Abstract: A system and method for measuring a driver's actual driving behaviors (e.g., acceleration, deceleration) in a manual driving mode to determine their preferred driving style, and then causing an autonomous or semi-autonomous vehicle to operate itself, within limits, in accordance with the drivers' driving style when operating in a self-driving mode, thereby providing a more familiar and comfortable driving experience for the driver. Data is collected on the actual driving behavior, any pre-existing data is accessed on the actual driving behavior, and the collected data and the pre-existing data are combined. A custom control is then created based upon the combined data, and the custom control is applied to manage the self-driving behavior of the autonomous or semi-autonomous vehicle in a self-driving mode. Additional data continues to be collected on the actual driving behavior, and the custom control is adjusted based upon the collected additional data.

Abstract: In variants, the method for automatic debris detection includes: determining a region image; optionally determining a parcel representation for the region image; generating a debris representation using the region image; generating a debris score based on the debris representation; and optionally monitoring the debris score over time.

Abstract: A data file comprising a plurality of rows, each of the rows includes at least a first column and a second column, the first column contains a first-level resource ID that identifies a first-level resource, the second column provides information regarding the first-level resource. For each respective unique first-level resource ID, the processing circuitry identifies a row set for the respective first-level resource ID, performs a sequential deduplication process on the row set, and enqueues remaining rows in a queue for a thread assigned to the respective first-level resource ID. For each row enqueued in the queue for the thread, the thread dequeues the row from the queue for the respective thread, requests creation of a second-level resource that stores a version of the data element contained in the second column of the dequeued row, and requests creation of relationship data for the second-level resource.

Abstract: A method and related system for generating and presenting queries is disclosed. The method includes selecting a first context based on a set of inputs including a first query and determining a match between the first context and a stored context associated with a schema. The method further includes generating a second query based on the set of inputs with a first language model in response to the determination of the match and identifying an indicated portion of the second query by providing, as a second input, the second query to a second language model. The method also includes generating data, the data including an issue indicator of the second query based on the indicated portion; and sending the data to the client device.

Abstract: An apparatus for classifying an entity to an executable data structure, the apparatus including a processor and a memory communicatively connected to the processor, the memory containing instructions configuring the processor to receive entity input from an entity using a graphical user interface, wherein receiving the entity data includes receiving a low-level entity data at a first time and receiving a high-level entity data at a subsequent time determine a degree of interaction pertaining to the entity by comparing the low-level entity data to the high-level entity data, identify at least a protocol metric as a function of the degree of interaction, determine a protocol object as a function of the high-level entity data and the at least a protocol metric, establish an executable data structure for the entity as a function of the protocol object and display the executable data structure using the graphical user interface.

Abstract: The present invention generally relates to computer systems, methods and program products that allow a digital asset exchange to provide an option to customers to lend all or a portion of the digital assets associated with at least a first blockchain and held by the exchange on behalf of the customer in exchange for payments such as interest.

Abstract: A method includes displaying, by an electronic device, a first page, enabling, by the electronic device, a page content hiding function for the first page in response to a first preset input of a user, receiving, by the electronic device, a second preset input of marking a hidden area on the first page by the user after enabling the page content hiding function, and hiding, by the electronic device, display content in the hidden area in response to the second preset input.

Abstract: A management method and apparatus for vehicle safety, and a computer storage medium. The method includes: acquiring at least one of meteorological data and environmental data, the environmental data is collected by an on-board device on a vehicle; determining a weather warning type based on at least one of the meteorological data and the environmental data; determining whether the weather warning type meets a predetermined warning condition; determining vehicle insurance data matched with the vehicle, based on at least one of the meteorological data and the environmental data as well as driving data of the vehicle; and displaying an identifier associated with the vehicle insurance data on at least one of a mobile device and an on-board display screen of the vehicle, the mobile device is associated with the vehicle when a predetermined operation is detected on the mobile device.

