The acquisition adds the capabilities of Quantimon’s machine learning platform for anti-money laundering (AML) risk detection to Hummingbird’s artificial intelligence-powered orchestration platform for financial crime compliance. It also adds Quantimon’s federated learning network that shares patterns seen across other institutions without sharing customer data, according to the release.
This combination means that the platform where compliance teams resolve alerts will now be equipped with machine learning models that learn from how the alerts are resolved, per the release.
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For Hummingbird customers, this will mean richer rule-based detection; machine learning models that rank alerts by risk based on what they have learned from past alert outcomes; and, over time, the ability to detect risks based on signals from third-party intelligence or patterns across the Hummingbird network, the release said.
Hummingbird Co-Founder and CEO Joe Robinson said in the release that while the ways compliance teams investigate financial crime have been changed by AI, the systems that generate alerts have remained largely unchanged.
“Today our customers can clear alerts faster than ever, but they shouldn’t have to spend that capacity on noise,” Robinson said. “With Quantimon, every alert worked by an AI agent or analyst sharpens detection, so more of the alerts that reach our customers will be the ones worth their time.”
In his own announcement of the acquisition, Quantimon Co-Founder and CEO Ben Duranske said that as part of Hummingbird, the Quantimon team will reach even more financial institutions and continue paving the way for what AML transaction monitoring looks like in the agentic era.
“Hummingbird customers already run monitoring and investigations in one place, with AI agents and analysts producing structured alert data — exactly the foundation our models need,” Duranske said. “Together, our combined solution makes AML transaction monitoring meaningfully better, with every alert that a team resolves feeding back into detection.”
The PYMNTS Intelligence report “New Data Shows How Tech Sectors Are Turning AI Into Strategy” found that cybersecurity firms are scaling AI for protection and compliance.
As businesses in the cybersecurity sector consider what artificial intelligence should do, 80% are emphasizing productivity or efficiency gains, while 75% are motivated by risk reduction, according to the report.
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