Abrégé

……, 418) for insurance management along a risk transfer supply chain (600). The modules of the infrastructure domain (200), the risk assessment domain (300) and/or the risk transfer domain (400) form a bonded context structure, which is based on a microservices architecture (500) providing the modules as decentralized independent microservice modules which are distributed in the digital network environment (100).

Classes IPC  ?

• G06Q 40/08 - Assurance

Produits et services

Software platforms; software; software, software platforms relating to insurance and reinsurance; software, software platforms with technical content intended for use in the field of reinsurance and insurance, particularly for insurance claim and risk calculation, risk analysis and management; downloadable electronic data and publications; downloadable electronic data and publications relating to insurance and reinsurance and to technical subjects concerning insurance loss prevention, risk analysis and management, as well as financial services in the field of insurance and reinsurance. Commercial business management; commercial administration; company management advisory services particularly in the fields of insurance, reinsurance, risk analysis and modeling, risk transfer, risk management and financial services; company management assistance and advice in the fields of insurance, reinsurance, risk analysis and modeling, risk transfer, risk management and financial services; collecting and processing information; compiling and systemizing data in computer databases; compilation of statistics. Insurance services; reinsurance services; financial services; real estate services; services, advice and information in the fields of insurance, reinsurance, risk analysis, risk modeling, risk transfer and risk management (insurance services and financial services); actuarial services; insurance claims adjustment and settlement services; all the aforementioned services, including via global computer networks (the Internet); management and execution of insurance policies. Scientific and technological services and research and development services relating thereto; industrial research and analysis services; computerized, industrial and scientific data analysis; designing and developing computer programs, applications and models; providing and hosting online platforms (software), applications and software; data storage; Software as a Service (SaaS); platform as a service; electronic data storage.

Abrégé

Proposed is a machine-learning-based cyber-attack susceptibility detection and/or monitoring system (100) and method providing quantitative measures for a system's cyber-attack susceptibility, in particular a machine-learning-based cyber risk method and system (100) for technical measuring a quantitative cyber risk score measure indicating a potential damage or loss related to a cyber risk event (80) impacting a computer application (200). A computer application (200) is using at least one computer device (210) and a cloud infrastructure (2220), which comprises at least one storage module (221) providing information data for the computer application (200) and/or one or more processing/operating tools (222) processing information data and/or one or more cyber security tools (223) configured to identify and/or fend off a potential cyber risk event (80). The machine-learning-based cyber risk system (100) comprises a status assessment module (1 10) for receiving a computer application status report (111), wherein the status assessment module (110) comprises a detection means (113) for detecting and/or extracting type parameters identifying a set of type identification data (50) from the computer application status report (111). A risk allocation module (120) receives the set of type identification data (50) allocates cyber risk factors (61) to at least one type parameter (51, 52, 53 ) of the set of type identification data (50). The risk factors (61) are based on a risk classification scheme (60) classifying the potential damage or loss. A weighing module (130) comprises a machine learning structure (131) and obtains the set of type identification data (50) and the associated risk factors (61) of the at least one type parameter (51, 52, 53), wherein the machine learning structure (131) includes a regression model for dynamically defining weighing factors (70) for the one or more risk factors (61). The weighing module (130) weighs the one or more risk factors (61) associated to a detected type parameters (51, 52, 53) of the set of type identification data (50) based on the weighing factors (70). An aggregation module (140) aggregates the weighted risk factors (71) as an aggregated cyber risk score (10) for the computer application (200), and an output signal generator (150) providing the aggregated cyber risk score (10) as an output signal of the machine-learning-based cyber risk system (100).

Classes IPC  ?

• G06F 21/57 - Certification ou préservation de plates-formes informatiques fiables, p. ex. démarrages ou arrêts sécurisés, suivis de version, contrôles de logiciel système, mises à jour sécurisées ou évaluation de vulnérabilité
• G06Q 40/08 - Assurance
• H04L 9/40 - Protocoles réseaux de sécurité

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
• G06Q 10/067 - Modélisation d’entreprise ou d’organisation

Abrégé

A drone-survey measurement-based inundation probability forecast and flood hazard vulnerability measuring system and method. Location-specific elevation data are measured by drones of the measuring system, the measured location-specific elevation data being transmitted to an inundation engine for forecasting flood hazard vulnerability zones and risk zones based on the measured location-specific elevation data depending on return periods or inundation heights of a flood hazard.

Classes IPC  ?

