Giuseppe Liotta - We present visualization techniques for the visual analysis of financial activity networks. We combine enhanced graph drawing methods to devise novel algorithms and interaction functionalities for the visual exploration of networked data sets, together with tools for Social Newtork Analysis and for the automatic generation of reports. An application example constructed on real data is presented. We also report the results of a study aimed at qualitatively understanding the satisfaction level of the analysts when using VisFAN, a system designed according to the above principles.

1. 1
Giuseppe (Beppe) Liotta
Network Visualization for Financial
Crime Detection
UNIVERSITÀ DEGLI
STUDI DI PERUGIA

2. Overview
•A crash introduction to Visual Analytics
•Visual Analytics for Crime Discovery
•A demo
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3. UNIVERSITÀ DEGLI
STUDI DI PERUGIA
Visual Analytics: Crash Intro
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4. Visual Analytics: A “Dangerous” Zone?
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Drew Conway's Data Science Venn Diagram

5. Visual Analytics: A “Dangerous” Zone?
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Drew Conway's Data Science Venn Diagram
Data mining by humans
who know math

6. Visual Analytics: A “Dangerous” Area?
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Drew Conway's Data Science Venn Diagram
Data mining by computers
that replace humans
Data mining by humans
who know math

7. Visual Analytics: A “Dangerous” Zone?
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Drew Conway's Data Science Venn Diagram
Data mining by humans
assisted by computers
Data mining by computers
that replace humans
Data mining by humans
who know math

8. A Conceptual Model for Visual Analytics
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Data
Extraction
Data
Processing
Visualization Interaction

9. Networked (Typically Big) Data Sets
•Data can often be modeled as a network (also
called a graph)
• they consist of entities (vertices) and relationships
(edges) connecting them
•Relational data are used in a large variety of
application domains
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10. Social Network Analytics
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11. Bioinformatics
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12. Sentiment (Political) Analysis
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13. UNIVERSITÀ DEGLI
STUDI DI PERUGIA
A Visual Analytics System for
Crimes Investigations
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14. Financial Crimes
• Financial crimes represent a
worldwide critical problem
• They are based on relevant volumes
of financial transactions to conceal the purpose, the
source, or the destination of illegally gained money
• They weaken the integrity of worldwide financial markets
• They strengthen organized crimes that can mine the
homeland security

15. Financial Intelligence Units
• To face this problem, most governments have created
special investigation agencies, called Financial Intelligence
Units
• The major challenge of financial subjects and of FIUs is to
deal with the volume and the complexity of the collected
data

16. Financial Intelligence Units
FIU
INTELLIGENCE
PRODUCTION
CYCLE
COLLECT
PROCESS
ANALYZE
DISSEMI
NATE

17. Financial Intelligence Units
FIU
INTELLIGENCE
PRODUCTION
CYCLE
COLLECT
PROCESS
ANALYZE
DISSEMI
NATE

18. Financial Intelligence Units
FIU
INTELLIGENCE
PRODUCTION
CYCLE
COLLECT
PROCESS
ANALYZE
DISSEMI
NATE
Persons, companies, banks, bank
accounts, financial
transactions…

19. Financial Intelligence Units
FIU
INTELLIGENCE
PRODUCTION
CYCLE
COLLECT
PROCESS
ANALYZE
DISSEMI
NATE
Persons, companies, banks, bank
accounts, financial
transactions…

20. Financial Intelligence Units
FIU
INTELLIGENCE
PRODUCTION
CYCLE
COLLECT
PROCESS
ANALYZE
DISSEMI
NATE
Persons, companies, banks, bank
accounts, financial
transactions…
Financial Activity Networks (FANs)

21. Force directed e FAN
Visualizzazione dell'Informazione 21

22. User Evaluation
Q1 How much can VISFAN reduce the time and increase the productivity of the
investigation processes in AIF?
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Q2 How much can VISFAN increase the effectiveness (i.e., the ability of identifying
potential criminal activities) of the investigation processes in AIF?
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Q3 Within an investigation, how much do you benefit from the bottom-up
exploration (incremental exploration) feature of VISFAN?
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Q4 Within an investigation, how much do you benefit from the top-down
exploration (clustering) feature of VISFAN?

23. User Evaluation
Q5 How much do you benefit from the possibility of combining bottom-up and
top-down exploration features of VISFAN in an effective way?
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Q6 Within an investigation, how much do you benefit from imposing the
geometric constraints of the network layouts in VISFAN?AIF?
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Q7 How much are you satisfied with the interaction level of VISFAN?
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Q8 Within an investigation, how much do you benefit from the set of centrality
indexes of VISFAN?
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Q9 Within an investigation, how much do you benefit from the tree-based saving
system of VISFAN?
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Q10 Within an investigation, how much do you benefit from the reporting
functionality of VISFAN?

24. User Evaluation
1 = nothing
2 = not much
3 = enough
4 = a lot
Question Score
Q1 3.25
Q2 3.0
Q3 3.25
Q4 3.25
Q5 2.75
Q6 3.25
Q7 3.0
Q8 3.0
Q9 3.25
Q10 3.0

25. UNIVERSITÀ DEGLI
STUDI DI PERUGIA
Thank You!!
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