Knowledge Hub Your trusted source for information on AI in financial crime

AML thresholds are a cornerstone of risk-based approaches but come with several challenges. They are often a significant source of false positive alerts due to their generic nature. However, raising all thresholds to reduce false positives and missing genuine financial crime risk is not an acceptable trade-off either. We explore how AI can help.

Hawk has announced the launch of its groundbreaking Anti-Money Laundering AI Overlay solution, enabling banks to significantly reduce false positives and detect novel crime without replacing their existing anti-money laundering platforms.

Find out how cryptocurrency firms can combine blockchain analytics tools with AML transaction monitoring solutions to detect money-laundering.

“Hawk has helped us up-level our AML program. We’ve already seen transformative process efficiencies that improve our operations," read more from payment platform ONE on how Hawk is supporting their growth.

Hawk’s platform was chosen to support a range of critical functions for Vodafone Fiji, including transaction monitoring, payment screening, customer due diligence, risk profiling and advanced fraud prevention.

Michael Shearer, Hawk's Chief Solution Officer, shares some of his learnings on how to implement AI within AML and fraud prevention operations – and also what should be avoided.

We asked Michael Shearer, Chief Solution Officer at Hawk, to tell us about why he’d written a book on entity resolution and its importance to anti-financial crime (AFC) programs.

We share our list of the top 20 money laundering books. Learn how criminals exploit financial systems and how experts fight fraud, corruption, and other forms of financial crime.

In this article, we discuss how rule experimentation tools can help banks test AML transaction monitoring rules. Learn how these tools make rule experimentation less expensive, faster, and easier.

In this article, we explore how Entity Risk Detection technology helps banks solve risk management problems by surfacing unknown money laundering, fraud, and sanctions risk in customer attribute data.

We discuss how AI technology can help banks perform more trigger-based AML checks instead of periodic reviews, making their AML programs more effective and efficient.

In this article, we discuss how Entity Risk Detection technology helps financial institutions identify entity risk at onboarding, connections to higher-risk entities, shell company risk, and account opening fraud risk.