Abstract: Methods and systems for monitoring use and determining risks associated with operation of a vehicle having one or more autonomous operation features are provided. According to certain aspects, operating data may be recorded during operation of the vehicle. This may include information regarding the vehicle, the vehicle environment, use of the autonomous operation features, and/or control decisions made by the features. The control decisions may include actions the feature would have taken to control the vehicle, but which were not taken because a vehicle operator was controlling the relevant aspect of vehicle operation at the time. The operating data may be recorded in a log, which may then be used to determine risk levels associated with vehicle operation based upon risk levels associated with the autonomous operation features. The risk levels may further be used to adjust an insurance policy associated with the vehicle.

Abstract: Described herein are techniques for receiving, from a first device, first data about a physical object located in a physical space. The techniques further including storing, in a catalog of objects generated for the physical space, information about the physical object and indicating at least a first location of the physical object in the physical space. The techniques include receiving, from a second device, second data about the physical space, the second data sent from the second device upon or after an occurrence of an event. The techniques include determining, based on the second data, at least an impact area of the event to the physical space and determining, based on the catalog of objects and the second data, whether the physical object is impacted by the event. The techniques include causing an output indicating whether the physical object is impacted by the event.

Abstract: A system for electronically automating reduction component selection, conversion, disaggregation, and assignment is provided. The system generates graphical user interfaces that accept data relating to a reduction component to be analyzed and assigned to a qualified facility. The system identifies a segment associated with each reduction component and identifies all reduction components within a segment. A reduction concentration is determined in near real time for each segment by totaling the concentrations for each reduction component within a segment. The reduction concentration is compared to an Available Reduction Threshold to determine if facility capacity has been exceeded for new reduction components and for previously assigned reduction components.

Abstract: A system and method for analyzing a service provider of a retirement plan and comparing the service provider against the service providers associated with a group of similar plans is disclosed. In one embodiment, a computer system for evaluating a service provider of a retirement plan comprises a computer server having a database comprising a plurality of data defining a plurality of characteristics of each of a plurality of retirement plans, software configured to identify a subset of the plurality of retirement plans having characteristics comparable to characteristics of the selected retirement plan in view of the type and characteristics of the service provider, software configured to permit the selection of at least one report providing the comparison of the service provider, and software configured to automatically generate and deliver the selected at least one report to a user for display on a user interface.

Abstract: A rental self-service (“RSS”) computer system, including a processor and a memory, is provided. The processor is programmed to: (i) retrieve policyholder insurance data using a claim identifier and a policyholder identifier; (ii) generate a customized link including the claim identifier and the policyholder identifier, wherein the customized link is executable on a user device to cause display of a searchable interface configured to enable the claimant to search for rentable vehicles from a plurality of vendors; (iii) in response to receiving the customized link from the user device, retrieve rental vehicle data including at least one rental vendor location and vehicle rental cost information; (iv) cause the retrieved rental vehicle data to be displayed on the user device to enable the claimant to view available rental options; and (v) receive confirmation of a rental reservation request of a selected rental option at a selected rental vendor location.

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.

Abstract: Systems and methods for selectively transmitting alerts based on monitored behavior of a driver are disclosed. A system can calculate a driver score for a driver based on a set of driving events detected from sensor data captured while a vehicle was operated by the driver. Each of the set of driving events is associated with a driving behavior in a driving scenario. The driver score is further calculated based on historic driving event data. The system can assign the driver to a category of a number of categories based on the driver score. The system can determine that a change to a habitual driving behavior in a monitored driving scenario would result in reassignment of the driver to another category. The system can transmit an alert to the vehicle based upon a subsequent detection of a driving event that is associated with the monitored driving scenario.

Abstract: Systems, methods, and computer-readable media for performing feature engineering on a dataset for predictive modeling are disclosed. A dataset may comprise a plurality of features that are used for the predictive model. The dataset may be fed to a neural network to determine which features have the greatest impact on the predictive model and which features do not positively impact the predictive model. A deep reinforcement learning agent may select an action to perform on the dataset. The action may be applied to the dataset to generate new features and obtain a transformed dataset. Features that do not positively impact the predictive model may be removed from the dataset. A reward may be calculated for the transformed dataset. The transformed dataset and the reward may be passed to the neural network for further iteration and optimization of the features for the predictive model.

