the motor vehicles (41,..., 45). In return of issuing an individualized risk-transfer profile (114) over said user unit (461,..., 465), payment-transfer parameters are transmitted from the first risk-transfer system (11) to the provider of the telematics-based system (1).

Classes IPC  ?

• G06Q 40/08 - Assurance
• G06Q 50/30 - Transport; Communications
• G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projets; Planification d’entreprise ou d’organisation; Modélisation d’entreprise ou d’organisation
• G06Q 30/02 - Marketing; Estimation ou détermination des prix; Collecte de fonds

Abrégé

Proposed is a secure key management, peer-to-peer transmission system (6), and method thereof, based on a controlled, double-tier cryptographic key structure (2), providing a closed cryptosystem for secure content distribution and further processing within a provided, secured network environment (11). Individual, user- specific data (331) are captured by means of capturing device (33) associated with a user network node (3). Based on the individual, user-specific data (331), data services (101) are requested from and provided to the user network node (3), by means of a data consumer network node (4). The captured individual, user-specific data (331) are transmitted from the user network node (3) to a central P2P transmission system (1) and are processed by a non-storage-based processing unit (10), providing the requested data service (101) of the data consumer network node (4) requested by the user network node (3). A first cryptographic key (21) is generated by the non-storage-based processing unit (10), wherein service response data (211) of the requested service (101) are encrypted, by means of the first cryptographic key (21), to single encrypted service response data (212) and transmitted to the user network node (3), in response to the requested service (101). The received single encrypted service response data (212) are double encrypted, by means of a generated second cryptographic key (22), to double encrypted service response data (221) by the user network node (3) and transmitted back and stored in the central, P2P transmission system (1). The first cryptographic key (21) is transmitted and/or made accessible to the user network node (3), if predefined authorization-parameters (102) are triggered, by means of the central, P2P transmission system (1).

Classes IPC  ?

• H04L 29/06 - Commande de la communication; Traitement de la communication caractérisés par un protocole
• H04L 29/08 - Procédure de commande de la transmission, p.ex. procédure de commande du niveau de la liaison
• H04L 9/00 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité
• H04L 9/32 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
• G06Q 30/00 - Commerce

Abrégé

Proposed is an automated, self-adaptive, machine-learningtelematics- based system (1) for score-driven operations associated with motor vehicles (41,…,45) or transportation means of passengers or goods and based on a dynamic, telematics- based data aggregation, and method thereof, for automated risk-transfer related to complex peer-to-peer lending schemes, especially related to vehicles and car sharing schemes and sharing economy transportation schemes related to risks associated with damages to third parties. The telematics-based system (1) comprises telematics devices (411,…,415) associated with the plurality of motor vehicles (41,…,45), wherein the telematics devices (411,…,415) comprise a wireless connection (42101-42108) to a central, expert-system-based circuit (11). The telematics devices (411,…,415) are connected via interfaces (421,…,425) to the sensors and/or measuring devices (401, …, 405) and/or an on-board diagnostic system (431,…,435) and/or an in-car interactive device (441,…,445), wherein the telematics devices (411,…,415) capture usage-based (31) and/or user-based (32) and/or operational (33) telematics data (3) of the motor vehicle (41,…,45) and/or user (321, 322, 323). In response to an emitted shadow request (109) individualized risk-transfer profiles (114) based upon the dynamically generated variable scoring parameters (1011,…,1013) are transmitted from a first risk-transfer systems (11) to the corresponding motor vehicle (41,…,45) and issued by means of a user unit (461,…,465) of the motor vehicle (41,…,45) for selection by the driver of the motor vehicles (41,…,45). In return of issuing an individualized risk-transfer profile (114) over said user unit (461,…,465), payment-transfer parameters are transmitted from the first risk-transfer system (11) to the provider of the telematics-based system (1).

Classes IPC  ?

• G06Q 40/08 - Assurance
• G06Q 50/30 - Transport; Communications
• G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projets; Planification d’entreprise ou d’organisation; Modélisation d’entreprise ou d’organisation
• G06Q 30/02 - Marketing; Estimation ou détermination des prix; Collecte de fonds

Abrégé

Proposed is a secure key management, peer-to-peer transmission system (6), and method thereof, based on a controlled, double-tier cryptographic key structure (2), providing a closed cryptosystem for secure content distribution and further processing within a provided, secured network environment (11). Individual, user-specific data (331) are captured by means of capturing device (33) associated with a user network node (3). Based on the individual, user-specific data (331), data services (101) are requested from and provided to the user network node (3), by means of a data consumer network node (4).The captured individual, user-specific data (331) are transmitted from the user network node (3) to a central, P2P transmission system (1) and are processed by a non-storage-based processing unit (10), providing the requested data service (101) of the data consumer network node (4) requested by the user network node (3). A first cryptographic key (21) is generated by the non-storage-based processing unit (10), wherein service response data (211) of the requested service (101) are encrypted, by means of the first cryptographic key (21), to single encrypted service response data (212) and transmitted to the user network node (3), in response to the requested service (101). The received single encrypted service response data (212) are double encrypted, by means of a generated second cryptographic key (22), to double encrypted service response data (221) by the user network node (3) and transmitted back and stored in the central, P2P transmission system (1). The first cryptographic key (21) is transmitted and/or made accessible to the user network node (3), if predefined authorization-parameters (102) are triggered, by means of the central, P2P transmission system (1).

Classes IPC  ?

