
How Network Analysis Can Help Identify Money Laundering Schemes - pyduan
http://www.bayesimpact.org/stories/?name=the-mob-the-money-and-the-mayhem
======
leereeves
Interesting analysis, but better without the names.

It's dangerous to publicly suggest that people might be laundering money
without evidence (even with a disclaimer), especially people with unusual
names on a site indexed by search engines.

~~~
Lorento
That's debatable. First, it's public information he used. Anyone could have
analysed it themselves if they wanted to find suspicious people. Further, if
someone discriminates against these people just because their names appear on
a website alongside "we're not accusing them of anything", then that person
may be doing something wrong. But that person probably discriminates against
all sorts of people for trivial reasons anyway, and maybe we should think of
ways to make them behave in a more socially tolerable way if we don't like it.

------
peregrine
Finding the datasets for these kind of endeavours seems like a full time job.
Hats off to them for doing the work and making it happen!

------
dmichulke
TLDR;

Connect all people, addresses and businesses in the business register in a big
graph, sort each node by its amount of neighbours and work from there through
the list of best connected people.

The underlying idea is that money laundering requires a good network (of
people, addresses, companies) while staying "under the radar", so unknown
people that are well connected are potential money launderers.

------
jvilledieu
Too bad the analysis can't be reproduced. I can find data about the companies
([http://download.companieshouse.gov.uk/en_output.html](http://download.companieshouse.gov.uk/en_output.html))
but not the directors.

Anyone has had more luck?