• G06V 20/17 - Scènes terrestres transmises par des avions ou des drones
• B64U 10/13 - Plates-formes volantes
• B64U 101/30 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques à l’imagerie, à la photographie ou à la vidéographie
• B64U 101/40 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques à l’agriculture ou à la sylviculture

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 40/08 - Assurance
• G06F 30/23 - Optimisation, vérification ou simulation de l’objet conçu utilisant les méthodes des éléments finis [MEF] ou les méthodes à différences finies [MDF]
• G06Q 30/0201 - Modélisation du marchéAnalyse du marchéCollecte de données du marché
• G06Q 40/02 - Opérations bancaires, p. ex. calcul d'intérêts ou tenue de compte

Abrégé

Proposed is an open, digital data driven underwriting and loss event simulation platform comprising an automated digital processing core for risk-transfer assessment based on risk measurements providing measures for potential damages or losses related to a future occurrence of a defined loss event causing a physical impact or loss to an event-exposed structure, object or individual. The automated digital processing core comprises a processing entity with a data interface for receiving input data of physical measurement values quantifying a risk parameter captured by measuring devices and a risk-transfer analyzing structure for processing the input data and allocating one or more risk-measure scores quantifying the potential damage or loss, and an output signal generator providing the one or more risk-measure scores as an output signal of the automated digital processing core.

Classes IPC  ?

• G06Q 40/08 - Assurance

Abrégé

A digital health or life claim processing system providing electronic integration of multiple digital automated claims channels, in which a digital claims channel includes a claims data set, a policy data set regarding a claim event and/or a services data set, and processing one or more claims of a customer based on at least one claims channel related to the customer, the system including a cloud-based infrastructure platform accessible via a digital network, which hosts a storage module, a data modelling module, a claims processing module, and a communication module, and at least one data transmission interface for exchanging data and/or information provided by at least one user device with the infrastructure platform.

Classes IPC  ?

• G06Q 40/08 - Assurance

Abrégé

Proposed is an open, digital data driven underwriting and loss event simulation platform (1) comprising an automated digital processing core (10) for risk-transfer assessment based on risk measurements providing measures for potential damages or losses related to a future occurrence of a defined loss event (2) causing a physical impact or loss (4) to an event-exposed structure, object or individual (3). The automated digital processing core (10) comprises a processing entity (101) with a data interface (100) for receiving input data (10011) of physical measurement values (100111) quantifying a risk parameter captured by measuring devices (6) and a risk-transfer analyzing structure (1012) for processing the input data (10011) and allocating one or more risk-measure scores (10121) quantifying the potential damage or loss, and an output signal generator (1012) providing the one or more risk-measure scores (10121) as an output signal (10012) of the automated digital processing core (10).

Classes IPC  ?

• G06F 16/908 - Recherche caractérisée par l’utilisation de métadonnées, p. ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement utilisant des métadonnées provenant automatiquement du contenu

Produits et services

Commercial business management; commercial administration; company management advisory services particularly in the fields of insurance, reinsurance, risk analysis and modeling, risk transfer, risk management and financial services; company management assistance and advice in the fields of insurance, reinsurance, risk analysis and modeling, risk transfer, risk management and financial services; collecting and processing information; compiling and systemizing data in computer databases; compilation of statistics. Software platforms; software; software, software platforms relating to insurance and reinsurance; software, software platforms with technical content intended for use in the field of reinsurance and insurance, particularly for insurance claim and risk calculation, risk analysis and management; downloadable electronic data and publications; downloadable electronic data and publications relating to insurance and reinsurance and to technical subjects concerning insurance loss prevention, risk analysis and management, as well as financial services in the field of insurance and reinsurance. Insurance services; reinsurance services; financial services; real estate services; services, advice and information in the fields of insurance, reinsurance, risk analysis, risk modeling, risk transfer and risk management (insurance services and financial services); actuarial services; insurance claims adjustment and settlement services; all the aforementioned services, including via global computer networks (the Internet); management and execution of insurance policies. Scientific and technological services and research and development services relating thereto; industrial research and analysis services; computerized, industrial and scientific data analysis; designing and developing computer programs, applications and models; providing and hosting online platforms (software), applications and software; data storage; Software as a Service (SaaS); platform as a service; electronic data storage.

Abrégé

Proposed is a system and method for measuring relative risk measurands of living individuals. 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 within a defined cohort of living individuals relative to a randomized cohort of living individuals. The system provides automation of the risk assessment and measuring process with a high efficiency and accuracy.

Classes IPC  ?

