If I told you that you had a 1 and 10,000 chance of dying this year, would it help you decide to buy life insurance?
When I first pondered this question, my analytical mind naturally starting churning statistics. I said to myself, "Well, if I want $1 million in term life insurance for the year, than it would only make sense if the cost of insurance was $100 per year ($1 million multiplied by 0.01%). Maybe to be safe, I'd pay a little more, let's say $200, or $300, or…"
The problem with this thinking is that I was taking the wrong perspective. I was analyzing it like the insurance company would. If millions of people similar to me have a 1 and 10,000 chance of dying, then offering less than $100 for a $1 million policy is a bad business decision. They use the law of large numbers to make actuarial decisions.
You as the individual are different. You only have one chance to live or die this year. Unlike the insurance company who spreads the risk across many individuals, you don't get to experience the year 10,000 times and see if you died once (statistically speaking you would want to run the scenario many more times than 10,000 to increase your confidence in the measurement).
Instead, what matters is what happens if you do die. Can you, your dependents, and loved ones maintain a lifestyle you would prefer them to? Even if the chance is very small, can you accept that scenario? The question is not the probability of an event, it is the possibility.Similar logic can be employed when considering other types of insurance such as disability or long-term care.
If you are stuck on how to think about insurance, ask yourself if worse case is tolerable.
The information is the personal views of Josh Stillman and is not necessarily indicative of those of Capitol Securities Management. The information contained herein has been compiled from sources believed to be reliable; however, there is no guarantee of its accuracy or completeness. Any opinions expressed here are statements of judgment on this date and are subject to certain risks and uncertainties which could cause actual results to differ materially from those currently anticipated or projected.