Quaintitative
AI for people who need to get it right. From someone who built the models and frameworks.
Whether you're managing AI risk, setting governance strategy, or building your team's AI capability, I help you move from overwhelmed to equipped. No hype. No prompt engineering. No AI governance theatre. Just transferable understanding.
What I do
Training & Workshops
Your team leaves with practical frameworks they can apply immediately, not just concepts or prompt engineering tips.
Advisory & Speaking
You'll have a clear picture of where you stand on AI governance and risk management, what to do next and why it matters.
Research & Tools
Tools and frameworks built from the ground up, informed by published research and real regulatory experience.
About
Top Voice in AI
Hi, I'm Gary Ang. I'm a regulator turned independent, a quant who illustrates, and someone who loves to design AI models but also write the rules that govern them. I'm still not sure how that happened.
Quaintitative - a play on quantitative and AI - is my independent practice, covering AI training, advisory, speaking, and research. My core focus is AI governance and risk management in financial services, with programmes extending to machine learning fundamentals, Agentic AI, and AI for domain professionals.
My training engagements include the Monetary Authority of Singapore (MAS), the Association of Banks in Singapore, and the Singapore College of Insurance. I'm a module lead for Cambridge Centre for Alternative Finance's AI programme for global regulators, affiliate faculty and incoming adjunct at the Singapore Management University (SMU). I sit on Rutgers Business School's Masters of Quantitative Finance Advisory Board.
I'm also a pro bono advisor to the Institute of Banking & Finance (IBF), a co-author of a recently published paper on Agentic AI model risk management. Other current projects: papers on AI and workforce transformation, Agentic AI evaluation; and applications for customising AI governance policies, controls, and competency testing.
I previously led AI risk supervision at the MAS, where I developed Singapore's AI Risk Management Guidelines (AIRG) - the country's first sector-wide AI risk framework for financial institutions. I was also division head for investment risk management, overseeing risk management of Singapore's foreign reserves, and have deep expertise in Basel capital rules, banking and capital market policies, and model risk supervision. I was also a member of the Singapore Accreditation Council working group for the accreditation programme for ISO 42001 (AI Management Systems).
I hold a PhD in Computer Science from Singapore Management University (Presidential Doctoral Fellowship, 2022). My research focused on deep learning for networks, time series, and multimodal data, with publications at leading venues including ACL and ACM conferences. I also hold Masters degrees in Financial Engineering and Knowledge Engineering from NUS, and an Electrical Engineering degree from the University of Toronto.
I also illustrate professionally, with commissions from Wallpaper, Tatler, Jetstar, and the Esplanade.