• G16H 50/30 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicalesTIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour le calcul des indices de santéTIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicalesTIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour l’évaluation des risques pour la santé d’une personne
• G06Q 40/08 - Assurance
• G16H 50/20 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicalesTIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour le diagnostic assisté par ordinateur, p. ex. basé sur des systèmes experts médicaux
• G16H 50/70 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicalesTIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour extraire des données médicales, p. ex. pour analyser les cas antérieurs d’autres patients

Abrégé

Proposed is a digital system 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 on the cargo and/or the cargo logistics services. Sets of measurable cargo logistics parameters are captured by the system as logistics input signals from a cargo logistics services database and are transmitted to an allocation structure. Each set of measurable cargo logistics parameters at least comprises cargo parameters and/or logistics parameters. At least one risk factor indicating a measured negative impact risk for the cargo and/or the cargo logistics services is captured by the system as risk input signals. Each of the risk factors at least corresponds to a measured impact strength or impact type of a negative impact on the cargo and/or the cargo logistics services, and/or a quantified damage at the cargo and/or on the cargo logistics services. At least one measurable cargo logistics parameter is assigned a risk factor by the allocation structure that corresponds to a measured value of the measurable cargo logistics parameters. An aggregated risk measure for the cargo logistics services is automatically generated by an aggregating structure of the processing unit based on the at least one risk factors allocated to measurable cargo logistics parameters and is provided as output signal by a signal generator to predict an occurrence of a measurable negative impact.

Classes IPC  ?

• G06Q 10/0635 - Analyse des risques liés aux activités d’entreprises ou d’organisations
• G06Q 10/0833 - Repérage
• G07C 5/00 - Enregistrement ou indication du fonctionnement de véhicules

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
• G06N 20/00 - Apprentissage automatique
• G06Q 10/0635 - Analyse des risques liés aux activités d’entreprises ou d’organisations
• G06Q 50/18 - Services juridiques

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 - NavigationInstruments de navigation non prévus dans les groupes

Abrégé

Proposed is a vehicle embedded or mobile-phone-based, automated dynamic routing unit associated with a vehicle and/or a user along a route traveled and method thereof. The dynamic routing unit provides an optimized route between a departure location and a destination location, wherein the automated dynamic routing unit comprises a routing interface for receiving destination input parameters of a destination location and/or departure location input parameters of a departure location, and wherein the automated dynamic routing unit comprises a routing generator for generating one or more routes between the departure location and the destination location.

Classes IPC  ?

• G01C 21/34 - Recherche d'itinéraireGuidage en matière d'itinéraire
• G01C 21/36 - Dispositions d'entrée/sortie pour des calculateurs embarqués

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 adoptive 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  ?

• G01W 1/10 - Dispositifs pour la prévision des conditions météorologiques
• G06V 20/13 - Images satellite

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 40/06 - Gestion de biensPlanification ou analyse financières
• 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

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

Classes IPC  ?

• G06F 16/29 - Bases de données d’informations géographiques
• G06T 17/05 - Modèles géographiques

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  ?

• G06Q 40/08 - Assurance

Abrégé

Proposed is a digital and automated underwriting system and method with fast point of sale decision-making and intelligent data processing engine for the coverage of possible damage impacted by the occurrence of health events to users. The automated system captures user-specific medical parameter data sets. The captured medical parameter data sets are processed by the electronic signal processing engine, wherein the electronic signal processing engine 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.

Classes IPC  ?

• G06Q 40/08 - Assurance

Abrégé

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

Classes IPC  ?

• B60W 50/06 - Détails des systèmes d'aide à la conduite des véhicules routiers qui ne sont pas liés à la commande d'un sous-ensemble particulier pour améliorer la réponse dynamique du système d'aide à la conduite, p. ex. pour améliorer la vitesse de régulation, ou éviter le dépassement de la consigne ou l'instabilité
• B60W 60/00 - Systèmes d’aide à la conduite spécialement adaptés aux véhicules routiers autonomes
• G07C 5/02 - Enregistrement ou indication du temps de circulation, de fonctionnement, d'arrêt ou d'attente uniquement
• G06F 30/20 - Optimisation, vérification ou simulation de l’objet conçu

Abrégé

Proposed is a digital platform 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 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 maintains a plurality of location digital twins of a plurality of physical property assets providing a basis for the risk analysis.

Classes IPC  ?

• 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
• G06V 20/10 - Scènes terrestres
• G06F 30/12 - CAO géométrique caractérisée par des moyens d’entrée spécialement adaptés à la CAO, p. ex. interfaces utilisateur graphiques [UIG] spécialement adaptées à la CAO

Abrégé

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

Classes IPC  ?

