Course Code: FIN205

Synopsis

A business graduate needs to be conversant with data and spreadsheet technologies so that he/she will be able to implement financial models effectively for analysis, budgeting, forecasting, planning and simulations matter in organisations pertaining to financial matters. FIN205 Data Technologies for Financial Modelling aims to equip business graduates with the requisite knowledge and skills relating to the kinds of technologies that are available and how to use the most popularly important ones (e.g. Excel) in calculations and the modelling of financial situations. A broad range of topics, including financial modelling methods, financial valuation, pricing and risks, strategies for decision making, FinTech applications and financial data tools and technologies is covered. Such knowledge and skills would be highly useful for those considering to work in the financial industries as well as the finance or analytics department of a company, those aspiring to start their own business or those who work in smaller firms that do not employ finance specialists.
Level: 2
Credit Units: 5
Presentation Pattern: EVERY REGULAR SEMESTER

Topics

  • Financial statements modelling
  • Pro forma financial statements
  • Using data and data sources
  • Discounting and compounding cash flows
  • Valuation in major asset classes
  • Options basics
  • Using Excel tools to power up modelling
  • Using Python to power up modelling
  • Modelling and managing risk with data technologies
  • FinTech valuation
  • FinTech applications
  • Distributed ledger technology

Learning Outcome

  • Demonstrate understanding of the basics of financial modelling
  • Illustrate considerations in financial statements with modelling
  • Analyse different financial pricing/valuation models
  • Appraise the notion of risk and measurements through modelling methods
  • Develop strategies in finance and FinTech for decision making
  • Contrast the limitations and advantages of different data analytics tools
  • Use data technologies such as Excel and Python to model and understand financial problems effectively


Who Should Attend

A business graduate needs to be conversant with data and spreadsheet technologies so that he/she will be able to implement financial models efficiently for analysis, budgeting, forecasting, planning and simulations in their work in organisations pertaining to financial matters.

 

Relevance of Course to employment/upskilling/reskilling

This course equips learners with practical financial modelling, valuation, and data-driven decision-making skills highly sought after in finance, analytics, and business roles. By strengthening Excel, data technologies, and FinTech literacy, participants enhance employability, support career transitions, and stay competitive in organisations increasingly reliant on digital financial tools and evidence-based analysis.

 

Schedule

S/NTimeAgenda
 1
Lecture 1
19:00 – 19:15
19:15 – 20:30
20:30 - 20:40
20:40 – 21:45
21:45 - 22:00
Lecture Contents
Introduction and course expectations
Financial Statements and Analysis – Part 1
Break
Financial Statements and Analysis – Part 2
Summary of Lecture 1
2
Lecture 2
19:00 – 19:15
19:15 – 20:30
20.30 – 20.40
20:40 – 21:45
21:45 – 22:00
Lecture Contents
Recap of last lecture and relevance to new lecture contents
Financial Statements and Analysis – Part 3
Break
Financial Statements and Analysis – Part 4
Summary of Lecture 2
3
Lecture 3
19:00 – 19:15
19:15 – 20:30
20:30 – 20:40
20:40 – 21:45
21:45 – 22:00
Lecture Contents
Recap of last lecture and relevance to new lecture contents 
Time Value of Money – Part 1
Break
Time Value of Money – Part 2
Summary of Lecture 3
4Class Test
To be confirmed
To be scheduled between Lecture 3 and 4
In-person at SUSS premises
Attendance sign-in & administrative briefing
Class Test (Content from Lecture 1-3)
Attendance sign-out
5
Lecture 4
19:00 – 19:15
19:15 – 20:30
20:30 – 20:40
20:40 – 21:45
21:45 – 22:00
Lecture Contents
Recap of last lecture and relevance to new lecture contents
Time Value of Money – Part 3
Break
Time Value of Money – Part 4
Summary of Lecture 4
6
Lecture 5
19:00 – 19:15
19:15 – 20:30
20:30 – 20:40
20:40 – 21:45
21:45 – 22:00
Lecture Contents
Recap of last lecture and relevance to new lecture contents
Financial Modelling Preparatory - Part 1
Break
Financial Modelling Preparatory - Part 2
Summary of Lecture 5
7
Submission of Group-based Assignment (GBA)
Before 23:55 of submission date
To be scheduled between Lecture 5 and 6
To be submitted online.
8
Lecture 6
19:00 – 19:15
19:15 – 20:30
20:30 – 20:40
20:40 – 21:45
21:45 – 22:00
Lecture Contents
Recap of last lecture and relevance to new lecture contents
Financial Modelling - Part 1
Break
Financial Modelling - Part 2
Summary of Lecture 6
9
Final Assessment
To be confirmed
To be scheduled in April (November) in January (July) semester In-person at SUSS premises
Final Assessment

