With limited visibility into correspondent networks, banks lack insight into the cross-border transactions they process. Alongside increased regulatory scrutiny in the industry, banks are under pressure to reduce risk by ceasing their relationships with foreign financial institutions. This is no longer necessary.
ThetaRay’s AML solution for correspondent banking, banks and financial institutions can now maintain and scale their global business while mitigating counterparty risk in correspondent channels. Harnessing next-generation AI, ThetaRay’s algorithms simulate the decision-making aptitude of human intuition, using advanced unsupervised machine learning to provide reliable, accurate, and comprehensive ML detection, independent of rules or training.
Survey all transactional flows at the account level and throughout the correspondent network with enhanced transparency and insight.
Seamlessly integrate terabytes of SWIFT data into AML controls with precise and rapid-fire analysis of complex transactional information.
Achieve e full-path visibility into all links of the cross-border payment chain, from originator to beneficiary.
Effectively detect third-and-fourth-party risk using unsupervised machine learning and Artificial Intuition to identify previously undetectable rogue actors and suspicious activity.
Optimize SWIFT data to uncover suspicious transaction profiles and unlock hidden insights.
Leverage existing IT infrastructure with minimal disruption to existing processes and workflows with Thetaray’s out-of-the-box design and API-based architecture.
Use unsupervised machine learning to mitigate risk and scale correspondent banking relationships, leveraging foreign partners to support global trade and achieve agile growth.
Enhance operational efficiency and shed non-essential compliance costs with agile technology that helps financial investigator’s analysts focus on the most crucial risk priorities.