Abstract: Systems and methods provide customers with a need-based warranty using a deep learning neural network. After categorizing, a customer need is mapped to a warranty type based on the SLA needs. Warranties may then be suggested based on customer need. In another embodiment, systems and methods detect an optimal warranty based on part failure and performance of a server. A mean time to resolve or replace can be minimized in future failure instances by comparing the derived replacement time with available warranty offerings to identify potential deviations and thereby recommend an optimal warranty from the available offerings. In a further embodiment, systems and methods identify and offer additional service contracts for vender services. A warranty proposer looks for warranty types that are emitted by a warranty-types analyzer and by a technical-support analyzer. The overlapping warranty offers are provided to customers.

Abstract: A system includes a non-transitory computer-readable storage medium. The non-transitory computer-readable storage medium has instructions stored thereon that, upon execution by a processor of a portable user device, cause the processor to acquire data from a reader of the portable user device regarding an identifier on a machine, perform a verification process to verify that a user of the portable user device has access to the machine based on the identifier, wirelessly connect the portable user device to the machine in response to the user being verified to access the machine, display a control interface for the machine on a user interface of the portable user device, receive a user input through the control interface regarding operation of a controllable component of the machine, and provide a command to the machine based on the user input to facilitate remote operation of the controllable component of the machine.

Abstract: A method includes monitoring environmental conditions surrounding a moving vehicle, using an on-board sensor of the moving vehicle, detecting that at least one of the environmental conditions surrounding the moving vehicle is likely to impair visibility for a driver of the moving vehicle, based on an output of the on-board sensor, acquiring static map data for a location surrounding the moving vehicle, acquiring real time sensor data for the location surrounding the moving vehicle, where the real time sensor data comprises outputs of a plurality of on-board sensors of a plurality of other vehicles, generating an augmented reality view of the location surrounding the moving vehicle, using the static map data, the real time sensor data, and the output of the on-board sensor, and displaying the augmented reality view of the location surrounding the moving vehicle on a display within the moving vehicle.

Abstract: Vehicle costs may be allocated between users of a vehicle, including autonomous vehicles. A vehicle cost allocation (VCA) computing device receives an anticipated trip report associated with an anticipated future trip, the anticipated trip report associated with at least one vehicle user including an anticipated driver of the vehicle and an anticipated passenger, the anticipated trip report including at least one of an anticipated destination and a distance of the anticipated future trip. The VCA computing device is also configured to determine one or more anticipated vehicle costs for the anticipated future trip. The vehicle costs may include usage-based or trip-based insurance. The VCA computing device is also configured to allocate a respective portion of the vehicle cost to the anticipated driver and passenger and transmit the anticipated vehicle costs to for review by the anticipated driver.

Abstract: Provided methods and systems allow dynamic rendering of a reflexive questionnaire based on a modifiable spreadsheet for users with little to no programming experience and knowledge. Some methods comprise receiving a modifiable spreadsheet with multiple rows, each row comprising rendering instructions for a reflexive questionnaire from a first computer, such as a data type cell, statement cell, logic cell, and a field identifier; rendering a graphical user interface, on a second computer, comprising a label and an input element corresponding to the rendering instructions of a first row of the spreadsheet; receiving an input from the second compute; evaluating the input against the logic cell of the spreadsheet; in response to the input complying with the logic cell of the spreadsheet, dynamically rendering a second label and a second input element to the displayed on the graphical user interface based on the logic of the first row.

Abstract: The disclosure relates to technology for determining vehicle environment interaction metrics and/or passenger behavioral metrics for autonomous vehicles in a driving environment. A group of one or more autonomous vehicles independently determine a VEI score for a target vehicle within a predefined vicinity of the group of one or more vehicles. A target vehicle may determine a VPB score based on passengers within the target vehicle. VEI scores and/or VPB scores determined for a target vehicle may be used by the target vehicle to reinforce and/or correct driving actions of the target vehicle.

Abstract: Machine learning models can assess historical insurance claims data and prescription fulfillment records to reduce paybacks to prescription payers in the form of direct and indirect remuneration fees. A pharmacy computer receives prescription data and communicates at least a portion of the prescription data to a pharmacy benefit manager. The pharmacy computer receives a prescription benefit response back at the computerized application from the prescription payer software application. The pharmacy computer is configured to develop machine learning request data, selected from the prescription data and prescription benefit response data, and send the machine learning request data to machine learning software. The machine learning software calculates payback forecast data for the prescription data.

