Jenny M Melendez

20220414652, Dec 29, 2022

Jun 23, 2021

17/355709

- McLean VA, US
David Septimus - New York NY, US
Jenny Melendez - Falls Church VA, US
Samuel Rapowitz - Roswell GA, US
Viraj Chaudhary - Katy TX, US
Daniel Miller - Astoria NY, US
Tyler Maiman - Melville NY, US

G06Q 20/38
G06Q 40/02

Aspects discussed herein may relate to techniques for authenticating a user using transaction-based authentication questions. Hold transactions conducted using a financial account may be identified and verified. The hold transactions may be transactions that do not post to the financial account, and therefore are not provided on any financial account statement. The transaction-based authentication questions may be generated based on the identified and verified hold transactions. The user may be authenticated based on responses by the user to the transaction-based authentication questions. Malicious actors that gain access to financial account statements are unlikely to answer the transaction-based authentication questions correctly as they are based on financial transaction data that is not provided on the financial account statements.

20220358193, Nov 10, 2022

May 7, 2021

17/314683

- McLean VA, US
David Septimus - New York NY, US
Jenny Melendez - Falls Church VA, US
Samuel Rapowitz - Roswell GA, US
Tyler Maiman - Melville NY, US
Joshua Edwards - Philadelphia PA, US

G06F 21/31
G06N 3/08
G06F 16/2455
G06Q 40/02

Methods, systems, and apparatuses are described herein for improving the accuracy of authentication questions using transaction limitations provided by users. A request for access to an account associated with a user may be received from a user device. An account restrictions database may be queried to determine one or more transaction rules associated with the account. The one or more transaction rules may have been created by the user and indicate limitations on financial transactions that may be performed via the account. An authentication question may be generated that is associated with a violation of the one or more transaction rules. The authentication question may be provided to the user device, and a response to the authentication question may be received. Access to the account may be provided to the user device based on the response.

20230030389, Feb 2, 2023

Jul 28, 2021

17/387690

- McLean VA, US
David Septimus - New York NY, US
Jenny Melendez - Falls Church VA, US
Samuel Rapowitz - Roswell GA, US
Tyler Maiman - Melville NY, US
Joshua Edwards - Philadelphia PA, US

G06Q 20/40
H04L 29/06

Methods, systems, and apparatuses are described herein for authenticating access to an account using questions relating to which user, of a plurality of users authorized to access the account, performed certain actions. A request for access to an account may be received. Transaction data for the account may be received. A list of merchants may be generated for at least one transaction. An authentication question relating to the identity of a user that conducted a transaction may be generated. For example, the authentication question may prompt the user to indicate which authorized user(s) conducted particular transaction(s). The user device may be provided the authentication question. A response to the authentication question may be received. Access to the account may be provided based on the response.

20230034204, Feb 2, 2023

Jul 28, 2021

17/387683

- McLean VA, US
David Septimus - New York NY, US
Samuel Rapowitz - Roswell GA, US
Jenny Melendez - Falls Church VA, US
Viraj Chaudhary - Katy TX, US
Joshua Edwards - Philadelphia PA, US

G06Q 20/40
G06K 9/62
G06N 20/20

Methods, systems, and apparatuses are described herein for authenticating access to an account using questions which allow users to provide textual information about transactions conducted by an account. A machine learning model may be trained to predict the guessability of merchants. A request for access to an account may be received, and transaction data for that account may be received. An authentication question may be presented. For example, a user may be prompted to list places they have shopped recently. A user response comprising text data may be received. The text data may be processed to identify one or more merchants. If the one or more merchant(s) are represented in the transaction data, the machine learning model may be used to determine the guessability of the one or more merchants. An authentication score may be determined based on the guessability, and access to the account may be provided.

20230004973, Jan 5, 2023

Jul 1, 2021

17/365642

- McLean VA, US
David Septimus - New York NY, US
Samuel Rapowitz - Roswell GA, US
Jenny Melendez - Falls Church VA, US
Tyler Maiman - Melville NY, US
Viraj Chaudhary - Katy TX, US

G06Q 20/40
G06Q 20/32
G06N 20/00
G06K 9/62

Aspects described herein may allow for authenticating a user by generating a customized set of authentication questions based on patterns that are automatically detected and extracted from user data. The user data may include transaction data collected over a period of time. By automatically detecting user patterns that correspond to user behavior over a period of time, an authentication system may be able to generate information that is recognizable to an authentic user but difficult to guess or circumvent for any other user.