• H04L 29/06 - Commande de la communication; Traitement de la communication caractérisés par un protocole
• H04L 29/08 - Procédure de commande de la transmission, p.ex. procédure de commande du niveau de la liaison
• H04L 9/00 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité
• H04L 9/32 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
• G06Q 30/00 - Commerce

Abrégé

Proposed is a intelligent, automotive, OEM-linked telematics system (1) dynamically triggering and selt-actingly steering automated, self-sufficient operated, automotive systems (11/12) based on real-time capturing of vehicle telematics data for score-driven operations based on scaled, real-time risk-measuremenfs associated with a plurality of motor vehicles (41 45), the felematics-based system (1) comprising vehicle embedded telematics devices (411,...,415) associated with a plurality of interfaces (421,....., 425) to sensors and/or measuring devices (401 405) and/or an on board diagnostic system capturing usage-based (31) and/or user-based (32) and/or operational (33) real-time telematics data (3) of the motor vehicle (41 45) and/or user (321, 322, 323), wherein a data link (21) is set by means of at least one wireless connection (4210) between an intelligent, central circuit (10) transmitting dynamically the captured usage-based (31) and/or user-based (32) and/or operational (33) telematics data (3) from the vehicle embedded telematics devices (411,415) to the central, intelligent circuit (10), and wherein the automotive telematics system (1) generates and transfers corresponding electronic signaling to the automated automotive systems (11/12) dynamically controlling and selt-actingly steering the operation of the automated automotive systems (11/12).

Classes IPC  ?

• G06Q 40/08 - Assurance

Abrégé

Proposed is an OEM-linked, telematics-based system and platform (1) for score-driven operations associated with motor vehicles (41,…,45) or transportation means of passengers or goods and based on a dynamic, telematics-based data aggregation, and method thereof. The telematics-based system (1) comprises vehicle-embedded telematics devices (OEM line fitted)(411,…,415) associated with the plurality of motor vehicles (41,…,45), wherein the vehicle-embedded telematics devices (OEM line fitted) (411,…,415) comprise a wireless connection (42101-42108) to a central, expert system-based circuit (11). The telematics devices (411,…,415) are connected via interfaces (421,…,425) to the sensors and/or measuring devices (401, …, 405) and/or an on-board diagnostic system (431,…,435) and/or an in-car interactive device (441,…,445), wherein the telematics devices (411,…,415) capture usage-based (31) and/or user-based (32) and/or operational (33) telematics data (3) of the motor vehicle (41,…,45) and/or user (321, 322, 323). In response to an emitted shadow request (109) of a central, expert system-based circuit (10) of the system (1) associated with a second risk transfer system, individualized risk transfer profiles (114) based upon the dynamically-generated variable scoring parameters (1011,…,1013) are transmitted from a first risk transfer system(11) to the corresponding motor vehicle (41,…,45) and issued by means of a dashboard (461,…,465) of the motor vehicle (41,…,45) for selection by the driver of the motor vehicles (41,…,45). In return for issuing an individualized risk transfer profile (114) over said dashboard (461,…,465), payment transfer parameters are transmitted from the first risk transfer system (11) to the OEM of the OEM-linked, telematics-based system and platform (1).

Classes IPC  ?

• G06Q 40/08 - Assurance

Abrégé

Proposed is an intelligent, self-adaptivemobile automotive car system (1), and method thereof, for a dynamic, telematics-based risk-measurement and a dynamic connection search engine and telematics data aggregator, wherein risk- transfer profiles (124) are captured and categorized in a resultslist (118) from a plurality of first risk-transfer systems (12) based on dynamically generated driving score parameters (10131/1111,...,1117) by means of appropriately triggered automotive data (3). For the self-adaptive, real-time risk measurements, telematics data-based triggers (1012)are dynamically applied based on self-learning structures of an intelligent central automotive circuit (11) triggering, capturing, and monitoring operating parameters (40121) and/or environmental parameters (40111) during operation of the motor vehicle (41,...,45). By means of a driving score generator (111/1013) of thecentral automotive circuit (11) a single or compound of variable scoring parameters (1111,...,1117/10131) are measured providing physical risk measures of use and/or style and/or environmental condition of driving during operation of the motor vehicle (41,...,45) based on the triggered, captured, and monitored operating parameters (40121) and/or environmental parameters (40111).

Classes IPC  ?

• G06Q 40/08 - Assurance

Abrégé

Proposed is a mobile automotive car system (1), and method thereof, for a dynamic, telematics-based connection search engine and telematics data aggregator, wherein risk-transfer profiles (124) are captured and categorized in a results list (118) from a plurality of first risk-transfer systems (12) based on dynamically generated driving score parameters (10131 /1111..... 1117) by means of appropriately triggered automotive data (3). As a variant, during a predefined trial period (e.g. 1 -2 months), the automotive and driving behavior data (3) can be collected, which are transmitted together with the generated driving score parameters (10131 /1111..... 1117) to multiple automated first risk-transfer systems (12) for quotation. The user is able to dynamically select the best-fitting first risk-transfer system (12) for risk-transfer by means of the results list (118), which is provided and updated in real-time for display to and selection by a user of a mobile telecommunication apparatus (10) by means of a mobile telematics application (101) of the mobile telecommunications apparatus (10).

Classes IPC  ?

