Abstract: Disclosed embodiments may include a system for generating aggregate records. The system may retrieve data corresponding to a first user. The system may receive, from the first user, first sharing preference(s) associated with a second user. The system may extract first data subset(s) from the data based on the first sharing preference(s). The system may generate block(s) of a blockchain ledger. The system may append the first data subset(s) to at least a first block of the block(s) of the blockchain ledger. The system may provide the second user with access to the first data subset(s) on the at least first block.

Abstract: The present disclosure provides systems and methods for predictive modeling to facilitate peer-to-peer distributed guarantor marketplaces. Example embodiments provide for generating a predictive model configured to calculate a coverage amount associated with a lease agreement. Example embodiments further provide for collecting lease information, gathering responses from guarantors, analyzing lease information and the guarantor responses, generating a predictive model, and calculating a coverage amount.

Abstract: In some implementations, a device may obtain interaction data for an evaluator in a communication session with an individual based on interactions of the evaluator with the individual during the communication session, wherein the evaluator is to provide the evaluation of the individual. The device may obtain evaluation information identifying the evaluation of the individual by the evaluator. The device may determine a degree of bias of the evaluator toward the individual during the communication session based on at least the interaction data. The device may adjust the evaluation of the individual based on the degree of bias of the evaluator.

Abstract: Systems and methods for implementing a single step processing for two-step transactions involving an initial and a final amount. The proposed systems and methods incorporates a built-in logical operations and parameter acquisition scheme for identification of two-step transaction and internal computation of the final amount based on user specified logical operations and input parameters. Data values, corresponding to the input parameters, may be dynamically extracted from the transactions string and/or obtained from one or more applications running on the user device, and subsequently, processed with the specified logical operations to generate a final transaction amount from the initial transaction amount referenced in the transaction request. The final transaction amount may then be validated and a single authentication response transmitted to a payment gateway initiating the request.

Abstract: Systems and methods of the present disclosure enable database search. The systems and/or methods may include receiving a search query that includes an input document having text. Word embeddings are generated within the input document, where the word embeddings include vector representations of words in the text of the input document. An average input document word embedding vector is determined for the word embeddings of the input document. A set of stored documents is accessed, where each stored document includes a stored text has a particular average stored document word embedding vector. A similarity model is used to determine a similarity metric measuring the similarity between the input document and each stored document based on the average input document word embedding vector and the particular average stored document word embedding vector of each stored document.

Abstract: Systems and methods of context-aware caller identification via machine learning techniques are disclosed.

Abstract: Systems and methods of caller identification differentiation via machine learning techniques are disclosed. In one embodiment, an exemplary computer-implemented method may include: receiving a permission indicator identifying a permission by the user to detect calls being received by a computing device; receiving an indication of a current call being received; utilizing a trained call differentiation machine learning model to determine a likelihood that the current call is of a first call type or a second call type, where the first call type is associated with a first type of activity and the second call type is associated with a second type of activity.

Abstract: Methods and systems are described herein for manipulating a communication acceptance screen, manipulating an interactive communication acceptance icon, and restricting access to accounts based on voice communication parameters. In particular, when a communication is detected from one device to another device, that communication may be risky. Thus, the risk is mitigated by giving a user information about the source of the communication to give a user a chance to reject the communication. In addition, in instances where the user accepts the communication, the system enables monitoring the communication and restricting any accounts that are disclosed within the communication.

Abstract: Systems and methods for decision-making with multi-channel data inputs are provided. The system includes a plurality of devices, and a server in data communication with the plurality of devices. The server includes a decision engine, a sentiment analysis machine learning model, and a behavior analysis machine learning model. The server is configured to: receive the at least one data input from each of the plurality of device; perform, using the sentiment analysis machine learning model, a sentiment analysis on the at least one data input to generate sentiment information indicative of an emotional state of a user; perform, using the behavior analysis machine learning model, a behavior analysis on the at least one data input to generate behavior information indicative of a behavioral state of the user; determine, using the decision engine, a responsive action based on the sentiment information and the behavior information; and perform the responsive action.

Abstract: Disclosed embodiments may include a method for generating a trip plan with trip recommendations. The method may include generating and transmitting a graphical user interface to a user device and receiving, from the user device, criteria, which is then used to retrieve candidate data. The criteria and candidate data may then be used to generate potential leads using a machine learning model. The method may include generating a graphical user interface to display the potential leads and receive timing and preference data from the user. The method may further include generating, using a machine learning model, a plan based on the potential leads and other data. The plan may be presented to a user via graphical user interface, which may be used to modify and update the plan. The plan may be stored and accessed by the user at a later time through a user device.

