Machine Learning in Finance programme

Workshop 2: Machine Learning in Finance

Dr Simon Goo

Executive Director – Head, Group Risk Analytics


Simon leads a multi-disciplinary risk analytics team that oversees enterprise-wide risk management models at United Overseas Bank. The team validates a wide range of risks and measurement models. Those models can be used to assess and manage credit, market and balance sheet risks across the bank’s global business.

Prior to joining the bank, Simon held senior corporate positions in technology and finance related companies in areas such as strategic planning, private equity investments and mergers and acquisitions. He has also worked with promising enterprises to assess the potential of their technologies for product commercialization and strategic investment.

Simon holds a PhD in the field of decision control systems from the University of Newcastle- upon-Tyne (UK). He received an IChemE Jubilee prize for his research applying Statistical and Artificial Intelligence Methodologies for on-line fault detection and diagnosis in 1997.

Simon was part of the banks’ Innovation Workgroup member to bring The Finlab to launch and he had been a mentor in The FinLab. He was part of the judging panel in the Global Fintech Hackcelerator. Simon serves as a member in the Product Program Committee and the Alt-Chair person in the Valuation Adjustments working group in the bank.

Aaron Hallmark

Chief Executive Officer


Aaron is CEO of Catena Technologies, a solutions company that helps financial institutions improve their business capabilities using cutting-edge technologies. Aaron has twenty-five years of technology experience in cross-asset trading, clearing, risk management, accounting, and compliance. His career has spanned across the U.S., Canada, the Middle East, and throughout Asia Pacific, and he has managed projects for such clients as JPMorgan Chase, HSBC, Citibank, Morgan Stanley, HKMA, and SGX. Aaron received his B.S. from Stanford University in Artificial Intelligence, as well as an MBA from the USC Marshall School of Business. Aaron is a frequent lecturer for Singapore Management University's Master of IT in Financial Services program.

Prior to joining Catena, Aaron spent more than 9 years with Calypso Technology, a global financial software and services company focused on cross-asset trading, risk management, and processing. At Calypso, Aaron led the Professional Services team for the Americas based in New York. He later took on the Singapore-based role of Director of Professional Services, Asia, where he directed the APAC region's first-ever implementation of OTC derivatives clearing.

In his current role, Aaron has led the development of Catena TRACE Reporting, a solution that automates financial institutions' workflow for regulatory reporting, as well as TRACE Analytics, a system that consolidates trade data to provide a wide range of descriptive and predictive analytics.

Joseph Toh


FinTech Association Singapore

Serial entrepreneur. Investor. C-Suite Advisor, Blockchain, XR, AI expert, Founder of FinTech Association Singapore, ex-Credit Suisse/Accenture Head of Technology Consulting and Andersen Ventures.

Founder and advisor to Award winning Tech companies. Extensive international network & experience with Fortune 500 companies and start-ups, successfully delivering award winning businesses in Digital, Software, Mobile and Brand management. Strategy to commercialization, managing large complex transformations.

Former Accenture executive and Credit Suisse’s Strategy & Innovation across Asia Pacific; key leadership roles working closely with global and regional C-suite leadership to drive digital innovation, early stage deal structuring, industry consortium's/partnerships and delivering next generation industry awarding winning Digital platforms that drive customer experience and sales.

A regular contributor to industry thought leadership, advisor, government bodies with over 100+ industry leading publications. Prior roles include, Global Head of Strategy & Solutions, Head of Architecture at Standard Chartered Bank, Program Director for Singtel/Optus, Head of Accenture Technology Consulting Korea and CIO for Best Buy China.

Jonathan Morgan


Kobe International Blockchain Research Centre

Experienced risk specialist and a lead researcher in AI, Machine Learning & Blockchain, with a passion to be the bridge between traditional banking and digital transformation. 16+ years track record of transforming business operations, enhancing processes via technologies, re-defining policies and frameworks in the risk & compliance environment and launching new ventures partnering with solution providers. 