Abstract: A method of generating a user mobility profile includes receiving mobility data; storing the mobility data; analyzing the mobility data; generating information; transmitting the generated information; and displaying the generated information. A computing system includes a processor; and a memory storing instructions that, when executed by the one or more processors, cause the computing system to receive mobility data; store the mobility data; analyze the mobility data; generate information; transmit the generated information; and display the generated information. A non-transitory computer readable medium contains program instructions that when executed, cause a computer to receive mobility data; store the mobility data; analyze the mobility data; generate information; transmit the generated information; and display the generated information.

Abstract: An anthropomorphic, artificial intelligence-based system and method to provide benefits products field underwriting and post-enrollment customer services through a cognitive virtual assistant. The system can contact to one or more third-party benefits provider systems to obtain coverage details, provider types and location details, and to modify member coverage types on behalf of the member. The system can contact third-party pharmacy systems to fill medical prescriptions. The system can contact third-party medical services for providing information directed to medical services.

Abstract: A computer system includes memory hardware and processor hardware configured to execute instructions, including training a machine learning model to generate a claim prediction output, obtaining structured claim data and demographic data specific to a patient entity, processing the structured data to generate the claim prediction output, storing the claim prediction output as a predicted future claim value specific to the patient entity, and assigning the patient entity to a first entity subset or to a second entity subset according to the structured demographic data specific to the patient entity.

Abstract: Embodiments of the present invention relate to transportation systems. More particularly, embodiments relate to methods and systems of vehicle data collection by a user having a mobile device. In a particular embodiment, vehicle movement data (also termed herein “driving data” or “data”) is collected, analyzed and transformed, and combinations of collected data and transformed data are used in different ways, including, but not limited to, reporting and display of the combinations.

Abstract: There is a need for more accurate and more efficient predictive data analysis steps/operations. This need can be addressed by, for example, techniques for efficient predictive data analysis steps/operations. In one example, a method includes generating, by a processor, utilizing a risk determination machine learning model and based at least in part on one or more hidden features of the first predictive entity, the predicted risk measure, and performing one or more prediction-based actions based at least in part on the predicted risk measure.

Abstract: A system may include a vehicle system configured to monitor one or more monitor variables related to a vehicle. The system may also include a processor that may receive a selection of the one or more monitor variables to monitor and receive data from the vehicle system. The data may be limited based on the selection of the one or more monitor variables. The processor may then determine a fixed rate premium for at least two years based on the data and display a visualization that may include the fixed rate premium on a display.

Abstract: Systems and methods for estimating current roof conditions and potential underwriting risk using insurance claim data. Historical claims for confirmed weather-damaged homes may be clustered by claims stemming from one or more weather events to determine potential areas where damage has occurred, but a claim has not yet been filed. In certain implementation, claims for weather-related vehicle damage may be utilized to predict weather-related roof damage.

Abstract: A computer-implement method and computer system may be configured to facilitate insurance claim processing and estate handling. An audible or visible chatbot avator or dopplegänger may lead a trustee, beneficiary, or family member through the estate of an impaired or deceased user. A computer system may have been provided with, or gather, sample voice and visual recordings associated with a user that are used to build the chatbot avatar that simulates the user audibly and/or visually. The computer system may have previously prompted the user for necessary items to properly handle their estate, such as information related to financial accounts, loans, insurance policies, etc. and user names and passwords to various electronic accounts.

Abstract: A method and system for modeling of physical phenomena associated with natural disasters, including prediction of damage caused by wildfire conflagration. Such modeling involves dividing a target land area into a set of regions and a set of structures that are located within the target land area, each of the regions and structures are characterized by various vulnerabilities to fire conflagration, and are scored and subject to execution of simulation and regression, and other types of mathematical representation and statistical inference to support human intelligence and decision making.