Abstract: In an illustrative embodiment, systems and methods for monitoring insurance claims include identifying, based on predetermined monitoring frequency, insurance claims identified for vulnerability detection processing. Vulnerability detection features may be extracted from data files of the claims, which provide an indication of claim handling deficiencies that can cause claim leakage. A trained vulnerability detection data model can be used to detect claim handling vulnerabilities within the extracted vulnerability detection features where each of the vulnerabilities may include a likelihood of the vulnerability resulting in claim leakage. The vulnerability detection data model may be trained with a data set customized to a respective insurance provider for each claim. Vulnerability scores indicating an overall likelihood of claim leakage can be calculated for the claims based on the detected claim handling vulnerabilities.

Abstract: According to some embodiments, a risk relationship data store may contain electronic records, each electronic record representing a risk relationship between an enterprise and a risk relationship provider (e.g., an insurer), and including, for each risk relationship, an electronic record identifier and a set of estimated usage attribute values. A back-end application computer server may receive, from a current usage data source, current usage information for the enterprise (e.g., financial information, utility information, IoT information, etc.). Based on the current usage information, the computer server may infer a likely actual current usage for the enterprise. The computer server may then compare the likely actual current usage with the predicted usage attribute value to determine a risk difference result and adjust a risk relationship parameter based on the risk difference result.

Abstract: A computer-implemented method includes receiving a work item associated with a structure, determining, using an inspection model, that an inspection is needed for the work item, retrieving an aerial image corresponding to a geographic location associated with the structure, and analyzing the aerial image to identify a first object within the aerial image. Identifying the first object includes (i) identifying a first object data category corresponding to the first object, and (ii) determining a data value descriptive of the first object and corresponding to the first object data category. The method also includes identifying one or more action items based upon the first object data category and the data value, linking the one or more action items to a customer account that is associated with the geographic location, and performing one or more actions corresponding to the one or more action items.

Abstract: A system including at least one processor programmed to identify, based on a policy to be enforced, one or more metadata symbols corresponding to an entity name; identify, from a target description describing a target system, an entity description matching the entity name, wherein the entity description describes an entity of the target system; and apply a metadata label to the entity of the target system, wherein the metadata label is based on the one or more metadata symbols corresponding to the entity name, as identified based on the policy.

Abstract: Data processing systems for identifying new indications for a drug can include a computer-readable memory including computer-executable instructions; and at least one processor configured to execute executable logic including the computer-executable instructions and at least one machine learning model to perform one or more operations. The one or more operations can include receiving data representing medical records of a plurality of patients; selecting a set of patients; determining a plurality of patient characteristics of the set of patients; grouping, in accordance with the plurality of patient characteristics, the set of patients to generate a plurality of distinct groups, each of the distinct groups including at least one patient of the set of patients; selecting, based on one or more group selection criteria, a set of distinct groups of the plurality of distinct groups; and identifying one or more relevant patient characteristics by analyzing each distinct group of the set of distinct groups.

Abstract: Event-based connected vehicle control and response systems, methods, and apparatus are disclosed. An example method comprises identifying the occurrence of an event, storing first data corresponding to apparatus operation for a first threshold amount of time prior to the event, during the occurrence of the event, and for a second threshold amount of time after the event, determining whether a responsive object is involved in or near the event, in response to determining that the responsive object is involved in or near the event, transmitting the first data to the responsive object, and receiving, from the responsive object, second data, analyzing the first data and the second data to determine a party at-fault for the event, aggregating the first data and second data into an event report, and causing, automatically, a response to be initiated through an entity associated with the party at-fault.

Abstract: A mobile telecommunications device configured to log driving information associated with a vehicle is described.

Abstract: Systems and methods are disclosure for using sensors to deliver educational content to vehicle users during critical events. One method comprises: receiving, by a first computing device having at least one processor and from a user device of a vehicle user via a wireless data connection, a notification of a critical event for a vehicle of the vehicle user and a vehicle identification of the vehicle; receiving, from the user device via the first wireless data connection, user input soliciting educational content to remedy the critical event; determining, based on the received user input, a first set of search parameters; for each of the search parameters in the first set of search parameters, selecting educational content for a first list of educational content from a second list of educational content; and displaying, on the user device, the first list of educational content based on the first set of search parameters.

