FSI & AI Hong Kong Summit
The Financial Service Industry is an early adapter with AI. Early use cases have been deployed in numerous cases including customer experience, fraud detection, investment selection, KYC, onboarding, personalization, security, GRC, credit and underwriting decisioning and ESG.
Nonetheless, trust, ethics, compliance, governance, and scaling at speed remain challenging to AI and Data leaders in FSI. With fairness and privacy under scrutiny, AI models must be robust, explainable, and validated.
The FSI & AI Hong Kong Summit aims to provide a platform for AI & Data leaders in the Banking, Financial Services, and Insurance industries to explore the AI Future. The Summit, which will feature a blend of insightful presentations and panel discussions, aims to accelerate AI adoption responsibly to maximize business impacts securely in a heavily regulated environment.
This Summit is for all professionals involved in digital, data, cybersecurity, transformation, and IT, including:
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Chief Data Officers
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Chief AI Officers
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Chief Analytic Officers
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Chief Digital Officers
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Chief Information Officers
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Chief Technology Officers
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Chief Transformation Officers
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Chief Innovation Officers
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Chief Customer Officers
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Chief Compliance Officers
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Heads of AI
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Heads of Data Science and Analytics
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Heads of Governance, Risks and Compliance
AGENDA
AI has become mission critical for leading banks, financial service firms, and insurance companies. With the potential to revolutionize traditional operating models, AI is expected to enhance engagement, boost efficiency, and refine decisioning. in multiple areas across financial institutions. An AI leader will illustrate his/her vision of AI in FSI, and the challenges we need to overcome to realize its potential.
Whether your business-critical challenges are in customer analytics, trading, AML, fraud detection, risk management, underwriting, or customer experience, advanced analytics could be the solution. Yet for BFSI firms to adopt analytics efficiently, solutions need an extra boost. Find out how AI-embedded analytics can help you financial institutions grow and innovate.
AI is expected to have significant impact on the financial services landscape, revolutionizing operations and processes on multiple fronts. While some concepts have been proven and use cases have been launched, the shadow of failed hypes from blockchain is creating doubts for some. This panel will explore the opportunities, hurdles, solutions and use cases in various areas primed for AI including:
- Customer experiences, marketing, and personalization
- Operational efficiency and automation
- Governance, risk, compliance, fraud detection, and security
- Credit score and underwriting decisioning
- Investment, trading, and portfolio optimization
- Sustainable finance and ESG
FSIs are training their own AI. And to do so accurately requires sufficient data size. While data volume is exploding, data complexity is multiplying. To ensure proper governance while maintaining accessibility and efficient usage in various AI projects, your data ecosystem needs a rethink. This session will explore the latest data architecture that propel your AI strategies, and the platforms that power them.
HK is becoming a world-class green finance hub. But to leverage opportunities from ESG investing, data-driven decision-making is crucial. From sentiment analysis to unstructured data processing, find out what benefits and risks AI present in sustainable decision-making.
Policymakers across the globe are focusing on AI’s unprecedented growth to safeguard their citizens. Financial institutions are under further scrutiny to upholding their fiduciary duty to ensure fairness, accuracy, and reliability in their business dealings, which impact the lives of their clients significantly. Thus, addressing the opportunities and challenges presented by regulatory uncertainties of AI is essential. This panel will discuss:
- AI and data sovereignty legislations around the world: Notable policies and similarities
- Accelerating and aligning the development of AI regulatory regimes with concrete practical guidelines
- Safeguards required for compliance without impeding AI progress
- Balancing innovation with responsibility in AI development
- Leveraging AI legislations as opportunities to rethink data structure and architecture
SPEAKERS
