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?
In this webinar, Bci Miami, the largest Chilean bank operating in the U.S. and QuantaVerse, explore the role of technologies, such as AI and machine learning, in automating complex and human-led processes in AML programs. The webinar covered the following topics:
- The many possible opportunities available for automation (where AI makes sense, and where it doesn’t)
- How to apply recent innovations to your enterprise (e.g., what are machine learning and natural language processing and how can these techniques help your compliance department)
- Case studies of successful automation including what worked, what didn’t, and what the impact was
- How auditors and regulators view the advances in technology and how you can validate the results
Disruptive technologies are no longer the stuff of science fiction. They’re not even the “next big thing.” Successful firms are using them right now to automate manual processes in their AML programs.
Pandemic disruption in 2020 prioritized the automation of anti-money laundering (AML) investigations for compliance teams. Risk related to inconsistent investigation decision-making and reporting multiplied. The danger of penalties heightened. And now, the 2021...
While this is debated, the problem persists as legacy AML technology such as transaction monitoring systems (TMS) have little to no ability to identify and assess risk created by shell companies. And while policies, procedures, and processes, if applied correctly, can protect financial institutions from becoming conduits for some fraction of money laundering, terrorist financing, and other financial crimes, identifying shell company risk continues to be elusive.