WSQ - Generative AI for Finance and Fintech

Topic 1: Introduction to Generative AI and Its Foundations in Finance 

• Basics of AI and Machine Learning
• Introduction to Generative AI (GAI)
• AI and GAI use cases in finance

Topic 2: Core Generative AI Models and Technologies 

• Large Language Models (LLM) and Transformer model
• Text-to-Image and Diffusion model
• Text-to-Speech (TTS) and Speech-to-Text technologies
• Retrieval Augmented Generation (RAG)
• Autonomous AI agents and bots

Topic 3: Practical Applications and Case Studies 

• Risk management and fraud detection
• Customer service agent and chatbot
• Generating synthetic financial data
• Algorithmic trading
• Robo-advisors

Topic 4: Ethical, Legal, and Regulatory Considerations 

• AI Ethics and Governance in Finance
• Deepfakes and voice cloning
• Data Privacy and Security
• Regulatory Compliance and Governance

Topic 5: Future Trends and Innovations in Generative AI for Finance

• Latest Developments and Research in Generative AI
• Emerging Applications and Strategic Implications
• Preparing for the Future of Finance with AI

Final Assessment

• Written Assessment - Short Answer Questions (WA-SAQ)
• Practical Performance (PP)

Promotion Code

Promo or discount cannot be applied to WSQ courses

Minimum Entry Requirement

Knowledge and Skills

• Able to operate using computer functions
• Minimum 3 GCE ‘O’ Levels Passes including English or WPL Level 5 (Average of Reading, Listening, Speaking & Writing Scores)

Attitude

• Positive Learning Attitude
• Enthusiastic Learner

Experience

• Minimum of 1 year of working experience.

Minimum Software/Hardware Requirement

Softtware: Windows / Mac

Hardware: Laptop

About Progressive Wage Model (PWM)

The Progressive Wage Model (PWM) helps to increase wages of workers through upgrading skills and improving productivity. 

Employers must ensure that their Singapore citizen and PR workers meet the PWM training requirements of attaining at least 1 Workforce Skills Qualification (WSQ) Statement of Attainment, out of the list of approved WSQ training modules.

For more information on PWM, please visit MOM site.

Funding Eligility Criteria

Steps to Apply Skills Future Claim

• The staff will send you an invoice with the fee breakdown.
• Login to the MySkillsFuture portal, select the course you’re enrolling on and enter the course date and schedule.
• Enter the course fee payable by you (including GST) and enter the amount of credit to claim.
• Upload your invoice and click ‘Submit’

SkillsFuture Level-Up Program

The  SkillsFuture Level-Up Programme provides greater structural support for mid-career Singaporeans aged 40 years and above to pursue a substantive skills reboot and stay relevant in a changing economy. For more information, visit SkillsFuture Level-Up Programme

Get Additional Course Fee Support Up to $500 under UTAP

The Union Training Assistance Programme (UTAP) is a training benefit provided to NTUC Union Members with an objective of encouraging them to upgrade with skills training. It is provided to minimize the training cost. If you are a NTUC Union Member then you can get 50% funding (capped at $500 per year) under Union Training Assistance Programme (UTAP).

For more information visit NTUC U Portal – Union Training Assistance Program (UTAP)

Steps to Apply UTAP

• Log in to your U Portal account to submit your UTAP application upon completion of the course.

Note

• SSG subsidy is available for Singapore Citizens, Permanent Residents, and Corporates.
• All Singaporeans aged 25 and above can use their SkillsFuture Credit to pay. For more details, visit www.skillsfuture.gov.sg/credit
• An unfunded course fee can be claimed via SkillsFuture Credit or paid in cash.
• UTAP funding for NTUC Union Members is capped at $250 for 39 years and below and at $500 for 40 years and above.
• UTAP support amount will be paid to training provider first and claimed after end of class by learner.

Appeal Process

1. The candidate has the right to disagree with the assessment decision made by the assessor.
2. When giving feedback to the candidate, the assessor must check with the candidate if he agrees with the assessment outcome.
3. If the candidate agrees with the assessment outcome, the assessor & the candidate must sign the Assessment Summary Record.
4. If the candidate disagrees with the assessment outcome, he/she should not sign in the Assessment Summary Record.
5. If the candidate intends to appeal the decision, he/she should first discuss the matter with the assessor/assessment manager.
6. If the candidate is still not satisfied with the decision, the candidate must notify the assessor of the decision to appeal. The assessor will reflect the candidate’s intention in the Feedback Section of the Assessment Summary Record.
7. The assessor will notify the assessor manager about the candidate’s intention to lodge an appeal.
8. The candidate must lodge the appeal within 7 days, giving reasons for appeal 
9. The assessor can help the candidate with writing and lodging the appeal.
10. he assessment manager will collect information from the candidate & assessor and give a final decision.
11. A record of the appeal and any subsequent actions and findings will be made.
12. An Assessment Appeal Panel will be formed to review and give a decision.
13. The outcome of the appeal will be made known to the candidate within 2 weeks from the date the appeal was lodged.
14. The decision of the Assessment Appeal Panel is final and no further appeal will be entertained.
15. Please click the link below to fill up the Candidates Appeal Form.

