Recent advances in technology and an increasing internal focus on efficiency and effectiveness present an opportunity for compliance professionals to yield significant organizational benefits. However, how can these advances be used in real world situations, and how do they meet expectations of auditors and regulators.
This webinar explores the role of technologies such as Machine Learning and Natural Language Processing, often called Artificial Intelligence, in automating complex and until recently human-led processes in AML and FCPA programs. Specifically, real world cases of a financial institutions automating significant parts of their AML program will be discussed, including an overview of the organizational and regulatory challenges faced.
The key take-aways
The many possible opportunities available for automation. Where does AI make sense, and where it doesn't.
How to apply recent innovations to your enterprise. What are Machine Learning and Natural Language Processing and how can these techniques help your compliance department.
Case studies of successful automation, what worked, what didn't, and what was the impact.
How auditors and regulators view the advances in technology and how can you validate the results
This webinar is in partnership with
Founded in 2014, QuantaVerse uses artificial intelligence (AI) to find financial crimes.
QuantaVerse is a leader of AI and machine learning solutions purpose-built for identifying financial crimes. QuantaVerse solutions help organizations comply with AML (Anti-Money Laundering), KYC (Know Your Customer) and FCPA (Foreign Corrupt Practices Act) regulations and to rid their institutions of the money laundering and other financial crimes that support our greatest global ills —drug trade, human trafficking, terrorism and political corruption.
QuantaVerse leverages big data technologies along with its proprietary AI and machine learning algorithms to ingest and process data from a wide variety of external sources, many of which go unassessed by organizations today. These data sources include unindexed deep web data; open source public internet data; and government and commercially produced datasets on known financial criminals and other prohibited or high-risk persons or entities. QuantaVerse rationalizes this data with transaction and customer information from disparate operational systems to create an unparalleled understanding of legitimate patterns and quickly identify anomalies that are indicative of illicit activities.