Abstract: In some implementations, a server may receive, from a first user, an indication of a first set of times and receive, from the second user, an indication of a second set of times. The server may determine a first location associated with the first user and a second location associated with the second user. Accordingly, the server may identify a set of events based on the first location, the second location, the first set of times, and the second set of times. The server may further select a subset of events, from the set of events, based on first event data associated with the first user and second event data associated with the second user. Based on a selected event from the subset of events, the server may identify an API associated with the selected event and may trigger a call to the identified API.

Abstract: A device may receive a VCN generation request comprising a primary account number (PAN) and an approved URL. A device may generate a VCN based on the PAN, the VCN being associated with the approved URL. A device may receive a VCN use request from an external entity, the VCN use request comprising the VCN. A device may receive a use request URL associated with the VCN use request. A device may compare the use request URL to the approved URL. A device may provide a VCN use decision based on the comparing the use request URL to the approved URL, the VCN use decision including a VCN use authorization or a VCN use denial.

Abstract: Systems and methods of the present disclosure enable virtual tokens for dynamically mapping virtual account numbers to actual accounts. The systems and methods include receiving an electronic data modification instruction of a virtual record modification to cause at least one data modification to at least one attribute of a virtual record data structure associated with the actual account. A user record associated with the virtual record is determined, and a record modification preference associated with the user record is determined based on the modification condition. An authorization instruction is generated to authorize the electronic data modification instruction to cause the modification by instructing at least one database management system to modify the user record according to the record-specific modification.

Abstract: Systems and methods for delayed interaction with an entity are disclosed. A method includes receiving data packets including data associated with an interaction between a user device and an entity. The data may include a completion date for the interaction and authentication data executable to activate the interaction with the entity. The method further includes receiving activation timing information from the entity comprising an estimated duration between an activation and a completion of the interaction. The method also includes generating, with reference to the activation timing information, primed activation data that includes the estimated activation date such that the interaction is complete by the completion date. On the estimated activation date, the primed activation data is activated, which includes accessing the entity using the authentication data, and executing the interaction with the entity on the estimated activation date.

Abstract: Systems and methods for training a machine learning model by extracting targets from records are disclosed. A method includes receiving data packets including data associated with previous interactions of a user, determining at least one party to the previous interactions with whom the user interacted at a level above a threshold, and comparing the at least one party to a plurality of parties identified in a target database to identify at least one potential target, for each potential target, determining a respective target metric by inputting the data packets into a machine learning model, providing an identification of the at least one potential target, with reference to the respective target metrics, to a user device associated with the user, receiving, via the user device, feedback regarding the identification, and training the machine learning model based on the feedback.

Abstract: In some embodiments, the present disclosure provides an exemplary method that may include steps of receiving a notification to engage a transmission guard bot in a communication session; generating a trained transmission guard bot configured with communication capabilities to engage the communication session; engaging the trained transmission guard bot into the communication session between the plurality of computing devices associated with the plurality of users; utilizing the trained transmission guard bot to continually monitor a plurality of content data associated with the communication session for a predetermined period of time; detecting a suspicious content data point within the plurality of content data associated with the communication session based on the continual monitoring of the at least one transmission guard bot; determining a risk assessment metric associated with the communication session; and invoking an action related to spam prevention via the at least one trained transmission guard bot.

Abstract: In some implementations, a style system may receive, from a repository, a plurality of files associated with an entity. The style system may apply a machine learning model to the plurality of files to determine a set of rules associated with images or text included in the plurality of files. The style system may generate a document that indicates the set of rules and may output, to a user device, the document.

Abstract: A computer-implemented method for recordation of interaction data is disclosed. The method may include causing, via a remote device, a first electronic application operating on a user device to: monitor activity of a second electronic application operating on the user device; detect, based on the monitoring, an interaction between a user of the user device and an entity via the second electronic application; extract interaction data associated with the detected interaction from the second electronic application; and transmit the extracted interaction data to the remote device.

Abstract: Systems and methods are described herein for novel uses and/or improvements to artificial intelligence applications. As one example, systems and methods are described for the use of an artificial intelligence-based solution in identifying fraudulent documents and/or other content. In particular, the systems and methods adapt the artificial intelligence-based solution to overcome the technical problem of insufficient training data and/or solutions that are commensurate with the time frame and resources available.

Abstract: Disclosed embodiments may include a system for converting a physical meeting into a virtual meeting. The system may receive scheduling and location data associated with a first user. The system may determine whether the first user has an upcoming meeting at a physical location, and responsive to such determination, may determine a proximity of the first user to the upcoming meeting. The system may determine, by an MLM and based on the proximity, a probability that the first user will be late to the upcoming meeting. The system may determine whether the probability exceeds a predetermined threshold, and responsive to such determination, may convert the upcoming meeting to a virtual meeting by generating a virtual meeting link, and may transmit, to user device(s), a notification comprising the virtual meeting link.

Abstract: In some implementations, a user device may receive one or more first advertisements from one or more first beacons. Accordingly, the user device may exchange check-in messages with a remote device based on the one or more first advertisements. The user device may track a location using at least one or more signal strengths associated with the one or more first beacons and one or more signal strengths associated with one or more second beacons. The user device may further display and update a map based on tracking the location. The user device may receive one or more second advertisements from the one or more second beacons. Accordingly, the user device may request first information associated with the one or more second beacons that is different from second information associated with one or more third beacons. The user device may further display the first information.

