GCIP: Applied Finance
Master Financial Analysis and Valuation with AI.
Duration
7 Days
Learner Profile
UG & PG Students
Programme Fee
Enter your name, email and phone number to view the current programme fee.
Certificate
SMU
Certificate of Participation
Your Pathway to SMU Masters
Immersion (GCIP)
Applied Finance
7 DaysVisiting Scholar Programme
Upto 4 Finance Modules
4 MonthsMasters Admission
MSc in Applied Finance (MAF) & MSc in Wealth Management (MWM)
1 YearImmersion (GCIP)
Applied Finance
7 DaysVisiting Scholar Programme
Upto 4 Finance Modules
4 MonthsMasters Admission
MSc in Applied Finance (MAF) & MSc in Wealth Management (MWM)
1 Year*All admissions to the Master's programme are subject to SMU's selection criteria and approval process.
Applied Finance
Master AI-powered financial statement analysis, company valuation, and corporate finance decisions with SMU
This course introduces undergraduate students to the fundamentals of applied finance, with a focus on understanding financial statements, basic company valuation, and key corporate finance decisions. Using simplified real-world examples, students will learn how businesses generate value, how financial performance is assessed, and how financial decisions are made in practice.
Through interactive lectures, guided exercises, and a team-based final presentation, students will gain a practical understanding of finance concepts and build confidence in discussing financial information in a professional setting.
Learning Outcomes
By the end of the course, students will be able to:
- Read and interpret basic financial statements to understand a company's performance.
- Use key financial ratios to assess profitability, liquidity, and leverage at a foundational level.
- Explain common corporate finance decisions such as capital investment and the use of debt versus equity.
- Present a simple, structured financial analysis clearly in a team presentation.
Final assessment includes a group presentation on financial analysis evaluated by SMU faculty.
SMU Faculty Sessions
15 Academic Hours| Session | Duration | Topics Covered |
|---|---|---|
| 1 | 3 hours | Financial Statement Analysis and Business Quality Assessment Business models: competitive advantages, revenue drivers, cost structures. Three financial statements and quality of earnings assessment. Key financial ratios: profitability, leverage, liquidity, efficiency. Using GenAI for data extraction, ratio comparisons, peer identification. |
| 2 | 3 hours | AI in Finance - Fundamentals and Applications AI/ML fundamentals: supervised learning, unsupervised learning, deep learning (conceptual, non-technical). Current AI applications: private equity and venture capital deal sourcing, credit scoring, fraud detection, robo-advisors. Generative AI in finance: effective use cases vs. limitations. AI disruption across financial sectors and hands-on GenAI application. |
| 3 | 3 hours | Company Valuation - DCF and Relative Valuation DCF approach: free cash flow projections, WACC, terminal value, sensitivity analysis. Relative valuation: P/E, EV/EBITDA, P/B multiples and comparable company selection. Reconciling DCF and multiples approaches. Hands-on valuation exercise and GenAI application for scenario generation. |
| 4 | 3 hours | Corporate Finance Decisions - Capital Budgeting and Capital Structure Capital budgeting: NPV, IRR, payback period, handling uncertainty. Capital structure: debt vs. equity trade-offs, financial leverage, optimal capital structure. Dividend policy considerations. Case studies on capital project evaluation and capital structure financing decisions. |
| 5 | 3 hours | Final Presentation Day Student group presentations. Course wrap-up and key takeaways. |
Financial Statement Analysis and Business Quality Assessment
Business models: competitive advantages, revenue drivers, cost structures. Three financial statements and quality of earnings assessment. Key financial ratios: profitability, leverage, liquidity, efficiency. Using GenAI for data extraction, ratio comparisons, peer identification.
AI in Finance - Fundamentals and Applications
AI/ML fundamentals: supervised learning, unsupervised learning, deep learning (conceptual, non-technical). Current AI applications: private equity and venture capital deal sourcing, credit scoring, fraud detection, robo-advisors. Generative AI in finance: effective use cases vs. limitations. AI disruption across financial sectors and hands-on GenAI application.
Company Valuation - DCF and Relative Valuation
DCF approach: free cash flow projections, WACC, terminal value, sensitivity analysis. Relative valuation: P/E, EV/EBITDA, P/B multiples and comparable company selection. Reconciling DCF and multiples approaches. Hands-on valuation exercise and GenAI application for scenario generation.
Corporate Finance Decisions - Capital Budgeting and Capital Structure
Capital budgeting: NPV, IRR, payback period, handling uncertainty. Capital structure: debt vs. equity trade-offs, financial leverage, optimal capital structure. Dividend policy considerations. Case studies on capital project evaluation and capital structure financing decisions.
Final Presentation Day
Student group presentations. Course wrap-up and key takeaways.
* Session sequence and contents subject to changes. Programme curriculum may be adjusted based on cohort composition and learning needs.
Learning Intervention
Interactive Lectures
Core concepts in applied finance and valuation
Guided Exercises
Hands-on financial analysis practice
Case Studies
Real-world corporate finance scenarios
GenAI Applications
AI tools for data extraction and analysis
Team Presentation
Final group investment recommendation
Assessment Criteria
Programme Completion Documents
Certificate of Participation
from Singapore Management University
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Frequently Asked Questions
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