 

Assessments

The overall course grade is determined by

  • Tutor-marked assignment (TMA) in the form of a class test – 10%
  • Group based assignment (GBA) – 20%
  • Participation – 10%
  • Written Exam – 60%

 

Requirements

  • Need to have basic knowledge of maths and statistics.
  • A laptop, with an installation of Microsoft Office, is required for the coursework.
  • Basic Excel usage is advantageous but not required.

 

About the Trainers

A/P Tan Chong Hui is with the School of Business at SUSS, where he has been a faculty member since 2013. He graduated from UCLA with a PhD in mathematics. He has rich experience in teaching computational and quantitative finance as well as applied computing technology to undergraduate and post-graduate students. He has also conducted executive training programmes in the finance industry, and his research interest lies in the areas of FinTech, human sociality and semantics modelling.

Mr. Ke Yan is the founder and CEO of DZT Research. He has more than 10 years of experience covering Asia equities. He has been a sector analyst covering offshore & marine service, consumer, metal & mining, and healthcare, as well as strategist for holding company discount arbitrage, and equity capital market. His working experience includes Singapore Exchange, Religare Capital Markets, Smartkarma, and Aequitas Research. His research work is frequently quoted by international media including Bloomberg, Reuters and Forbes.

 

Course Fees, payment and refund policy

 International ParticipantsSingapore Citizen Below 40 years old/ Permanent ResidentSkillsFuture Mid-Career Enhanced Subsidy1 (Singaporeans aged 40 and aboveEnhanced Training Support for SMEs2 (Singaporeans and PRs)
Full Course Fee (A)$ 1,753 $ 1,461 $ 1,461 $ 1,461
SSG Grant Rate (B)0%70%70%70%
SSG grant (C)-$ 1,022.70 $ 1,022.70 $ 1,022.70
Nett course fee (A)-(C) = (D)$ 1,753.00 $ 438.30 $ 438.30 $ 438.30
9% GST on net course fee (E)$ 157.77 $ 39.45 $ 39.45 $ 39.45
SSG Enhanced Funding Rate (F)0%0%20%20%
SSG Enhanced Grant (G)- -$ 292.20 $ 292.20
Total nett course fee payable, including GST (D) + (E) - (G) = (H)$ 1,910.77 $ 477.75 $ 185.55 $ 185.55

1 Mid-Career Enhanced Subsidy: Singaporeans aged 40 and above may enjoy subsidies up to 90% of the course fees.
2 Enhanced Training Support for SMEs: SME-sponsored employees (Singapore citizens and PRs) aged 21 and above may enjoy subsidies up to 90% of the course fees.

For the various payment mode, please refer here.
For the refund policy, please refer here

A written request for a refund must be submitted and is subject to approval. If written notice of withdrawal is given within the cooling off period1 and before the course start date, a full refund of the fees paid less an administrative charge of $110.00 (exclusive of GST) will be given. No refund will be given for withdrawal thereafter.

1The cooling off period is defined as 7 working days after payment of course fee.

 

Completion Requirement

  • Attendance: Participants must achieve at least 75% attendance.
  • Assessment: Participants must sit and pass all prescribed assessments and submit all course work stipulated in the section Assessments.
  • Evaluation: Participants are required to complete course evaluations conducted by SUSS and SSG at the end of the training.
Students who achieve at least 75% attendance and meet the course completion requirements will be awarded a Certificate of Completion. For those who do not meet the course requirements, a Certificate of Participation will be issued instead.

 

For clarification, please contact the SUSS Academy via the following:
Telephone: +65 6248 0263
Email: [email protected]