• G06Q 40/08 - Assurance

Abrégé

Proposed are an automated, distinct triage or channel-based (81,82,83) automated mortality classification and measuring system (1) and a method for the automated assessment, measurement, and monitoring of life risks (9), wherein life risks associated with risk-exposed individuals (91, 92, 93) are transferable to a first insurance system (2) and/or from the first insurance system (2) to an associated second insurance system (3). The system (1) comprises a table (10) with retrievable stored risk classes (101, 102, 103) each comprising assigned, triggerable risk class criteria (110, 111, 112). Individual-specific parameters (911, 921, 931) of the risk-exposed individuals (91, 92, 93) are captured relating to criteria (110, 111, 112) of the stored risk classes (101, 102, 103) and a specific risk class (101, 102, 103) associated with the risk of the exposed individual (31, 32, 33) is identified and selected from said stored risk classes (101, 102, 103) based on the captured parameters (311, 321, 331). The individual-specific parameters (911, 921, 931) comprise at least parameters indicating a captured self-declaration of smoking or non-smoking. Upon triggering (71 /711) parameters (916, 926, 936) indicating a captured self-declaration of smoking (8111, 8112, 8113), the risk-exposed individual (91, 92, 93) is automatically assigned to a first triage channel (81). However, upon triggering (71 /712) of a captured self-declaration of non-smoking, the triggered individual-specific parameters (911, 921, 931) are processed by a machine learning- based pattern recognition module (8) automatically assigning risk-exposed individuals (91, 92, 93) with detected non-smoking patterns (8211, 8212, 8213) to a second triage channel (82) as predicted non-smokers, and automatically assigning risk-exposed individuals (91, 92, 93) with detected smoking patterns (8311, 8312, 8313) to a third triage channel (83) as predicted smokers. For risk-exposed individuals (91, 92, 93) in the third triage channel (83), laboratory-scaled individual-specific parameters (915, 925, 935) are measured by means of laboratory measuring devices (914, 924, 934), and the laboratory-scaled individual-specific parameters (915, 925, 935) are triggered for measured smoking and not-measured smoking.

Classes IPC  ?

• G06Q 40/08 - Assurance

Abrégé

Proposed is an automotive car system (1), and method thereof, associated with a plurality of autonomous or partially autonomous driving motor vehicles (41,...,45). The autonomous or partially autonomous motor vehicles (41,...,45) comprise exteroceptive sensors (4011) for sensing environmental parameters (40111), and proprioceptive sensors (4012) for sensing operating parameters of the motor vehicles (41,...,45). The motor vehicles (41,...,45) further comprise an autonomous or partially autonomous driving control system (461 465) interpreting the sensory data (40111 /40121) of the exteroceptive and proprioceptive sensors (4011 /4012) and identifying appropriate navigation paths and/or obstacles and/or relevant signage. The motor vehicles (41,...,45) or the automotive control systems (461 465) are connected to a central, expert-system based circuit (11) by means of a data link (21) transmitting at least usage-based (31) and/or user-based (32) and/or operating (33) automotive data (3) to the central, expert-system based circuit (11), and wherein the usage-based (31) and/or user-based (32) and/or operational (33) automotive data (3) are based on the sensory data (40111 /40121) and/or operating parameters (4611) of the automotive control system (461,...,465). The automotive car system (1) provides an automated first and/or second risk-transfer based on dynamic generated first and/or second risk transfer parameters (501,..., 505/1021,...,1025) from the motor vehicles (41,...,45), wherein by means of the central, expert-system based circuit (11) the first and/or second risk transfer parameters (501,...,505/1021,...,1025) and correlated first and/or second payment transfer parameters (1021,...,1025/1221,...,1225) are dynamically generated, adapted and/or optimized, wherein, in the case of triggering the occurrence of one of defined risk events (61 63), the occurred loss (71,..., 75) is automatically covered by the automotive car system (1).

Classes IPC  ?

• G08G 1/01 - Détection du mouvement du trafic pour le comptage ou la commande
• G06Q 40/08 - Assurance

Abrégé

Disclosed is a dynamically triggered risk-transfer system based on an automatically steered, floating recoverable basis. The system triggers coupled first and second insurance systems providing self-sufficient risk protection for a variable number of defined risk exposure components. The trigger system comprises an aggregation module for automatically aggregating captured loss parameters of the measured occurrence of risk events over all risk exposure components within a predefined time period by incrementing an associated stored aggregated loss parameter and for automatically aggregating the received and stored first payment parameters overall risk exposure components within the predefined time period by incrementing an associated stored, aggregated payment parameter, and wherein the variable loss ratio parameter is generated dynamically based upon the ratio of the aggregated loss parameter and the aggregated payment parameter. When the variable loss ratio parameter exceeds a threshold value, a second trigger module is activated, wherein a floating activation value is dynamically set to the value of the variable loss ratio. The floating activation value is triggered by means of an adjustable minimum activation threshold trigger.

Classes IPC  ?

• G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projets; Planification d’entreprise ou d’organisation; Modélisation d’entreprise ou d’organisation
• G06Q 40/08 - Assurance

Abrégé

Proposed is a machine-learning based telematics system 1, and method thereof, with mobile telematics devices (401,...,405) associated with a plurality of motor vehicles (41,...,45). The telematics devices (401,...,405) comprise wireless connections (411,...,415) to a data transmission network (2), and interfaces (421,...,425) to an on-board diagnostic system (431,...,435) or in-car interactive device (441,...,445) or cellular mobile node application (451,...,455). The telematics devices (401,...,405) capture usage-based (31) and/or user-based (32) telematics data (3) of the motor vehicle (41,...,45) and transmit them via a data transmission network (2) to a machine-learning based telematics circuit (11). The machine-learning based circuit (11) generates first risk transfer parameters (501,...,505) and correlated first payment transfer parameters (1021,...,1025) and transmits them to a first risk-transfer system (10), wherein, in the case of triggering the occurrence of a predefined risk events (61,..., 63), the occurred loss (71,.... 75) is automatically covered by the first risk-transfer system (10) based on the first risk transfer parameters (501,..., 505) and correlated first payment transfer parameters (1021,...,1025). Second risk transfer parameters (51 1,..., 515) and correlated second payment transfer parameters (1221,...,1225) are generated by means of the machine-learning based telematics circuit (11) and transmitted to the second risk-transfer system (12), wherein the occurred loss (71,..., 75) is at least partly covered by the second insurance system (12) based on the second risk transfer parameters (511,..., 515) and correlated second payment transfer parameters (1221,...,1225). The first and second risk transfer parameters (501,..., 505/511,..., 515) and the correlated first and second payment transfer parameters (1021,...,1025/1221,...,1225) are mutually adapted and/or optimized by means of the machine-learning based telematics circuit (11) based on the captured usage-based (31) and/or user-based (32) telematics data (3).

