Frank C. Kilcoyne, CSSC

Prognostication

As the title indicates, this month we are going to examine the practice of prediction: specifically, how long a person will live. This is a fundamental issue when designing settlement plans, because we need to know how many years of future living and medical support may be needed.

These are serious, important, and potentially expensive questions for which we seek equally serious answers. But how does one go about determining how long a person will live? Thank goodness we don’t actually have to: the problem of handling this “mortality risk” was solved long ago through the miracle of risk spreading – more commonly known as “insurance.”

It may be an unglamorous industry, but the invention of insurance stands as truly one of the major wonders of the financial world, indeed, perhaps of modern society. All people walking the earth face risks and there is no way to know which particular individuals bad luck will visit. But thanks to this mechanism, we don’t have to predict any one individual’s fate, we can employ a “risk pool” to manage that risk.

For this particular task, we rely on (appropriately-titled) “life insurance” companies. What can they do that we can’t? How is their math any better than ours? Well, their math isn’t any better than ours, but they have two big advantages: they can draw on the “law of large numbers” and they have a gigantic data base of actual lives lived upon which to draw.

The “law of large numbers” lets them change the question from “when will this particular person die” to “how many people this person’s age will die in the next year, the year after that, etc.?” Analyzing the duration of lives actually lived by a million people gives them a pretty good idea of how many on average out of a pool of 10,000 won’t survive the next twelve months. Instead of trying to predict the fate of one specific individual, they only have to know the approximate number who will die out of a much larger pool. And this converts their math from “WAG” (wild-ass guess) into a highly reliable algorithm. As it turns out, predicting how long a given percentage of the population will live is a surprisingly predictable and low-risk activity – assuming average health. Winners offset losers and the average will reign.

But how do we offload the mortality risk of a single person in poor health? That is a different matter altogether. From a risk management standpoint, the only prudent thing for a life insurance company to do would seem to be to decline that business (as they regularly do with standard life insurance policies). But the math flips again here because settlement annuities are not life insurance. What presents itself as an unacceptably high risk for a life insurance product becomes a potential opportunity when writing settlement annuities.

This dynamic translates directly into pricing. One of the most powerful benefits of a structured settlement is that we can provide tax-free income guaranteed for the rest of the claimant’s life; they cannot outlive the benefits of the settlement plan.

But, using standard annuity rates to provide a lifetime income for a person with a serious medical condition equates to statistical overpricing. Life insurers know this and employ a correction method known as “substandard underwriting.” Here, they request current medical records describing the person’s condition and have highly trained specialists review them. If they see evidence of a condition which tends to shorten life, they will assign that person a different age for pricing purposes. This adjusted age is called a “rated age” and it allows us to reduce annuity prices accordingly.

Example: Jane, a healthy 20-year-old female living in the United States can expect to live another 60 years to age 80. $ 1,000 per month to Jane for the rest of her life might cost $346,324 and pay out $790,000 in tax-free income over this expected lifetime. This plan has an internal rate of return of 3.02% (which will of course increase if she lives longer).

But if Jane has some medical condition or illness which diminishes her life expectancy by 20 years, Jane would have the life expectancy (or “rated age”) of a 40-year-old female. That same $1,000 per month for life would now cost only $300,442, a 14% discount which raises the internal rate of return of this adjusted plan from 3.02% to 3.69%.

Taking this further, if Jane’s condition was grave enough to diminish life expectancy by another 20 years, it would give her the life expectancy of a 60-year-old. $1,000 per month for life now costs only $232,971. This represents a 33% discount off the initial cost of the settlement annuity and bumps the internal rate of return up to 5.06%.

These examples illustrate cost reductions, but we can also use the rated age to increase benefits at a given level of cost. Given the original annuity cost of $346,324 and “rate-ups” of 20 and then 40 years, we could increase Jane’s lifetime income as follows:

Standard Life Expectancy            Rated Age of 40                 Rated Age of 60
$1,000 per month                   $1,154 per month             $1,487 per month

As you can see, rated ages can substantially increase the monthly benefit to the claimant without increasing cost one penny.

The following conditions may prompt a life company to assign a rated age: alcoholism, cancer, cardiac problems, chemotherapy, cigarette smoking, diabetes, drug addiction, high blood pressure, hepatitis, kidney failure, lung disease, multiple sclerosis, obesity, paralysis, stroke, severe burns. Note: the claimant’s medical condition need not have anything to do with the claim at hand and pre-existing conditions are fully acceptable.

Do you want to try using a rated age to increase the value of your settlements? Call Frank C. Kilcoyne, CSSC, at 800-544-5533. I am here to help.

(1) Social Security Actuarial Tables https://www.ssa.gov/oact/STATS/table4c6.html. Figure rounded down; exact life expectancy 61.72 years.