Palantir Technologies Inc.

Elizabeth Patitucci

Harkirat Singh

Matthew Julius Wilson

Nicolas Prettejohn

Juan Jimenez Puig

Maciej Biskupiak

Stephen Heitkamp

Jorien Van Den Bergh

Alexander Maass

Eugene Mak

Ben Regev

Richard Deitch

Rootul Patel

Duncan Hoffman

Marissa Miracolo

Kai Kamberger

Elise Norman

Yevhen Shevchuk

Patrick Walter

Joshua Aschheim

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

Growing community of inventors

London, United Kingdom

Elizabeth Patitucci