Capital One Services, LLC

Andrew Marr

Noble Ozoka

Matthew Reedy

Lin Ward

Kevin Grant Osborn

Wendy Wu

Disclosed embodiments may include a method for using accounts with multiple profiles where the system allows a primary user to create one or more secondary user profiles. Each secondary user profile is associated with its own VCN and one or more attributes. The one or more attributes can be used to limit the spending ability of each secondary user individually with hard and soft spending limits including merchant category, overall spending, and geographic limits. Purchases by a secondary user that violate the soft limits may be allowed by the primary user using an application associated with the primary account number. Attributes can be assembled by the primary user to create specific and creative spending limits. The system associates each transaction with the user profile using the specific VCN and generates a GUI for the primary user showing the second user profile, its current balance, and transaction history.

Systems and methods for accounts with multiple profiles

A device may receive, from account entity devices, sets of transaction data for transactions between merchants and customers, and may use a first machine learning model to assign the customers to clusters based on measures of similarity among the sets of transaction data. The device may determine travel-related data items in a set of transaction data, of the sets of transaction data, associated with a set of customers assigned to a particular cluster, and may use a second machine learning model to identify a travel experience that has a threshold likelihood of being of interest to the set of customers. The device may receive offers relating to the travel experience, and may provide, to customer devices associated with customers of the set of customers, travel offer packages that include at least one of the offers relating to the travel experience.

Utilizing machine learning models to recommend travel offer packages relating to a travel experience

A behavioral analytics platform may obtain a first data set associated with a first user and a second data set associated with a second user. The behavioral analytics platform may determine a first set of behavioral categories to classify the historical user activity data associated with the first user based on a first set of behavior vectors and determine a second set of behavioral categories to classify the historical user activity data associated with the second user based on a second set of behavior vectors. The behavioral analytics platform may populate one or more user interfaces that are accessible to the first user and/or the second user based on one or more values representing a degree to which the first set of behavioral categories and the second set of behavioral categories correspond to complementary behavioral tendencies, which may be determined using a machine learning technique.

Growing community of inventors

Midlothian, VA, United States of America

Andrew Marr