Trade-based money laundering (TBML) moves an estimated $2.2 trillion in illicit proceeds annually, and COVID-19, which has expanded remote work by AML professionals, increased remote transactions worldwide and disrupted global supply chains, raises additional risks. This authoritative webinar examines methods for strengthening anti-TBML oversight by supplementing traditional legacy systems with technological innovations such as artificial intelligence, machine learning and advanced data analytics and information management.
Reviewing unique anti-TBML challenges such as billions of pages of documents currently circulating in trade, extensive third-party networks and complex transaction lifecycles and deal structures to establish systemic needs and potential oversight gaps.
Identifying opportunities to apply digital solutions such as AI and machine learning to anti-TBML functions to speed decision processes, elevate data quality and create operational efficiencies.
Conducting institutional TBML risk assessment and analyzing regulatory expectations of anti-TBML oversight to gauge required economic and human resources
Trade Finance Specialists, Risk Officers, Compliance Managers, Fraud Investigators, FIU Personnel, IT Specialists, Heads of Trade Services, Chief Risk Officers, Chief Compliance Officers, Heads of Fraud, Other C-suite executives: CEO, CFO, COO, CIO, etc.
AP, Banking, Regulatory