Classes IPC  ?

• G06Q 40/08 - Assurance
• B60W 40/00 - Calcul ou estimation des paramètres de fonctionnement pour les systèmes d'aide à la conduite de véhicules routiers qui ne sont pas liés à la commande d'un sous-ensemble particulier
• G07C 5/00 - Enregistrement ou indication du fonctionnement de véhicules

Abrégé

The invention relates to an automated flight trajectory prediction system (1) and flight trajectory-borne automated delay risk-transfer system (1) related to airspace risks for risk sharing of a variable number of risk-exposed units (41,..., 43) by dynamically pooling and balancing resources of the risk-exposed units (41,...,43) based on predicted flight trajectories. The system (1) provides a self-sufficient operatable and dynamically self-adaptable risk-transfer system (1) based on the balanced, pooled resources (11) for the risk-exposed units (41,...,43), wherein an automated transfer of risk exposure associated with the units (41,...,43) is provided by the system (1). The system (1) comprises capturing means (31) to receive transmitted air data parameters (102, 202) of aircraft ground-based flight controllers (911,...,914/921,...,924). A trigger module (3) is dynamically triggering filtered flight time parameters (1231, 1232,...) via a data flow pathway of the controllers (911,..., 914/921,...,924) by means of a predefined time-delay threshold value, wherein in case of triggering of an excess of the design time-delay threshold value, operational parameters of the triggered flight (1221, 1222,...) comprising at least flight delay parameters (1322) and flight identification (1321) are captured and losses associated with the triggered time delay are distinctly covered by the system (1) by means of parametric payment transfer. For the prediction of the flight trajectories, the system dynamically generates a 3D grid network providing digitized airspace, where each grid point is a location of weather measure parameters, and generates cubes around these grid points, so the entire airspace is represented by a dynamically generated set of cubes, wherein each cube is defined by its centroid, the original grid point, and associated weather measuring parameters remaining homogeneous within the generated cube during a predefined period of time. The core engine (2) aligns generated raw trajectories to said set of cube centroids as fixed 3D positions independent of trajectory data, wherein form trajectories are generated as 4D joint cubes, and wherein each cube is a segment that is associated with not only spatio-temporal attributes and with the weather measuring parameters.

Classes IPC  ?

• G06Q 30/02 - Marketing; Estimation ou détermination des prix; Collecte de fonds
• G06Q 40/08 - Assurance

Abrégé

The invention relates to an automated, reactive flight delay risk-transfer system (1) and method thereof related to airspace risks for risk sharing of a variable number of risk-exposed units (41,..., 43) by pooling resources of the risk-exposed units (41,..., 43) and by providing a self-sufficient risk-transfer system (1) based on the pooled resources (11) for the risk-exposed units (41,..., 43) by means of a resource-pooling system (11) associated with the risk-transfer system (1), wherein an automated transfer of risk exposure associated with the units (41,..., 43) is provided by the automated flight delay insurance system (1). The system (1) comprises capturing means (31) to receive transmitted air data parameters (102, 202) of aircraft ground-based flight controllers (911,..., 914/921,..., 924). A trigger module (3) is dynamically triggering filtered flight time parameters (1231, 1232,...) via a data flow pathway of the controllers (911,..., 914/921,..., 924) by means of a predefined time-delay threshold value, wherein in case of triggering of an excess of the design time-delay threshold value, operational parameters of the triggered flight (1221, 1222,...) comprising at least flight delay parameters (1322) and flight identification (1321 ) are captured and losses associated with the triggered time delay are distinctly covered by the system (1) by means of parametric payment transfer.

Classes IPC  ?

• G06Q 30/02 - Marketing; Estimation ou détermination des prix; Collecte de fonds
• G06Q 40/08 - Assurance

Abrégé

Proposed is a patient data-driven insurance system for multi-pillar triggered risk transfer associated with prolonged independent living under elderly illness occurrence by providing a dynamic self-sufficient risk protection for a variable number risk exposure components (21, 22, 23,...) by means of a resource pooling system (1). The system (1) generates a multi-dimensional trigger-table (7) comprising a multi-layered data structure with predefined searchable elderly illness (71,..., 75) parameters for triggering, by means of elderly illness triggers (31,..., 35) in the patient dataflow pathway (213, 223, 233), the predefined parameters of a first-layer data structure (71) providing measuring parameters for the occurrence of serious elderly illnesses, and the predefined parameters of a second-layer data structure (72) providing measuring parameters for the occurrence of an acute broken bone trauma, and the predefined parameters of a third-layer data structure (73) providing measuring parameters for long-term care indications, and the predefined parameters of a fourth-layer data structure (74) providing measuring parameters for assisted living indications, and the predefined parameters of a fifth-layer data structure (75) providing measuring parameters for extended assistance indications. The insurance system (1) comprises elderly illness triggers (31,..., 35) triggering measuring values in patient dataflow pathways (213, 223, 233) of the connected risk exposure components (21, 22, 23,...). If an occurrence of an elderly illness (71,..., 73) is triggered by exceeding one of the predefined searchable elderly illness (71,..., 75) parameters, a corresponding trigger-flag is set and a parametric transfer of payments is assigned to that trigger-flag, wherein a loss associated with the acute or chronic elderly illness (71,..., 75) is covered separately by the insurance system (1) based on the respective trigger-flag and based on the received and stored payment parameters (214, 224, 234) from risk exposure components (21, 22, 23) by at least one parametric payment transfer to the risk exposure component (21, 22, 23,...), i.e., the insured elderly person.