• G06F 30/20 - Optimisation, vérification ou simulation de l’objet conçu

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

Proposed is an electronic vulnerability detection and measuring system and method for susceptibility or vulnerability measurements of a truck fleet to occurring accident events caused by a carriage vehicle of the carriage vehicle fleet. At least one data interface is associated with data access means to a carriage vehicle fleet database for capturing carriage vehicle data as a fleet input signals from the carriage vehicle fleet database. The carriage vehicle data comprises: vehicle data comprising physical parameter measurements of carriage vehicle characteristics for the carriage vehicles, carriage vehicle driver data comprising physical parameter measurements of driver characteristics and/or carriage vehicle usage data comprising physical parameter measurements of carriage vehicle usage characteristics. At least one data interface is associated with data access means for capturing behavioral driving data of an electronic driving monitoring system of at least one carriage vehicle as a driving data input signal. A processing unit is designed for receiving the fleet input signal and the driving data input signal and comprises a machine learning module for analyzing the data provided by the fleet input signal and the driving data input signal by using one or more machine learning structures and generating a risk index value for the carriage vehicles. An aggregating module automatically generates an aggregated risk score measure for the truck fleet based on the risk index values of the carriage vehicles. A signal generator provides the aggregated risk score measure as output signal indicating the risk score measure of the truck fleet.

Classes IPC  ?

• B60W 30/09 - Entreprenant une action automatiquement pour éviter la collision, p. ex. en freinant ou tournant
• B60W 50/14 - Moyens d'information du conducteur, pour l'avertir ou provoquer son intervention
• G08G 1/00 - Systèmes de commande du trafic pour véhicules routiers

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 projetsPlanification d’entreprise ou d’organisationModélisation d’entreprise ou d’organisation
• G06Q 40/08 - Assurance

Abrégé

An aerial and/or satellite imagery-based, optical system and corresponding method for measuring physical impacts to land-based objects by impact measurands in case of an occurrence of a natural catastrophe event, the natural catastrophe event impacting the objects causing a physical damage. The method and system comprise the steps of capturing by remote airborne and/or spaceborne sensors digital aerial and/or satellite imagery and/or photography of an area affected by the natural catastrophe event and generating a digital natural catastrophe event footprint with a topographical map of the natural catastrophe event based on the captured digital satellite imagery. Finally, parametrizing, by an adaptive vulnerability curve structure, impact measurands for selected objects based on the measured topographical map and generating an impact measurand value for each of the land-based objects based on an event intensity measured by the natural catastrophe event footprint using the vulnerability curve structure. 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  ?

• G06V 20/10 - Scènes terrestres
• G06V 20/13 - Images satellite

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 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 5/08 - 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

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 21/60 - Protection de données

Abrégé

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

Classes IPC  ?

• G06Q 40/08 - Assurance
• G06N 5/022 - Ingénierie de la connaissanceAcquisition de la connaissance

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

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
• G01W 1/10 - Dispositifs pour la prévision des conditions météorologiques
• G01W 1/14 - Pluviomètres ou udomètres
• 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 20/10 - Architectures de paiement spécialement adaptées aux systèmes de transfert électronique de fondsArchitectures de paiement spécialement adaptées aux systèmes de banque à domicile
• G06N 3/0464 - Réseaux convolutifs [CNN, ConvNet]
• G06N 3/084 - Rétropropagation, p. ex. suivant l’algorithme du gradient

Abrégé

The invention relates to automated method and flood measuring and trigger system for providing a dynamic parametric flood impact cover for physical objects being measurably impacted by an occurrence of a flood event by using an adaptive damage-cover structure of a damage-cover system based on physical flood event measurements, wherein by flood detection devices and/or flood sensors, an occurrence of a flood event is measured by measuring floodings within the grid cells of the spatial grid, wherein flood measuring parameters of the flood detection devices and/or flood sensors are transmitted to the central measuring engine and wherein, based on the transmitted flood measuring parameters, grid cells measured as flooded are contributing to the area measured as affected while grid cells measured as not flooded are contributing to the area measured as not affected.

Classes IPC  ?

• G06Q 40/08 - Assurance
• G01W 1/14 - Pluviomètres ou udomètres

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 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 santéTIC 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 50/20 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicalesTIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour le diagnostic assisté par ordinateur, p. ex. basé sur des systèmes experts médicaux
• G06Q 40/08 - Assurance

Produits et services

Software for management, automated review and analysis of contractual documents. Computer management of contractual documents; contractual document management. Legal services, namely, reviewing and analyzing contractual documents.

