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: Example embodiments of systems and methods for card production are provided. A card may include processing circuitry including a chip and memory. The card may include one or more antennas in communication with the chip. The card may include a first layer of material aligned within a perimeter of the card via laminate encapsulation. The first layer of material may comprise a non-rectangular shape. The first layer of material may be offset with a shape of the card. The first layer of material may be in communication with the chip. The first layer of material may comprise at least one selected from the group of steel, tungsten, titanium, or any combination thereof. The card may be compliant with one or more form factors.

Abstract: Disclosed embodiments may include systems and methods for providing modified order recommendations. Line item data from a set of transactions associated with a vendor can be collected. The line item includes transactional data such as price, quantity, and frequency. The set of transactions are associated with a plurality of customers of the vendor. Correlations between line item data can be determined via one or more machine learning techniques to train a recommendation model. An order recommendation to a customer can be determine based on the correlations of the recommendation model. An order of the customer can be modified according to the order recommendation.

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: 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 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: Systems and methods of the present disclosure enable intelligent dynamic caching of data by accessing an activity history of historical electronic activity data entries associated with a user account, and utilizing a trained entity relevancy machine learning model to predict a degree of relevance of each entity associated with the historical electronic activity data entries in the activity history based at least in part on model parameters and activity attributes of each electronic activity data entry. A set of relevant entities are determined based at least in part on the degree of relevance of each entity. Pre-cached entities are identified based on pre-cached entity data records cached on the user device, and un-cached relevant entities from the set of relevant entities are identified based on the pre-cached entities. The cache on the user device is updated to cache the un-cached entity data records associated with the un-cached relevant entities.

Abstract: In some embodiments, the present disclosure provides an exemplary method that may include steps of obtaining a trained spam upsurge detection machine learning model that determines when a current frequency associated with spam communications received by a current user exceeds a baseline frequency associated with the current user; receiving a permission indicator identifying a permission by the user to detect communications being received by the computing device; receiving an indication of at least one communication being received; determining the at least one communication as a particular spam communication; updating a frequency at which spam communications have been received by the user based at least in part on the particular spam communication; utilizing the trained spam upsurge detection machine learning model to determine that the frequency exceeds a baseline frequency associated with the user; and initiating a scan of one or more dark web resources.

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: 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: Systems and methods of caller identity verification and notification are disclosed. In one embodiment, an exemplary computer-implemented method may include: configuring a notification application, executing at a first computing device associated with a first user, the first user associated with an entity; receiving, from the notification application executing on the first computing device, an indication when the first user initiates a particular call to a second user; determining an application associated with the entity and installed on the second computing device of the second user, the application having an icon displayed at a screen of the second computing device; and instructing the application, executing on the second computing device, when the second computing device has received the particular call from the first user, to update an appearance of the icon associated with the application to display an indicator with regard to that the first user is associated with the entity.

Abstract: Systems and methods of the present disclosure enable split communication routing. A communication request associated with an electronic activity is received, the communication request specifying a virtual token and a data content, where the virtual token is a proxy for multiple actual data source profiles. A split rule defining a proportion of the data content to be attributed to each actual data source profile is determined. A security score is determined based on each actual data source profile and each proportion of the data content. The communication request is authorized based on the security score exceeding a threshold security score and access to the proportion of the data content in each actual data source profile is enabled. Each proportion of the data content is consolidated into a single response, and the electronic activity is executed with the single response.

Abstract: The present disclosure provides an exemplary method, system, and computing device that may include the steps of receiving a first indication that information of a user has been detected at one or more dark web resources; classifying the item of the compromised information into an information type category; receiving a permission indicator to detect communications by the computing device; receiving a second indication of a communication; receiving a third indication that the user engages an interaction with the communication; instructing the computing device to execute a technique to obtain data for the communication; receiving the data for the communication; determining the communication is a spam communication; determining a current information type category being discussed during the spam communication; making a determination that the current information type category corresponds to the information type category; and instructing a graphical user interface to display an alert to the user.

Abstract: Systems and methods of location-aware caller identification via machine learning techniques are disclosed. In one embodiment, an exemplary computer-implemented method may include: utilizing a trained call annotation machine learning model to determine one or both of an annotating condition and annotating location granularity, and associate one location of a user with one phone number of the user based at least on one or both of the annotating condition and the annotating location granularity; receiving second transactional information of one transaction associated with a first user; extracting second location information from the second transactional information of the one transaction; utilizing the trained call annotation machine learning model to automatically annotate one phone number record of one phone number of the first user, with the second location information at the annotating location granularity to form at least one user-specific location-specific annotated phone number record.

Abstract: A computer-implemented method comprising: instructing a computing device to obtain a permission from the user to monitor a plurality of activities executed within the computing device; receiving a call session request from a computing device associated with a second user; utilizing a trained machine learning algorithm to confirm an identity of the user based on the call session interaction parameter to confirm the call interaction session as a verified call interaction session; generating a fictitious call session interaction parameter that differs from the at least one call session interaction parameter; modifying the call session request into a verified call session request by replacing the call session interaction parameter with the fictitious call session interaction parameter; utilizing a telecommunication network to transmit the verified call session request with the at least one fictitious session interaction parameter to the first calling-enabled computing device; automatically instructing the first c

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 of caller identity verification and notification are disclosed. In one embodiment, an exemplary computer-implemented method may include: configuring a notification application, executing at a first computing device associated with a first user, the first user associated with an entity; receiving, from the notification application executing on the first computing device, an indication when the first user initiates a particular call to a second user; determining an application associated with the entity and installed on the second computing device of the second user, the application having an icon displayed at a screen of the second computing device; and instructing the application, executing on the second computing device, when the second computing device has received the particular call from the first user, to update an appearance of the icon associated with the application to display an indicator with regard to that the first user is associated with the entity.

Abstract: The present disclosure provides an exemplary method, system, and computing device that may include the steps of receiving a first indication that information of a user has been detected at one or more dark web resources; classifying the item of the compromised information into an information type category; receiving a permission indicator to detect communications by the computing device; receiving a second indication of a communication; receiving a third indication that the user engages an interaction with the communication; instructing the computing device to execute a technique to obtain data for the communication; receiving the data for the communication; determining the communication is a spam communication; determining a current information type category being discussed during the spam communication; making a determination that the current information type category corresponds to the information type category; and instructing a graphical user interface to display an alert to the user.

Abstract: Systems, methods, and non-transitory computer readable medium disclosed herein relate to identity verification and authorization method. In one embodiment, the system can generate and send a message to a device associated with a user based on an initiated request from the user and a determination the user should be authenticated, wherein the message requests a content-based response from the user to authenticate the user. In another embodiment, the system can receive the content-based response from the user in reply to the message, wherein the content-based response comprises SMS (short message service) metadata, emoji, photo, video, audio, or a combination thereof. In another embodiment, the system can authenticate the user based on a determination of a confirmed match between the content-based response from the user and a response key preselected by the user.

Abstract: Disclosed herein are systems and methods for account status monitoring. The method can include receiving user registration information and account information corresponding to a first user account. The account information can include first user credit information. The method can include analyzing, by a machine learning rules engine, the account information and the user registration information to create a user behavior pattern associated with the first user account. The method can further include determining an anomaly in the user behavior pattern indicative of a life event. Based on the life event and the user registration information, the method can determine a second user account and corresponding account information comprising second user credit information. In response, the method can include predicting, by a convolutional neural network, an effect on the second user credit information resulting from the transfer of the first user credit information to the second user account.