With new regulations and more scrutiny (and lookback requests) from regulators, coupled with increasingly sophisticated criminal schemes, many of the current AML / Financial Crime prevention processes have become obsolete. Financial institutions must come together to develop a collaborative approach to information sharing and boost efficiency across their anti-financial crime programs to successfully face these challenges.
Advanced analytics technologies – including machine learning, graph analytics, and natural language processing – offer tremendous potential to augment the processes. Yet, while these technologies have been a hot topic for a number of years now, for many financial institutions they remain in the pilot phase or confined to siloed initiatives.
In this webinar, we will discuss practical examples of how to leverage these technologies to improve all aspects of anti-money laundering programs, including customer due diligence, transaction monitoring, and behaviour detection, and case management. We will show you how to take these technologies from pilot to scale and achieve cost efficiency.
The key take-aways
Examine emerging AML and FC risks highlighted by COVID-19 and increased digitisation
Explore advanced analytics technologies – machine learning, graph analytics, and natural language processing – to achieve efficiency and compliance
Algorithm Transparency – How can you explain the results? Understand the algorithms that govern decision making when it comes to financial crime prevention
Overcome Operational Challenges and How you are managing data Privacy while scaling up AI and ML deployment
This webinar is in partnership with
ORACLE FINANCIAL SERVICES
For over 20 years, our mission has been to create a safer world. We help financial institutions fight money laundering and achieve compliance with the industry's most effective and efficient suite of end-to-end anti-money laundering solutions, backed by unrivaled data management, advanced analytics, and a powerful platform.