Anti-Money Laundering in financial institutions is ripe for change. While banks still rely on rules-based legacy systems from the pre-Cloud and pre-AI era, ever tougher regulation forces them to throw bigger budgets and higher headcounts at AML/CFT processes to ensure compliance. All without solving the underlying issue, to be sure, as conventional AML/CFT solutions produce up to 95% false-positive alerts, contributing too little to a growing problem. Hawk AI’s mission is to change this for good.
The company was founded in Munich in 2018 by experienced fintech entrepreneurs Wolfgang Berner and Tobias Schweiger who saw the potential for a fresh start in technology for AML and regulatory compliance. Hawk AI dramatically reduces false-positive alerts, by applying fully transparent and auditable Machine Learning to high-volume transactions. The company’s solution was also designed from the ground up to form a platform for secure and privacy-compliant information sharing between multiple financial institutions. Ultimately, Hawk AI aims to become the new “gold standard” in AML worldwide, contributing to not just significant cost savings for financial institutions but also to actually fighting financial crime effectively.
Hawk AI is a software platform that combines AI with traditional rule-based approaches to monitor financial transactions in real-time, delivering next-generation anti-money laundering compliance for financial institutions. The solution offers classic rule-based models, which are enhanced by auto-closing features based on machine learning models that learn from the investigator’s own decisions through our case manager.
Hawk AI makes use of an unsupervised machine learning model, Anomaly Detection, to identify new patterns of crime through insights from the overarching nature of the platform spanning multiple financial institutions. The platform provides full transparency of machine decisions to deliver the necessary clarity for regulators that require “explainable AI”, as well as instill trust in the machine's decisions. Using Artificial Intelligence to maximize automation, Hawk AI delivers a significant cost benefit through an up to 70% reduction of required resources and better crime detection. The result: a more efficient and effective way of fighting financial crime.
Hawk AI provides a SaaS model through the cloud. Currently on AWS, the service can be deployed elsewhere using Kubernetes. For large clients, other options also exist.
Clients integrate through a RESTful JSON-based API or core banking system plugins. The platform makes use of machine learning by applying traditional supervised learning (XGBoost and similar) for automating human decisions, as well as unsupervised deep learning (Tensorflow) for outlier and anomaly detection.
Our solution differentiates in three key areas. First, it combines AI with traditional rules-based systems to significantly improve transaction monitoring speed and accuracy. Secondly, the cloud-native platform powers greater efficiencies and provides pattern data pooling and sharing among Hawk’s network of global financial institutions, creating a powerful network effect and ultimately enhancing the effectiveness of anti-money laundering while being fully compliant to privacy laws and regulations. Third, we are a pioneer in Explainable AI (patent pending), making the use of AI and Machine Learning in AML Compliance a reality.