As you may have read, for financial uses, many databases support special types such as money or smallmoney to provide for better data retention. Source
However, through some digging, I've found a pretty clear-cut answer to your question. Basically, it depends on the implementation and the needs of the data. If the data you're storing is to be manipulated (especially exponentially) stay away from floating type data.
It all depends on the accuracy you need to maintain in your data. Converting 1.1 to a float and then convert it back again, your result will be something like 1.0999999999989.
As my professors always said, and as another user points on here, this is a basic rule-of-thumb of when to use a floating type:
For values which are more artefacts of nature which can't really be
measured exactly anyway, float/double are more appropriate. For
example, scientific data would usually be represented in this form.
Here, the original values won't be "decimally accurate" to start with,
so it's not important for the expected results to maintain the
"decimal accuracy". Floating binary point types are much faster to
work with than decimals.