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 distributionGestion d’inventaires ou de stocks

Abrégé

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  ?

• G06Q 40/08 - Assurance
• G06V 20/00 - ScènesÉléments spécifiques à la scène

Abrégé

Proposed is an automated system 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 provides an automated multi-step trigger and detection cycle based on sensory measuring data for risk-exposed individuals thereby mitigating possibly occurring long-term care needs by means of the automated system based on a detected sufficient state of disability, possibly predetermined up-front amount parameters and an assigned care equity ratio associated with an asset. The state of disability of the risk-exposed individual is measurable by a definable set of risk-exposed individual measuring parameters.

Classes IPC  ?

• G16H 50/30 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicalesTIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour le calcul des indices de santéTIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicalesTIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour l’évaluation des risques pour la santé d’une personne
• G06Q 40/06 - Gestion de biensPlanification ou analyse financières

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

Produits et services

Downloadable software for management, automated review and analysis of contractual documents Records management services, namely, management of contractual documents by means of a computer Legal services, namely, reviewing and analyzing contractual documents

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 correspondanceConversion
• 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 - BureautiqueGestion du temps
• G06Q 50/16 - Immobilier

Abrégé

A method and system for electronic trip familiarity detection based on sensory data measured by a plurality of sensors of a mobile telematics device associated with a user and/or a vehicle, the plurality of sensors at least comprising a GPS sensor and/or an accelerometer, the mobile device comprising one or more wireless connections, wherein by at least one of the wireless connection the mobile device acts as a wireless node within a cellular data transmission network by means of antenna connections of the mobile device to the cellular data transmission network, and the plurality of sensors being connected to a monitoring mobile node application of the mobile device, wherein the monitoring mobile node application captures usage-based and/or user-based sensory data of the plurality of sensors of mobile device.

Classes IPC  ?

• H04W 4/029 - Services de gestion ou de suivi basés sur la localisation
• H04W 4/02 - Services utilisant des informations de localisation
• 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

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 - MarketingEstimation ou détermination des prixCollecte de fonds
• G06Q 50/16 - Immobilier
• G06T 7/00 - Analyse d'image
• G06T 7/90 - Détermination de caractéristiques de couleur

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 30/02 - MarketingEstimation ou détermination des prixCollecte de fonds
• G06Q 40/08 - Assurance
• G06Q 50/16 - Immobilier
• 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 pour obtenir des valeurs mesurées
• G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projetsPlanification d’entreprise ou d’organisationModélisation 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 measuring system for progress monitoring and steering of impacts of a complex system to world environment and ecosystem induced by environmental-human linkages and for quantitative measuring of effects of applied risk-transfer structures to said environmental-human linkages induced by risk-transfer-SDG linkages measuring quantifying distances of progresses toward at least one of a predefined sustainable development goal with and without applying said risk-transfer structures.

Classes IPC  ?

• G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projetsPlanification d’entreprise ou d’organisationModélisation d’entreprise ou d’organisation

Abrégé

An intermediary, digital, data-driven platform and procedures for heterogeneous industrial ecosystems for the standardised recording and automated management of risk transfers and assigned product- and company-specific capacities as a standardised digital channel between risk-exposed units of the industrial ecosystem and the systems of a heterogeneous risk transfer ecosystem.

Classes IPC  ?

• G06Q 40/08 - Assurance

Abrégé

A method and system for automated transportation mode recognition based on sensory data measured by a plurality of sensors of a cellular mobile device of a user, the plurality of sensors at least comprising an accelerometer and a gyroscope, the plurality of sensors being connected to a monitoring mobile node application of the mobile device, wherein the mobile device measures time series of sensory parameter values based on measuring parameters obtained from the sensors, the measuring parameters comprise time series of sensory parameter values of a 3-axis accelerometer as sensor and time series of sensory parameter values of GPS-based speed measurements of a GPS receiver as sensor, 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  ?

• G06N 20/20 - Techniques d’ensemble en apprentissage automatique
• H04W 4/029 - Services de gestion ou de suivi basés sur la localisation
• G06Q 50/30 - Transport; Communications
• G06Q 50/26 - Services gouvernementaux ou services publics
• G01C 21/30 - Mise en coïncidence avec des cartes ou des contours

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 projetsPlanification d’entreprise ou d’organisationModélisation 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

A measuring and monitoring system is proposed comprising a plurality of measuring sensors and measuring devices by means of which geographically cellularly delimited measuring parameters are acquired. The measuring parameters are aggregated to a BES index, wherein the measuring parameters are selected in relation to the desired measurement accuracy of the biodiversity and ecosystem services (BES) index. The measuring and monitoring system comprises selectable, various biodiversity and ecosystem services at least comprising measuring parameters for measuring the habitat intactness 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 protection and/or food provision and/or timber provision. The measuring and monitoring system further permits the quantitative acquisition/measurement of risk indices based on the measured ecosystem services as a function of sectoral economic services.

