Using graph visualization to lead an anti-money laundering investigation. A concrete example.

1. SAS founded in 2013 in Paris | http://linkurio.us | @linkurious
Visualizing an anti-
money laundering
investigation.

2. What is money laundering.
Money laundering is the
process in which the
proceeds of crime are
transformed into
ostensibly legitimate
money or other assets.

3. The 3 steps of the money laundering process.
Placement
Introducing cash into the
financial system by some
means.
Layering
Carrying out complex
financial transactions to
camouflage the illegal
source
Integration
Acquiring wealth generated
from the transactions of the
illicit funds

4. Criminals vs AML investigators.
Follow the trail of illegal
money to convict criminal
and seize assets.
Create a complex financial
maze to obfuscate the trail of
illegal money.
The
fraudsters
The
investigators

5. Graphs can help investigators
fight money laundering.
Linkurious allows
investigators to explore
visually the information and
to look for specific patterns.
More results, faster.
The investigators can use
visualization to communicate
their findings. It helps
collaboration and obtain
convictions.
Working with data coming
from various sources is
complex. A graph allows you
to link the events, persons or
organizations together.
Track the
relations
Find hidden
insights
Communicate
results
Graphs and data investigation.

6. Concrete example : scenario.
Who?
As a specialized police investigator, we are tasked with investigating a criminal organization.
What?
The leaders of the organization are Virginia Parker, Marilyn Meyer and Diane Lawson. They are suspected of
running a large drug operation. All we have at the start of the investigation is that a known associate of the
organization runs a small business called Tanoodle.
Why?
The objective of the investigation is to map the money laundering scheme in order to secure the convictions
of its perpetrators and seize their assets.
How?
We are going to use graph visualization to represent the information captured via the investigation. It will
help us target the suspects.

7. Concrete example : data.
ACME Corp
COMPANY
John Smith
PERSON
ACCOUNT ACCOUNT
SENDS_TOHAS_ACCOUNT HAS_ACCOUNT
Discovering links from
financial records.

8. Concrete example : a first suspicious company.
We are looking at Tanoodle, a company associated with the criminal
organization. It is linked to a bank account.
The interface of Linkurious also makes it easy to explore and edit a graph.

9. Concrete example : first connection.
Via its bank account, Tannodle is connected to Avavee a company it
transfers money to.

10. Concrete example : Avavee collects money.
The financial records of Avavee shows that it collects money from Avavee
and 6 other companies.
That money is then funnel to two bank accounts (bottom right corner).

11. Concrete example : another hub of companies.
Connected to Avavee and the first hub of companies is another company
called Youspan. It receives money from 5 companies and channels it to
the same 2 bank accounts as Avavee.
Avavee and Youspan are the second layer of the money laundering
scheme.

12. Concrete example : the third layer.
Further investigation, helps gather information about the two suspicious
bank accounts. They are associated with two other companies called
Digitube and Zava. It constitutes the third layer of the money laundering
scheme.

13. Concrete example : the first three layers.
The first three layers of the money laundering scheme form a directed
network.

14. Concrete example : the complete scheme.
By investigating Digitube and Zava, we are able to have a look at the
complete money laundering network with 2 new companies and three
people.

15. Concrete example : the leaders.
We are finally available to find the ultimate beneficiaries of the money
laundering scheme. Time to make arrests and seize funds!

16. You can do it too!

17. Contact us to discuss
your projects
contact@linkurio.us
Conclusion

18. Blog post on AML investigation : http://linkurio.us/investigating-a-money-
laundering-scheme
Dataset used in the example : https://www.dropbox.com/s/4yxslaysaagf17o/aml%
20dataset.zip?dl=0
Additional resources.