Palantir Technologies Inc.

Richard Deitch

Matthew Julius Wilson

Juan Jimenez Puig

Jorien Van Den Bergh

Maciej Biskupiak

Eugene Mak

Alexander Maass

Ben Regev

Stephen Heitkamp

Marissa Miracolo

Harkirat Singh

Nicolas Prettejohn

Rootul Patel

Duncan Hoffman

Joshua Aschheim

Elise Norman

Kai Kamberger

Elizabeth Patitucci

Yevhen Shevchuk

Patrick Walter

A customer risk trigger associated with a customer may be identified. A response to the customer risk trigger may be detected. First risk analysis data related to the customer risk trigger may be gathered, based on the response, from a first datastore. Second risk analysis data related to the customer risk trigger may be gathered, based on the response, from a second datastore. A customer risk profile to model risk attribute(s) of the customer may be gathered. The risk attributes may represent a risk correlation between the customer and a prohibited act. Customer risk visualization tool(s) configured to facilitate visual user interaction with the customer risk profile may be gathered. The customer risk visualization tools may be rendered in a display of the computing system. The customer risk visualization tools provide a customer-centric view of risk for various applications, including anti-money laundering applications.

Automated risk visualization using customer-centric data analysis

Display screen or portion thereof with graphical user interface

Growing community of inventors

Dallas, TX, United States of America

Richard Deitch