Abstract: Disclosed are methods and systems for targeted link sharing. For instance, a sharable link may be detected on a sharing user's computing device, and one or more users associated with the sharing user may be determined to be suitable to use the link. For each suitable user, an interaction history of the user, a code use behavior of the user, and information associated with the code are provided as inputs to a trained machine learning system to obtain, as output, a likelihood that the user uses the code. Each suitable user determined to have the output meet a predefined criterion may be included in a list of receiving users for display within a notification on the sharing user's computing device. The link may be distributed to a computing device of at least one receiving user selected from the list to share the link.

Abstract: Disclosed are methods and systems for prioritization and/or validity monitoring of shared links. For instance, a share request for a link associated with a site may be received from a sharing user computing device. The link and associated information, including a valid status, may be stored. An interaction with the site on a receiving user computing device may be detected, and the link may be determined to be valid based on the stored information. A notification including the stored link may be generated and displayed on the receiving user computing device to prompt code use. Interactions indicating code use may be monitored for, code use may be detected, and the status may be updated to invalid. If a plurality of links associated with the site have been received, the links may be prioritized for inclusion in the notification based on a determined priority among sharing users of the links.

Abstract: In some implementations, a device may obtain video and/or lidar data relating to a physical card captured while the physical card is flipped from a first side of the physical card to a second side of the physical card. The device may determine an authenticity of the physical card, where the authenticity of the physical card is based at least in part on one or more physical characteristics of the physical card identifiable from the video and/or the lidar data. The one or more physical characteristics may relate to a thickness of the physical card, a length and width of the physical card, a shape of the physical card, and/or a design feature of the physical card. The device may cause, based on a determination that the physical card is authentic, information associated with the physical card to be transmitted or stored to be used in connection with a transaction.

Abstract: Disclosed aspects and embodiments pertain to customer distress assistance. A call can be detected to a callee from a caller. The call can be analyzed and determined to be a fraud or spam risk. In response, callee monitoring is triggered. The monitoring can capture biometrics or speech of the callee. Distress in the callee can be determined through analysis of the biometrics or speech and comparison to reference biometrics or speech of the callee. An individual associated with the callee can be selected based on determining the distress in the customer. The individual can be contacted through a notification or a call to assist the callee in distress.

Abstract: A device may configure a browser to permit cash payments for online transactions. The device may monitor a browser session of the browser. The device may detect, during the browser session, navigation of the browser to a transaction page of a website. The transaction page may be configured to facilitate an online transaction with the website. The device may determine, based on detecting the navigation of the browser to the transaction page, that a cash payment is to be provided. The device may cause a validation code to be generated. The device may cause, based on the validation code being processed, a virtual transaction card to be generated. The device may facilitate, using virtual card information associated with the virtual transaction card, execution of the online transaction.

Abstract: In some implementations, a device may obtain video and/or lidar data relating to a physical card captured while the physical card is flipped from a first side of the physical card to a second side of the physical card. The device may determine an authenticity of the physical card, where the authenticity of the physical card is based at least in part on one or more physical characteristics of the physical card identifiable from the video and/or the lidar data. The one or more physical characteristics may relate to a thickness of the physical card, a length and width of the physical card, a shape of the physical card, and/or a design feature of the physical card. The device may cause, based on a determination that the physical card is authentic, information associated with the physical card to be transmitted or stored to be used in connection with a transaction.

Abstract: A computer-implemented method for authenticating a source of a telephone call to a recipient of the telephone call may include receiving, prior to receiving the telephone call, a request to input first authentication information. The first authentication information may include a passcode or a selection of a security question. The method may include receiving input of the first authentication information and sending, by the user device, the first authentication information to a computing device associated with the source of the telephone call. The method may include receiving the telephone call from the source and receiving input from the recipient of the telephone call to answer the telephone call. The method may include receiving second authentication information from the computing device, where the second authentication information may include the passcode or an answer to the security question. The method may include outputting the second authentication information.

Abstract: A computer-implemented method for transmitting electronic data. The method may include receiving a user data set for a user, wherein the user data set includes a user identifier and one or more user authentications for one or more entities, each entity of the one or more entities having an entity eco-friendly score, determining a user eco-friendly score for the user based on the one or more user authentications and a respective one or more entity eco-friendly scores, modifying a data store server to store the user identifier and the eco-friendly score for the user, generating a targeted event associated with a user medium, based on the user eco-friendly score, and transmitting, to a user device of the user, the targeted event via the user medium.

Abstract: Systems and methods for preventing fraud using behavioral biometrics may include a server with memory and a processor. The processor may be configured to create a behavioral biometric use-print for a user based on a plurality of observed and recorded user interactions and then monitor one or more behavioral biometrics of the user while the user accesses a user account. These monitored behavioral biometrics may be compared against the behavioral biometric use-print to determine if there are material deviations indicating that the user is under stress. When the server determines that the user is under stress, it may provide an intervention to help safeguard against potential in-process fraud.