• AI Financial Analyst
• Generative AI Fintech Developer
• AI-Driven Risk Management Specialist
• GAI-Enhanced Fraud Detection Analyst
• Financial Data Scientist using AI
• AI-Integrated Wealth Management Advisor
• AI-Powered Regulatory Compliance Officer
• Fintech Innovation Strategist with AI
• AI-Driven Investment Portfolio Manager
• GAI Solutions Architect for Finance
• AI-Enhanced Credit Analyst
• Financial Technology Product Manager with AI
• AI-Driven Financial Planning Consultant
• GAI-Based Financial Market Researcher
• AI-Enhanced Banking Operations Manager
• Fintech Customer Experience Designer with AI
• AI-Driven Financial Reporting Specialist
• GAI Implementation Consultant in Finance
• AI-Enhanced Insurance Underwriter
• GAI-Powered Blockchain Specialist

Dr. Alfred Ang: Dr. Alfred Ang is a distinguished academic and technology consultant with over 20 years of experience in artificial intelligence, data analytics, and digital transformation. Holding a PhD in Computer Science, his research and professional practice focus on the integration of AI technologies in business and finance ecosystems. Dr. Ang has collaborated with financial institutions and technology firms to design and implement data-driven solutions that enhance predictive analysis, risk management, and operational efficiency. As an experienced educator and curriculum developer, he has trained countless professionals in areas such as AI applications, fintech innovation, and data governance, bridging the gap between technical expertise and business impact.

In this course, Dr. Ang guides participants through the practical use of generative AI tools and frameworks tailored for finance and fintech applications. His sessions emphasize hands-on learning, where learners explore AI-driven automation, financial forecasting, and decision-support systems powered by generative models. With a balance of technical depth and industry relevance, Dr. Ang equips participants with the knowledge to apply AI strategically—enhancing productivity, optimizing workflows, and driving innovation in the evolving financial technology landscape.

Iris Wang: Iris Wang is an accomplished corporate trainer and adult educator with a strong foundation in business communication, digital literacy, and AI-driven workplace transformation. She holds the WSQ Advanced Certificate in Training and Assessment (ACTA) from the Institute for Adult Learning, equipping her with the pedagogical skills to deliver engaging and industry-relevant programs. Iris has worked extensively with corporate and professional learners, focusing on technology integration, productivity enhancement, and future-ready competencies in business and finance.

In “Generative AI for Finance and Fintech,” Iris helps professionals understand the transformative power of AI in financial decision-making, compliance, and client engagement. Her training approach combines clear explanation with hands-on learning, guiding participants to apply AI tools for data visualization, report generation, and predictive analysis. She is particularly skilled at simplifying complex AI concepts into accessible insights, enabling finance professionals to leverage generative AI for greater innovation and strategic impact.

Gary Chan Kim Heng: Gary Chan is a Chartered Accountant (ISCA, ACCA) and seasoned corporate trainer with over 25 years of executive experience in finance, strategic management, and business transformation. Having served as Regional CFO, Vice President, and Director in multinational corporations, Gary brings real-world insight into financial leadership and innovation. He holds an MBA in International Business from Brunel University (UK) and a Master of Science in Strategic Marketing from the National University of Ireland, along with the ACTA certification as a professional trainer.

In “Generative AI for Finance and Fintech,” Gary integrates his extensive corporate background with cutting-edge AI applications, helping learners understand how AI can enhance financial modeling, compliance monitoring, and investment analytics. His sessions emphasize practical use cases—such as using generative AI for financial forecasting, fraud detection, and automated reporting—preparing participants to navigate the rapidly evolving digital finance landscape with confidence and strategic foresight.

Bell Ang Chai Huat: Bell Ang is a Chartered Accountant (CPA Australia, CPA Singapore) and experienced finance and IT professional with over 40 years in accounting, financial systems implementation, and ERP integration. She has served in leadership roles across Asia Pacific, including Regional Finance Manager and Senior IT Consultant, and has implemented major financial systems such as Oracle, Hyperion, and Scala ERP. A WSQ-certified trainer, Bell specializes in bridging finance and technology to drive digital efficiency and financial insight.

In “Generative AI for Finance and Fintech,” Bell focuses on helping finance professionals harness AI for automation, predictive analytics, and process optimization. Drawing on her deep ERP and data management expertise, she teaches how generative AI can be used to streamline budgeting, reporting, and auditing workflows. Her practical and structured approach empowers learners to transform financial operations into agile, data-driven systems ready for the AI economy.

Malcolm Soo Chee Kong: Malcolm Soo is a finance professional and experienced lecturer with extensive expertise in financial planning, analysis, and management reporting. He has held leadership roles at JTC Corporation and Sumitomo Electric, where he oversaw financial modeling, budgeting, and SAP system implementation. A Chartered Accountant of Singapore and ACTA-certified trainer, Malcolm is known for his ability to make complex financial topics approachable and practical for diverse learners.

In “Generative AI for Finance and Fintech,” Malcolm bridges traditional financial expertise with AI-driven innovation. His training emphasizes using generative AI tools for financial analysis, scenario simulation, and visualization. He guides participants through real-world applications of AI in cash flow forecasting, performance analysis, and risk evaluation, helping finance professionals enhance productivity, accuracy, and strategic insight in an increasingly data-centric industry.

Sam Wadia: Sam Wadia is a fintech strategist and data analytics consultant with over 20 years of experience in financial technology, business intelligence, and enterprise digital transformation. Having advised leading financial institutions on AI adoption and regulatory technology, he specializes in integrating advanced analytics, natural language processing, and generative AI tools into financial systems. Sam is recognized for his practical, innovation-focused approach to bridging finance and data science.

In “Generative AI for Finance and Fintech,” Sam empowers participants to leverage AI for smarter financial operations and innovation. His sessions explore real-world fintech applications, including generative AI for market analysis, automated portfolio management, and algorithmic risk assessment. With a strong focus on ethics and governance, Sam helps finance professionals embrace AI responsibly—transforming insights into actionable, compliant, and strategic business value.