Classes IPC  ?

• G06Q 40/08 - Assurance
• G06Q 50/22 - Aide sociale

Abrégé

Proposed are a digital key management system (1) and a method based on layered, two-tier double cryptographic keys (2) providing a closed cryptosystem for secure content distribution within a secured network environment (11). A first-tier cryptographic key (21) is generated and made public accessible within a first secured walled region (111), wherein the first secured walled region (111) is accessible to supply network nodes (3) registered to a first authentication database (121) associated with an access server (12) of the digital key management system (1). With the first-tier cryptographic key (21) the supply network nodes (3) access and decrypt first content (211). With a second-tier cryptographic key (22), the digital key management system (1) encrypts a second content (221) generating encrypted second content (222), wherein the second-tier cryptographic key (22) is accesses and decrypted by the supply network node (3) accessing the secured second walled region (112).

Classes IPC  ?

• H04L 9/08 - Répartition de clés
• H04L 29/06 - Commande de la communication; Traitement de la communication caractérisés par un protocole

Abrégé

Proposed are an automated, distinct-channel-based automated mortality classification system and a method for the automated assessment, measurement, and monitoring of preferred life risks, wherein life-risks associated with risk exposed individuals (31, 32, 33) are transferable to a first insurance system (2) and/or from the first insurance system (2) to an associated second insurance system (3). The system (1) comprises a table (10) with retrievable stored risk classes (101, 102, 103) each comprising assigned, triggerable risk class criteria (110, 111, 112). Individual-specific parameters (311, 321, 331) of the risk exposed individuals (31, 32, 33) are captured relating to criteria (110, 111, 112) of the stored risk classes (101, 102, 103) and a specific risk class (101, 102, 103) associated with the risk of the exposed individual (31, 32, 33) is identified out and selected of said stored risk classes (101, 102, 103) based on the captured parameters (311, 321, 331). The system (1) comprises a selectable first channel (21) providing a possible movement of specific single or select combination impairment risks not matching any class criteria to an accepted risk class, a selectable second channel (22) providing the movement of risks between different categorizations, thereby dynamically reclassify risks on a mortality consistent basis, and a selectable third channel (23) providing automated assessment of a risk decline.

Classes IPC  ?

• G06Q 40/08 - Assurance

Abrégé

Proposed area system and a method for a convertibly triggered insurance system (1)providing self-sufficient risk protection for a variable number of defined risk exposure components (21, 22, 23). The convertibly triggered system (1) comprises a first layer trigger structure (71) comprising an aggregation module (5) for aggregating captured loss parameters (92) over all risk exposure components (21, 22, 23) and all occurrences of risk events (501) within a predefined time period (713) by incrementing an associated stored aggregated loss parameter (93). When the aggregated loss parameter (93) exceeding a defined stop loss threshold value (712) is triggered via the first layer trigger structure (71), the occurred loss (92) exceeding the defined stop threshold value (712) is automatically covered by a second insurance system (10) based on the equitable, mutually aligned second risk transfer parameters (504). The system (1) comprises an intermediate layer trigger structure (73) with an associated switching device (3), wherein by triggering the aggregated loss parameter (93) exceeding said defined stop threshold value (712) by means of the first trigger module (711), a second layer trigger structure (72) is activated. The second layer trigger structure (72) comprises a second trigger module (721), wherein if the second layer trigger structure (72) is activated via the switching device (3)by triggering loss parameters (92) measuring the loss at the risk exposure components (21, 22, 23)not to be transmitted to the convertibly triggered system (1) within the predefined time period and falling outside a retention threshold value (722) of the first insurance system (10), the occurred loss exceeding said retention threshold value (722) is automatically covered by the second insurance system (12)based on the equitable, mutually aligned second risk transfer parameters (504).

Classes IPC  ?

• G06Q 40/08 - Assurance
• G06Q 10/10 - Bureautique; Gestion du temps

Abrégé

Proposed is an operationally independent clash loss event triggering risk transfer system(1) and a method for risk sharing for a variable number of risk exposure components (21, 22, 23) through the provision of independent risk protection for the risk exposure components by means of a risk transfer structure, which captures risk transfers of the exposure to multiple retentions of the components that may occur when two or more of the associated risk exposure components (21, 22, 23) suffer a loss from the occurrence of the same risk event. The automated switching (11) captures the covers of the additional retentions. The system (1) is capable of triggering and handling, by means of its risk transfer structure, clash loss events simultaneously impacting various layers an/or segements of the risk transfer structure. In particular, the invention relates to an event-driven switching device (11) for the complementary switching of two coupled, autonomously operated resource-pooling systems, where the operation of the systems remains stable under particularly large losses triggered by the same measurement of a risk event.

Classes IPC  ?