Abstract: Instances of claim data are received by an apparatus. Each instance of claim data corresponds to an entity. A claim vector is generated for each instance of claim data. The claim vector is added to a group of claim vectors that all correspond to a same entity. Each group of claim vectors is aggregated to generate an entity vector corresponding to the entity. Based at least in part on the entity vector and (a) an entity profile corresponding to the corresponding entity or (b) an entity cluster with which the entity is associated, at least one behavior signal value is determined for the entity. A behavior signal is amended to include the behavior signal value. The behavior signal comprises at least two behavior signal values. Each of the behavior signal values are associated with a different time period. The behavior signal is provided for display and/or further processing.

Abstract: Aspects of the disclosure relate to computing platforms that utilize improved natural language processing techniques for claims processing. A computing platform may receive an audio file and determine one or more utterance segments based on the audio file. The computing platform may generate and send one or more audio chunks based on the one or more utterance segments to an audio transcription system. The computing platform may receive one or more text segments in response and may generate an audio transcription file accordingly. The computing platform may assign a category to each word in the audio transcription file, and may send user interface information to a user device along with one or more commands directing the user device to generate a user interface based on the user interface information, which may cause the user device to display the user interface.

Abstract: Systems and methods including one or more processors and one or more non-transitory computer readable media storing computing instructions that, when executed on the one or more processors coordinate analysis of data streams from separate computing systems communicatively coupled to different computing networks to build a personalized permanent life insurance product. In particular, the coordinated analysis builds a permanent life insurance product where one or more term life insurance policies, one or more annuity policies, and qualified additional benefit policies are combined into one master product for the purpose of creating a new overarching permanent life insurance product on the same insured. Systems and methods disclosed herein include IRC section 7702 & 7702A compliance testing on the insured's portfolio of individual policies as an integrated permanent life insurance product.

Abstract: At least a method for determining risk behavior of a driver is described. While a vehicle is being driven, data is obtained related to the position and movement of a wireless communications device. The data may indicate the type of behavior exhibited by the driver while the vehicle is being driven.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, to process audio and visual data. One of the methods includes receiving, from a mobile device, image data and audio data, wherein the image data and audio data were obtained within the same time frame. The method includes processing the image data to identify a first set of facts. The method includes processing the audio data to identify a second set of facts. The method includes processing meta-data associated with the image data to identify a third set of facts. The method also includes performing at least one process using the first set of facts, the second set of facts, and the third set of facts.

Abstract: According to one embodiment, there is provided a computing device and method for evaluating driving risk. The computing device includes an input circuit and a processor. The input circuit is configured to receive data from a vehicle. The data includes at least one of GPS data, acceleration data or image data of views external of the vehicle or inside the cabin. Thereafter, the processor is configured to identify a plurality of risks based on the data received from the vehicle, determine a plurality of weightages which are assigned to the plurality of risks, and generate a score based on the plurality of weightages for the plurality of risks.

Abstract: This technology relates to providing a web-based digital claims platform to provide users with a simple and customized experience when filing insurance claims. The platform is enabled by a plurality of back-end application programming interface (API) resources. These API resources are event-driven (e.g., when an “event” associated with the claim occurs, the status of the claim changes and the API is provided with updated information indicative of the change). The platform includes a customized user interface (UI) that tailors the claim experience to a particular user's needs. The customization can be based off of stated user preferences and/or learned user preferences associated with the user's past behavior. A user can perform/request various services through the customized UI's self-service function (e.g., rent a car, find a hotel room, select a repair shop, etc.). Additionally, the customized UI can enable the user upload documents, track claim status, find relevant help topics, etc.

Abstract: Computer program products, methods, systems, apparatus, and computing entities are provided for an augmented reality display using an actual image of the item. Additionally, the present disclosure provides for a proportionally dimensioned representation of the item in the augmented reality display. In some aspects, a beacon/tag/sensor-based approach may be used. In some aspects, a marker-based approach may be used.

Abstract: An insurance audit device, an insurance audit system, an insurance audit method, and a program for appropriately and easily conducting an audit related to cyber insurance are provided. An insurance audit device includes a monitoring result acquisition unit for acquiring a result of monitoring communication of a network in operation from a monitoring device configured to monitor the communication of the network, the network being a target for an audit related to insurance and an insurance audit unit for conducting the audit related to the insurance covering the network based on the result of monitoring in a predetermined period of time.

