Updated on: July 29, 2021

Client longevity is often a top concern for financial professionals in retirement planning. How long a client lives impacts the number of years in retirement that need to be funded, the number of market cycles they live through, and the lifestyle that client can maintain while retired.

Financial professionals take different tactics to manage the risk associated with longevity financial planning. Some may try to estimate a client’s longevity based on family and medical history. Others will take a universally conservative approach to ensure clients don’t outlive their assets. Regardless of the tactic your firm takes today, there are demographic changes taking place that may alter your outlook on longevity.

Increasing Client Longevity in Financial Planning Complicates Risk Management

It’s impossible to predict exactly how long someone will live, which is exactly why financial professionals use broad assumptions. This matter is complicated by the fact that lifespans continue to increase.

Since the mid-19th century, the lifespan of the average citizen of a wealthy country has increased steadily, with that trend now accelerating. According to research from the MIT AgeLab, average life expectancy could extend well past the age of 100.¹

This same research also found that because a 60-year-old today has at least 20 more years of healthy living, the fastest growing population segment is over 85. If current trends hold, half of babies born in wealthy countries today will reach 100.¹

We tend to think linearly, and in that way, many of us tend to underestimate how long we’ll live, but medical science, technology, and our understanding of what constitutes a healthy lifestyle are constantly evolving.

Greater longevity, coupled with a tendency to underestimate that longevity, introduces greater risk into financial plans. So how do you compensate for this risk? Do you make plans even more conservative? To answer these questions, it helps to first take a look at Monte Carlo simulations.

What Monte Carlo Simulation in Financial Planning Doesn’t Tell You

Monte Carlo simulations are a great tool for showing a plan’s probability of success. It’s an effective way to secure a client’s confidence in their plan and the most common way today for advisors to demonstrate a plan’s ability to fund a client’s retirement. It does, however, have inherent limitations.

If a plan succeeds 85 percent of the time, that’s a great sign it’s resilient and will likely fund a client’s retirement, given the longevity assumptions are appropriate. But with a single Monte Carlo score, there’s no insight into how, why, or when the plan fails that other 15 percent of the time. There’s also no telling how resilient the plan is beyond the given longevity assumptions.

Many firms understand this and may run a few plans to generate multiple probabilities of success at different ages, but this requires additional time and effort yet still does not paint the full picture of a plan’s likelihood to succeed.

Using a Monte Carlo By Age (MCBA) method, alongside a Confidence Age score, is a new alternative that’s emerging.

Managing Longevity Risk in Retirement Planning with Monte Carlo By Age and Confidence Age

Monte Carlo By Age is a way of generating a probability of success at every age, as opposed to having a singular endpoint or a few potential endpoints. This fills in the gaps that a traditional Monte Carlo simulation would leave. Having a Monte Carlo score at every age gives planners a lot more insight into the nuances of a plan and important trends in the plan’s probabilities of success.

MCBA also allows you to leverage Confidence Age metrics—displaying a plan’s resilience with an age number instead of a percentage. From the client’s perspective, hearing that a plan will last until age 104 is a lot more intuitive than hearing their plan has a 75 percent chance of succeeding. Confidence age metrics make the conversation easier and keep clients focused on what they have to do to keep their plan on track instead of wondering how their plan was calculated.

MCBA can also be combined with available actuarial data to create powerful narratives around a client’s likely-longer-than-expected lifespan and what it will take to fully fund their retirement.

If you want to take a deeper dive into longevity financial planning, I recently hosted a CE webinar on this topic with my colleague John Costello, Financial Planning Development Consultant at eMoney (on-demand version not eligible for CE credits). In the webinar, we explore the value of MCBA and field a ton of great questions from financial professionals on how it’s calculated, why it’s a more comprehensive metric than traditional Monte Carlo, and how the resulting Confidence Age metrics can make retirement conversations easier.

 

 

Sources:

1. “Longevity Planning: Help Clients Envision New Retirement Realities.” Charles Schwab n.d. https://advisorservices.schwab.com/insights-hub/perspectives/longevity-planning-new-retirement-realities.

2. “U.S. High-Net-Worth and Ultra-High-Net-Worth Markets 2018: Shifting Demographics of Private Wealth.” Cerulli Associates, 2019. November 29. https://info.cerulli.com/HNW-Transfer-of-Wealth-Cerulli.html.

DISCLAIMER: The eMoney Advisor Blog is meant as an educational and informative resource for financial professionals and individuals alike. It is not meant to be, and should not be taken as financial, legal, tax or other professional advice. Those seeking professional advice may do so by consulting with a professional advisor. eMoney Advisor will not be liable for any actions you may take based on the content of this blog.

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