• G06Q 40/00 - Finance; Assurance; Stratégies fiscales; Traitement des impôts sur les sociétés ou sur le revenu

Abrégé

Proposed is a pattern-recognition-based control and monitoring system (10) for automated underwriting systems (20, 21), or automated data capturing systems, or automated data surveillance systems, in particular network surveillance systems, and a method thereof. The underwriting workflow of the underwriting system (20, 21) is monitored by capturing underwriting objects (71, 72, 73) in the underwriting process flow (19) and/or by forming a source of pooled underwriting objects (71,72,73), and by activating additional process states (1911, 1912, 1913), when non-conforming underwriting workflow objects (71, 72, 73) are triggered within the underwriting process flow (19). A recognition block-map (111) comprising a plurality of block elements (1112, 1113, 1114) is generated and captured by means of a first searchable datastructure (112) of a first database (11), and a plurality of historical underwriting workflow objects (1211, 1212) is captured by means of a second searchable datastructure (121) of a second database (12). Underwriting objects (71, 72, 73) are captured, wherein the captured workflow objects (71, 72, 73) are scanned for block elements (1112, 1113, 1114) of the stored recognition block-map (111). Based on the filtered block elements of the captured workflow object (71, 72, 73), a proximity factor with regard to each of the stored workflow objects (1211, 1212) of the second database (12) is determined. A conformity index value is triggered by the workflow objects of the second database (12) within a predefined range of the proximity factor, and the additional process states are triggered and assigned to the process flow (19) by means of a process management engine (13) of the measurement and monitoring system (10), when the measurement that is taken of the conformity index exceeds a risk threshold value (141).

Classes IPC  ?

• G06Q 10/10 - Bureautique; Gestion du temps
• G06Q 40/08 - Assurance

Abrégé

Proposed are a computer-based disaster management and management forecast system (1) and method for forecasting the impact of disaster mitigation and financing means (30) based on location-dependent natural disaster impacts, wherein measuring parameters of historical disaster events are captured in order to determine the impact of natural disaster events and critical values of parameters of natural disaster events are triggered to generate forecasts of the impacts of disaster events within a geographic area (501,..., 531). Country-specific parameters (1211, 1212, 1213) are captured, relating to stored predefined criteria (1221, 1222, 1223). Disaster event types (101) are assigned to a disaster history table (10), wherein each disaster event type (101) comprises a plurality of type-specific measuring parameters of historical natural disaster events and type-specific loss frequency function parameters (102) that provide a corresponding loss frequency function (103). Risk mapping parameters (201) for capturing a geographic risk map (20) are stored defining danger zones for the specific natural disaster event type (101). A selectable disaster financing means (30) is assigned to a definable cost factor (301, 302, 303) capturing the capital cost of the disaster financing means (30) in relation to its application for disaster mitigation, wherein a variable budgetary share factor (411, 412, 413) can be allocated and adapted, thus defining a coverage structure (401) in case of a catastrophic disaster event. Finally, expected catastrophe losses are determined by means of the loss frequency function (103) and the geographic risk map (20) for various scenarios of occurring natural disaster event types (101) and a forecast of the effect of the disaster financing means (30) is prepared based on the coverage structure (401), the assigned cost factors (301), and the determined expected catastrophe losses.

Classes IPC  ?

• G06Q 40/00 - Finance; Assurance; Stratégies fiscales; Traitement des impôts sur les sociétés ou sur le revenu

Abrégé

Proposed are a system and a method for the automated measurement, accumulation and monitoring of diverging cyber risks, wherein risk components (21, 22, 23,...) are exposed by electronic means (213, 223, 233) of the risk components (21, 22, 23,...) to a plurality of cyber risks (51, 52, 53, 54). An accumulation device (5) is used for the segmentation of the total cyber risk (50) of a risk component (21, 22, 23,...) by means of parametrizable risk exposure segments, and wherein, in a searchable trigger table (7), retrievably stored segmentation parameters (721, 722, 723, 724) are associated with corresponding measuring parameters (71 1, 712, 713, 714) for capturing the risk exposure of a specific risk exposure segment. The system comprises a trigger module (3) that is connected to the risk components (21, 22, 23,...) by means of capturing devices (31, 32, 33) in order to dynamically detect and capture measuring values for the measuring parameters (71 1, 712, 713, 714) related to the occurrence of cyber risk events within the data pathway of said electronic means (213, 223, 233). By means of the accumulation device (5), the total risk (50) is accumulated, segmentation by segmentation, by sequentially selecting the segmentation parameters (721, 722, 723, 724) from the trigger table (7) and retrieving the associated measuring parameters (71 1, 712, 713, 714) for each of the segmentation parameters (721, 722, 723, 724), and then triggering the trigger module (3) based on the retrieved measuring parameters to capture measuring values for the retrieved measuring parameters (71 1, 712, 713, 714) from the risk components (21, 22, 23,...) by means of the capturing devices (31, 32, 33).

Classes IPC  ?

• G06F 21/55 - Détection d’intrusion locale ou mise en œuvre de contre-mesures
• G06Q 20/08 - Architectures de paiement

Abrégé

Proposed are a system (1) and a method for an event-triggered switching device (11) envisioned for the complementary switching of two coupled insurance systems by providing self-sufficient risk protection of a variable number of risk exposure components (21, 22, 23) by means of two resource-pooling systems (10, 12) associated with the insurance systems, and wherein data structures (711, 712, 713) for storing a plurality of variable risk transfer segments (721, 722, 723) are provided by means of a segmentation table (7) of the switching device (11), and wherein an adaptable risk transfer function (73) is generated based on the structure (74) of the plurality of variable risk transfer segments (721, 722, 723). A payment parameter (731, 732, 733) is assigned to each variable risk transfer segment (721, 722, 723) of the segmentation table (7),and, upon triggering the total payment sum of the payment parameters (73, 732, 733) at the second payment-transfer module (42), the risk exposure of the first insurance system (10) associated with the variable risk transfer segments (721, 722, 723) of the top- down table (7) is transferred to the second insurance system (12). When the occurrence of a risk event is detected by means of event-driven triggers (31, 32) in the data flow pathway (213, 223, 233) of measuring devices (215, 225, 235), the corresponding variable risk segment (721, 722, 723) is determined within the segmentation table (7) and an activation signal is generated based on the corresponding risk transfer function (73), wherein the complementary activation of the first and second resource-pooling systems (10, 12) is triggered by means of the generated activation signal, and risk protection for the risk exposure components (21, 22, 23) is provided based on the transferred activation signal by means of the first and/or second resource pooling system (10, 12).

