Retirement income planning is often one of the primary reasons prospective clients approach a financial advisor. In a world of increasing longevity and declining reliance on defined benefit retirement plans, being able to give clients an estimate of how much they can ‘safely’ spend each year, given their available assets, is a major part of an advisor’s value proposition. To do so, advisors often rely on Monte Carlo analyses, which provide the probability of a particular course of action being ‘successful’ (and, therefore, implying the corresponding probability of ‘failure’). However, these results can be confusing for clients, as they overemphasize the probability of success/failure while not accounting for the magnitude of such outcomes (i.e., in ‘failure’ scenarios, this analysis does not show how much the client would need to adjust spending before their portfolio is emptied in order to turn the plan back into a ‘success’).
To make up for this shortfall, other strategies, such as risk-based retirement-income guardrails (which prescribes adjustments to client spending when the probability of success hits certain upper or lower thresholds) have been developed not only to better capture the nuances of a client’s unique situation, but also to serve as a better way of communicating Monte Carlo results to clients. Yet, one of the real challenges with these conventional methods for displaying simulations is that results are often conveyed in a manner that doesn’t allow for easy comparison across various spending or risk levels.
An alternative method to ameliorate this problem is to leverage technology to graphically display curves that relate a client’s spending levels with corresponding risk outcomes. These “Spending Risk Curves” can be far more insightful than a single probability-of-success result, and very useful for an advisor to gain a higher-level understanding of a client’s financial options by visually illustrating the trade-offs between a client’s spending choices and risk in retirement.
At their core, Spending Risk Curves show the trade-off between risk (framed in terms of probability of success or otherwise) and spending in retirement planning (i.e., as annual portfolio withdrawals increase, so does the spending risk level) based on a client’s particular circumstances (e.g., mixes of ages, longevity expectations, or Social Security benefits). In this way, Spending Risk Curves give advisors an idea not only of the full range of options for the initial risk/income levels, but also of the future adjustments to spending that might be needed (these could be to the upside or the downside, depending on portfolio performance) to keep the client at the desired risk level.
Ultimately, the key point is that Spending Risk Curves are highly versatile tools that can help advisors better conceptualize a vast range of variables relevant to their clients so that they can more easily design relevant and suitable financial plans. By understanding the full range of spending options at all levels of risk for a given client’s situation and being able to estimate future spending adjustments that might be needed to maintain a desired level of risk, advisors can not only give clients a more accurate view of their choices but also communicate what changes to spending might be needed down the line to keep their plan on track. In the end, this can lead clients not only to make better-informed decisions but also to have more confidence in their financial plan!