FSI & AI Singapore 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, operational efficiency, 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 Singapore Summit aims to provide a platform for AI & Data leaders in the Banking, Financial Services, and Insurance industries to explore the way forward. 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:
Chief Data Officers
Chief AI Officers
Chief Analytic Officers
Chief Digital Officers
Chief Information Officers
Chief Technology Officers
Chief Transformation Officers
Chief Innovation Officers
Chief Customer Officers
Chief Compliance Officers
Heads of AI
Heads of Data Science and Analytics
Heads of Governance, Risks and Compliance
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.
AI is shifting to the center of the modernized tech stacks of financial institutions. From personalization to automation, insight creation to fraud detection, decisioning to cybersecurity, AI is fast becoming the future of financial services. And with that, your core IT needs to be optimized and simplified to provision sufficient computing power and enhance efficiency. This session will illustrate the ways to transform your infrastructure to get ahead in the AI-era.
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 that 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.
The need for governance, risk and compliance is uncompromising in the heavily-regulated financial services industry. With the need to process larger amounts of data and to detect anomalies to prevent frauds and money laundering, AI is in the perfect position to boost GRC efficiency and accuracy. Explore how AI-based systems, with human-in-the-loop setups to make crucial decisions, can automate the processes.
Financial institutions have a fiduciary duty to ensure fairness, accuracy, and reliability in their business dealings, which impact the lives of their clients significantly. Thus, addressing the ethical gray areas and regulatory uncertainties of AI is essential. But are we ready to judge and regulate? This panel debates:
- Developing Theory of Mind AI
- Establishing a responsible and explainable AI culture and structure
- Navigating AI bias vs. human bias: who judges what is bias-free?
- Preventing AI hallucination and adopting Casual AI
- Accelerating the development of AI regulatory regimes with concrete practical guidelines
- Aligning AI regulatory standards across jurisdictions