Classes IPC  ?

• G06Q 40/08 - Assurance
• G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projets; Planification d’entreprise ou d’organisation; Modélisation d’entreprise ou d’organisation

Abrégé

Proposed are a parametric, event-driven critical illness insurance system based on a resource-pooling system (1) and method for risk sharing of critical illness risks associated with elderly persons by providing a dynamic self-sufficient risk protection for a variable number of risk exposure components (21, 22, 23) by means of the resource-pooling system (1). The resource-pooling system (1) comprises an assembly module (5) to process risk-related component data (211, 221, 231) and to provide the likelihood (212, 222, 232) of said risk exposure for one or a plurality of the pooled risk exposure components (21, 22, 23,...) based on the risk-related component data (211, 221, 231). The risk exposure components (21, 22, 23) are connected to the resource-pooling system (1) for the pooling of their risks and resources, and wherein the resource-pooling system (1) comprises an multiple event-driven core-engine (3) with critical illness triggers (31, 32, 33) triggering in a patient dataflow pathway (213, 223, 233) to provide risk protection for a specific risk exposure component (21, 22, 23) for the occurrence of acute and/or chronic critical illnesses, as e.g. dementia and/or heart attack. The operation of the resource pooling system (1) is further supported by a parametric multi-trigger stage risk-cover.

Classes IPC  ?

• G06Q 40/00 - Finance; Assurance; Stratégies fiscales; Traitement des impôts sur les sociétés ou sur le revenu

Abrégé

Proposed area parametric, event-driven critical illness insurance system based on a resource-pooling system (1) and method for risk sharing of critical illness risks of a variable number of risk exposure components (21, 22, 23) by providing a dynamic self-sufficient risk protection for the risk exposure components (21, 22, 23) by means of the resource-pooling system (1). The resource-pooling system (1) comprises an assembly module (5) to process risk-related component data (211, 221, 231) and to provide the likelihood (212, 222, 232) of said risk exposure for one or a plurality of the pooled risk exposure components (21, 22, 23, …) based on the risk-related component data (211, 221, 231). The risk exposure components (21, 22, 23) are connected to the resource-pooling system (1) for the pooling of their risks and resources, and wherein the resource-pooling system (1) comprises an event-driven core-engine (3) with critical illness triggers (31, 32, 33) triggering in a patient data flow pathway (213, 223, 233) to provide risk protection for a specific risk exposure component (21, 22, 23). The operation of the resource pooling system (1) is supported by a parametric draw-down risk-cover which can additionally be related to multiple occurrences of critical illness parameters 71,72,73 triggered in the related patient data flow pathway (213, 223, 233).

Classes IPC  ?

• G06Q 40/00 - Finance; Assurance; Stratégies fiscales; Traitement des impôts sur les sociétés ou sur le revenu

Abrégé

Proposed are a parametric, event-driven critical illness insurance system based on a resource-pooling system (1) and method for risk sharing of critical illness risks of a variable number of risk exposure components (21, 22, 23) by providing a dynamic self-sufficient risk protection for the risk exposure components (21, 22, 23) by means of the resource-pooling system (1). The resource-pooling system (1) comprises an assembly module (5) to process risk-related component data (211, 221, 231) and to provide the likelihood (212, 222, 232) of said risk exposure for one or a plurality of the pooled risk exposure components (21, 22, 23,...) based on the risk-related component data (211, 221, 231 ). The risk exposure components (21, 22, 23) are connected to the resource-pooling system (1 ) for the pooling of their risks and resources, and wherein the resource-pooling system (1 ) comprises an multiple event-driven core-engine (3) with critical illness triggers (31, 32, 33) triggering in a patient dataflow pathway (213, 223, 233) to provide risk protection for a specific risk exposure component (21, 22, 23). The operation of the resource pooling system (1) is further supported by a parametric risk-cover related to multiple occurrences of critical illness parameters 71, 72, 73 triggered in the related patient data flow pathway (213, 223, 233).

Classes IPC  ?

• G06Q 40/00 - Finance; Assurance; Stratégies fiscales; Traitement des impôts sur les sociétés ou sur le revenu

Abrégé

Proposed is a control device (10) and method for state-transition-based processing of objects following a state-structured process flow (12) with a plurality of process states (121,122,123),wherein for each process state (121, 122, 123), one or more tasks (131) are selected in order to process the transition of the selected object (71,72,73) from one process state (121,122,123) to the subsequent process state (121,122,123). State parameters of the selected object (71,72,73) are captured by capturing means (151,152,153,154), wherein the current process state (121,122,123) of the object (71,72,73) is determined based on the captured state parameters. The tasks (131) are generated by the control system (10) activatable for a specific process state (121,122,123) in dependence on assigned task parameters of a process task (131). Operating tags (132) are expendably assigned to a process task (131), the operating tags (132) comprising dynamically alterable operating parameters adding operational constraints to the processing of the process task (131) by the control system (10), wherein the state-structured process flow (12) is dynamically generated and processed by triggering defined threshold and/or trigger values and/or steering the processing of the process tasks (131) based on the operating parameters of the operating-tags (132).

Classes IPC  ?

