Your search did not match any results.
We suggest you try the following to help find what you're looking for:
Uncover how you can apply a risk-based approach using latest data science tools for criminal pattern discovery. A look at next generation AML compliance driven by machine learning and graph analytics.
Chartis rated Oracle as category leader in its RiskTech Quadrant® for AML/watchlist monitoring solutions, 2019. Oracle was rated highly for a variety of capabilities, including regulatory compliance reporting and controls, alert/case management, and advanced analytics.
Understand how you can overcome common AML/CTF challenges for smaller institutions with cost-effective and efficient behavior detection and investigation systems.
Blockchain can help increase the level of data traceability and integrity, improving the quality of your banks’ transaction monitoring capabilities. How does it really work?
Identify money launderers and comply with CDD and KYC regulations over the entire customer lifecycle. Quickly and accurately assess risk and compare customers to global sanctions and watchlists. Onboard good customers quickly and seamlessly.
At least $1.8 trillion in criminal proceeds are laundered every year. How much of it goes through your bank? Use Oracle to identify unusual customer behavior and suspicious money movements.
AI-powered, enterprise-level investigation and case management can uncover criminal networks. Spend more time investigating truly suspicious activities instead of sifting through false positives.
Generate and file SARs and STRs. Stay compliant with global AML reporting guidelines and regulations. Manage compliance faster and smarter with streamlined regulatory analytics and sound data integrity.
With the Financial Services Data Foundation, unite previously siloed internal data for a complete customer view, a streamlined financial crime compliance program, and lower costs. Reduce time spent on data gathering through robotic process automation. Run applications on your data lake and relational databases together, and perform batch and real-time analytics on one platform. The, turn your compliance data into a competitive advantage by using it for customer analytics.
Traditional rules can’t evaluate the vast amount of context needed to accurately distinguish money launderers from good customers. By analyzing relationships among entities instead of just the entities themselves, graph analytics easily identifies complex money movement patterns, multi-hop relationships, and hubs and spokes of activity. This, in combination with entity resolution and advanced decisioning, powers greater accuracy, better case creation, and intuitive visualizations that enable better investigations.
Oracle AML and Financial Crime Compliance dates back to work begun in 1996 for the National Association of Securities Dealers. These capabilities eventually become Mantas, which was acquired by Oracle in 2006. Our clients benefit from our enterprise-grade, resilient architecture that easily integrates cutting-edge innovations with a comprehensive suite of applications for a streamlined compliance program at scale.
Arin Ray, senior analyst at Celent, writes about the growing pains in anti-money laundering (AML) operations, potential opportunities gained by leveraging advanced analytics, and its adoption trends and impact.