Abstract: Methods and systems for an intelligent technical debt helper may include receiving, via a processor, a level of technical debt associated with a technical debt of a computer program code and determining, via the processor, whether the level of technical debt is greater than a technical debt threshold. The method may also include generating, using an artificial intelligence neural network model communicatively coupled to the processor and based on the computer program code, an automated code recommendation to address the technical debt of the computer program code when the level of technical debt is greater than the technical debt threshold.

Abstract: Systems, apparatuses, and methods for providing roadside assistance services are described herein. The system can include network computing devices and computing devices associated with vehicles and service vehicles. Requests for roadside services can be automatically assigned to an available service provider. Service providers can be ranked based on a variety of criteria and requests can be assigned based on the ranking. The ranking of service providers can be adjusted based on the performance of the service provider. If a service provider takes too long to respond to a request, the request can be automatically declined and an alternative service provider can be selected.

Abstract: A central claims adjuster control unit associated with an entity may oversee the assignment of claims cases to claims adjusters. The control unit may designate that a threshold number of cases may be assigned to certain claims adjusters. When new claims cases arrive, the control unit may monitor the workload of each of the claims adjusters and the threshold value assigned to any of the claims adjusters before assigning the case to one of the adjusters. If no adjuster is available, the control unit may store the case(s) in a memory until one of the adjusters becomes available. An additional feature of the control unit includes a user interface for modifying information about claims adjusters, including whether or not a threshold value is associated with them, the value of any associated threshold, and the reassignment of cases from one adjuster to another.

Abstract: Aspects of the invention are directed to methods and systems for efficiently communicating data between an insurer and a non-referral repair shop, e.g., vehicle repair shops that are normally not preapproved by the insurer to perform the estimating and repair work. The methods and systems described herein are particularly useful for insurers utilizing non-referral repair shops for servicing vehicles involved in insurance claims. According to aspects of this invention, the insured may be able to select a non-referral repair shop, not delegated or preapproved by the insurer, thereby generally allowing the insured to select any available vehicle repair shop.

Abstract: Aspects of the disclosure relate to computing platforms that utilize machine learning to reduce false positive/negative collision output generation. A computing platform may apply machine learning algorithms on received data to generate a collision output. In response to generating the collision output indicating a collision, the computing platform may identify a data collection location. If the data collection location is within a predetermined radius of a false positive collection location, the computing platform may modify the collision output to indicate a non-collision. If the data collection location is not within the predetermined radius, the computing platform may compute a score using telematics data and compare the score to a predetermined threshold. If the score does not exceed the predetermined threshold, the computing platform may modify the collision output to indicate a non-collision.

Abstract: Systems and apparatuses for generating customized driving assistance outputs are provided. The system may collect initial sensor data from a rotating mobile device. The system may analyze the initial sensor data to determine whether to collect additional sensor data. Based on analysis of the initial sensor data and the additional sensor data, the system may determine a customized driving assistance output. The system may determine one or more notification outputs and one or more instruction outputs for the driver based on the customized driving assistance output. The system may update an aggregate driving output based on whether or not the instruction output was completed, as determined from subsequent sensor data.

Abstract: Methods, computer-readable media, software, and apparatuses provide a system for controlling access to text messaging capabilities of a mobile computing device of a user while the user is driving. The mobile computing device may be configured to restrict a user from sending or receiving text messages while the user is driving depending on a current driving situation. Whether a user can send or receive text messages may further depend on a priority of the text message or a priority level of a sender or intended recipient of the text message. The system may include devices for collecting information regarding the vehicle and its surroundings and for determining the current driving situation based on the collected information. Further, the system may include devices for maintaining records of the restrictions placed on text messaging and of rewards earned for agreeing to be subject to such restrictions.

Abstract: A risk management system that includes an internet of things (IoT) integrated logic engine connected to IoT-capable sensors and devices and autonomous entity sensors and devices. The logic engine processes and analyzes in real-time the data from the plurality of IoT-capable sensors and the autonomous entity sensors. The logic engine further identifies novel patterns and pre-defined data patterns in the data from the plurality of IoT-capable sensors and the autonomous entity sensors to determine that a risk is occurring or imminent. The logic engine further sends real-time notifications to a set of subscribers of the risk management system about the risk that is occurring or imminent and provide inter-device communications to provide real-time warnings between one or more of the plurality of sensor-enabled devices and the autonomous entity devices.

Abstract: Methods and apparatuses allow an insurance agency to track their current performance in managing existing customers and bringing in new customers. A tool may obtain information from a user regarding characteristics of the user's agency and/or agency goals. The tool may use this information to determine an agency's business efficiency. The tool may also provide advice regarding marketing spending and/or additional human resources needed. The tool may benchmark an insurance agency against other agencies in the market. The tool may also display how generated leads are converted to new business and/or income for an agency.