• G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projets; Planification d’entreprise ou d’organisation; Modélisation d’entreprise ou d’organisation

Abrégé

Proposed is a control device (10) and method for state-transition-based processing of objects following a state-structured process flow (12) with a plurality of process states (121, 122, 123), wherein for each process state (121, 122, 123), one or more tasks (131) are selected in order to process the transition of the selected object (71, 72, 73) from one process state (121, 122, 123) to the subsequent process state (121, 122, 123). State parameters of the selected object (71, 72, 73) are captured by capturing means (151, 152, 153, 154), wherein the current process state (121, 122, 123) of the object (71, 72, 73) is determined based on the captured state parameters. The tasks (131) are generated by means of the control system (10) activatable for a specific process state (121, 122, 123) in dependence on assigned task parameters of a process task (131). Operating tags (132) are expendably assigned to a process task (131) by means of an assigner unit (31,...., 34) or assignee unit (41,...., 44), the operating tags (132) comprising dynamically alterable operating parameters adding operational constraints to the processing of the process task (131) by the control system (10). The state-structured process flow (12) is dynamically generated and processed by triggering defined threshold and/or trigger values and/or steering the processing of the process tasks (131) based on the operating parameters of the operating-tags (132).

Classes IPC  ?

• G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projets; Planification d’entreprise ou d’organisation; Modélisation d’entreprise ou d’organisation

Abrégé

The invention relates to an avionic system (1) for emergency interception preventing imminent grounding or damages of aircraft fleets (81,…,84) following natural disaster events or terroristic activities and to a corresponding method thereof. The avionic system (1) comprises a selectable hash table (103, 203) assigned to a flight plan (102, 202) of an aircraft fleet (81,…,84) with operational parameters of airports (91,…94). Said airports (91,…,94) are airports (91,…,94) flown to according the fight plan (102, 202).A plurality of ground stations (911,…,914) is situated at the airports (91,…,94). The ground stations (911,…,914) are linked via a communication network (50,51) to a receiver (3) of a central processing unit (2) receiving transmissions from a detection device (4). Based on said transmission,a filter module (5) dynamically incrementing a stack with transmitted time interval parameters (1011, 2011) of an airport closing and activating a failure deployment device (6) if a threshold, triggered on the incremented stack value, is reached, thereby generating an output signal (61) to provide operational interruption cover for the aircraft fleet (41,…,44) by means of an automated damage covering system (7).

Classes IPC  ?

• G06Q 40/08 - Assurance
• G08G 5/00 - Systèmes de commande du trafic aérien

Abrégé

The invention relates to a self-sufficient resource-pooling system (1) for risk sharing of a variable number of risk exposed aircraft fleets (81,..., 84) related to airspace risks, wherein resources of the risk exposed aircraft fleets (81,..., 84) are pooled by the system (1) and a self-sufficient risk protection is provided for the risk exposed aircraft fleets (81,..., 84) by means of the system (1) preventing imminent grounding or operational collapse as a consequence of an occurrence of a natural disaster events, such as volcanic eruptions. The risk exposed aircraft fleets (81,..., 84) are connected to the system (1) by means of a plurality of payment-receiving modules configured to receive and store payments from the risk exposed aircraft fleets (81,..., 84) for the pooling of their risks and resources and loss cover is provided based on the pooled resources and risks by means of the system (1).

Classes IPC  ?

• G06Q 40/08 - Assurance
• G08G 5/00 - Systèmes de commande du trafic aérien

Abrégé

The invention relates to a resource-pooling system (1) and to a corresponding method for risk sharing of a variable number of risk exposure components (21, 22, 23,...) by providing a self-sufficient risk protection for the risk exposure components (21, 22, 23,...) by means of the resource-pooling system (1). The risk exposure components (21, 22, 23,...) are connected to the resource-pooling system (1) by means of a plurality of payment receiving modules (2) configured to receive and store payments from risk exposure components (21, 22, 23,...) for the pooling of their risks. The total risk of the pooled risk exposure components (21, 22, 23,...) comprises a first risk contribution (211) associated to risk exposure in relation to loan losses, and a second risk contribution (212) associated to risk exposure based on emergency expenses. The pooled risk is divided in a parameterizable risk part (11) and a non-parameterizable risk part (21) by means of an indexing module. In case of triggering a loss by means of a trigger module, the suffered loss is covered by releasing associated loans and emergency expenses of the risk exposure components (21, 22, 23,...) based on the parameterizable risk part (11) from the connected loss coverage system (3) and based on the non-parameterizable risk part (12) from the received and stored payments from risk exposure components (21, 22, 23,...).

Classes IPC  ?

• G06Q 10/00 - Administration; Gestion

Abrégé

Proposed is a system and method for a control unit controller (10) for steering liability risk driven interaction between an insurance unit (40) and a plurality of operating units (30) with at least one measurable liability exposure (31 ), whereas in case of an occurring loss at a loss unit (20,..., 26) induced by an operating unit (30) the insurance unit (40) is activated by the control unit controller (10) and the loss is automatically resolved by means of the insurance unit (40). Measure parameters associated with the liability risk drivers (311-313) are measured and transmitted to a central processing device (13) of the control unit controller (10). The operational interaction is adapted by means of the central processing device (13).

Classes IPC  ?

• G06Q 40/00 - Finance; Assurance; Stratégies fiscales; Traitement des impôts sur les sociétés ou sur le revenu

Abrégé

The invention relates to a forecast system (5) and method for automated location dependent natural disaster impact forecast, whereas natural disaster events are measured by located gauging stations (401,..., 422). Location dependent measurement parameters for specific geotectonic, topographic or meteorological conditions associated with the natural disaster are determined and critical values of the measurement parameters are triggered to generate a dedicated event signal (31/32) for forecasted impacts of the disaster event within an area of interest. In particular, the signal generation is based upon the affected population or object within the area of interest.

Classes IPC  ?

• G08B 21/10 - Alarmes pour assurer la sécurité des personnes réagissant aux événements désastreux, p.ex. les tornades ou les tremblements de terre