Radha Pendyala

Enterprise Data Scientist


Radha works as an Enterprise Data Scientist at Refinitiv. His work involves applying machine learning and quantitative financial modeling techniques to large datasets in order to solve specific problems in the financial and risk domain. Prior to Refinitiv, he has worked as a portfolio manager at Goldman Sachs Asset Management. He has more than a decade of experience in building financial and statistical models.

Johnson Poh

Executive Director - Head, Group Enterprise Artificial Intelligence (AI)


Johnson Poh has been a Data Scientist with experience spanning across the finance, consulting and government sectors for the past decade. His present and past professional appointments include being Executive Director & Head Enterprise Artificial Intelligence for UOB Group, Head Data Science/Practice Lead at DBS Bank, Chief Data Scientist, ASEAN at Booz Allen Hamilton as well as Principal Data Scientist at Ministry of Defence, Singapore respectively.

Johnson also serves as an Adjunct Faculty at Singapore Management University (SMU) where his focus areas include applied statistical computing, machine learning as well as big data tools and techniques. He completed his bachelor’s degree at University of California, Berkeley, majoring in the subjects of Pure Mathematics, Statistics and Economics. He received his postgraduate degree in Statistics at Yale University.

Nagarajan Ramamurthi

Founder and CEO


Nagarajan started career in Information Technology Consultant and consulting with big financial institutions in Asia and Americas.

He leads and successfully executed number of financial solution programs covering Payment systems, Risk systems, Investment Products, Private wealth Management, Asset and Compliance business.

He has vast experience within digital transformation solution that includes Data Analytics, Machine Learning, Deep Learning and Blockchain. He designed and developed digital solution targeting Z-generation called Smart Product analyser.

He has held several senior leadership positions in the large Financial Institutions covering Asia and Americas.

He is a volunteering with People Association as Grassroot leader for 7 years, serving different part of the Singapore society.

He volunteering on offering Digital transformation training for the students from Indian University.

Nagarajan is a Project Management Professional of the Project Management Institute of Company Directors (PMI), USA.

He has presented and has been part of expert panel in various business forums.

Amandeep Singh Sidhu

Machine Learning Quant


Amandeep currently works as a machine learning quant at the Standard Chartered Bank (Singapore), where he is involved in predictive time series modelling for the entire group. Prior to this, he undertook roles in derivative pricing and risk management at Murex and OCBC Bank (Singapore). Publications authored under his name primarily span the research area of reinforcement learning.

Amandeep graduated with B.Eng (Hons) in Computer Engineering from the Nanyang Technological University. Thereafter, he attended University of Chicago as a Monetary Authority of Singapore scholar where he graduated with a M.S. in Financial Mathematics.

Eric Tham

Senior Lecturer & Consultant of Analytics & AI


Eric is presently a senior lecturer in AI and data science in the National University of Singapore. Previously he has over 15 years of financial experiences in banks, Fintech start-ups and oil major. His diverse financial experiences in risk management, quantitative analytics and energy economics include as a vice-president with Credit Suisse, Standard Chartered bank, BP Oil and DBS. He was also director of data science in a China Fintech start-up with 5 million users doing AI and NLP on the China equity indices and selling the data to global hedge funds. His educational qualifications include MS Financial Engineering from Columbia University and a Phd in Finance from Edhec (2019/20 expected). He mixes practice financial experience with AI expertise.

Lawrence Wee

Director, Data Science


Machine Learning in Finance Programme 

**This programme is recognised under the Financial Training Scheme (FTS) and is eligible for FTS claims subject to all eligibility criteria being met.




