FinTech Training · A newly revamped curriculum
Generative AIin Finance
Updated for the Next Wave of AI in Finance
Practical knowledge for a smarter, more resilient financial future.
- Format
- Online (Asynchronous)
- Duration
- 12 hours
- Programme Registration Date
- 11 Nov 2026 - 15 Jan 2027
Programme overview
Generative AI is evolving rapidly — and so is our curriculum.
The Generative AI in Finance course has been revamped to reflect the latest developments in AI and their growing impact on the financial industry.
Read programme overview
The refreshed curriculum takes participants from AI and machine learning foundations to Generative AI and Large Language Models, before exploring their applications across financial services. It also addresses the realities of AI adoption — including implementation challenges, emerging risks, AI governance, Agentic AI and Responsible AI.
Participants will develop a well-rounded understanding of how AI works, where it can create value in finance, its limitations and risks, and how it can be adopted responsibly within financial institutions.
Who is this program for?
Designed for finance professionals, business leaders and individuals looking to stay ahead of the rapidly evolving AI landscape, this programme is ideal for financial analysts, executives, traders, portfolio managers, quantitative analysts, risk and compliance professionals, as well as anyone keen to understand how Generative AI is transforming financial services—from real-world applications and emerging technologies to responsible adoption and governance.
Industry context
82%
of global financial services CEOs say their AI initiatives are performing ahead of expectations.
Source: EY-Parthenon CEO Outlook Survey, 2026
89%
of financial services respondents say AI is helping increase annual revenue and decrease annual costs.
Source: NVIDIA, 2026
Program highlights
- Follow the latest developments, from AI and machine learning to Generative AI and agentic systems.
- Explore practical applications across financial services.
- Understand limitations, governance and responsible adoption.
View all program highlights
Newly Revamped Curriculum
Stay current with an updated curriculum reflecting the latest developments and evolving applications of Generative AI in financial services.
Real-World Finance Applications
Explore applications across credit and risk, investment research, customer servicing, financial crime, robo-advice and algorithmic execution.
AI to Agentic AI
Build a connected understanding of AI and machine learning through to LLMs, RAG, tool use and emerging agentic AI systems.
Beyond the GenAI Hype
Develop a balanced perspective on what Generative AI can do, where its limitations lie, and when assistive, augmented or autonomous use is appropriate
Inside the Financial Industry
Discover how financial institutions are adopting AI, where value is being realised, and what separates successful implementations from unsuccessful pilots.
Responsible AI in Practice
Explore AI governance, emerging risks, MAS FEAT principles, Veritas methodology and evolving expectations for responsible AI adoption.
Program fees & funding
Course Fees: SGD 1722.20 (before subsidies)
SkillsFuture Code:TGS-2024048817
This programme is eligible for subsidies under SWDA Funding. Singaporeans and Permanent Residents can enjoy subsidies up to 70%.
Self-sponsored participants
Singapore Citizens aged 40 years and above
SGD 545.10²Including 9% GSTInternational Participants
SGD 1722.20Including 9% GSTProgram modules
Introduction to AI and Machine Learning
- Understand the fundamentals of AI, machine learning, and deep learning.
- Explore supervised, unsupervised, and reinforcement learning in financial services.
- Learn how big data, machine-generated data, and IoT shape financial decisioning.
Introduction to Generative AI and its related models
- Learn how neural networks and transformers power modern generative AI.
- Understand tokens, embeddings, and the role of the context window.
- Explore major generative model families and why hallucination occurs.
Digital Transformation and the impact of AI
- Examine how AI supports business transformation and evolution.
- Identify where AI creates real value across the organisation.
- Understand trust as a key factor in AI adoption and scaling
Key Developments in the Finance Industry and AI
- Review the current state of the financial industry and its AI direction.
- Compare AI adoption trends with public announcement activity.
- Study what institutions have disclosed about deployments and failures.
Benefits and Challenges of Generative AI in Finance
- Assess the business benefits of generative AI in finance realistically.
- Understand the key risks, limitations, and implementation challenges.
- Learn when generative AI should assist, augment, or remain out of scope
Large Language Model (LLM) and Use cases
- Understand the science behind LLMs as prediction systems, not retrieval engines.
- Learn the capability classes that emerge from how LLMs work.
- Explore grounding, retrieval-augmented generation, tool use, and agents.
AI in Finance: Use cases and examples
- Review how classical machine learning is already used in production.
- Explore anomaly detection, financial crime surveillance, and computer vision.
- Understand use cases such as robo-advice and algorithmic execution.
Use Cases of Generative AI in Finance
- Examine practical applications in credit, risk, and documentation workflows.
- Explore use in investment research, analysis, and customer servicing.
- Understand the risks in financial crime, including both attack and defence.
The Art of Prompt Design
- Learn to treat prompt design as structured specification writing.
- Walk through a regulated drafting task using prompt best practices.
- Understand how to evaluate outputs and extend prompt performance.
Governance of AI
- Identify the main risks AI creates in a financial institution.
- Review ethical AI principles and governance mechanisms.
- Understand the regulatory direction and emerging expectations for AI.
Key Trends and Developments in Generative AI and Financial Applications
- Examine how AI is reshaping financial services and operating models.
- Understand the rise of agentic AI and the accountability gap.
- Assess third-party reliance, provider concentration, and systemic exposure risks.
Responsible AI and the MAS FEAT framework
- Introduce the core concepts of Responsible AI in financial services.
- Explain the FEAT principles, Veritas methodology, and supervisory expectations.
- Compare MAS guidance with regional and global approaches to AI governance.
Program Director
Over 30 years of experience in financial services and digital innovation across Asia and the Middle East.
Read full biography
Prof. Tek Yew Chia is a leading voice in financial services and digital innovation, with over 30 years of experience spanning strategy, technology, and regulation across Asia and the Middle East. He is Adjunct Professor and Advisor at the NUS Asian Institute of Digital Finance, and formerly Vice Chairman of Oliver Wyman Singapore and Head of Financial Services Advisory in KPMG Singapore.
Prof. Chia is concurrently a Senior Advisor in Boston Consulting Group (BCG) and also serves as an advisor to the ASEAN Bankers Association (ABA) and the Global Finance and Technology Network (GFTN – a spin-off from the Monetary Authority of Singapore). A sought-after speaker, he brings sharp insights on the future of finance at the intersection of policy, technology, and business.
Register your interest
Contact our team for more information about Generative AI in Finance.