With the rise of Monte Carlo analysis as the most commonly used method of conducting retirement projections for clients, ‘probability of success’ has become the focal point for communicating retirement preparedness to clients. While a number of issues with framing results around probability of success have been noted – from not accounting for the magnitude of failure, to not acknowledging that small ‘adjustments’ can often save a ‘failing’ plan, and even some biases related to how we think about ‘wrong’ probabilistic forecasts – there is an additional issue with the current usage of Monte Carlo analyses that has gone largely unnoticed: If you are doing ongoing planning for a client who is willing to adjust their spending, then the norms that have emerged – particularly strong negative perceptions of planning results below 70% probability of success – may not be as problematic as most advisors (and clients!) think. In fact, a 50% probability of success (or lower!) may be reasonable for retirees who are willing to make spending adjustments.
One concern when reporting Monte Carlo results to a client framed around ‘probability of success’ is that anything less than 100% can sound scary. Consider a 50% probability of success: ‘Failing’ one-out-of-two times when failure implies running out of money in retirement simply does not sound acceptable. Such a result can make clients feel that they are unprepared for retirement and that they must save even more or retire even later so that they can achieve a higher probability of success. It is important, however, to think carefully about what a 50% result actually implies. First, this metric alone actually tells us nothing about how severe ‘failure’ is. If 90% of a client’s desired income comes from guaranteed income sources, then ‘failure’ is capped at a relatively modest 10% cut in a client’s income, which is not ideal but far from devastating. Moreover, adjustments can often save a ‘failing’ plan, so simply shifting a 50% probability of success framing to a 50% probability of adjustment can take a lot of sting out of that result.
Additionally, the difference between setting spending based on a one-time projection versus ongoing projections should be acknowledged, as these two approaches are fundamentally very different. If you only had one opportunity to select a spending level and you were forced to stick with that no matter what happened in the future, then selecting a spending level with a 95% (or higher) probability of success may make a lot of sense. But the reality is that planners generally provide ongoing projections for clients, and even those who provide one-time plans will recommend periodic updates. And if a retiree is going to keep their plan up to date (which allows for opportunities to identify when a plan is veering off course and adjust as needed), then planning to a 50% probability of success (i.e., a plan that needs to be adjusted one-out-of-two times) is not nearly as scary. Furthermore, it should be noted that a 50% probability of success means adjustment at any point in time in the future, and not necessarily even an adjustment in the near future.
To examine what planning using lower probability of success levels actually looks like, we compare planning outcomes using spending levels continually adjusted to maintain a constant 95%, 70%, 50%, and 20% probability of success throughout retirement using actual historical outcomes going back to 1871. What may be surprising is that we find that median, minimum, and maximum spending levels throughout 30-year retirement periods are actually quite consistent regardless of the probability of success used! In other words, if you are going to adjust spending on an ongoing basis, then returns experienced end out being the largest factor in determining how much can be spent, with income shaded either slightly higher (lower probability of success) or lower (higher probability of success) based on the success level targeted. Where we do see larger differences (although still smaller than many might anticipate) is with respect to terminal wealth levels, which suggests that when using Monte Carlo analyses for ongoing clients, the probability of success level targeted is actually more about a trade-off between income and legacy than any genuine difference in the risk that a portfolio will be depleted.
Since our intuitions generally tell us that a 50% probability of success is insufficient, advisors may wish to further consider how Monte Carlo results are framed to clients. Presenting clients with a range of potential strategy considerations may be beneficial in helping explore what best fits a client’s preferences. Furthermore, advisors should give thought specifically to what probability of success level best balances the trade-off between income and legacy for a client. Unfortunately, current planning tools do not make illustrating these types of dynamic strategies easy, but ultimately, the key point is that choosing a probability of success level to use is not as simple as being able to apply a one-size-fits-all rule or a natural tilt toward being ‘conservative’ for the sake of not running out of money. For those retirees who are willing and able to make needed adjustments along the way, a 50% (or lower!) probability of success may provide a better result than most advisors (and clients) realize!