A short podcast/transcript excerpt in which Richard Canfield discusses a mortality table (originally from 1958) and Nelson Nash's 'pig in the python' metaphor to explain aggregated mortality risk, large-number pooling, and how insurers price long-term benefits over multi-decade horizons.
Chapters
For anyone that's got the book in your hand, go to page 36. He's talking about how they create the entity for this. So he's explaining like how the insurance company kind of does things. And he's got this diagram. This is basically a mortality table. Now, it's from 1958, but the mortality table today looks the exact same. The only difference is it's stretched out wider. So Nelson used to say the pig in the python. You know, when a python eats a pig, it kind of is a big lump and then the lump goes through and it gets smaller as it goes down to the end. That's what this diagram is. It's the pig in the python. It does look like that. And so, out of a thousand Americans or North Americans born, a thousand die. Oh, my God. Go figure. Isn't that amazing how that works? That's called science, everybody. And this was a problem for the longest period of time in human existence. A large bulk of them die, unfortunately, before age 21. And you can see there's a big strong line there. That is still the case today, but that is a much more minimized case because of the advances of modern technology. But now, as you go forward, you see that each year it's how many die each and every year it gets wider and wider and they don't know which person is going to go, they just know how many. They do pandemic modeling, do all of this stuff. They just do it on a massive scale. And it's the power of large numbers being aggregated. And so we get the privilege to pay a little itty bit for this big, massive benefit because they understand how those flows work over 100 year time frames.
