Case Study: Leading U.S. Broker-Dealer achieves 28% reduction in false positives and 33% increase in approvals with Fraud.net

Comprehensive Protection for a Leading U.S. Broker-Dealer

Leading U.S. Broker-Dealer struggled with growing fraud, false positives and compliance risk across new account openings, logins and transactions and needed a scalable, brokerage-specific solution to speed decisions and reduce manual investigations. They selected Fraud.net’s fraud and risk management platform (including Transaction AI, Application AI, Login AI and other modules) to centralize data, AML checks and real-time rule enforcement.

Fraud.net implemented a customizable, real-time fraud prevention solution that integrated the broker-dealer’s data and automated workflows and investigations. The case study reports measurable impacts: a 33%+ increase in fully automated new investor approvals, a 28% reduction in false positives and faster investigations, plus additional reported reductions (including 48% in related metrics), real-time rule activation (~300ms) and improved customer satisfaction—demonstrating clear ROI for the Leading U.S. Broker-Dealer.