Early Warning Services, LLC

Jie He

Laura E Weinflash

Deepakshi Aswal

Eric D First

Edwin F Campos Ortega

Robert Lawrence Hill

Robin S Love

James R Mortensen

Dan Hayden

Scott Leighton

Jinghong Qi

Matt Work

James Napier

Systems and methods are disclosed in assessing and determining the health of social tokens associated with certain events. More specifically, but not by way of limitation, this disclosure relates to determining dynamic scores associated with social tokens for senders and receivers in those events and using those scores to assess whether to allow or reject the event. An example embodiment may include receiving data associated with a sender including a social token associated with the sender, receiving account data associated with a plurality of accounts maintained at the entities, generating a health score for the social token associated with the sender, receiving data associated with an event initiated by the sender using the P2P account associated with the sender, generating a health score for the social token associated with the receiver, determining a health score for the event, determining that the event should be approved or declined based on the health score for the event, and if declined locking the application at the network device associated with the sender.

Systems and methods for determining the health of social tokens

A method of providing sentiment analysis includes training a computer system to identify a polarity of a sentiment for a plurality of phrases and receiving, at the computer system, an input from a website. The input includes a text string including a phrase. The method includes determining, by the computer system, the polarity of the sentiment of the phrase by comparing the phrase to the plurality of phrases and sending, by the computer system, a command to the website that causes the website to display predetermined content based on the determined polarity of the sentiment of the phrase.

Systems and methods of artificially intelligent sentiment analysis

A method of providing sentiment analysis includes aggregating, by a processor, a plurality of text-based comments, classifying, by the processor, the plurality of text-based comments as being associated with a polarity of sentiment, and generating, by the processor, a plurality of phrases from the plurality of text-based comments. The method also includes identifying, by the processor, a predetermined number of most common phrases for a particular polarity of sentiment from the plurality of phrases and outputting, by the processor, a graphic that includes the predetermined number of most common phrases for the particular polarity of sentiment.

Identity data for an applicant opening a bank account is provided to an ID confidence scoring system. The scoring system accesses a multi-source data management system, using queries that include a base component, a link component and a function component. Data records maintained by the multi-source data management system include header data having identity data elements, with the header data analyzed pursuant to the queries. Queries may also be provided to an entity resolution system having data records organized in data networks, each data network corresponding to a single entity. Query results are used to develop an ID confidence score for applicant identity data.

Identity confidence scoring system and method

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Naperville, IL, United States of America

Jie He