Abstract: In some implementations, a device may determine an interaction profile for a provider that is to engage with a user in a communication session. The interaction profile may be based on interaction data relating to interpersonal interactions involving the provider during one or more previous communication sessions. The interaction profile may indicate a bias of the provider in connection with one or more categories of users. The device may generate, based on the interaction profile, a visual representation that depicts at least a face of a person for presentation to the provider during the communication session. One or more characteristics associated with the one or more categories of users may be absent from the face of the person. The device may cause presentation of the visual representation to the provider during the communication session.

Abstract: Systems and methods for providing variable and temporary access to account content for a user in a secured manner through the use of an access token with variable properties are described. The systems and methods provide improved navigability to account content accessed via the access token through the customization of user interfaces. For example, the system and methods may generate user interface templates that comprise a recommended selection and organization of user input fields and/or user interface pages.

Abstract: Systems and methods for providing variable and temporary access to account content for a user in a secured manner through the use of an access token with variable properties are described. The systems and methods provide improved navigability to account content accessed via the access token through the customization of user interfaces. For example, the system and methods may generate user interface templates that comprise a recommended selection and organization of user input fields and/or user interface pages.

Abstract: In some embodiments, the present disclosure provides an exemplary method that may include steps of obtaining a permission from the user to monitor a plurality of activities executed within the computing device; continually monitoring the plurality of activities executed within the computing device for a predetermined period of time; identifying an indication of an incoming interaction session within the predetermined period of time; verifying at least one session interaction parameter associated with the incoming interaction session to identify the incoming interaction session as a repeat interaction session; dynamically retrieving at least one relation-specific notation from a plurality of relation-specific notations to display; instructing an input GUI element to display input data associated with the repeat interaction; automatically updating the plurality of relation-specific notations associated with the historical data relationship; and instructing at least one programmable output GUI to display a notif

Abstract: Disclosed herein are system, method, and computer program product embodiments for recommending a service provider. An embodiment operates by receiving a search request specifying a service request by a user and location for the requested service, retrieving prior financial transactions of the user to purchase the service from a database, and determining a preference of the user based on the retrieved prior financial transactions. The embodiment further operates by applying the preference to a model trained to output a recommended service provider and selecting the recommended service provider for display on a user's device. The model more likely recommends service providers in the location having a higher ratio of tip-to-price relative to other providers for the service in the location based on a history of prior financial transactions of a plurality of users.

Abstract: Methods and systems are described herein for manipulating a communication acceptance screen, manipulating an interactive communication acceptance icon, and restricting access to accounts based on voice communication parameters. In particular, when a communication is detected from one device to another device, that communication may be risky. Thus, the risk is mitigated by giving a user information about the source of the communication to give a user a chance to reject the communication. In addition, in instances where the user accepts the communication, the system enables monitoring the communication and restricting any accounts that are disclosed within the communication.

Abstract: A processor may receive data and generate a quantified representation of the data by processing the data using at least one machine learning (ML) algorithm, the quantified representation of the data indicating a sentiment of content of the data. The processor may automatically revise the content of the communications data. The revising may include determining a reaction to the content of the communications data, generating a quantified representation of the reaction, determining a difference between the quantified representation of the reaction and the quantified representation of the communications data, identifying, based on the difference, a portion of the content having an unintended sentiment, and replacing the portion of the content with different content.

Abstract: Systems and methods for decision-making with multi-channel data inputs are provided. The system includes a plurality of devices, and a server in data communication with the plurality of devices. The server includes a decision engine, a sentiment analysis machine learning model, and a behavior analysis machine learning model. The server is configured to: receive the at least one data input from each of the plurality of device; perform, using the sentiment analysis machine learning model, a sentiment analysis on the at least one data input to generate sentiment information indicative of an emotional state of a user; perform, using the behavior analysis machine learning model, a behavior analysis on the at least one data input to generate behavior information indicative of a behavioral state of the user; determine, using the decision engine, a responsive action based on the sentiment information and the behavior information; and perform the responsive action.

Abstract: Systems and methods of context-aware caller identification via machine learning techniques are disclosed. In one embodiment, an exemplary computer-implemented method may comprise: obtaining a trained call verification machine learning model that determines when a phone number is associated with a service provider that is associated with a delivery portion of a user activity with an entity within a time window; receiving, from a computing device of a first user, an indication of a communication being received from a second user; receiving activity information of a particular activity associated with the first user and a particular entity; utilizing the trained call verification machine learning model to determine, based at least in part on the activity information and the communication, that the second user is the particular service provider that is associated with a delivery portion of the particular activity associated with the particular entity.

Abstract: Systems and methods of video password based user authentication via machine learning techniques are disclosed. In one embodiment, an exemplary computer-implemented method may comprise: receiving a request to register a video password from a first user; establishing at least one user-specific authentication criterion for the first user based on first video password data; receiving a login attempt from a second computing device associated with a second user who submits to be the first user, the login attempt comprising second video password data; utilizing a trained video password authentication machine learning model to determine a first comparison result and a second comparison result based on the first and second video password data, and accepting or rejecting the login attempt based on at least one of the first comparison result and the second comparison result.