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How Entity Risk Detection Improves AML, Fraud, and Sanctions Operations

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.

How AI facilitates trigger-based AML checks

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. 

4 Anti-Financial Crime Use Cases for Entity Risk Detection Technology

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.

5 Takeaways from Wolfsberg Group Guidance on Monitoring for Suspicious Activity

Learn about the Wolfsberg Group's Statement on Effective Monitoring for Suspicious Activity, which recommends that banks move from AML transaction monitoring only to a broader approach incorporating more customer data. 

The BaaS Challenge: How AML Tech Facilitates Growth While Maintaining Compliance

Learn how banks and other financial institutions can facilitate partnerships with BaaS providers to create new business opportunities while maintaining AML compliance. 

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Learn how Generative AI can help Financial Institutions detect sanctions violations, money laundering, and fraud, aid investigations, and improve QA processes.

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The FCA has recognized machine learning, entity resolution, and network analysis as key tools in the fight against financial crime going forward.

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A combined Fraud Prevention and Anti-Money Laundering (FRAML) solution can help financial institutions safeguard their operations.  We cover five essential questions to determine whether a particular FRAML solution is a good fit for your FI.

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Financial institutions can realize valuable synergies in effectiveness and efficiency by using the same system to monitor both AML and fraud risk. 

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Learn how Hawk helps clients ensure the effectiveness, accuracy, and compliance of systems in their AML model validation process. 

4 essential AML use cases for AI technology

Built-for-purpose AI technology helps banks identify suspicious activity in real-time, at scale via Anomaly Detection, Pattern Detection, False Positive Reduction, and pKYC use cases.

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Instant payments can create headaches for fraud teams, as faster payments enable faster fraud. The good news is that AI can help.