Abstract: Systems and methods for performing insurance damage inspection by an unmanned aerial vehicle (UAV) are provided. A computing device may receive a request to inspect a vehicle, the request comprising a location of the vehicle. The computing device may identify a UAV from a plurality of UAVs that is located closest to the location of the vehicle from other UAVs in the plurality of UAVs. The computing device may instruct the UAV to travel to the location of the vehicle. The computing device may instruct the UAV to collect damage information on the vehicle using one or more onboard sensors of the UAV. The computing device may determine an amount of insurance payout to approve for repairs to the vehicle based on the damage information collected by the UAV.

Abstract: A claim-based capitation model is proposed for handling vehicle repair insurance claims. Rather than determining a detailed estimate of the expected actual cost of repair, the estimate may be determined using a simpler model. For example, the insurance company and a repair facility may agree to following a predictive payment model in which the insurance company pays a fixed predicted capitated amount of money for each repair claim, regardless of the amount of repair work that will be needed. Alternatively, the insurance company may pre-pay a fixed capitated amount for a predicted number of future insurance claims.

Abstract: Methods, computer-readable media, systems and apparatuses for determining a blind corner navigational score based on real-time or near real-time navigational analysis using sensor data, digital image data, and a map database are discussed. In some arrangements, detection of a blind sensor may be performing using sensor data, digital image data, and navigational data from a map database system. In at least some arrangements, a warning signal or a vehicle control signal may be transmitted to a vehicle in response to a determination that the blind corner navigational score is above a threshold. In at least some arrangements, route correction and/or route modification based on an upcoming blind corner may be performed if a blind corner navigational score is above a threshold.

Abstract: Aspects of the disclosure relate to using vehicle telematics data to assess parameters associated with vehicle operation. In some instances, a driving assessment system may include a first computing device associated with a user in a vehicle and a second computing located remotely from the first computing device. The first computing device may collect, by way of one or more of an accelerometer and global positioning system (GPS), vehicle operational data and vehicle locational information associated with the vehicle and corresponding to a trip of the vehicle and may transmit such information to the second computing device. The second computing device may identify actionable and second order actionable trip data from the vehicle operational data and vehicle locational information and may calculate a behavior score for the trip.

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: 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, computer-readable media, software, and apparatuses may determine whether a human driver, or an autonomous driving system, should be in control of a vehicle in response to a detection of an unexpected event. A decision may be made to pass control from the autonomous driving system to the human driver, if it is determined that the human driver can handle the unexpected event more safely than the autonomous vehicle.

Abstract: A system comprising a telematics device associated with a vehicle, a first computing device, a second computing device associated with a driver of the vehicle, and a server is disclosed. The server may be configured to receive maintenance data from the telematics device, determine a repair for the vehicle based on the maintenance data, send a request to the first computing device for the repair to be performed by one or more service providers, estimate a period of time for performing the repair, assign an alternative form of transportation to be provided to the driver during the estimated period of time, and send, to the second computing device, one or more notifications regarding at least one of the repair to be performed by the one or more service providers, the estimated period of time for the repair, or the assigned alternative transportation to be provided to the driver.

Abstract: A system for a predictive claims computing platform may comprise a plurality of vehicles, a computing device associated with a repair facility, a network, and a server. The server may be configured to determine an insurance coverage type needed for repairing each vehicle in the plurality of vehicles, identify a location of the repair facility for repairing each vehicle, assign a standard amount to reimburse the repair facility for repairing each vehicle based on insurance coverage type and the location of the repair facility, transmit the standard amount to the computing device associated with the repair facility, receive from the computing device, a cost for actual repair of each vehicle after the actual repair for each vehicle has been completed, and adjust the standard amount to reimburse the repair facility for future repairs based on identifying a difference between the standard amount and the actual repair cost for each vehicle.

Abstract: An aerial image system may generate images of structures providing views that might otherwise be difficult to obtain. These images may be used to determine various characteristics of the structure, which may then be processed for a variety of tasks including product marketing, claim processing and post-claim analysis. The images may be analyzed by the aerial image system or by a ground-based processing system to determine the structural characteristics such as roof age, roof type and roof pitch. In some examples, image analysis techniques such as edge detection and contrast determination may assist in determining the requisite data. Additionally or alternatively, the processing system may direct or control one or more image capture devices to obtain desired images.

Abstract: Methods of preparing retail establishments are disclosed. An area for a retail location may be chosen and an individual may be selected to manage the retail location. The selection of the area may include an evaluation of geographical factors. From the area, a retail location may be selected based on an aggregate score of a set of characteristics of the retail location. The individual may remotely select the layout and furnishing of the retail location and may remotely monitor the progress of the preparation of the retail location. In an embodiment, the individual may be prepared to manage the retail location at a centralized location that is distinct from the area where the retail location is located.