Abstract: A system for generating and managing usage-based contracts using blockchains configured to (i) store an insurance contract for a currently occurring or upcoming trip, where the insurance contract is to insure the driver, passenger, and/or vehicle during the trip, where the insurance contract includes terms, conditions, or other clauses (e.g., mileage limitations, limitations on autonomous vehicle operation, etc.) and is in a blockchain structure, and where several nodes store copies of the insurance contract in the blockchain structure; (ii) receive, from the driver and/or (autonomous) vehicle, a requested modification of one or more terms, conditions, or other clauses of the insurance contract, (iii) transmit the requested modification to an insurance auction network, (iv) receive a response to the request from the insurance auction network; and (v) store the response in a new block in the insurance contract (e.g., a smart contract) to facilitate providing trip insurance in a transparent manner.

Abstract: This disclosure is directed to systems, methods, apparatuses, and techniques that utilize enhanced gesture-based input mechanisms to facilitate designing custom non-level life insurance benefits policies and supporting customized pricing. These technologies can be specially designed and configured to optimize creation, editing, and/or sharing of life insurance benefits policies. The technologies include multi-gesture functionalities that enable users to view and access various features. Other embodiments are disclosed.

Abstract: A system may include a router that may receive a plurality of data packets from one or more devices that communicatively couples to the router. The system may also include at least one processor that identifies an identity of a device based on a data packet received by the router from the device, generate an insurance policy that includes the device in response to identifying the identity of the device, and sends a notification indicative of the insurance policy to a computing device in response to generating the insurance policy.

Abstract: A system for collecting vehicle crash data at a vehicle crash site of a vehicle crash is provided. The system may include an emergency response unit that includes an emergency response vehicle and an unmanned aerial vehicle (UAV) that is automatically deployed from the emergency response vehicle at the vehicle crash site. The UAV may be an autonomous or semi-autonomous drone, and include a processor, memory, and sensor, wherein the sensor collects vehicle crash data (such as image, video, or audio) at the crash site. The system may include a remote computing device and an insurance computing device to process the vehicle crash data collected by the UAV and/or initiate a crash insurance claim. The vehicle crash data may be used for one or more insurance-related purposes or activities, such as handling, adjusting, or generating auto or homeowners insurance claims; crash reconstruction; fault determination; damaged vehicle repair; and/or buildup identification.

Abstract: There is provided a method for providing driver's driving information of a user terminal device, including accessing a driving information providing server storing data generated in a driving recording device for a vehicle, receiving driving record data including event record data corresponding to a driving-related event of a driver from the driving information providing server, and displaying a driving-related event occurrence location on a map using the received driving record data. The driving-related event may include at least two or more of a lane departure event, a forward collision possibility event, a rear side collision possibility event, a sudden deceleration event, a sudden acceleration event, a sudden stop event, a sudden start event, and a speeding event.

Abstract: Methods and system for guiding user data capture during a scan of a vehicle using a mobile device are disclosed. A user may scan a vehicle using a camera or other sensors of the mobile device to capture data from which a three-dimensional virtual model may be generated. During the scanning process, models may be generated and evaluated according to quality metrics. Visual cues may be determined and presented to the user during scanning to indicate areas sufficiently scanned or areas requiring additional scanning to meet data quality requirements for model generation. Damage to vehicle components may be identified by analysis of the generated model, and addition data capture or user annotation entry may be directed based upon the identified damage.

Abstract: When a parked vehicle sustains accidental damage, the system automatically communicates with the vehicle owner and optionally the perpetrator of the damage via, e.g., WLAN communications.

Abstract: The present disclosure relates to an evaluation method and system for steering comfort in a human machine cooperative take-over control process of an autonomous vehicle, and a storage medium, thereby avoiding a defect that most comfort evaluation methods are applicable only in laboratory conditions, and also solving a problem that most comfort evaluation methods do not consider non-traditional control characteristics of a driver in a take-over control process. The method of the present disclosure includes: acquiring vehicle data information in a current driving cycle, and preprocessing the vehicle data information to form preprocessed vehicle data information; and using the preprocessed vehicle data information as an input to a well-trained comfort model library, and performing log probability matching calculation on the basis of the comfort model library, to form a comfort recognition result corresponding to comfort.

