Episode summary
Calculating Personalized Client Lifespan Estimates, With Jeremy Ko
Financial Advisor Success (Kitces)
· · 30 min · Hosts: Michael Kitces, Adam Van Deusen · Guests: Jeremy Ko
Summary
The episode argues that retirement planning is often weakened by using generic life expectancy assumptions when a client’s actual longevity can differ materially based on a few observable factors. Jeremy Ko says the most useful predictors he found were self-rated health, smoking status, gender, and education, while race loses much of its explanatory power once those factors are controlled for. He also notes that a fair or poor self-rating can reduce expected lifespan by roughly 8 to 10 years, and current smoking by about 5 to 7 years.
Ko says advisers do not need an exhaustive medical intake to improve planning. Instead, they can use free tools such as the Society of Actuaries’ longevity illustrator, the University of Connecticut’s actuarial calculator, Northwestern Mutual’s longer survey, and ShoreUp Retirement Solutions’ own calculator. He emphasizes that these tools can estimate not just average lifespan, but higher percentiles as a way to build in conservatism without defaulting to the same cushion for every client.
The practical payoff shows up most clearly in Social Security and retirement income planning. Ko cites research suggesting personalized lifespan estimates can improve Social Security claiming outcomes by around $10,000 on average, and that the retirement assets needed to fund a comfortable retirement can vary by hundreds of thousands of dollars depending on longevity assumptions. His broader point is that advisers already personalize many inputs, so retirement length should be treated as a critical planning variable too.
Key takeaways
- Jeremy Ko says self-rated health and current smoking status are among the strongest practical predictors of lifespan, with fair or poor health cutting expected life by about 8 to 10 years.
- Ko says race adds little predictive value once health, smoking, gender, and education are included, so advisers should not rely on race as a primary longevity input.
- Ko says free calculators from the Society of Actuaries, University of Connecticut, Northwestern Mutual, and ShoreUp can help advisers estimate lifespan more precisely without building a model from scratch.
- Ko says personalized lifespan estimates can improve Social Security claiming decisions by about $10,000 on average.
- Ko argues that advisers should still add a cushion for longevity risk, but do it based on the client’s actual profile rather than a one-size-fits-all age assumption.
Notable quotes
“First and foremost, how people rate their own health from excellent to very good to average to fair to poor”
“And believe it or not, that's a really strong predictor of lifespan for a retiree”
“So, I think that there's three common practices that each present their own problems”
“And what we found is that these variables really didn't have statistically significant impact on projected lifespan when controlling for other variables”
“personalized lifespan estimation really does make a difference in the amount of around $10,000 on average across individuals”
How the episode opens
First and foremost, how people rate their own health from excellent to very good to average to fair to poor. And believe it or not, that's a really strong predictor of lifespan for a retiree. Hello and welcome back to the Financial Advisor Technician podcast.
I'm your host, Adam Vanusen. On today's episode, we're going to discuss one of the major challenges when it comes to retirement planning, which is that clients have unknown lifespans. Because if an adviser could know exactly when a client was going to pass away, they could fine-tune the financial plan to precisely meet the client's goals.
However, in the real world, where longevity is uncertain, it can make sense to take a conservative approach when it comes to estimating a particular client's lifespan. As clients and adviserss alike are likely to consider the consequences of underestimating a client's lifespan, which could result in the premature exhaustion of their assets, to be more severe than those from overestimating the lifespan, which could result in less lifetime spending than the client might have enjoyed otherwise. Which is why many financial planning software programs use a default age at death for clients that is beyond what actuarial tables might suggest.
That said, given the many planning applications of lifespan assumptions, from determining how much a client might need to save for retirement to optimal social security claiming strategies, having a better estimate of a particular client's lifespan could lead to better planning outcomes. So to help us dig deeper into how advisers might approach the challenging issue of estimating a particular client's lifespan, I'm joined today by Jeremy Co, an economist and the founder of Shore Up Retirement Solutions to discuss different ways to estimate a particular client's lifespan, how generating personalized lifespan assumptions might be easier and less expensive than many advisers might expect, and how advisers can tactfully raise this sensitive issue with clients.
From the episode’s captions: roughly the first two minutes, lightly cleaned. Keep watching on YouTube →
Topics
- retirement planning
- lifespan assumptions
- client longevity factors
- financial planning software
- client communication
Companies and tickers mentioned
- ShoreUp Retirement Solutions
Watch the episode
Watch “Calculating Personalized Client Lifespan Estimates, With Jeremy Ko” on YouTube
Summary, takeaways and quote selection by Octagon. Quotes are short excerpts; the full conversation is in the episode.
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Financial Advisor Success (Kitces), this episode and its artwork belong to Michael Kitces. Octagon is not affiliated with the show; this page is an independent summary.