Machine Learning Models for Risk Management

  • Supervised Learning
  • Unsupervised Learning
  • Semi-supervised Learning
  • Reinforcement Learning
  • Deep Learning
  • Advanced Machine Learning models
  • Case Study Examples

Aaron Hallmark, Chief Executive Officer, CATENA TECHNOLOGIES


Morning coffee break


Machine Learning in the Regulatory Compliance and Risk Management

  • Sharing of the current state in managing regulatory compliance matters in banking, and challenges faced by various banks across the globe 
  • The dreadful amount of regulations specific to various countries required to be adhered to
  • Traditional Banking vs Digital Transformation: How things were operated for the past 15 years and where are we heading towards 
  • Why the need to prepare our people for digital transformation, not just implementing solutions
  • How AI and Machine Learning are transforming the way we access, store, update, process and analyse information
  • How risk and compliance management will evolve
  • We are not losing our jobs, our jobs are simply evolving. 

Jonathan Morgan, Regtech Lead Singapore, SIA PARTNERS




Machine Learning Applications in Non-financial Risk

  • Managing when data is not enough scenarios
  • Known “unknown” VS unknown “unknown”
  • Advanced fraud detection and neural networks
  • Managing machine learning black boxes
  • Case study examples 



Embracing Big Data and creating a comprehensive data strategy 

  • 3Vs of Big Data
  • Managing data from silo operations
  • Big data strategy and extracting value from limited sources
  • Gaining insights from complex data patterns
  • Learning from own ‘big data’ challenges
  • Case Study examples

Johnson Poh, Executive Director - Head, Group Enterprise Artificial Intelligence (AI), UOB


Afternoon coffee break


Advanced Analytics Models: Challenges for Model Management

  • Model risks – does it matter?
  • Is ML/AL changing the landscape of risk managing?
  • Emerging challenges of advanced analytics models
  • Managing risks arising from the use of ML/AI

Simon Goo, Executive Director – Head, Group Risk Analytics, UOB


End of day 1





Machine Learning and Portfolio Management- an Overview

  • The foundational theory of ML for financial trading
  • Can machines learn finance?
  • Overview of ML in trading & portfolio management
    • Types of ML strategies
    • From alpha to beta
  • Natural Language Processing of news sources/ social media
    • Financial sentiment
    • Risk & ambiguity

Eric Tham, Senior Lecturer & Consultant of Analytics & AI, NATIONAL UNIVERSITY OF SINGAPORE


Machine Learning & Portfolio Management – the techniques

  • ML in Portfolio strategy techniques
    • Unsupervised methods
    • Bayesian & mean-reversion
    • Factors-based
  • Financial theory & Machine Learning
    • ML in the eyes of finance
  • Demonstration example of portfolio strategies construction

Eric Tham, Senior Lecturer & Consultant of Analytics & AI, NATIONAL UNIVERSITY OF SINGAPORE


Morning coffee break


Machine Learning and Trade strategies

  • Finding alpha
  • Value investing
  • Factor investment
  • Reinforcement Learning
  • Q learning
  • AI for ESG
  • Sentiment Analysis 

Lawrence Wee, Chief Data Scientist, ALLIANZ ASIA PACIFIC




Conversational AI– Beyond the chatbot hype

  • Current state of the AI industry applied to digital assistants/chatbots
  • Source, real research and development behind it
  • Challenges
    • Data
    • Scalability and production issues
  • Practical possibilities ahead for organisations

Joseph Toh, Founder, FinTech Association Singapore


Machine Learning in Quantitative Trading

  • Setting up the problem
  • Feature selection
  • Supervised learning
  • Cross validation
  • Live example

Amandeep Singh Sidhu, Machine Learning Quant, STANDARD CHARTERED BANK

15:35 Afternoon coffee break


Trading Strategies based on news and sentiment data

  • Machine readable news - format and metadata description
  • Analyzing news data
  • Understand real time sentiment data
  • Using kalman filter on sentiment data and identifying sentiment regimes
    • Use case demo and discussion
  • Trading strategies based on sentiment data
  • Understanding multidimensional real time sentiment data
  • Cross rotation strategy formulation and back-testing
    • Use case demo and discussion
  • Deep learning based trading strategy
    • Use case demo and discussion

Radha Pendyala, Enterprise Data Scientist, REFINITIV


End of course