Overview

The Financial Action Task Force (FATF) published the Mutual Evaluation Report of Hong Kong in September 2019 which concluded that Hong Kong's anti-money laundering (AML) regime is highly compliant and effective with respect to the FATF Recommendations 2012. Riding on this outstanding achievement, regulators now promote financial institutions to adopt regulatory technologies to further enhance their KYC and transaction monitoring processes. This is seen as the next step in maintaining Hong Kong’s reputation as the role model for AML compliance among major financial centres worldwide.

This course will showcase how financial institutions conduct remote customer onboarding by using machine learning to carry out identity document verification and facial recognition. The speaker will also cover the application of fuzzy name screening for customer and counterparty risk assessments, as well as the use of big data to eliminate false positives in sanctions list matching and transaction monitoring. Participants will also learn how to develop an AML compliance programme by using artificial intelligence applications.

Content

• Regulatory requirements for AML
• Remote customer onboarding
• Facial recognition
• Fuzzy name screening
• False positive reduction with big data
• Compliance programme with artificial intelligence

Who should attend

• Practitioners involving AML matters and/or client onboarding process
• Compliance officers, money laundering reporting officers, risk managers and legal professionals
• Responsible officers, directors and MICs of licensed corporations