Grace Wu is a global data and AI transformation leader and scholar-practitioner with over 16 years in financial services, spanning investment banking, global markets, securities services, wholesale banking, and group functions across APAC and international markets. She has built her executive career on a deep belief that data and AI can best serve people and organizations when they are built on trust. She is dedicated to building enterprise-wide data controls and governance, scalable data assets, and AI-driven transformation in highly regulated environments, turning complex data ecosystems into strategic enablers of compliance, resilience, and growth. Her expertise spans enterprise data strategy, data & AI governance, master data management, big data engineering, and digital transformation, as well as the design of governance frameworks that make artificial intelligence trustworthy at scale. She has led large-scale enterprise data science and AI initiatives and transformed legacy applications and processes into data-driven solutions that reduce financial crime risk, strengthen regulatory compliance, accelerate commercialisation, and empower confident executive decision-making. As a scholar-practitioner, Grace is pursuing PhD research on enterprise data mastering in the age of GenAI, applying it to digital asset governance, financial crime risk, data quality, and enterprise AI success, while exploring the frontier where RWA tokenization, stablecoins, and cross-border payments meet enterprise data trust. She operates at the convergence of technology, business, and regulation, helping organizations unlock new opportunities while safeguarding the resilience and trust on which they depend.

From Data Controls to Programmable Trust: AI Governance for Cross‑Border and Digital Assets                                                                                                                                                                                                                                                                                                                                                                                                            In regulated financial services, AI is no longer confined to chatbots and credit scoring; it is becoming the invisible infrastructure behind cross‑border payments, products, tokenised assets, and programmable money. Yet most AI strategies still treat governance as an afterthought, bolted on as policies and review boards rather than designed into data, models, and workflows from the start. This keynote explores how financial services can move from static “single source of golden record” thinking to dynamic, federated data ecosystems that are safe enough for AI /GenAI to move real value across borders. Drawing on real‑world experience in global risk, master data, and cross‑border systems, Grace Wu will share a practical framework for governing data and AI across jurisdictions with regulatory expectations while preserving speed and innovation. The session will be especially relevant for leaders responsible for AI, data, risk, and technology strategy in financial services, payment firms, and regulators.