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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.

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.

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

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

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.

In May 2023, Hawk AI participated in the PwC Hackathon at ACAMS Hollywood.

The competition aimed to identify maximum suspicious transactions and/or new trends in the provided data and artfully present our findings. Based on our company vision of streamlining the process for frontline operators and enabling them to efficiently generate high-quality true positive Suspicious Activity Reports (SARs), our data science and product teams set on working through the supplied data sets to detect financial crime.

Financial criminals are becoming increasingly sophisticated, and so are the tools needed to catch them. Trust and transparency are key to successful deployment. AI models that emphasize explainability and auditability act as virtual teammates that work in partnership with their human operators.

Every day, banks and financial services generate an enormous amount of data – transactions, and customer information, to name a few dimensions. With the volume consistently growing, the connections between different data points become increasingly fuzzy. This makes it harder to get valuable insights out of financial (and other) data and turn those insights into actions.

Money laundering is abnormal behavior, which should make it easy to spot. However, money launderers change their methods to avoid prosecution, which makes it difficult to detect financial crime. Emerging AI technology provides anti-money laundering teams with the anomaly detection power they need to catch and fight financial crime.

One of the key responsibilities for payment providers under anti-money laundering (AML) regulations is to monitor transactions. We’re going to explore what that involves and how HAWK:AI can help streamline the process.