Abstract: A method for providing smart auto rental estimatics to a user includes training a machine learning model to predict repair information, receiving a report, analyzing the report to identify a coverage, determining a vendor, receiving a chosen vendor, determining a branch, receiving a chosen branch, analyzing the report and a volume data using the trained machine learning model to determine loss information, calculating out-of-pockets, and transmitting the out-of-pockets to the user.

Abstract: A method for providing smart auto rental estimatics to a user includes training a machine learning model to predict repair information, receiving a report, analyzing the report to identify a coverage, determining a vendor, receiving a chosen vendor, determining a branch, receiving a chosen branch, analyzing the report and a volume data using the trained machine learning model to determine loss information, calculating out-of-pockets, and transmitting the out-of-pockets to the user.

Abstract: A method of determining an injury segment includes receiving a loss report, analyzing the loss report using a trained model to determine a severity of an injury, determining, based on the severity of the injury, an injury segment, and storing, via a processor, an indication of the injury segment. A computer system includes a processor configured to receive a loss report, analyze the loss report using a trained model to determine the severity of an injury, determine an injury segment, and store an indication of the injury segment. A non-transitory computer readable medium containing program instructions that when executed cause a computer to receive a loss report, analyze the loss report using a trained model to determine the severity of an injury, determine an injury segment, and store an indication of the injury segment.

Abstract: A method of determining an injury segment includes training a machine learning model, receiving a loss report, analyzing the loss report using the trained model to determine a severity of an injury, determining, based on the severity of the injury, an injury segment, and storing, via a processor, an indication of the injury segment. A computer system includes a processor configured to train a machine learning model, receive a loss report, analyze the loss report using the trained model to determine the severity of an injury, determine an injury segment, and store an indication of the injury segment. A non-transitory computer readable medium containing program instructions that when executed cause a computer to train a machine learning model, receive a loss report, analyze the loss report using the trained model to determine the severity of an injury, determine an injury segment, and store an indication of the injury segment.

Abstract: Systems and methods are disclosed with respect to providing seamless customer experience transactions, in particular, linking disparate systems to facilitate a lower friction customer experience. An exemplary embodiment includes receiving recorded data from one or more connected devices at a geographic location; analyzing the recorded data, wherein analyzing the recorded data includes determining that an collision has occurred involving one or more vehicles; generating a transaction including the data indicative of the collision based upon the analysis; and transmitting the transaction to at least one other participant in the distributed ledger network.

Abstract: A method for classifying total loss based on claim characteristics may include training a machine learning model using labeled data to classify a loss report, receiving a loss report associated with a policy, analyzing the loss report using the trained model to classify the loss report into a category, and storing an indication of total loss in association with the loss report when the category is a total loss category. A method for automating loss report taking may include receiving loss report data and telephony data from a user, correlating the user to a policy and a profile, determining a preferred language of the user and displaying a prepopulated loss report and a loss report word track in the preferred language of the user to a customer support user, wherein the prepopulated loss report and loss report word track are interpolated into predetermined locations in a loss report template.

Abstract: A method of determining an injury segment includes training a machine learning model, receiving a loss report, analyzing the loss report using the trained model to determine a severity of an injury, determining, based on the severity of the injury, an injury segment, and storing, via a processor, an indication of the injury segment. A computer system includes a processor configured to train a machine learning model, receive a loss report, analyze the loss report using the trained model to determine the severity of an injury, determine an injury segment, and store an indication of the injury segment. A non-transitory computer readable medium containing program instructions that when executed cause a computer to train a machine learning model, receive a loss report, analyze the loss report using the trained model to determine the severity of an injury, determine an injury segment, and store an indication of the injury segment.

Abstract: A method of assigning and/or routing an auto claim to an appropriate claim handling tier to mitigate delay may include training a machine learning model using historical claim data to determine a severity corresponding to an injury claim, receiving a loss report corresponding to an auto accident, analyzing the loss report using the trained machine learning model to determine the severity of at least one injury corresponding to the loss report, determining an injury segment, and storing the indication of the injury segment in association with the loss report.