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Dr. Zhao Jingyuan
Head, Group Data Office
OCBC
Dr. Zhao Jingyuan is Head of Group Data Office at OCBC, where she drives business value through Data & AI, strengthens data-driven decision-making, and builds enterprise data & Intelligence foundations for long-term success.
With 20 years of experience across Great Eastern, Capgemini, Lazada (Alibaba Group), and A*STAR, she brings deep expertise in AI, big data, and data monetisation. Previously, as Managing Director at Great Eastern, she shaped the Group’s Data & AI strategy and led high-impact solutions.
Jingyuan holds a Ph.D. in Statistics from NUS, is an adjunct professor, and is recognised among Singapore 100 Women in Tech (2021) and recipient of the NUS Outstanding Science Alumni Award (2024) in recognition of her contributions to the Technology and Science sector.
“Data and AI unlock new value and reimagine what’s possible.”
Speaking At
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9:45–11:15amMon 16 NovPublic-Private RoundtableRoundtable Room 2Open
Accountability & Liability In Agentic Systems
Build, Buy, or Own: Strategies for Responsible AI Adoption in Finance
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Jason LeeCo-Head, Legal & RegulatoryTemasek
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Jeremy HorExecutive Director, Enterprise Knowledge DepartmentMonetary Authority of Singapore
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Levan KobakhidzeHead of Payments Business DirectionBank of Georgia
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Louise JohnstonDigital Assets & Blockchain, Global PolicyMastercard
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MP OliveiraHead of Venture InvestmentsNeoVentures by Mashreq
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Nilanshuk HaldarGlobal Head of PartnershipsNucleus Software
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Norbert IzerExecutive Director for Financial Markets & DigitalizationCentral Bank of Hungary (Magyar Nemzeti Bank, MNB)
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Sunayna TutejaFormer Chief Innovation OfficerFederal Reserve System
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Varun KapoorDirector, Digital Strategy Group (FSI)Adobe
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Dr. Zhao JingyuanHead, Group Data OfficeOCBC
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Prof. Heng WangProfessorSingapore Management UniversityModerator
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Kaitlyn ThinnChief Strategy OfficerGlobal Finance & Technology Network (GFTN)Moderator
About this session
Financial institutions are moving well beyond experimentation with AI, deploying it across credit decisioning, fraud detection, and everyday employee workflows at genuine scale. But how they get there differs sharply: some are building their own foundation models on proprietary data to avoid depending on external providers with their most sensitive information; others adopt commercial AI tools but wrap them in anonymization and strict governance before sensitive data reaches them; and some capital allocators are treating AI infrastructure itself — compute, data centres, foundation models — as a strategic asset worth direct ownership.
Regulation is catching up fast and unevenly, with major regimes now treating data location and third-party AI access as a risk to be supervised, not just a technology choice. Given the different AI strategies already in motion, what would it actually take to make them auditable and defensible across jurisdictions?
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1:15–2:45pmTue 17 NovPublic-Private RoundtableRoundtable Room 3Open
Accountability & Liability In Agentic SystemsSovereignty & Resilience in a Rewired Financial System
Open Data: Fuel for Financial AI
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Adeline TungDirector, Policy & Technology, Data Innovation & Protection GroupIMDA
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Dr. Amanah RamadiahDirector, Asia PacificFNA
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Dr. Alex PalmerChief Operating OfficerDataMasque
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Dr. Duan PuHead of Privacy-Enhancing Technologies DepartmentAnt International
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Mani GuptaVice PresidentVisa
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Rajat MaheshwariSenior Vice President, Strategic Growth, Asia PacificMastercard
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Ramakrishnan TGStrategic Partnerships Lead, Google Payments, APACGoogle
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Shebani BawejaGroup Chief Data OfficerStandard Chartered Bank
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Dr. Uzair JavaidChief Executive Officer & Co-founderBetterdata
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Dr. Zhao JingyuanHead, Group Data OfficeOCBC
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Selene YoeDeputy DirectorMonetary Authority of SingaporeModerator
About this session
While AI is creating new opportunities across financial services, its effectiveness ultimately depends on access to high-quality and trusted data. Building on emerging open data sharing initiatives across the financial sector, this roundtable will explore how financial institutions can collaborate to unlock greater value from data while preserving privacy, security, and trust. Bringing together industry leaders, technology providers, AI practitioners, and policymakers, the discussion will examine practical approaches to data sharing, privacy-enhancing technologies, common data standards, and trusted data ecosystems that can accelerate AI innovation, enable the development of more capable and reliable financial AI models, strengthen risk management, and support the next generation of AI-enabled financial services.
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