Bank of America Corporation

Nathan Alexander Dalpini

Richard Scot

Peter George Kurrasch

Stephen Jack Williams

Rebecca Lynn Pietro

John Shelton

Abelardo Espinoza

Vani Reddy Nareddy

Tomas Mata Castrejon, Iii

James J Siekman

An apparatus for security management of a plurality of interactions comprises a processor operable to receive a plurality of interactions, where each interaction comprises interaction information associated with at least one of a plurality of users and a first entity. The processor is operable to determine a threshold value of the plurality of interactions and a threshold volume of the plurality of interactions, determine that a value of each of the plurality of interactions has not exceeded the threshold value of the plurality of interactions, and determine that the plurality of interactions has not exceeded the threshold volume of the plurality of interactions. The processor is operable to determine a number of instances of the plurality of interactions that were invalid, determine that the number of instances of the plurality of interactions that were invalid exceeds a threshold, and determine that the first entity is associated with suspicious indicators.

System and method for security management of a plurality of invalid interactions

Systems, methods, and computer program products are provided for detecting a synthetic identity. The method includes receiving an identity verification request relating to an individual. The identity verification request includes one or more individual identifiers of the individual. The method also includes comparing at least one of the one or more individual identifiers to one or more known synthetic indicators. The one or more known synthetic indicators including at least one of a synthetic identifier type or a synthetic identifier value that correspond to one or more known synthetic identities. The method further includes determining a synthetic identity determination based on the comparison of the at least one of the one or more individual identifiers to the one or more known synthetic indicators. The synthetic identity determination indicates whether an identity verification request is a potential synthetic identity.

Systems and methods for detection of synthetic identity malfeasance

A system for predicting an anomalous request comprises a processor associated with a server. The processor is configured to generate a first set of data objects associated with a first user profile. The processor is configured to compare the first set of the data objects to approved data and audit data to generate a second set of data objects with a set of anomalous data indicators for the first user profile. The processor is further configured to process the second set of the data objects through an anomaly learning model to determine a predictive degree of approval associated with the user profile. The processor is further configured to determine to how to process the user profile based on the predictive degree of approval. The processor is further configured to assign a profile indicator to the user profile.

System and method for predicting anomalous requests and preventing anomalous interactions in a network

An apparatus for security management of application information comprises a processor operable to receive the application information associated with a first entity and to receive entity device information for a first entity device associated with the first entity. The processor is operable to determine that a portion of data fields of the application information associated with the first entity corresponds to a portion of data fields of entity account data associated with a second entity and to determine that a portion of the entity device information associated with the first entity device corresponds to a portion of the entity device information associated with a second entity device that is associated with the second entity. The processor is further operable to determine that the first entity is associated with suspicious indicators, wherein suspicious indicators signal that there is suspicious activity associated with the first entity.

System and method for security management of application information

A system for predicting an anomalous request comprises a processor associated with a server. The processor is configured to parse a user profile from a plurality of user profiles to generate a first set of data objects associated with the first user profile. The processor is configured to compare the first set of the data objects to approved data and audit data to generate a second set of data objects with a set of anomalous data indicators for the first user profile. The processor is further configured to process the second set of the data objects through an anomaly learning model to determine a predictive degree of approval associated with the user profile. The processor is further configured to determine to approve, flag or disapprove the user profile based on the predictive degree of approval. The processor is further configured to assign a profile indicator to the user profile.

An apparatus for security management of a plurality of interactions comprises a processor operable to receive a plurality of interactions, where each interaction comprises interaction information associated with one of one or more users and a first entity. The processor is operable to determine a threshold value of the plurality of interactions and a threshold volume of the plurality of interactions, determine that a value of each of the plurality of interactions has not exceeded the threshold value of the plurality of interactions, and determine that the plurality of interactions has not exceeded the threshold volume of the plurality of interactions. The processor is operable to determine a number of instances of the plurality of interactions that were invalid, determine that the number of instances of the plurality of interactions that were invalid exceeds a threshold, and determine that the first entity is associated with suspicious indicators.

A system for predicting an anomalous request comprises a processor associated with a server. The processor is configured to parse a user profile from a plurality of user profiles to generate a first set of data objects associated with the first user profile. The processor is configured to compare the first set of the data objects to approved data, audit data, disapproved data to generate a second set of data objects with a set of anomalous data indicators for the first user profile. The processor is further configured to process the second set of the data objects through an anomaly learning model to determine a predictive degree of approval associated with the user profile. The processor is further configured to determine to approve, flag or disapprove the user profile based on the predictive degree of approval. The processor is further configured to assign a profile indicator to the user profile.

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McKinney, TX, United States of America

Nathan Alexander Dalpini