If I'm watching a series of accounts for transactions going in and transactions going out, I want to notice unusually large or transactions for any particular account on any particular day.
So if account A typically moves a few hundred dollars and one day moves five thousand dollars, that's a clear outlier. If account B typically moves a few million dollars in or out and one day moves 20 million dollars, that's a clear outlier.
What I'd like to do is present a measure that should highlight outliers - I was thinking number of standard deviations versus a population of the rolling last 60 days, but I'm wondering if that's correct. I'm checking to see if it's a gaussian distribution, but are there better ways to hit what I'm looking for?
I think this poses a different set of questions than Robust outlier detection in financial timeseries.