Oracle’s Latest AI Cloud Service Assists Banks in Managing Anti-Money Laundering Risks

Oracle Financial Services has launched a new AI-powered cloud service, Oracle Financial Services Compliance Agent, to assist banks in mitigating anti-money laundering (AML) risks. With an estimated $5.05 trillion to be laundered this year, banks face significant challenges in compliance complexity and costs. This new service enables banks to conduct inexpensive scenario testing, adjust thresholds, and controls to detect suspicious activities, and meet compliance requirements more efficiently.

Rajaram Vadapandeshwara, vice-president of FSGIU Analytics development at Oracle Financial Services, emphasizes the potential of AI and machine learning to enhance AML and financial crime detection programs. He highlights how the Compliance Agent can help banks prevent money laundering opportunities more swiftly and affordably in the rapidly growing banking sector in India.

As part of Oracle Financial Services’ portfolio of AML and financial crime solutions, Compliance Agent offers various benefits for financial institutions:

1. Assessing the risk profile of new banking products: The service objectively evaluates the AML risk profile of new products and assesses controls to mitigate risks cost-effectively, reducing time to market for innovative products while maintaining compliance.

2. Proactively addressing risks from high-risk typologies: Compliance Agent helps banks proactively assess and mitigate risks from high-risk typologies, such as human trafficking, by tuning controls to catch suspicious transaction patterns, ensuring preparedness for potential attacks and maintaining compliance standards.

3. Making faster, evidence-supported decisions for risk modeling: The service provides evidence to model risk teams and regulators, enabling efficient transaction monitoring and updating controls to combat evolving money laundering tactics. Its AI-powered analytics facilitate evidence-based compliance decisions, offering insights for stronger transaction monitoring and optimal control selection.