Hummingbird, the AI-powered orchestration platform for financial crime compliance, today announced the acquisition of Quantimon, the machine learning platform for AML risk detection. The acquisition deepens Hummingbird’s investment in transaction monitoring, bringing machine learning models that learn from alert outcomes and federated learning technology onto the same platform where compliance teams resolve those alerts.
Most anti-money laundering (AML) transaction monitoring still runs on rules, and most of the alerts those rules generate turn out to be nothing. Machine learning has been slow to help because models need labeled outcomes and, at most institutions, those outcomes sit in case notes that are too expensive to turn into training data. That’s changing with AI. When AI agents and compliance analysts work alerts in Hummingbird, each disposition is recorded in a structured form a model can learn from. With Quantimon integrated into the platform, those dispositions feed back into detection and improve it.
“AI has changed how compliance teams investigate financial crime, but the systems generating the alerts have stayed largely the same,” said Joe Robinson, co-founder and CEO of Hummingbird. “Today our customers can clear alerts faster than ever, but they shouldn’t have to spend that capacity on noise. With Quantimon, every alert worked by an AI agent or analyst sharpens detection, so more of the alerts that reach our customers will be ones worth their time.”
Quantimon’s machine learning models learn from how alerts are resolved, leveraging an institution’s own data in a closed feedback loop. The company also built a federated learning network, designed to let compliance teams benefit from patterns seen across other institutions without sharing customer data.
“At Apple, Xoom, and PayPal, we watched our compliance teams spend their days working on seemingly endless alert backlogs. We started Quantimon to fix that at the source,” said Ben Duranske, co-founder and CEO of Quantimon. “I’m thrilled Quantimon is joining Hummingbird, where our technology can be at the center of a loop that makes both detection and investigation smarter.”
The Quantimon team is joining Hummingbird to enhance the platform’s transaction monitoring solution. Customers can expect:
- Richer rule-based detection: Rules that are easier to build, test, and manage for larger and more complex monitoring programs. Strong rule coverage in AML is the foundation on which machine learning works best.
- Machine learning models trained on each institution’s alert outcomes: Models that learn from what a team decides to close, escalate, or file on, so alerts can be ranked by risk and activity that resembles confirmed cases can be caught even when no rule fires.
- A network that sees beyond an institution’s own walls: Over time, customers will be able to draw on signals from third-party intelligence or patterns across the wider Hummingbird network, so teams can detect risks they didn’t even know to look for.
To learn more about how Hummingbird is bringing Quantimon’s technology into its platform, visit https://www.hummingbird.co/resources/hummingbird-acquires-quantimon.
About Hummingbird
Hummingbird is the leading AI-powered orchestration platform for financial crime compliance. The platform replaces fragmented tools with a unified workspace where AI agents and human analysts work together across the compliance lifecycle. With integrated solutions for customer screening, transaction monitoring, investigations, and regulatory reporting, financial institutions reduce risk, scale capacity, and strengthen governance across their program. Industry-leading banks, fintechs, gaming operators, and crypto companies, including Raymond James, Symetra, Crypto.com, DraftKings, and Etsy, run on Hummingbird. Learn more at hummingbird.co.
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