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13:05
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15 mins
13:20
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50 mins
- How are banks approaching consistent global standards for AML controls to mitigate money laundering and financial crime?
- What emerging regulatory trends do banks foresee that could impact current AML control frameworks?
- Which strategies can banks implement to align AML controls with evolving regulatory expectations, particularly with cross-boarder transactions and near real-time payments?
- How are banks collaborating with regulatory bodies to ensure a more coherent approach to AML risk management? Are there lessons to be learnt from past regulatory action and the difficulty of implementing certain legislation?
14:15
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40 mins
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40 mins
15:05
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50 mins
- How can financial crime functions link up structured and unstructured data to incorporate a holistic view across varying functions such as sanctions and AML?
- What technological advancements are crucial for enabling effective data pooling and collaborative analytics in AML functions?
- How can collaborative analytics enhance the detection and prevention of financial crimes compared to traditional, isolated approaches?
- How feasible is it for banks to pool data from multiple sources?
- What issues of privacy must banks overcome for effective data sharing across institutions?
13:05
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15 mins
13:20
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50 mins
- Why are the key obstacles preventing effective integration of cybersecurity and AML teams? What are the potential drivers and benefits in integrating the functions?
- To what extent do current AML frameworks adequately address the sophisticated tactics used in modern cybercrime? What steps can be taken to enhance the resilience of systems against cyber threats?
- How can banks ensure that the use of advanced technologies such as artificial intelligence (AI) and machine learning (ML) does not create vulnerabilities or blind spots in AML processes?
- What potential regulatory risks could be associated with converging cybersecurity and AML functions, and how can banks effectively mitigate these risks without duplicating efforts or resources?
14:15
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40 mins
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40 mins
15:05
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50 mins
- How effective are current AI and ML models in detecting suspicious trade transactions? Is there a shift in banks moving towards advanced technologies from traditional rules-based monitoring?
- How can AI-drive anomaly detection systems be tailored to effectively recognise and flag irregularities in trade-based money laundering?
- Which specific threat typologies should models be trained on to spot irregularities? How can banks enhance their existing model risk governance oversight to effectively manage new AI and ML models?
- How do predictive analytics and risk scoring models contribute to proactive trade-based money laundering risk management, and what role do they play in real-time transaction monitoring?