It is correct! Using decimal types is the widely recommended way of solving this problem. That includes fixed and floating point types. The problem is using base-2 floating point types, since those are subject to the kinds of rounding errors in the OP. But decimal floating point types are not subject to these kinds of rounding errors.

But they still can't precisely represent quantities like 1/3 or pi.

> Using decimal types is the widely recommended way of solving this problem.

No, it's not. The widely recommended way of solving this problem is to use fixed-point numbers. Or, if one's language/platform does not support fixed-point numbers, then the widely recommended way of solving this problem is to emulate fixed-point numbers with integers.

There is zero legitimate reason to use floating-point numbers in this context, regardless of whether those numbers are in base-2 or base-10 or base-pi or whatever. The absolute smallest unit of currency any (US) financial institution is ever likely to use is the mill (one tenth of a cent), and you can represent 9,223,372,036,854,775,807 of them in a 64-bit signed integer. That's more than $9 quadrillion, which is 121-ish times the current gross world product; if you're really at the point where you need to represent such massive amounts of money (and/or do arithmetic on them), then you can probably afford to design and fabricate your own 128-bit computer to do those calculations instead of even shoehorning it onto a 64-bit CPU, let alone resorting to floating-point.

Regardless of all that, my actual point (pun intended) is that there are plenty of big ERP systems (e.g. NetSuite) that use binary floating point numbers for monetary values, and that's phenomenally bad.