Hi, I'm Gary Ang, or Ming.
I bridge AI, quantitative finance, and risk management (or at least I think I do). Most recently, I led AI risk supervision at the Monetary Authority of Singapore (MAS), where I developed Singapore's first AI risk management guidelines (AIRG) for the financial sector. Before that, I was division head for investment risk management, overseeing risk management of Singapore's foreign reserves. I also spent years deep in the weeds of Basel 2, 2.5, and 3 capital rules, model risk audits, and banking policy. Basically, I did work so technical that it clears a room at parties when people ask what I do.
I have a PhD in Computer Science, where I researched deep learning for networks, time series, and multimodal data, publishing 11 papers at venues like ACL, ACM Transactions on the Web, and IEEE Big Data, including an honourable mention at ACM IUI. I also have Masters degrees in Financial Engineering and Knowledge Engineering from NUS, and an Electrical Engineering degree from the University of Toronto. Yes, that's a lot of degrees. No, I don't know when to stop.
I've taught Python, machine learning, deep learning, and AI at NUS, SMU, SUSS, Nanyang Polytechnic, and MAS Academy, to audiences ranging from central bankers to healthcare workers to policemen. I'm currently developing AI risk management materials for the Cambridge Centre for Alternative Finance. I actually enjoy explaining complicated things to rooms full of people who didn't ask for it. Masochist, I know.
Before all of this, I spent four years at the Ministry of Information, Communications and the Arts, where I helped develop Singapore's creative industries strategy and created the Creative Youth eXchange, a regional design competition that somehow became a reality TV programme. I also helped (coloring and contributing a chapter) with a series of Mr Kiasu books from 2017-2019, which may be the most widely read publication I've had a hand in.
Beyond finance and technology, I'm a watercolor artist and illustrator whose work has been commissioned by Wallpaper, Tatler, Jetstar, and the Esplanade, hard proof that not everything I do involves code.
Let's connect. I'm always up for interesting conversations. Reach me on LinkedIn or at gary(at)quaintitative.com. I'm particularly interested in conversations about AI governance, strategy, and risk management, as well as their intersections with finance and art. I'm open to collaborations, talks, and exploring opportunities that align with my interests, particularly since I am transitioning to a portfolio career in 2026.
Why Quaintitative?
The name reflects my belief that the most interesting insights emerge at intersections. The name itself is a play on 'quantitative' and 'AI', with a touch of 'quaint'. It's where I explore ideas that don't fit neatly into institutional frameworks.
More about me.
I led the development of supervisory frameworks for responsible AI and AI risk management at the Monetary Authority of Singapore (MAS) from 2023 to 2025.
One of the first pieces of work I embarked on was to synthesize my past experience in model risk management with my background in AI to deliver the Information Paper on AI Model Risk Management in banks at the end of 2024. I also developed Singapore's first AI Risk Management Guidelines (AIRG) for the financial sector in 2025. I was also part of the Singapore Accreditation Council's Working Group for the development of the accreditation programme for ISO 42001: AI Management System.
Prior to this role, I was division head of the investment risk management division in MAS, and oversaw a division of 20 to risk manage Singapore's multi-billion dollar foreign reserves. I was responsible for a wide range of areas - from working with the portfolio managers on asset allocations, to risk limits, inhouse risk systems, as well as managing external fund managers.
Prior to all this, I spent many years looking deeply at Basel 2, 2.5 and 3 rules for banks, as well as the equivalent rules in the capital market space. I also spent many years auditing models in banks and exchanges, ranging from credit scoring models, to market pricing and risk models, as well as margin models.
My PHD research focuses on deep learning models for networks, time series and multimodal data, with practical applications in human-computer interaction and finance. My research works have been accepted by conferences and journals such as the Annual Meeting of the Association for Computational Linguistics (ACL) and ACM Transactions on the Web, and received an honorable mention award at the ACM Annual Conference on Intelligent User Interfaces in 2022. I received the SMU Presidential Doctoral Fellowship in 2022, and also did part of my PhD on an MAS scholarship. I still review papers for conferences such as ACL, UIST, AIES (under AAAI) regularly. My research can be viewed here.
I also teach to learn to better communicate complexity. I have conducted courses on Python, Machine Learning, Data Science, AI at various institutions including NUS, SMU, SUSS.
I also illustrate and do watercolors. As an illustrator, I've received commissions from well known publications and brands such as Wallpaper, Tatler, Jetstar. My artworks can be viewed at playgrd.com.