Financial Modelling - eLearning

This activity is presented by SumProduct.

It will enable you to build efficient and effective models for business decision making, focusing on the construction of the Income Statement, Balance Sheet and Cash Flow Statement.  The module comprises best practice guidelines as well as practical advice on common challenges involved in building financial models.

This interactive online module uses a combination of slides, videos, quizzes and hands-on case studies to develop a model from a blank Excel canvas, enabling you to build a full set of financial statements and apply it to your own model developments.

Learning Outcomes:
Upon satisfactory completion of this activity you will be able to:

  • Explain the concepts of an Income Statement, Balance Sheet and Cashflow Statement.
  • Construct a financial model to meet your organisation’s needs.
  • Use checks intelligently to eliminate spreadsheet error.
  • Build Balance Sheets that balance in seconds.
  • Determine the appropriate methodology and sequential process of building your own models.

This module ensures participants understand the fundamentals of financial models and are able to use a model building approach applicable for all of their financial modelling requirements.

The course has been developed by Liam Bastick and Tim Heng, who are both well respected financial modelling trainer in Australia and around the world and have been awarded the title of Most Valuable. Professional by Microsoft, specialising in Excel. Liam and Tim are also the author and editor respectively of the textbook “Introduction to Financial Modelling”.
*The course provider, SumProduct, will email you login details within 48 hours of receiving your registration. Please contact us if you have not received your login details after this time.
*Your login is valid for a 12 month period.


Topic: Financial Advisory and Superannuation

Sub-Topic: Financial Modelling

Format: eLearning

Proficiency Level: Foundation, Intermediate, Advanced

CPD: Upto 16 hours