Classes IPC  ?

• G06T 17/05 - Modèles géographiques
• G06F 16/29 - Bases de données d’informations géographiques

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'itinéraireGuidage 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’intersectionsAnalyse 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 digital multi-channel platform based on a multi-channel, high-layer data-transfer structure accessible by means of web-client applications running on front-end network-enabled devices providing discrete high-layer data-flow and capturing of structured and unstructured data content transferred from the front-end network-enabled devices over a data transmission network to a digital multi-channel back-end system.

Classes IPC  ?

• G06Q 40/08 - Assurance
• G06F 40/205 - Analyse syntaxique
• G06F 40/284 - Analyse lexicale, p. ex. segmentation en unités ou cooccurrence
• H04L 67/50 - Services réseau

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 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, (iii) turning features into 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 into a structure generating a default risk assessment allocating the actual risk into a risk quality 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
• G06Q 40/06 - Gestion de biensPlanification ou analyse financières

Abrégé

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

Classes IPC  ?

• G06Q 40/08 - Assurance
• B60W 40/09 - Style ou comportement de conduite

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 santéTIC 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

An automated real-time fraud monitoring and detection system for detecting unusual and/or suspicious activities within a network of nodes interconnected by edges triggered by captured synthetic forms of social data, in particular social networking and/or linkage and/or relationship data and social metadata including at least data from microblogging services and/or social networking services by pattern recognition and matching.

Classes IPC  ?

• G06Q 20/40 - Autorisation, p. ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasinExamen et approbation des payeurs, p. ex. contrôle des lignes de crédit ou des listes négatives

Abrégé

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

• H04M 1/72454 - Interfaces utilisateur spécialement adaptées aux téléphones sans fil ou mobiles avec des moyens permettant d’adapter la fonctionnalité du dispositif dans des circonstances spécifiques en tenant compte des contraintes imposées par le contexte ou par l’environnement
• B60W 40/08 - 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 conducteurs ou aux passagers

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 projetsPlanification d’entreprise ou d’organisationModélisation 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

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

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 10/10 - BureautiqueGestion du temps
• G06Q 40/06 - Gestion de biensPlanification ou analyse financières
• G06Q 10/067 - Modélisation d’entreprise ou d’organisation
• G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projetsPlanification d’entreprise ou d’organisationModélisation d’entreprise ou d’organisation

Produits et services

Software; software for computers; downloadable applications; applications for computers, tablets and smartphones; software platforms; software and applications for the collection, systematization, processing and analysis of information and data; software and applications for risk management platforms; downloadable electronic data and publications; application software; application software for mobile telephones. Business management; company administration; business management assistance and management advisory services; business and market analysis; customer and market studies; commercial management advisory services in the fields of analysis and risk prevention and in the field of risk management; commercial management assistance in the fields of analysis and risk management, in the field of risk management, and in the field of insurance, reinsurance and financial services; database management services; collection and processing of information and data by computer; collection and systematization of information and data in computer databases; analysis of information and data; analysis of large amounts of data; processing of information and data; computer data processing services; establishing statistics; compilation, offer and distribution of applications for computers, tablets and smartphones; services of an applications store. Insurance and reinsurance services; financial affairs; real estate affairs; advisory and information services with respect to insurance, reinsurance and financial services; actuarial consultancy services; services, advice and information with respect to risk analysis, modelling, transfer and management, (insurance and financial services); insurance claim adjustment and settlement; management and administration of insurance policies; financial advisory services with respect to risk analysis, prevention and management; advisory services with respect to insurance, reinsurance and financial services. Telecommunication services; transmission of information and data via networks; providing access to data via networks; providing access to computer platforms via networks; providing access to computer risk management platforms. Scientific and technological services as well as research and design services relating thereto; industrial analysis, industrial research and industrial design services; computerised industrial and scientific data analyses; design and development of non-downloadable software, applications and models; providing and temporary hosting of online platforms (software), non-downloadable applications and software; electronic data storage; Software as a Service (SaaS); platforms as a service (PaaSs); SaaS and PaaS for the collection, management, processing and analysis of data, including by artificial intelligence methods; research and development in the field of artificial intelligence; design, creation, development, programming, installation, configuration, maintenance, updating, servicing, repair, rental and hosting of non-downloadable software and applications; advice with respect to software and non-downloadable applications; design, development, programming, installation, configuration, maintenance, updating, servicing, rental, repair and hosting of software and non-downloadable applications for the collection, systematization, processing and analysis of information and data; creation of databases; computerized analysis of industrial data; design and development of data models and databases; development of algorithms.

