The life insurance underwriting process is an evaluation of an applicant that insurers use to categorize policyholders. The regular categories looking something like: standard, preferred, and preferred plus or some equivalent idea.
But what does it means to be standard or preferred? And why do insurance agents and brokers sometimes talk about waiting until the end of the year to apply for insurance for those who are on the bubble between various risk classes?
The evaluation process involves a list of several health related questions that check for medical history of various diseases or impairments. It also looks at common biomarkers used to check ones current overall health.
The underwriter then takes this information and places the applicant in a risk pool based on the information discovered through this evaluation.
Being offered standard rates for life insurance doesn’t mean you are unhealthy. It means you are normally healthy. The underwriter sees no need to believe that you might not live as long as any other member of the population.
Being offered preferred rates for life insurance means you are potentially a little healthier than standard applicants, but it also means that certain things about your lifestyle or situation would suggest there is a lower probability of your dying sooner than normally expected.
There is a subtly to the above that I want to highlight. Being preferred or even preferred plus doesn’t mean the life insurer thinks you are going to necessarily live longer than standard risks; it means they believe the probability of your dying early is lower.
It’s incorrect to assume that being issued preferred or preferred plus rates means you specifically are destined to live a long life. If this were true Bayes Theorem would suggest there’s no reason for you own insurance if you were offered preferred or preferred plus rates. Underwriting itself does nothing to speculate what will happen to you specifically.
Instead being issued a preferred or preferred plus policy merely means that you’ve been placed in a group of people with similarly expected probability of dying early. Insurance underwriting can do nothing to predict the individual’s life expectancy, but it can effectively predict how many people in the group are going to die early, and this application of probability theory has been keeping insurance companies in business since their inception.
For example if I have a 20,000 person group of 45 year old women for who have completed the life insurance underwriting process and are categorized as preferred risks, I can’t tell you much about how long each individual member of the group will live. What I can tell you is how many people in the group will likely die this year, and so long as the premium paid by each member of the group will bring in more money the claims paid for the number expected to die, the operation remains profitable.
The implications of that last paragraph are quite substantial, and I won’t be able to explicitly call out each one, but I’ll note one such circumstance that comes up because it can incorrectly make people assume recklessness among life insurers.
There is a common trend in the industry to become less discerning about applicants in the last quarter of the year. To be clear, this doesn’t mean people who shouldn’t be issued life insurance policies suddenly get a policy. It does mean that people who sort of teeter between two categories tend to more easily fall into the better category.
Life insurers can do this when they’ve determined that they have a large enough number of people placed in one category to effectively absorb the entrance of a questionable applicant. The best time to determine how well the company has added the right kind of applicants to the risk pool comes—as is no surprise—near the end of the year. This is of course much more prudent than placing an applicant into a higher risk class at the beginning of the year, and hoping that there will be sufficiently high numbers of better applicants later on in the year.
This works less well for those trying to push themselves into preferred territory or better. It’s simply trickier to evaluate preferred categorization. Or looked at another way, it’s easier to identify the things that will increase the probability that you will die at or before your life expectancy than it is to identify the things that will decrease the probability.
Brandon launched the Insurance Pro Blog in July of 2011 as a project to de-mystify the life insurance industry. Brandon was born in Northern New England, and he currently calls VT home. He attended Syracuse University and graduated with a triple major in Economics, Public Administration, and Political Science.
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