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Read about the missteps to avoid when employing AI in your fraud prevention system, like underusing internal data, relying on generic models, or ignoring explainability.
From our recent research with Celent: read about the top challenges faced by banks when it comes to ensuring AML compliance and how those challenges can be overcome.
Learn about Hawk's Day One Defense Models and how they enable you to bring the power of AI to your fraud prevention program quickly and accurately.
Discover how US banks are approaching the convergence of fraud and AML and read all the takeaways from our webinar with ACAMS.
The AI keynote on Day 2 of ACAMS Hollywood was a highlight of this year's event - we've shared our takeaways.
Real-time AML has been talked about for many years. This article explores its risks, pitfalls, and the key drivers that are making real-time AML much more important today than ever before.
Build AI augmentations in-house or partner with specialized vendors like Hawk? That's the question that banks with data science teams need to answer as they look to enhance AML with AI.
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.
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.