More than ever, clients are concerned about their retirement timelines
by Matt Rogers
Mr. Rogers is the Director of Financial Planning at eMoney Advisor.Over the last 20 years, Monte Carlo analysis has become a go-to financial planning tool for many advisors. It’s a proven, reliable way to determine whether or not a client’s plan is on track.
Over time, though, some challenges have emerged in explaining the complexities of Monte Carlo analyses, including disagreement on what constitutes a good score, and how to best convey results in a digestible way for clients.
Recent innovations in Monte Carlo simulations are starting to overcome these challenges, especially in the way results are conveyed to clients.
Managing Longevity Risk Like Never Before
Advisors have always had the difficult task of making sure financial plans are resilient enough to handle ever-increasing longevity expectations. Traditionally, this has been challenging with Monte Carlo simulations for retirement.
The traditional Monte Carlo result is based on a singular life expectancy, such as age 90 or 95. Advisors must run multiple different Monte Carlo analyses and reports if they want to see what would happen if the client lived 5 more year or 5 less years, still only giving a few snapshots in time.
A newer and better way to address longevity is to have a Monte Carlo score automatically run for each year, allowing both advisor and client to clearly see their sensitivity to longevity risk. Getting insight into Monte Carlo scores over time paints a much more holistic picture, showing the approximate age at which a client’s financial situation could start to weaken and, importantly, how quickly it could weaken. This gives the client a true feel for their longevity risk.
Assessing Predicted Returns to Account for Inflation
Added to the challenge of longevity risk is the newer risk of inflation. When you think about how inflation can reduce Monte Carlo scores, increased lifetime expenses may be the first thing that comes to mind. But oftentimes an overlooked, and potentially more harmful, effect of inflation is stock market gloom and lower predicted returns. The negative effect on assumed returns will likely be more damaging to a client’s Monte Carlo score than higher lifetime expenses.
Advisors who are using Monte Carlo today to talk to clients may want to assess their expected returns for each asset class. Does today’s inflation mean a permanent paradigm shift in expected returns for your clients? Or is this a temporary shift that will only be a blip on the radar of financial plans that are projecting out 30-40 years?
To take a conservative approach, advisors may want to adjust their planning software’s market assumptions, run new Monte Carlo analyses, and prepare to talk to clients about a potentially lower score. This can be a powerful way to start the conversation about inflation.
Monte Carlo Features to Make Inflation Conversations Easier
Clients will naturally be concerned about the impact of inflation on their plan, and fortunately, Monte Carlo analyses are an excellent way to demonstrate the impact of down markets to clients.
Even in an environment where inflation may lead to lower Monte Carlo scores, you can still use Monte Carlo to frame the entire conversation around either one of two statements: “I’m confident you’re still on track to reach your goals,” or “We may need to make adjustments for you to reach your goals.”
Monte Carlo inherently accounts for poor market conditions, and with newer solver features in planning software, advisors can quickly facilitate conversations around raising Monte Carlo scores to give clients peace of mind in uncertain times.
It’s possible that the current inflation environment could drive further evolution in Monte Carlo capabilities as well. For example, Monte Carlo results could be based on a tiered set of capital market assumptions with less optimistic returns for a period of years, followed by assumed returns closer to historical averages after that period. This would create a more flexible set of return assumptions that more accurately reflect market behavior.
Further, Monte Carlo features could one day allow advisors to segment trials based on key attributes, such as the sequence of returns. This would allow, for example, advisors to drill into trials that had low returns in the short-term and higher returns later in life, once again potentially modeling a scenario that more closely resembles the market today. This would lead to more detailed insight into how the current market could affect your client’s financial goals.
Upending the Traditional Monte Carlo Score for Better Client Communication
Clients will likely be most interested in their Monte Carlo score when external events create anxiety or uncertainty. Today’s inflationary environment is exactly that kind of external event.
When clients are interested in their score, advisors may find themselves trying to explain how a Monte Carlo analysis runs 1,000 different trials and how this is supposed to account for bad markets, and even more, why a score in the 80s could be perfectly acceptable for a financial plan.
One important evolution in Monte Carlo is eschewing the traditional percentage score altogether. Monte Carlo scores, because of the advancements in longevity analysis, allow scores to be presented as an age instead of a probability of success. This is a far more intuitive way for clients to understand the resiliency of their plan.
Saying “I’m confident in your plan until age 95,” is very different from saying “Your plan has an 85 percent probability of success,” especially when clients are seeking more confidence in the state of their financial circumstances.
When advisors can adjust Monte Carlo assumptions to account for current market conditions, leverage the latest longevity risk features, and present scores in a seamless, intuitive fashion, they will be able to better communicate complex topics with clients.
This is true for inflation, increased longevity expectations, or any other circumstance that creates doubt in a client’s mind.
