Crediting Rate Scenario Modelling and Impact Analysis

Location: Melbourne, VIC

Duration: 5 months

Proposed start date: ASAP

Please note: Due to existing requirements, students must have Australian or New Zealand Citizenship or Permanent Residency to apply. Any applicants not meeting this requirement will automatically be deemed ineligible for this project.

Project Background

AustralianSuper is for all Australians and businesses putting members first in everything they do with the goal of helping to create the best possible retirement outcome. More than 2.2 million members trust AustralianSuper to invest more than $155 billion on their behalf.

The Corporate Services, Finance Team provide strategic advice, financial management, investment accounting, group tax, procurement and facilities management services to the Fund.

The Corporate Services, Finance Team is seeking a PhD intern to conduct analysis and deep dive into the existing crediting rate (unit pricing) analysis and modelling.

This includes:

  • Critically analysing the inputs and assumptions within the models.
  • Conducting a reconciliation and validation process to understand and solve for variances.
  • Understanding the drivers and sensitivity of drivers through build out of scenario modelling, including the impact on the outputs, and how those sensitivities could change as the Fund increases in size and members continue to become more active.
  • Researching industry treatment and best practice around application of crediting rates and deriving key learnings to aid recommendations.
  • Drawing data led insights from outputs and evaluating the global tax impacts for the tax component of the crediting rate.
  • Provide a series of recommendations and present findings including a view on current state versus a target state (internal best practice) and summarise key findings/analysis from various scenarios modelled.

Research to be Conducted

  • Conduct a deep dive into the existing crediting rate process and various components of the crediting rates. Understand how the modelling works, including impacts (monthly movements) and identify potential opportunities for improvement. The modelling completed should include assessing the potential impacts which could occur as the Fund size increases as well as the member behaviours and market conditions change.
  • Research, collate and draw insights from key external learnings around crediting rate process (global best practice). Assess the impact of applying key changes, including forming a view on a potential future target state.
  • Review the current crediting rate analysis and modelling process, including understanding key inputs, assumptions and drivers (internal and external).
  • Conduct analysis on the outputs, including building out scenario modelling and evaluating outcomes. Explore the impact of changes in economic factors (internal and external) including the tax component of crediting rates on the crediting rate system.

Skills Required

We are looking for a PhD student with the following:


  • Experience in advanced analytical modelling and scenario modelling analysis
  • Excellent research skills together with the ability to apply the research
  • Strong communication and presentation skills to translate analysis into insights and present findings
  • Ability to simplify large amounts of data and complex information into a simple format
  • Positive Attitude
  • Commercial awareness and knowledge of financial markets
  • Advanced Excel skills
  • Strong analytical and problem solving skills
  • Attention to detail


  • Knowledge of Superannuation and Financial Services industry
  • Financial/Economics/Accounting Experience

Expected Outcomes

The expected outcomes include:

  • Develop a current state view of the crediting rate system and identify process improvement opportunities, especially around analysis and models completed as part of the central control processes.
  • Build out scenario modelling capability.
  • Report on drivers of current monthly variances and potential impacts of scenarios given increase Fund size, member behaviour and system limitations.
  • Report on key learnings from research (benchmarks and best practice) and recommendations.
  • Develop robust insights into:
    • The components of the crediting rate components (e.g. Tax)
    • Drivers impacting the crediting rate (internal and external factors)
    • The associated flow on effects of specific scenarios and sensitivity of changes to assumptions.

Additional Details

The intern will receive $3,000 per month of the internship, usually in the form of stipend payments.

It is expected that the intern will primarily undertake this research project during regular business hours, spending at least 80% of their time on-site with the industry partner.  The intern will be expected to maintain contact with their academic mentor throughout the internship either through face-to-face or phone meetings as appropriate.

The intern and their academic mentor will have the opportunity to negotiate the project’s scope, milestones and timeline during the project planning stage.

Applications Close

28 August 2019


APR – 0836