Whole of fund modelling
A whole of fund modelling exercise involves the projection of fund data over time, allowing for key drivers of fund growth and demographics, such as:
At each projected year we are able to output a number of statistics based on the distribution of the projected fund, such as:
Each of the above results from the model can then be further analysed and separated by a number of different cohorts, such as:
The results and demographic splits can form an invaluable tool in a number of areas of fund governance. For example, the results of the modelling could be used to:
- Review and set executive/management KPIs based on likely range of projected funds under management, membership levels, etc.
- Liquidity stress testing regarding exposure to illiquid investments and likely range of cashflow requirements
- Assessment of likely “servicing requirements” for various member facing teams within the fund
- For example, call centre capacity, administration team, financial advice team, investment management, etc.
- Fee sustainability analysis across administration, investments, financial advice
- Marketing and member education demand can assessed to provide greater focus on the target demographics that are more likely to drive the growth of the fund.
Why Towers Watson?
Towers Watson is uniquely positioned to conduct such whole of fund modelling as we have the necessary expertise and experience on both the liabilities and assets “sides of the equation”. On the liabilities side, having been the actuarial consultants to the industry for decades, we are experts in the field of cash flow management, fund valuations and complex projections.
On the assets side, through the global investment model continuously maintained by Towers Watson’s international investment practice, we have access to up to date modelling of future investment risk and return expectations covering the shorter, medium and longer terms.
This means that we have all the tools and expertise necessary to correctly model the complex interaction within a fund’s investments and membership demographics over time.
Towers Watson have also been at the forefront of developing online calculators and projection tools for the Australian superannuation market. These tools and calculation engines can also be leveraged in such modelling exercises to enable trustees to drill deeper and drive greater efficiencies in the way they communicate with their members. Calculations can be prepared across the entire membership base to identify key membership demographics as targets for outbound communication, education, and advice services. These results can also feed into product design and overall fund strategy planning.
Case study: Whole of fund modelling exercise for large industry fund
For its strategic planning session, an industry fund needed to understand how its potential membership and assets may grow over the next five to ten years. It also wished to test a number of “what if” scenarios concerning factors that will influence how the fund grows. Key were the rates at which new members may join the fund, the rates at which members may leave the fund, the rates at which retiring members may remain in the fund and setup an account based pension, etc.
We constructed a whole of fund model to project how the membership and assets of the fund are likely grow into the future. We derived key demographic assumptions for the model from an analysis of the fund’s experience over the last three years. We used the past demographic experience to set assumptions about future member behaviour for a central estimate, and varied these assumptions to test the “what if” effect of these assumptions varying from past experience.
Further, given the significant impact that investment return volatility can have on future fund growth, we took a stochastic approach to modelling the effect of future investment returns. The stochastic modelling involved running the model under 5,000 investment scenarios, which permitted depicting not only what the expected outcome might be, but also provided an illustration to the potential range, and likelihood, of potential outcomes.
The results were segmented in many ways, including by age, gender and account balance. For the report, results were broken down by different age cohorts and member section (pre-retirement and post-retirement) cohorts. Cash flows were also examined on a cohort basis.
Results provided a clear picture for the trustees on how the fund may grow in future, both in terms of membership and funds under management, under a range of scenarios.
Seeing the results under the central case position, with the range of potential outcomes under the stochastic modelling of investment returns and the range of “what if” scenarios, provided a much richer picture of how the fund could look in the future. It also enabled a deeper understanding of the key factors effecting the growth of the fund.
The trustees also identified potential future applications of the model which would be beneficial for strategic planning. Possible further applications identified included:
- Analysing the split between active and inactive members of the fund.
- Identifying any trends about such factors as the age of active members, time spent inactive, ages of which inactive members become active again, etc.
- Examining sustainability of the administration fee structures with changing demographics, e.g. the split between fixed fees and variable fees, and the sustainability of caps on variable fees.
- Assessing the implications for liquidity of increasing proportions of assets in alternatives.
- Estimating what the growth in various member segments might means for servicing requirements.
Case study: Retirement adequacy study for a large corporate super fund
For a strategic planning session, the trustee of a large corporate superannuation fund needed to understand how its members were tracking towards an “adequate” retirement income. The trustee wanted to identify particular demographic sections of the fund that were not on track to reach an adequate retirement income and use this analysis to drive the direction of communication and education programs offered to members.
We worked with the trustee to design a target retirement income that was deemed to meet the needs of their fund’s membership. The target retirement income was a hybrid of measures seen in market today, being a mix of ASFA retirement standard measures and replacement rates of after-tax pre-retirement income.
The fund then provided data across their membership including balances, salaries/contributions, etc which we then fed through the Towers Watson retirement planner engine to compute adequacy measures for each member. The adequacy measure used was the ratio of retirement income the member was projected to be able to maintain from a retirement age of 65 to a life expectancy of 90 to the member’s individual target retirement income.
The computed retirement adequacy measures were then segmented in a number of different ways, including age, salary, plan membership, gender, etc to identify key demographics that were materially different to the broader membership base.
The results identified a particular age and service demographic of the membership that were very likely to have balances in other funds. This sparked a focus of communications regarding rollovers and account consolidation.
The trustee also identified that a regular revision of the exercise would allow the trustee to measure changes over time and could provide critical input to the KPI setting process.