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
Packaged financial crime solutions are built from the ground up by proven AI experts working alongside experienced AML professionals. Unlike other AI for AML approaches, packaged AI solutions are quick to implement and are continuously updated by the solution provider based on input from multiple customers and regulators.
Serving almost 20 million customers, the bank was concerned about the risks associated with false negatives that its current AML compliance technology was missing. Intent on driving financial crime out of its operation, the bank began searching for a solution that could enhance its existing rules-based transaction monitoring system (TMS) and minimize the risk related to undiscovered financial crime.
While all agree the promise of AI for AML is great, taking the steps to select and implement AI within an institution is relatively new. So, what is the best approach for implementing AI and machine learning into your efforts to combat financial crime?