Correlation versus Causation
The human brain has a strong natural tendency, proven time and time again in experiments, to seek patterns or correlations to help people more quickly understand cause and effect. Unfortunately, the same human brain has severe limitations which can cause people to jump to conclusions. They think they see a pattern when there is none or they think that because a pattern (correlation) exists, that causation exists when it does not. With modern software, people who do not know what they are doing and people who are unethical suggest correlations exist between two items because they can plot correlations using scatter graphs. Just because one can graph a line from all the samples does not mean that a correlation, much less causation exists.
An interesting intersection of life insurance and COVID-19 may present a great example of this conundrum. An article in A.M. Best noted that a large life insurance company "hasn't seen non-COVID-19 mortality diverge substantially from historic trends..." Some researchers have counted large increases in excess deaths. Let's assume those counts are correct for argument’s sake. This means that the way to avoid an extra death risk is to buy life insurance. If deaths are rising but people with life insurance are not dying, a correlation exists. As such, it makes sense that a conspiracy may exist to make sure people with life insurance live longer, so they keep paying premiums and the carrier does not have to pay claims. Now we have causation.
Absent a conspiracy, a different set of reasons may exist for the divergence and that is people who do not buy life insurance may live their lives in a way that is more likely to cause an early death. They are too young and don't feel they need it could be a reason. Drug addicts might be thinking of more immediate needs. People with the co-morbidities associated with COVID-19 severity are also people within socio-economic groups that might purchase less or no life insurance. Healthy people then, those less likely to actually die early and with the economic means, buy more life insurance. Carriers like healthy consumers because the profit margins are better and those consumers, for many reasons financial and psychological, buy more life insurance to fulfill their financial planning needs.
A correlation exists, but not a causation. Buying life insurance offers zero COVID-19 or any other virus inoculation qualities. Instead, what this situation describes is that people who have better health are more likely to buy more insurance and simultaneously will die from this virus with less frequency. Considering old people who likely quit paying life insurance premiums years ago are the most common COVID-19 victims, this alone makes sense. Being middle aged and healthy correlates with less death and the drive to buy more life insurance. That is the cause and effect. Two variables with the same result.
When you see a consultant or an executive or an analyst promoting some kind of cause and effect because of a correlation, always ask for proof that the correlation is proof of the cause rather than allowing them to convince you the correlation is proof by itself of causation.
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None of the materials in this article should be construed as offering legal advice, and the specific advice of legal counsel is recommended before acting on any matter discussed in this article. Regulated individuals/entities should also ensure that they comply with all applicable laws, rules, and regulations.