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Overview
Financial institutions across APAC are under immense pressure to modernise their anti-money laundering (AML) systems. Faced with rapidly evolving financial crime and intensifying regulatory scrutiny, traditional on-premise infrastructures are proving inadequate. These legacy systems, often hampered by rigid architectures and slow processing, struggle to adapt to today’s dynamic and interconnected financial ecosystem.
Cloud technologies are the critical enabler for this transition, offering the scalability, flexibility, and processing power that older systems lack. By providing the foundation for artificial intelligence (AI) and advanced analytics, cloud platforms are transforming how institutions operate. They allow for the integration of vast datasets and the deployment of AI-driven tools that can uncover hidden patterns, enhance detection, and adapt swiftly to emerging risks.
This On-Demand webinar will explore how cloud technology is reshaping the AML landscape, enabling financial institutions to overcome the limitations of legacy systems and harness the full potential of AI. We will discuss how to drive operational efficiency, enhance detection capabilities, and address the unique regulatory challenges of APAC's diverse and fragmented landscape.
Key Topics
- Leveraging Cloud in APAC: Overcome legacy limitations and enable effective group-wide compliance.
- Data Sovereignty and Regulation: Balance local data requirements with the need for cross-border data sharing in a fragmented regulatory landscape.
- AI-Driven Compliance: Transition from rigid, rules-based models to adaptive, AI-powered frameworks to reduce false positives and uncover hidden risks.
- Managing Transformation: Address internal resistance, skill gaps, and organisational silos to ensure successful cloud migration.
- Cost-Efficiency and Scalability: Use AI and advanced analytics to lower compliance costs while building scalable, future-proof solutions.
- Developing a Practical Roadmap: Create a clear, step-by-step plan for cloud adoption and the transition to an AI-enabled future.
