David Bell (left) and Geoff Warren

Retirement plans provided by financial advisers should be superior to those provided at scale by super funds. The comprehensiveness of the advice service provided by planners means they can account for the personal circumstances and needs of their clients and provide a more holistic solution. It is important that adviser-provided retirement plans are superior, and viewed as superior, given the far greater cost of advice provided by financial planners.

However, one threat to this competitive advantage could be a failure by financial planners to incorporate stochastic frameworks, which establish the range (and likelihood) of possible financial outcomes, into their advice processes. Super funds will likely use such tools as the engine driving their more limited advice.

The risk to the financial planning industry is that retirement strategies delivered by financial advisers are somehow viewed as inferior to the retirement solutions provided by super funds, which will be more limited in scope but packaged up in a more sophisticated framework. That would be a topsy turvy outcome.

The ‘quant’ of assessing retirement income strategies

We recently completed a research piece titled ‘How to approach quantitative assessment of retirement income strategies‘, written with the assistance of modelling expert Gaurav Khemka from the ANU. It sets out a framework for how quant modelling could be used to assess the retirement income solutions provided by super funds.

The paper sets out a framework for assessing retirement income strategies, which we illustrate with examples. We do not prescribe a single overarching framework because super funds, just like planners, will have different views around what they are trying to achieve for their members and how success should be assessed.

Core to the framework is stochastically modelling retirement outcomes. Projecting the range of outcomes entails accounting for sources of uncertainty such as investment returns and mortality. The alternative is known as deterministic analysis, which simply focuses on the expected outcome.

Most financial advisers don’t use stochastic modelling

The assessment and modelling frameworks used by financial advisers would generally fall short of the standards set out in our paper. Our observation is that stochastic modelling is not in wide use within the financial planning industry. Whenever we make this claim a few individuals write in sharing their developments. We would be happy to be proven wrong by the broader advice community.

In the absence of a stochastic framework, advisers can’t readily answer questions like: “what is the likelihood of not getting a minimum income”, “how low can my income go if things don’t work out”, “what happens if markets perform poorly”, and “what if I live longer than expected”?

The modelling challenge for advisers is far more complex than for super funds. Advisers consider all assets and develop a household plan, beyond the scope of what super funds will likely provide. Every additional consideration adds to modelling complexity. Nevertheless, tools that improve the understanding of risk are better than nothing.

How consumers might view the solutions provided by advisers and super funds

The risk is that the advice provided by financial planners will not be viewed as superior to the retirement solutions being offered by super funds which may showcase their use of stochastic tools.

Leading super funds are on the pathway to utilising stochastic frameworks to design retirement solutions for members. These modelling engines can be re-purposed to produce clever and engaging member guidance designed to give members confidence that the retirement solution is robust to a range of scenarios. Development of their products and services is supported by scale. Large super funds in particular have the financial resources and can spread development costs across a large member base.

This doesn’t mean that super fund retirement solutions will deliver better outcomes compared to the strategies that advisers develop for their clients. There are various considerations:

  1. Advisers have closer, more personal relationships with their clients that enable them to collect all necessary information about the household and assess client preferences. Super funds are more distant from their members and much more limited in the information that they can capture and use.
  2. While advisers will have access to a broad (and expanding) universe of retirement products, they may struggle to make full use of this product range due to limits on understanding many complex offerings and the lack of stochastic models to assess their outcomes. Meanwhile, super funds are playing a simplified game. They will likely use a narrower range of products – including basic asset pools and a longevity product – and can use stochastic models to inform solution design and support member communications.
  3. Advisers can develop far more comprehensive retirement plans that can be directed at all members of the household, go beyond the superannuation balance to consider all financial assets, account for home equity release, and more. The plan can be readily tailored for areas like reversionary and aged care considerations. Super funds will find it hard to deliver this sort of advice at scale.
  4. Finally, advisers will likely have a large engagement advantage with their clients through direct conversation. Meanwhile, super funds will be reliant on scalable communications such as digital tools, mail-outs and more general and limited advice.

Our lingering concern is whether or not planner-provided financial advice will look like a premium service when compared against the retirement solutions provided by super funds. The advice sector could ensure the premium nature of their service by upgrading to a stochastic framework.

One comment on “The topsy turvy world of retirement advice and guidance”

    This is a good call to arms for the financial planning industry and supports what I, and my colleagues, have been pushing for many years – stochastic modelling is necessary for good advice. And not only us, for example the Actuaries Institute thinks that the basis for advice needs a technical paper, and stochastic modelling is good practice; it’s in the title of their paper “Good Practice Principles for Retirement Modelling” .

    It’s not as if such software is not available. For example, stochastic modelling software for financial planners is available that covers the points you mention above, and more – reverse mortgages, non-super assets, part-time work in retirement, gaps in working during the accumulation phase, etc.

    And the danger to financial planners is not only from the large super funds, there’s plenty of evidence that many SMSF members don’t use financial planners because of the perceived high cost. These investors are very capable of understanding the value of stochastic modelling when it’s presented properly. Software is available to retail investors as well.

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