State Farm Mutual Automobile Insurance Company

United Services Automobile Association (usaa)

William Guthrie

Bharat Prasad

Michael Shawn Jacob

Sharon Kay Haverlah

Nolan White

Karen Marie Shackelford-George

Timothy J Nickel

Dustin Helland

Brian William Batronis

Kyle D Weber

Edward Austin

Robert D Rariden

Frank Matthew McCully

Ryan Maurer

Benjamin D Schappaugh

Aspects of distributed ledger technology are leveraged to verify subrogation settlements. In particular, two parties to a subrogation claim provide cryptographic hashes to a subrogation demand smart contract stored at an address on a blockchain. The subrogation demand smart contract determines that the parties have reached an agreement by determining that the cryptographic hashes match. A settlement amount from the subrogation claim may be appended to a set of settlement amounts to determine a net settlement amount to facilitate a single payment between the parties on a periodic basis, such as daily, to alleviate the need for the parties to send or receive a payment for each individual settlement amount.

Net settlement of subrogation claims using a distributed ledger

Techniques for identifying faults in a collaborative computing system including a plurality of disparate, geographically separated computing systems are described herein. An intelligent monitoring (IM) server computing system may receive data from the plurality of computing devices and may monitor the health of the collaborative computing system. The IM server computing system may analyze the data and identify one or more faults associated with a portion of the collaborative system (e.g., an associated computing device, platform, network, etc.). In some examples, the IM server computing system may be configured to identify potential future faults associated with the portion of the collaborative system. Based on the fault, the IM server computing device may determine an action to take to remedy the fault and/or prevent the potential future fault. The IM server computing device may either automatically perform the action or send a notification to the associated computing system to perform the action.

Error monitoring and prevention in computing systems based on future fault prediction and historical values of a network characteristic

Techniques for providing recommendations of actions for a user to perform to improve efficiency in user interactions with a user interface of a user computing device. An intelligent monitoring (IM) computing system may receive data from a user computing device and may determine user interactions associated with the user interface. The user interactions may include selections, an order associated with the selections, times associated with the selections, and/or other data corresponding to user interaction with a user interface. The IM computing device may be configured to determine a fault (e.g., inefficiency) associated with the user interactions and determine an action for the user to perform to correct the fault. The IM computing device may cause a notification including the action to surface on a display of the user computing device, such as to inform the user of a means by which they can improve efficiency of the user interactions.

Intelligent user interface monitoring and alert

Error monitoring and prevention in computing systems based on determined trends and routing a data stream over a second network having less latency

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Mesa, AZ, United States of America

William Guthrie