Abstract: Disclosed are systems and methods for intelligently transforming data to generate improved output data, including, for example, for use in a multi-application network with disparate parties. The systems and methods include transforming data using a probabilistic network and a knowledge base generated using historic data to generate improved output data and include the steps of receiving first data associated with a first user and associated with a first incident object.

Abstract: A property is identified for inspection based on a determination of a weather event impacting the property. A flight plan usable by an unmanned aerial vehicle (UAV) in identifying an extent of damage to the property caused by the weather event is determined. A user interface is presented at a user device. The user interface includes user interface controls configured for toggling layers of the user interface. The layers include a first layer that includes a geofence, a second layer that includes an inspection area of the property, a third layer that includes one of a launch location or a landing location of the UAV, and a fourth layer that includes a base map layer of an area that includes the property. A modification to the flight plan is received via the user interface.

Abstract: Systems, methods, and computer-readable storage media utilized for revoking access to a financial account held by a customer of a financial institution. One method includes determining, by at least one processing circuit, an access level based on information stored in an account database and an adverse event experienced by a customer. The method further includes authorizing, by the at least one processing circuit, a designee of the customer comprising the access level for at least one future payment request. The method further includes transmitting, by the at least one processing circuit, an alert message corresponding to the authorization of the designee for the access level. The method further includes in response to receiving an input from a user device, withdrawing, by the at least one processing circuit, the access level.

Abstract: A system comprising 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, cause the one or more processors to perform operations: receiving telematics data from a mobile device during one or more vehicle trips including a previous epoch for a driver and a current epoch for the driver; generating a previous epoch score for the driver based on the telematics data of the previous epoch for the driver; generating, using a trained machine learning model, a predicted epoch score for the driver based on the telematics data of the current epoch for the driver; generating a hybrid epoch score for the driver from at least portions of the previous epoch score for the driver and the predicted epoch score for the driver; and transmitting the hybrid epoch score for the driver. Other embodiments are described.

Abstract: 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.

Abstract: A computer system performs live natural language processing (NLP) on data sources that are complex, remotely stored, and/or large, while satisfying restrictive time constraints. The computer system divides the NLP process into a batch NLP process and a live NLP process. The batch NLP process operates asynchronously over the relevant data set, which may be complex, remotely stored, and/or large, to summarize information into a summarized NLP data model. When the live NLP process is initiated, live NLP process receives as input the relevant information from the summarized NLP data model, possibly along with other data. The prior generation of the summarized NLP data model by the batch NLP process enables the live NLP process to perform NLP within time constraints that could not have been satisfied if the batch NLP process had not pre-processed the data set to produce the summarized NLP data model.

Abstract: Systems and methods for verification of information completeness are disclosed. They include a processor; a network; a network communication device; and a data store positioned in communication with the processor. The data store contains instructions that announce an association between a subject and an aggregator; record the association between the subject and the aggregator; submit a permission to allow a reporter to submit information regarding the subject to the aggregator; notify to the reporter of the permission; verify the permission granted to the reporter; submit the metadata to a datum of information to the aggregator by the reporter; submit the same datum of information to the subject by the reporter; provide a first aggregated report of all metadata tied to the datums from the aggregator; and provide a second aggregated report containing all the metadata and the datums associated with the first aggregated report.

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: Autonomous management of risk transfer is provided using an automated underwriting processor that creates a contract block by compiling the request into a computational graph-based format, links the contract block to the requester, stores the contract block into memory, retrieves a plurality of available underwriting agreements from memory, and creates an offer list by perform computational graph operations on the contract block to determine viable risk-transfer agreements; and presenting the offer list to the requester.