Abstract: One or more devices in a life insurance clearinghouse system may be configured to store and maintain life insurance customer data and policy data in one or more life insurance databases. A life insurance clearinghouse may store, for example, customer information, policy types and terms, and coverage amounts for life insurance policies associated with multiple different life insurance providers. Various systems and devices, such as insurance provider computer hardware memory and processor systems, insurance clearinghouse computer memory and processor devices, and customer terminals, may retrieve life insurance customer data and/or policy data associated with multiple different life insurance providers, from one or more databases in a life insurance clearinghouse.

Abstract: To automate a pricing strategy for an otherwise unpriced service or item, prices may be generated through a plurality of different pricing models, via a pricing engine passing input data to a plurality of discrete pricing models. Those pricing models may pass data back to the pricing engine, which then adjudicates the results of the pricing models to identify a most-relevant pricing model for the particular unpriced service or item.

Abstract: A method of deriving a financial conscientiousness score from visual choices, using a machine learning model that is trained at a server is provided. The method includes (i) obtaining visual selection as an input from the user that is selected from one or more different visual choices that are displayed to the user, (ii) determining trait scores for a subset of traits based on the points that are attributed to the visual choices, (iii) training, a machine learning model by correlating the trait scores for the subset of traits with a previous credit history or a loan repayment record of the user to obtain a trained machine learning model, and (iv) determining, using the trained machine learning model, a financial conscientiousness score based on the trait scores for the subset of traits.

Abstract: A computing system can receive loss information from a computing device of a claimant, the loss information indicating damage or loss to property of the claimant from an event. The system can connect with a plurality of data sources to receive contextual information corresponding to the event. Based at least in part on the contextual information corresponding to the event, the system generates a graphical user interface for a policy provider of the claimant, the graphical user interface providing a set of fraud scores for the loss information provided by the claimant.

Abstract: Method and system for generating a hybrid epoch score and driver feedback for a user. In some examples, a computer-implemented method includes: receiving prior telematics data indicative of the operation of a vehicle by the user during one or more prior trips in a prior epoch; receiving recent telematics data indicative of the operation of the vehicle by the user during one or more recent trips in a current epoch; generating a prior epoch score based at least in part upon the prior telematics data; generating a partial current epoch score based at least in part upon the recent telematics data; generating a hybrid current epoch score based at least in part upon the prior epoch score and the partial current epoch score; generating a driver feedback based at least in part upon the hybrid current epoch score; and presenting the driver feedback to the user via a display.

Abstract: Aspects of the present disclosure describe systems, methods, and devices for vehicle mode detection based on acceleration data and location data during a trip detected by mobile devices in a vehicle. According to some examples, location data will be compared to known routeway data to detect a vehicle mode. In other examples acceleration data will be used to calculate the consistency of vehicular velocity during a trip to detect a vehicle mode. In some additional aspects, multiple analyses will be performed on the same data sets to check for false positives with vehicle mode detection.

Abstract: A method for calibrating a driving risk identification model includes: S1. establishing a vehicle platform by installing an information acquisition device on a test vehicle; S2. acquiring synchronized test data related to the test vehicle and driving scenarios; S3. extracting moments when the drivers start to press the accelerator pedal, start to release the accelerator pedal, start to press the brake pedal in the driving scenarios, and start to release the brake pedal, so as to define risk level values respectively corresponding to the moments; S4. obtaining a risk identification curve of the drivers in different driving scenarios, wherein the risk identification curve represents the drivers' judgment of the risk level over time; S5. using the risk identification curve to calibrate the driving risk identification model.

Abstract: A semantic parser can process natural language of a traditional contract to generate variables and rules which can be implemented in a smart contract. The smart contract can be provided to a distributed ledger, such as a blockchain network, to execute the smart contract. Execution of the smart contract can be documented in the distributed ledger and in association with the smart contract.

Abstract: In some examples, a computing device creates an event log when an event occurs. If the event log includes a path comprising one or more components, the computing device may determine a hash, using a hash function and a salt, for each of the components and substitute each component in the path with an index to the hash stored in a dictionary. In this way, the computing device replaces each component of the path with an index to a hash in the dictionary to create a modified path. The resulting modified path can be traversed and searched. For example, a search term may be hashed using the hash function and salt, and the dictionary associated with the logs searched for a match. In this way, a particular file name or a particular folder name can be identified in the modified path.

