Singapore University of Social Sciences

Data Technologies for Financial Modelling

Data Technologies for Financial Modelling (FIN205)

Applications Open: 01 October 2021

Applications Close: 30 November 2021

Next Available Intake: January 2022

Course Types: Modular Undergraduate Course, SkillsFuture Series

Language: English

Duration: 6 months

Fees: To be confirmed

Area of Interest: Finance

Schemes: Alumni Continuing Education + (ACE+), Lifelong Learning Credit (L2C)

Funding: SkillsFuture

School/Department: School of Business


A business graduate needs to be conversant with data and spreadsheet technologies so that he/shewill be able to implement financial models effectively for analysis, budgeting, forecasting, planningand simulations matter in organisations pertaining to financial matters.FIN205 Data Technologies for Financial Modelling aims to equip business graduates with therequisite knowledge and skills relating to the kinds of technologies that are available and how touse the most popularly important ones (e.g. Excel) in calculations and the modelling of financialsituations.A broad range of topics, including financial modelling methods, financial valuation, pricing andrisks, strategies for decision making, FinTech applications and financial data tools and technologiesis covered. Such knowledge and skills would be highly useful for those considering to work in thefinancial industries as well as the finance or analytics department of a company, those aspiring tostart their own business or those who work in smaller firms that do not employ finance specialists.

Level: 2
Credit Units: 5
Presentation Pattern: Every semester


  • 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
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