Abstract: A system includes an application programming interface, a database, and a server. The application programming interface can make recommendations to a user at a point of sale to display a recommended payment method from a set of payment methods associated with the user. The database can store past transactions for each payment method in the set of payment methods. The server can generate payment analytics by analyzing the past transactions in the database for each payment method. The server can determine potential benefits available to the user. The server can determine the recommended payment method by using the payment analytics and maximizing the potential benefits available to the user.

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: A device identifies one or more user interface elements, in a user interface, associated with a fixed positioning characteristic and not positioned within another user interface element with the fixed positioning characteristic. The device repositions the one or more user interface elements in the user interface to vacate space for a new user interface element based on a size of the new user interface element and forgo repositioning one or more other user interface elements in the user interface that do not have the fixed positioning characteristic or are positioned within another user interface element with the fixed positioning characteristic. The device inserts the new user interface element into the user interface in a portion of the user interface vacated in connection with repositioning the one or more user interface elements, and provides the user interface for display based on inserting the new user interface element into the user interface.

Abstract: The disclosed technology includes systems and methods for determining secondary authentication of a user's log-in attempts by comparing received behavioral biometric data and/or received scenario-specific data to saved behavioral biometric data and/or saved scenario-specific data, respectively. Responsive to determining that the received behavioral biometric data and/or received scenario-specific data is above a predetermined threshold of similarity with respect to the saved behavioral biometric data and/or saved scenario-specific data, respectively, the systems and methods can determine that the corresponding log-in attempt is secondarily authenticated. of a user device via behavioral biometric data. Responsive to determining that the level of similarity is not above the predetermined threshold, the systems and methods can initiate a secondary authentication method and can associate the received behavioral biometric data with a second user model.

Abstract: A device receives, from a user device, plan information that identifies a plan for an event and includes information identifying an account associated with the plan, plan items of the plan, and priorities and preferences associated with the plan items, where the user device is associated with a user of the account and the plan. The device receives transaction information identifying transactions associated with the account, and processes the plan information and the transaction information, with a first model, to identify transactions related to the plan. The device processes information associated with the particular plan item, the plan information, and the transaction information, with a second model, to determine recommendations for the plan, where the information associated with the particular plan item includes information identifying a priority and a preference associated with the particular plan item. The device provides information indicating the recommendations to the user device.

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: In certain embodiments, one or more images of an object may be received from a device associated with a first account on a communications network. Features of the object may be extracted based on the one or more images, and one or more content items related to the object may be determined based on the features. A hashtag associated with at least one of the features may be determined. A second account connected to the first account may be selected where the second account previously performed a search for the hashtag on the communications network, and at least one of the one or more content items may be provided to the second account.

Abstract: A device receives, from a user device, plan information that identifies a plan for an event and includes information identifying an account associated with the plan, plan items of the plan, and priorities and preferences associated with the plan items, where the user device is associated with a user of the account and the plan. The device receives transaction information identifying transactions associated with the account, and processes the plan information and the transaction information, with a first model, to identify transactions related to the plan. The device processes information associated with the particular plan item, the plan information, and the transaction information, with a second model, to determine recommendations for the plan, where the information associated with the particular plan item includes information identifying a priority and a preference associated with the particular plan item. The device provides information indicating the recommendations to the user device.

Abstract: The disclosed technology includes systems and methods for determining secondary authentication of a user's log-in attempts by comparing received behavioral biometric data and/or received scenario-specific data to saved behavioral biometric data and/or saved scenario-specific data, respectively. Responsive to determining that the received behavioral biometric data and/or received scenario-specific data is above a predetermined threshold of similarity with respect to the saved behavioral biometric data and/or saved scenario-specific data, respectively, the systems and methods can determine that the corresponding log-in attempt is secondarily authenticated. of a user device via behavioral biometric data. Responsive to determining that the level of similarity is not above the predetermined threshold, the systems and methods can initiate a secondary authentication method and can associate the received behavioral biometric data with a second user model.

Abstract: A device determines that a data breach of an application has been reported and determines that an individual has an account with the application based on identifying an association between an application identifier and a username the individual uses to access the application. The device receives, from a user device associated with the individual, password information used to access the application. The device uses the password information and usernames for a group of applications with which the individual has accounts to perform a login procedure for the group of applications to determine that login information for one or more of the applications includes the password information used to access the application affected by the data breach. The device provides, to the user device or another device, a recommendation to change the password information used to access the application and the one or more applications.

Abstract: A system includes an application programming interface, a database, and a server. The application programming interface can make recommendations to a user at a point of sale to display a recommended payment method from a set of payment methods associated with the user. The database can store past transactions for each payment method in the set of payment methods. The server can generate payment analytics by analyzing the past transactions in the database for each payment method. The server can determine potential benefits available to the user. The server can determine the recommended payment method by using the payment analytics and maximizing the potential benefits available to the user.

