Singapore University of Social Sciences

Data Technologies for Financial Modelling

CET Course | SkillsFuture Claimable Course

Data Technologies for Financial Modelling (FIN205)


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


  • 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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