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

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

Classes IPC  ?

• G06Q 30/06 - Transactions d’achat, de vente ou de crédit-bail
• G16H 20/60 - TIC spécialement adaptées aux thérapies ou aux plans d’amélioration de la santé, p. ex. pour manier les prescriptions, orienter la thérapie ou surveiller l’observance par les patients concernant le contrôle de l’alimentation, p. ex. les régimes

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 projetsPlanification d’entreprise ou d’organisationModélisation d’entreprise ou d’organisation

Abrégé

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

Classes IPC  ?

• G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projetsPlanification d’entreprise ou d’organisationModélisation d’entreprise ou d’organisation
• G06Q 40/06 - Gestion de biensPlanification ou analyse financières
• G06Q 50/08 - Construction
• G06N 3/02 - Réseaux neuronaux

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

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

Classes IPC  ?

• B60W 40/08 - 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 conducteurs ou aux passagers
• G01C 21/30 - Mise en coïncidence avec des cartes ou des contours
• G06N 20/20 - Techniques d’ensemble en apprentissage automatique
• G06Q 50/26 - Services gouvernementaux ou services publics
• G06Q 50/40 - Procédés d’affaires s’appliquant à l’industrie du transport
• H04W 4/02 - Services utilisant des informations de localisation
• H04W 4/029 - Services de gestion ou de suivi basés sur la localisation
• H04W 4/38 - Services spécialement adaptés à des environnements, à des situations ou à des fins spécifiques pour la collecte d’informations de capteurs
• H04W 4/48 - Services spécialement adaptés à des environnements, à des situations ou à des fins spécifiques pour les véhicules, p. ex. communication véhicule-piétons pour la communication dans le véhicule

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

Produits et services

Providing insurance underwriting to corporate customers in the fields of property and casualty, general liability, stop loss, fire and allied lines, ocean marine, inland marine, medical malpractice, earthquake, flood and natural disaster, workers compensation, excess workers compensation, products liability, commercial automobile, surety, burglary and theft and boiler and machinery; Insurance services, namely, writing property and casualty insurance and reinsurance to corporate customers; Insurance consultation provided to corporate customers in the areas of property and casualty, general liability, stop loss, fire and allied lines, ocean marine, inland marine, medical malpractice, earthquake, flood and natural disaster, workers compensation, excess workers compensation, products liability, commercial automobile, surety, burglary and theft and boiler and machinery; insurance services provided to corporate customers in the nature of loss control management for others; financial risk management and financial risk management consultation for corporate customers