Abstract: In an example embodiment, a solution is used to provide for multiple and concurrent web application accessing of a database in a database-as-a-service (DBaaS) framework. More particularly, a cloud solution is provided on a DBaaS for leveraging Docker network functionality to provide a virtual Internet Protocol (IP) address pool, while utilizing in-memory database technology to set up an entire accessing solution for multiple and concurrent DBaaS users and web applications, which serve the data-intensive jobs to the in-memory database. This allows for improved functionality, performance, concurrency, and handling of network stress.

Abstract: A computerized-method for predicting a probability of fraudulent financial-account access, is provided herein. The computerized-method includes a. building a Machine Learning (ML) sequence model; b. implementing a forward-propagation-routine in an encapsulated environment that runs applications to mimic a process of the ML sequence model. The forward-propagation-routine is mimicking processing of a chronical-sequence of a preconfigured number of non-financial activities sequence vector, layer by layer to generate a fraud probability score and using weights and biases which were extracted from each layer of the trained ML sequence model; and c.

Abstract: Methods and systems for maintaining and building an autonomous vehicle-related event blockchain are provided. One or more processors may receive indications of autonomous vehicle events. The autonomous vehicle events may include information relating to technology usage and/or operational events. The autonomous vehicle events may be compiled into a log of recorded autonomous vehicle events. Based upon the autonomous vehicle events, an action to implement may be determined. Additionally, the log may be distributed to a public or private network of distributed nodes to form a consensus on an update to the log of record autonomous vehicle events. As a result, the distributed nodes may maintain an up-to-date record of the shared ledger of autonomous vehicle events.

Abstract: Method and system for generating a hybrid epoch score for a user. In some examples, a computer-implemented method includes: receiving, from at least one of a mobile device associated with the user and a server, prior telematics data indicative of the operation of a vehicle by the user during one or more prior trips in a prior epoch; receiving, from the mobile device, recent telematics data indicative of the operation of the vehicle by the user during one or more recent trips in a current epoch; generating a prior epoch score based at least in part upon the prior telematics data; generating a partial current epoch score based at least in part upon the recent telematics data; and generating a hybrid current epoch score based at least in part upon the prior epoch score and the partial current epoch score.

Abstract: With the advent of augmented reality devices becoming increasingly prevalent, accessible, and cross-compatible, there is an opportunity to leverage the capabilities of such devices in order to streamline user interactions related to complex resource activities which require elevated security and typically are only conducted on an in-person basis. The present invention provides systems and methods for securely verifying a user during an augmented reality device session for the purposes of conducting complex resource activities.

Abstract: A system comprising a plurality of mobile devices, an insurance policy database, and a server is disclosed. The server may be configured to receive barometric data from one or more sensors in each of the plurality of mobile devices, identify that the barometric data indicates an occurrence of at least one catastrophic event, identify a geographic region affected by the at least one catastrophic event, access the insurance policy database to determine a number of insurance policies in the geographic region, estimate a number of catastrophe resources needed to handle the number of insurance policies in the geographic region, and assign at least one of the catastrophe resources to each of the insurance policies in the geographic region.

Abstract: Methods and systems described in this disclosure can identify, from a social media listening device, content items posted by a plurality of users, where each of the content items is associated with a social handle. Each of the content items can be mapped to a user identifier associated with a user or a potential user of a service using the social handle. A subset of the mapped content items can be created by selecting the mapped content items that correspond to an event based on content. The mapped content items are then categorized based on the corresponding events in the content items. Service or product opportunity leads can be determined from the mapped and categorized content items.

Abstract: Aspects of the present disclosure relate to using vehicle telematics to detect, evaluate, and respond to driving behaviors observed during a trip in a vehicle. The vehicle telematics information may characterize the observed driving behaviors, the segments traveled in the vehicle, and type of use of the vehicle. A rate to charge a driver may be based on the observed driving behaviors and a range of rates associated with the driver. The rate may fluctuate across a series of observation periods based on the driving behaviors observed during those observation periods. The rate may be presented to the driver in real-time while the driver operates a vehicle during a trip. The rate to charge the driver may further be based on use of the vehicle for personal use, ride shares, or vehicle shares.