The Anti-Money Laundering (AML), Cyber, and Fraud landscape in 2022 will face a significant change in operations due to a perfect storm of events, from Covid-19 causing exposure of workers to looser remote security capabilities, and the US government’s passage of the Anti-Money Laundering Act (“AMLA”). The new world of eager fraudsters and real time anti-fraud technology has created both problems and solutions. Join our panel of speakers from Microsoft, TigerGraph and Expero in a discussion about technology approaches and strategies to ensure your organization complies with the AMLA in 2022.
The focus of this webinar is to highlight Machine Learning, Visualizations, and Graph technology trends in 2022 that will increase the accuracy and output of systems, and how including the ‘Human in the Loop’ can get your teams ahead of potential gaps in your anti-fraud solutions and government AML legislation.
This event is designed as a 'Speed Dating' format, focusing on key topics for under 15 minutes in order to maximize the insights. During this online meetup, you'll learn from our experts on how Microsoft, TigerGraph and Expero can unlock the potential in your organization.
Key Learning Topics:
- Key Challenges in 2022 - discuss the AML process changes; New Fraud threat vectors, impact areas of audit & compliance and what is to be expected in 2022
- Technology Innovations - how new technologies like Microsoft 365 technology, master data matching, graph analytics, and ML are assisting in the reduction of false positives and increasing accuracy
- AML and Fraud Outlooks - discuss available resources and what anti-fraud practitioners are doing to create solutions for new processes and how they are using technology; process trends in how banks and other institutions are preparing for 2022
- Empower the Investigator - 2022 capabilities in visualization technology and human processes that increase throughput and provide valuable human intelligence, creating quicker and more efficient outcomes for different roles like Fraud Management, Investigators, and Data and Analytics teams
- Rise of ML & AI with ‘Explainable’ ML - how to implement practical uses and methods of fraud identification, complex dependency and case management with ‘humans-in-the-loop’ for higher accuracy and process streamlining