Produits et services

Telecommunication access services; Electronic transmission of information and data via networks; Providing access to data via networks, namely, providing access to telecommunication networks; Providing access to computer platforms via networks, namely, providing user access to a global computer network; Providing access to computer risk management platforms, namely, providing access to telecommunication networks Downloadable and recorded software and software platforms for underwriting and administration of insurance and reinsurance products and for calculating, analysing, presenting and managing data and insurance and reinsurance products; Downloadable and recorded software, applications and software platforms for computers for data analytics in the field of insurance and reinsurance; Downloadable mobile applications for underwriting and administration of insurance and reinsurance products and for calculating, analysing, presenting and managing data and insurance and reinsurance products; Downloadable mobile applications for computers, tablets and smartphones for providing insurance and reinsurance products and for calculating, analysing, presenting and managing data and insurance and reinsurance products; Downloadable software platforms for providing insurance and reinsurance products and for calculating, analysing, presenting and managing data and insurance and reinsurance products; Downloadable software and downloadable mobile applications for the collection, systematization, processing and analysis of information and data; Downloadable software and downloadable mobile applications for operating risk management platforms; Downloadable electronic data files and publications in the nature of magazines, journals and pamphlets in the field of insurance and reinsurance products and data analytics; Downloadable application software for underwriting and administration of insurance and reinsurance products and for calculating, analysing presenting and managing data and insurance and reinsurance products; Downloadable application software for mobile phones for underwriting and administration of insurance and reinsurance products and for calculating, analysing, presenting and managing data and insurance and reinsurance products Business management; Company administration, namely, business administration; business management assistance and management advisory services; business and market analysis; Customer and market studies, namely, market research studies; Commercial business management advisory services in the fields of analysis and risk prevention and in the field of risk management; Commercial business management assistance in the fields of analysis and risk management, in the field of risk management, and in the field of insurance, reinsurance and financial services; database management services; Collection and processing of information and data by computer, namely, collection and systematisation of information into computer databases; collection and systematization of information and data in computer databases; Analysis of information and data, namely, business data analysis; Analysis of large amounts of data, namely, business data analysis; Processing of information and data, namely, data processing services; computer data processing services; Establishing statistics, namely, compilation of statistics; Compilation, offer and distribution of applications for computers, tablets and smartphones, namely, online retail store services in the field of downloadable mobile applications; Services of an applications store, namely, online retail store services in the field of downloadable mobile applications Insurance and reinsurance services, namely, insurance brokerage and reinsurance underwriting; Financial affairs, namely, financial consultation; Real estate affairs, namely, real estate brokerage; advisory and information services with respect to insurance, reinsurance and financial services; actuarial consultancy services; Services, advice and information with respect to risk analysis, modelling, transfer and management, namely, financial risk assessment and financial risk management; Insurance claim adjustment and settlement, namely, insurance claims administration; Management and administration of insurance policies, namely, insurance consultation; financial advisory services with respect to risk analysis, prevention and management; advisory services with respect to insurance, reinsurance and financial services Scientific and technological services as well as research and design services relating thereto, namely, scientific research and development; industrial analysis and industrial research for the development of insurance models; Computerised industrial and scientific data analyses, namely, scientific research consulting; Design and development of non-downloadable software, software applications and computer-simulated models; providing and temporary hosting of online software platforms, non-downloadable applications and software, namely, providing temporary use of on-line non-downloadable software and applications for underwriting and administration of insurance and reinsurance products and for calculating, analysing, presenting and managing data and insurance and reinsurance products; electronic data storage; Software as a services (SAAS) services featuring software for underwriting and administration of insurance and reinsurance products and for calculating, analysing, presenting and managing data and insurance and reinsurance products; Platform as a service (PaaS) featuring computer software platforms for underwriting and administration of insurance and reinsurance products and for calculating, analysing, presenting and managing data and insurance and reinsurance products; Software as a Service (SaaS) services featuring software for the collection, management, processing and analysis of data, including by artificial intelligence methods; Platform as a service (PaaS) featuring computer software platforms for the collection, management, processing and analysis of data, including by artificial intelligence methods; research and development in the field of artificial intelligence; design, creation, development, programming, installation, configuration, maintenance, updating, servicing, repair, rental and hosting of non-downloadable software and software applications of others for underwriting and administration of insurance and reinsurance products and for calculating, analysing, presenting and managing data and insurance and reinsurance products; Advice with respect to software and non-downloadable applications, namely, computer software consultation; Design, development, programming, installation, configuration, maintenance, updating, servicing, rental, repair and hosting of software and non-downloadable applications of others for the collection, systematization, processing and analysis of information and data; Creation of databases, namely, database design and development; Computerized analysis of industrial data, namely, computer systems analysis; design and development of data models and databases; Scientific development of algorithms

Abrégé

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

Classes IPC  ?

• G06N 20/10 - Apprentissage automatique utilisant des méthodes à noyaux, p. ex. séparateurs à vaste marge [SVM]
• G06N 5/02 - Représentation de la connaissanceReprésentation symbolique
• G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques
• 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

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 - BureautiqueGestion 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

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

Classes IPC  ?

• G06Q 40/08 - Assurance
• G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projetsPlanification d’entreprise ou d’organisationModélisation d’entreprise ou d’organisation

Abrégé

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

Classes IPC  ?

• G06F 21/62 - Protection de l’accès à des données via une plate-forme, p. ex. par clés ou règles de contrôle de l’accès
• G06F 16/215 - Amélioration de la qualité des donnéesNettoyage des données, p. ex. déduplication, suppression des entrées non valides ou correction des erreurs typographiques
• G06F 21/57 - Certification ou préservation de plates-formes informatiques fiables, p. ex. démarrages ou arrêts sécurisés, suivis de version, contrôles de logiciel système, mises à jour sécurisées ou évaluation de vulnérabilité

Abrégé

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

Classes IPC  ?

• G06Q 40/08 - Assurance
• G06Q 40/06 - Gestion de biensPlanification ou analyse financières
• 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 projetsPlanification d’entreprise ou d’organisationModélisation d’entreprise ou d’organisation
• G06Q 10/10 - BureautiqueGestion du temps

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"