United Services Automobile Association (usaa)

Curtis Mark Bell

Yevgeniy Viatcheslavovich Khmelev

Ashley Raine Philbrick

Janelle Denice Dziuk

Cory A Matheson

Nathan Lee Post

Oscar Guerra

David M Jones, Jr

Zachery C Lake

Noe Alberto Martinez

Ruthie D Lyle

Reynaldo Medina, Iii

Andre Rene Buentello

Michael J Maciolek

Jose L Romero, Jr

Donnette Moncrief Brown

Gregory David Hansen

Bryan J Osterkamp

Sean Carl Mitchem

Stacy Callaway Huggar

Victor Kwak

Brennen Michael Ricks

Christopher James Waful

Kou Qunying

Kathryn Babb

Jon Daniel McEachron

Jon D Mceachron

Noe Albert Martinez

A computer may generate a temporary digital wallet containing one or more anonymous payment tokens and transmit the temporary digital wallet to a user device of a user. When the user provides an anonymous payment token of the one or more anonymous payment tokens to a point of sale (POS) system, the computer may receive from the POS system or other systems connected thereto, a request to authorize payment for the anonymous payment token. The request to authorize payment may also include an amount to be paid by the user to the POS system. Using the anonymous payment token, the computer may retrieve a user account and determine that the user account has sufficient funds for the transaction. Based upon the determination that the user account has sufficient funds, the computer may transmit an authorization confirmation back to the POS system or any other system that the authorization request originated from.

Systems and methods for generating and utilizing temporary digital wallet

Systems and methods ingest extensive data regarding real-time transactions to determine correlation between a variety of parameters and possible fraud events. Possible fraud can be predicted, and notifications delivered to a fraud team. Correlations can be discovered using unsupervised machine learning, and particular systems and methods can utilize natural language processing to both receive and provide information concerning fraud risk and countermeasures.

Fraud detection using augmented analytics

Data processing techniques are described to obtain user data previously collected when a user is requested to complete application forms associated with multiple servers. The application forms may include some fields that may be in common and that may request the same user data. For each application form requested by the user, the data processing techniques can identify and obtain the relevant previously collected data about the user for the application form. The application form for a product can have certain fields that may be pre-filled based on the relevant and/or non-confidential previously collected user data. The data processing techniques can also provide an estimate of the time that may be needed by the user to complete at least one application form so that the user can obtain a requested product.

Aggregated application data store

A method comprises receiving, by an artificial intelligence (AI) assistant, an input via a communication session between a customer device and a customer service representative device, wherein the AI assistant is trained using machine learning on a database containing previously-received inputs, previously-delivered outputs, and the previous results of previously-delivered outputs; processing, by the AI assistant, the input; determining, by the AI assistant, an output based on the processing of the input, wherein the output includes one of a suggested statement, change in tone, or correction for the customer service representative; and sending, by the AI assistant, an indication of the output to the customer service representative device.

Artificial intelligence assistance for customer service representatives

Disclosed herein are embodiments of systems, methods, and products comprises a server for enabling automatic shopping. The server may associate a shopping cart with a customer's electronic user device. The server may monitor the locations of the electronic user device. Based on the customer's location, the server may identify the shelves and items the customer has visited. When an item is lifted from the shelf, at least one weight sensor on the shelf may detect the weight change. The server may receive a notification comprising an amount of weight change from the weight sensor on the shelf. When the customer places the item into his/her shopping cart, the weight sensor on the shopping cart may detect the weight addition. If the weight change and weight addition match, the analytic server may determine that the item picked up from the shelf is placed within the customer's shopping cart.

Automated purchasing systems and methods

A communication session may be established between a customer device and a customer service representative device. An artificial intelligence assistant may access the communication session and receive an input. The artificial intelligence assistant may process in the input. The artificial intelligence assistant may determine one or more characteristics of the input. The artificial intelligence assistant may determine an output based on the characteristics of the input. The artificial intelligence assistant may communicate the determined output to the customer service representative.

Artificial intelligence assistant for customer service representatives

Described herein are methods and systems for anonymizing and securing digital transactions. These methods and systems describe a server that monitors web applications executing on a user device. Responsive to the web application displaying an input element requesting personally identifiable information of a user, the server inputs encoded user data corresponding to the input element, whereby a web application server hosting the web application does not receive the personally identifiable information of the user. The server then generate an optical code representing the personally identifiable information. Responsive to receiving a request for the personally identifiable information from a shipping entity computing device that scanned the optical code, the server first verifies the shipping entity computing device and then presents the personally identifiable information for display on the shipping entity computing device.

Secure and anonymized digital transactions

Growing community of inventors

San Antonio, TX, United States of America

Curtis Mark Bell