I'm pretty confident that dfp is used for financial computation. Both because it has been pushed heavily by IBM (who certainly are very involved in financial industry) and because many papers describing dfp use financial applications as motivating example. For example this paper: https://speleotrove.com/decimal/IEEE-cowlishaw-arith16.pdf
> This extensive use of decimal data suggested that it would be worthwhile to study how the data are used
and how decimal arithmetic should be defined. These
investigations showed that the nature of commercial
computation has changed so that decimal floating-point
arithmetic is now an advantage for many applications.
> It also became apparent that the increasing use of decimal floating-point, both in programming languages and
in application libraries, brought into question any
assumption that decimal arithmetic is an insignificant part of commercial workloads.
> Simple changes to existing benchmarks (which used incorrect binary approximations for financial computations) indicated that many applications, such as a typical Internet-based ‘warehouse’ application, may be spending 50% or more of their processing time in decimal arithmetic. Further, a new benchmark, designed to model an extreme case (a telephone company’s daily billing application), shows that the decimal processing overhead could reach over 90%
Wow. OK, I believe you. Still don’t see the advantages over using the same number of bits for fixed point math, but this definitely sounds like something IBM would do.
Edit: Back of the envelope, you could measure 10^26 dollars with picodollar resolution using 128 bits
> This extensive use of decimal data suggested that it would be worthwhile to study how the data are used and how decimal arithmetic should be defined. These investigations showed that the nature of commercial computation has changed so that decimal floating-point arithmetic is now an advantage for many applications.
> It also became apparent that the increasing use of decimal floating-point, both in programming languages and in application libraries, brought into question any assumption that decimal arithmetic is an insignificant part of commercial workloads.
> Simple changes to existing benchmarks (which used incorrect binary approximations for financial computations) indicated that many applications, such as a typical Internet-based ‘warehouse’ application, may be spending 50% or more of their processing time in decimal arithmetic. Further, a new benchmark, designed to model an extreme case (a telephone company’s daily billing application), shows that the decimal processing overhead could reach over 90%