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There is some statistical thing about fraud and the frequency of certain numbers being made up. I don't recall it specifically but made up amounts, dates, numb

There is some statistical thing about fraud and the frequency of certain numbers being made up. I don't recall it specifically but made up amounts, dates, number have certain clusters of numbers vs what normally occurs. edit; didn't get all that was in my head out :-) So, it could be made up or support the fact that actual docs or good record keeping weren't a thing.

nebalee 3y ago
https://en.wikipedia.org/wiki/Benford%27s_law https://en.wikipedia.org/wiki/Benford%27s_law
- saveferris 3y ago
  thanks, could not remember it and my google fu was poor trying to look for it :-)
actinium226 3y ago
I think you're thinking of Benford's law: https://en.wikipedia.org/wiki/Benford%27s_law https://en.wikipedia.org/wiki/Benford%27s_law It's pretty strange, basically if you have a document with a bunch of numbers (say, some company's quarterly report), look at the leading digit of all the numbers. For some reason, numbers with a leading digit of 1 show up more often than those with a leading digit of 9 (i.e. 1,234,567 is more likely that 987,123). You'd think there wouldn't be any particular pattern in the leading digit, I mean why should there be? But observational data seem to suggest a pattern. So Benford's law can be used as a leading indicator of fraud. If you apply it to a quarterly report and there's an unusually high distribution of 8's, for example, then while you can't be certain that it's fraud, it might be flag to an inspector/regulator to take a closer look.
- automatic6131 3y ago
  It's pretty obvious, really. A quick little sketchproof; say you have a metric, like headcount, revenue, expenses - whatever. These tend to grow exponentially-ish over time. When that's the regime, the number spends 1/3rd of it's time between 1 and 2 of its leading digit, and 2/3rds growing from 2 to the next power of 10. Similar logic applies if you're counting things that follow any power law - population of cities etc. Wherever you have a power law distribution, Benford's law applies. But when humans enter data, they tend to fake numbers with a uniform distribution - to appear more random. That's how you catch it.

nebalee 3y ago

https://en.wikipedia.org/wiki/Benford%27s_law https://en.wikipedia.org/wiki/Benford%27s_law

saveferris 3y ago
thanks, could not remember it and my google fu was poor trying to look for it :-)

actinium226 3y ago

I think you're thinking of Benford's law: https://en.wikipedia.org/wiki/Benford%27s_law https://en.wikipedia.org/wiki/Benford%27s_law It's pretty strange, basically if you have a document with a bunch of numbers (say, some company's quarterly report), look at the leading digit of all the numbers. For some reason, numbers with a leading digit of 1 show up more often than those with a leading digit of 9 (i.e. 1,234,567 is more likely that 987,123). You'd think there wouldn't be any particular pattern in the leading digit, I mean why should there be? But observational data seem to suggest a pattern. So Benford's law can be used as a leading indicator of fraud. If you apply it to a quarterly report and there's an unusually high distribution of 8's, for example, then while you can't be certain that it's fraud, it might be flag to an inspector/regulator to take a closer look.

automatic6131 3y ago
It's pretty obvious, really. A quick little sketchproof; say you have a metric, like headcount, revenue, expenses - whatever. These tend to grow exponentially-ish over time. When that's the regime, the number spends 1/3rd of it's time between 1 and 2 of its leading digit, and 2/3rds growing from 2 to the next power of 10. Similar logic applies if you're counting things that follow any power law - population of cities etc. Wherever you have a power law distribution, Benford's law applies. But when humans enter data, they tend to fake numbers with a uniform distribution - to appear more random. That's how you catch it.