Abstract: A device identifies one or more user interface elements, in a user interface, associated with a fixed positioning characteristic and not positioned within another user interface element with the fixed positioning characteristic. The device repositions the one or more user interface elements in the user interface to vacate space for a new user interface element based on a size of the new user interface element and forgo repositioning one or more other user interface elements in the user interface that do not have the fixed positioning characteristic or are positioned within another user interface element with the fixed positioning characteristic. The device inserts the new user interface element into the user interface in a portion of the user interface vacated in connection with repositioning the one or more user interface elements, and provides the user interface for display based on inserting the new user interface element into the user interface.

Abstract: Systems for securing transactions based on merchant trust score are disclosed. The system may receive information identifying a merchant from a user device and, in response, retrieve transaction data associated with the merchant and receive website data in response to receiving information identifying the merchant. The system may use a machine learning model to generate a merchant trust score for the merchant, and determine whether the merchant trust score is less than a predetermined threshold. The system may also generate or retrieve an alternative payment method and provide related information or a recommendation to the user device.

Abstract: Embodiments disclosed herein generally related to a system and method for assessing a fraud risk. In one embodiment, a method for assessing a fraud risk is disclosed herein. A web browser extension executing on the computing device identifies an account associated with the computing device. The web browser extension detects that the computing device navigated to a web page hosted by a third party server. The web browser extension determines that the third party server prompted the computing device to opt into two-factor authentication functionality. The web browser extension determines that the computing device did not opt into the two-factor authentication functionality. The web browser extension prompts, via an application programming interface (API), an organization computing system to update a fraud metric associated with the account.

Abstract: Systems for securing transactions based on merchant trust score are disclosed. The system may receive information identifying a merchant from a user device and, in response, retrieve transaction data associated with the merchant and receive website data in response to receiving information identifying the merchant. The system may use a machine learning model to generate a merchant trust score for the merchant, and determine whether the merchant trust score is less than a predetermined threshold. The system may also generate or retrieve an alternative payment method and provide related information or a recommendation to the user device.

Abstract: Embodiments disclosed herein generally related to a system and method for assessing a fraud risk. In one embodiment, a method for assessing a fraud risk is disclosed herein. A web browser extension executing on the computing device identifies an account associated with the computing device. The web browser extension detects that the computing device navigated to a web page hosted by a third party server. The web browser extension determines that the third party server prompted the computing device to opt into two-factor authentication functionality. The web browser extension determines that the computing device did not opt into the two-factor authentication functionality. The web browser extension prompts, via an application programming interface (API), an organization computing system to update a fraud metric associated with the account.

Abstract: A device identifies one or more user interface elements, in a user interface, associated with a fixed positioning characteristic and not positioned within another user interface element with the fixed positioning characteristic. The device repositions the one or more user interface elements in the user interface to vacate space for a new user interface element based on a size of the new user interface element and forgo repositioning one or more other user interface elements in the user interface that do not have the fixed positioning characteristic or are positioned within another user interface element with the fixed positioning characteristic. The device inserts the new user interface element into the user interface in a portion of the user interface vacated in connection with repositioning the one or more user interface elements, and provides the user interface for display based on inserting the new user interface element into the user interface.

Abstract: The disclosed technology includes systems and methods for determining secondary authentication of a user's log-in attempts by comparing received behavioral biometric data and/or received scenario-specific data to saved behavioral biometric data and/or saved scenario-specific data, respectively. Responsive to determining that the received behavioral biometric data and/or received scenario-specific data is above a predetermined threshold of similarity with respect to the saved behavioral biometric data and/or saved scenario-specific data, respectively, the systems and methods can determine that the corresponding log-in attempt is secondarily authenticated. of a user device via behavioral biometric data. Responsive to determining that the level of similarity is not above the predetermined threshold, the systems and methods can initiate a secondary authentication method and can associate the received behavioral biometric data with a second user model.

Abstract: A device identifies one or more user interface elements, in a user interface, associated with a fixed positioning characteristic and not positioned within another user interface element with the fixed positioning characteristic. The device repositions the one or more user interface elements in the user interface to vacate space for a new user interface element based on a size of the new user interface element and forgo repositioning one or more other user interface elements in the user interface that do not have the fixed positioning characteristic or are positioned within another user interface element with the fixed positioning characteristic. The device inserts the new user interface element into the user interface in a portion of the user interface vacated in connection with repositioning the one or more user interface elements, and provides the user interface for display based on inserting the new user interface element into the user interface.

Abstract: The disclosed technology includes systems and methods for determining secondary authentication of a user's log-in attempts by comparing received behavioral biometric data and/or received scenario-specific data to saved behavioral biometric data and/or saved scenario-specific data, respectively. Responsive to determining that the received behavioral biometric data and/or received scenario-specific data is above a predetermined threshold of similarity with respect to the saved behavioral biometric data and/or saved scenario-specific data, respectively, the systems and methods can determine that the corresponding log-in attempt is secondarily authenticated. of a user device via behavioral biometric data. Responsive to determining that the level of similarity is not above the predetermined threshold, the systems and methods can initiate a secondary authentication method and can associate the received behavioral biometric data with a second user model.