New Horizons is a mere few billion miles/km away, while financial matters these days sometimes involve trillions. Plus extra digits for cents and fractions thereof, of course.

“There are 10^11 stars in the galaxy. That used to be a huge number. But it’s only a hundred billion. It’s less than the national deficit! We used to call them astronomical numbers. Now we should call them economical numbers.” - Richard Feynman

JPL also has PhD applied mathematicians on staff to ensure numerical stability of their algorithms at double precision. Most developers do not have the ability to do that sort of non-trivial analysis. They are not just blindly saying "a double is good enough."

The problem with floating point for money is that simple calculations can give different answers than you would like because of how numbers are represented. E.g in a JS console:

    > 0.1 * 0.1
    <- 0.010000000000000002

This matters whenever you do things where the error might be allowed to accumulate and you're not careful to control for it. The general advice to avoid floating point for money is not because it's impossible to do correctly, but because it's very easy to get wrong in ways that are hard to discover with testing, and doing it with money is one of those areas where it's easy to get it wrong in ways that people will care about (because you're suddenly paying the wrong amount of tax, for example).

I don't know about you, but I don't trust myself to get this right, much less developers who often don't understand the issues involved.

It’s good enough for dollars and cents if you put thought into it, but you can’t just represent money as double-precision dollars and expect to get the results you need.

floating point was designed for scientific and numerical/math applications (written by people with numerical analysis skills), not money. There are decimal data types which are much better for money management.