Hawk AI, a German company developing anti-money laundering (AML) and tangential fraud prevention smarts for financial institutions, has raised $17 million in Series B funding.
Hawk AI has raised $10 million to date, and with the new $17 million in bank funding, the company says it plans to ramp up product development and global expansion plans. The Series B round was led by Sands Capital, with participation from Picus Capital, DN Capital, The Coalition and BlackFin Capital Partners.
It is estimated that up to $2 trillion in illicit profits are laundered each year, representing 5% of global GDP, and only 1% of these illicit profits are recovered. . And this is where the Hawk AI stalls.
Founded in Munich in 2018, Hawk AI helps banks and payment firms manage compliance risk through a cloud-native, modular AML monitoring system that promises “the highest level of explainability” with an AI-powered decision engine. Help improve your methods. This is extremely important for audits and regulatory investigations.
“Financial institutions and regulators need to understand and trust AI-driven decisions,” Hawk AI co-founder and CEO Tobias Schweiger told TechCrunch. “Full explainability of such AI is key to establishing trust and acceptance.”
Hawk AI: Monitoring AML Transactions, Explainable Results image credit: Hawk AI
Hawk AI offers products such as payment screening, customer screening, transaction monitoring, transaction fraud, and customer risk assessment, allowing customers to combine static data (such as product and geographic data) and dynamic data to create their own You can build risk assessment models (e.g. transactional data such as suspicious activity reports).
The company’s customers include European spend management platform Moss, US payment processor North American Bancard and Brazil’s Banco do Brasil Americas.
Black box
The space has traditional incumbents such as Verafin, BAE Systems and Oracle, as well as other notable new entrants such as financial fraud unicorn Feedzai and VC-backed Feature Space. However, Hawk AI touts its cloud-native credentials and SaaS business model as one of its key differentiators compared to the cumbersome on-premises deployments of many of the legacy players.
But the company wants to emphasize its focus on addressing the “black box” world in which AI and machine learning algorithms commonly exist. Understanding why algorithms made certain decisions is critical, and businesses need to be able to justify why a customer was flagged. as a potential fraudster.
Hawk AI: Customer Risk Assessment image credit: Hawk AI
It’s worth noting that other anomaly detection software provides insight into what factors led to flagging. But Hawk AI says its patent-pending technology uses natural human language to give scores for each risk factor, telling users the “expected range” of normal behavior. The company says this context is essential in assessing whether a case qualifies as suspicious activity.
“For Hawk AI, explainability consists of two domains,” said Schweiger. “What justifies AI-driven individual decision-making and how were the algorithms that contributed to AI developed? Compliance officers need to be transparent about both. “