Abstract: Systems and methods provide for an automated system for determining whether claims related to an insured item should proceed to an arbitrating body. A virtual assistant (also referred to herein as an “arbitration assessment assistant”) installed in a computing device (e.g., computer, laptop, tablet computer, mobile phone, etc.) may be responsible for managing and assisting an insurance representative (e.g., an insurance adjuster, subrogation representative, etc.) in determining liability and fault relating to a claim, conducting a subrogation process, and ultimately determining whether the claim should be submitted for arbitration. In one or more aspects discussed, herein the process may be fully automated.

Abstract: Systems and methods are disclosed for dynamic policy lifecycle management. In one implementation, one or more specifications are processed with respect to one or more first product requirements to configure a first product model with respect to a first tenant. A first request is received from a first user and the first product model is identified based on the first request. A first policy instance is generated in association with the first product model. A second product model is generated with respect to the first tenant. A second request is received, including a request to change one or more aspects of the first policy instance. In response to the second request, an operation with respect to the first policy instance is initiated based on the association between the first policy instance and the first product model.

Abstract: A computer-implemented method obtains information related to a business process. The computer-implemented method may include (1) capturing business event information for a business event that occurs during the business process; (2) generating a unique identifier configured to identify the business event; (3) translating the business event information into a final event record including the unique identifier, the final event record being configured according to a common data structure; and (4) storing the final event record in a database for analysis. As such, the computer-implemented method permits business information to be captured from disparate business processes and to be stored in a common format to facilitate efficient and productive analysis.

Abstract: An on-demand insurance (ODI) server for generating dynamic user offerings may be provided. The ODI server may include at least one processor in communication with a memory device. The at least one processor may be programmed to (i) receive, from a user computing device associated with a user, an insurance policy request for a trip from a start location to an end location, (ii) determine at least one transportation mode available for the trip, (iii) access contextual data associated with the trip, (iv) assess a risk associated with the at least one transportation mode, (v) calculate a risk score associated with the at least one transportation mode based upon at least the contextual data, (vi) generate an insurance offering associated with the at least one transportation mode, and/or (vii) transmit the insurance offering in real time to the user computing device for purchase by the user.

Abstract: A system may include processor(s), a memory in communication with the processor(s), and storing instructions, that when executed by the processor(s), are configured to cause the system to prevent unnecessary payments. The system may receive a signal indicative of an event in which a user device associated with a user enters a geofenced area associated with a merchant. The system may identify a merchant category code (MCC) associated with the merchant, and determine whether benefit(s) related to the MCC are associated with account(s) of the user. The system may receive an attempted purchase associated with the merchant, and may determine whether the attempted purchase relates to the benefit(s). The system may automatically block the attempted purchase related to the benefit(s) and associated with the user, and may transmit a message to the user via the user device, the message providing the benefit(s).

Abstract: Dynamically adapting provision of notification output to reduce distractions and/or to mitigate usage of computational resources. In some implementations, an automated assistant application predicts a level of engagement for a user and determines, based on the predicted level of engagement (and optionally future predicted level(s) of engagement), provisioning (e.g., whether, when, and/or how) of output that is based on a received notification. For example, the automated assistant application can, based on predicted level(s) of engagement, determine whether to provide any output based on a received notification, determine whether to suppress provision of output that is based on the received notification (e.g.

Abstract: An example method of reimbursing pharmacy-related transactions includes receiving first data describing a transaction between a patient and a pharmacy. The transaction includes dispensing of a medication. A reimbursement data packet is determined based on the first data. The reimbursement data packet includes second data describing a reimbursement claim to be submitted to a payer system for the transaction. The reimbursement data packet is transmitted from the computer system to a plurality of other computer systems. A response is received from each of the other computer systems. Each response indicates whether a respective one of the other computer systems determined that the reimbursement claim is valid. A determination is made that the reimbursement claim is valid based on the responses. An entry describing the transaction and reimbursement claim is added to a ledger, and the reimbursement claim is submitted for fulfillment.

Abstract: A policy management system can manage a set of insurance policies, for example by performing automated operations to renew policies for subsequent terms. Some insurance policies may be associated with the same household, company, or other insured party, but may be associated with different cars or other insured elements. The policy management system can have a policy consolidator that identifies database records for a target policy and a related source policy, and can consolidate data from the source policy into the record of the target policy. Thereafter, the policy management system can perform policy renewal operations and other policy management operations together based on the consolidated data in the record for the target policy.

Abstract: Various methods, apparatuses, and media for implementing a customizable rules engine module are provided. A database stores data related to skill set of each user and data related to availability information of each user. A receiver receives data associated with each of a plurality of work items. A processor dynamically allocates, from the received data, both a score value to assign a priority to each work item and a bit-mapped skill value for each work item regardless of the source system from which each work item is being received or work type of each work item. The processor queries the database to identify a user having availability data and associated skill set data that matches with the score value and the bit-mapped skill value for each work item and automatically assigns the work item to the user.

Abstract: A computer-implemented method for analyzing a survivability of a structure is presented. A distance extending radially from the structure defining an area surrounding the structure may be determined. The area surrounding the structure may be scanned to identify surrounding objects. The area surrounding the structure may then be segmented to create a plurality of area segments. A density of surrounding objects in each of the plurality of area segments may be determined. A risk score for each of the plurality of area segments may then be determined based on the density of surrounding objects in each of the plurality of area segments. An overall wind exposure risk value may be provided for further use.

Abstract: A system may include a processor configured to receive a first set of data indicating a first period of time during which a item has a first status, and a second period of time during which the item has a second status. The processor may generate, based on the first set of data, a second set of data containing a plurality of logical rows, each indicating an encoded value of the first status of the item and an encoded value of the second status of the item during a respective period of time that is smaller than or equal to each of the first period of time and the second period of time. The processor may cause a display to present, based on the first set of data and the second set of data, statistical information of the first status and the second status during a third period of time.

Abstract: Methods, systems, and computer-readable media for the generation of real-time recommendations using natural language processing. The method receives a request for a benefit recommendation; generates at least one tag based on input data; extracts, based on the at least one tag, at least one observation and at least one action from the input data; predicts at least one recommendation based on the extracted at least one observation and the extracted at least one action in real time; and sends the at least one predicted recommendation for display to a user device.

Abstract: The present disclosure relates to a method and apparatus for split liability assessment of a car accident video using deep learning. The method for split liability assessment of a car accident video using deep learning according to an embodiment of the present disclosure may include: (a) obtaining car accident video data; and (b) outputting accidental split liability information by applying the obtained car accident video data to an accidental split liability determination model.

Abstract: Systems and methods are discussed for providing sensor enhanced safety, recovery, and activity evaluation systems. Sensors that monitor user activity and behavior are worn by a user and/or placed in the user environment. Data from the sensors are processed to obtain a safety, recovery, and/or activity evaluation. Based on the evaluation, recommendations or adjustments to the terms of an insurance policy covering the user, the user's employer, or a facility providing health care to the user, are generated, to accurately reflect the risks associated with the user, employer, and/or facility. In embodiments, an alert may be generated when a failure to conform with activity guidelines is detected.

Abstract: Systems, vehicles, and methods for ensuring an insurance policy is in place to cover use of a vehicle by an authorized user. A computing device associated with the vehicle executes computer-executable instructions to determine an identity of a user seeking to operate the vehicle and whether an insurance policy associated with the vehicle covers operation of the vehicle by the user. Responsive to a determination that the user is not associated with the insurance policy covering the use of the vehicle, operation of the vehicle by the user is enabled in response to a further determination that the user is covered by an existing insurance policy associated with the user that provides coverage for the operation of the vehicle by the user and an on-demand insurance policy secured by the user that provides coverage for the operation of the vehicle by the user.

Abstract: According to some embodiments, an automated scoring analysis computer may access information in a historical data store, including sets of attribute values and prior results for a plurality of prior associations, to create a scoring model. An indication of a selected potential association from a potential association data store may be received, including a set of attribute values. The scoring analysis computer may then calculate a risk score for the selected potential association based on the scoring model. A front-end application computer server may automatically select a workflow path from a plurality of potential workflow paths.

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.