The recent financial crisis has brought to light the interconnected nature of modern financial systems. Academia, regulators and the industry have recently developed a stronger awareness of the need for new analytical methods and tools that can help to better monitor and safeguard the financial system and better manage systemic risks. In the presentation we will discuss new research in financial network analysis. How can network analysis of large-scale financial transaction data be used to gain a better understanding of the financial system. How can exploratory visual analytics of time-series networks bring new insights? How can cross-asset networks enable a better intuition of market dynamics? The topics will be analyzed and visualized with FNA (www.fna.fi) - an online platform for Financial Network Analytics.

1. PRMIA Webinar
1 February 2012
Financial Network Analytics
Kimmo Soramäki | www.fna.fi
kimmo@soramaki.net

2. “When the crisis came, the serious limitations of existing economic
and financial models immediately became apparent.
[...]
As a policy-maker during the crisis, I found the available models of
limited help. In fact, I would go further: in the face of the crisis, we
felt abandoned by conventional tools.”
in a Speech by Jean-Claude Trichet, President of the
European Central Bank, Frankfurt, 18 November 2010

3. 2003 2003 2004
3

4. “Is network theory the “Meltdown modeling - “... need for new and
best hope for regulating Could agent-based fundamental
systemic risk?” computer models prevent understanding of the
another financial crisis?” structure and dynamics of
economic networks.”
CFA Magazine, July 2009 Nature, August 2009 Science, July 2009

5. Network theory and related fields
Financial
Network
Analysis
Social Network Network
Analysis Science
NETWORK
THEORY
Graph & Matrix Computer
Theory Science
Biological
Network
Analysis

6. Main premise of network analysis:
Structure of links between nodes matters
• The properties and behavior of a node cannot be analyzed on the
basis its own properties and behavior alone.
• To understand the behavior of one node, one must analyze the
behavior of nodes that may be several links apart in the network.
• Bottom up approach. Generalize and describe.
• Financial contexts
– Network of interconnected balance sheets
– Network of asset dependencies

7. Systemic importance = “centrality”
• Degree: number of links
• Closeness: distance to other
nodes via shortest paths
• Betweenness: number of shortest
paths going through the node
• Eigenvector: nodes that are linked by/to
other important nodes are more central

8. Hundreds of research papers later…
….
www.fna.fi/library

9. What is a/the financial network?

10. Interbank payment networks
• Total of ~8000 banks
• 66 banks comprise 75% of value
• 25 banks completely connected
Soramäki, Bech, Beyeler, Glass and Arnold
(2006), Physica A, Vol. 379, pp 317-333.

11. Country exposures networks
• Claims of banking sector by
country

12. Asset correlation networks
• Cross-asset correlation tree of
German DAX index stocks
• Assets are linked in a backbone
correlation network
• Clusters of asset classes clearly
visible
• Data reduction method

13. Why are networks so topical?

14. Katsushika Hokusai. The great wave off
Kanagawa ~1830

15. Data tsunami
• Digital information is doubling every 1.2 years -> Open Data, Data
Science, „Chief Algorithms Officers‟…
• Regulatory response to recent financial crisis was to strengthen
macro-prudential supervision with mandates for more regulatory
data
• The challenge will be to
understand and analyze the data
• Analytics based decision-making,
i.e. the application of computer
technology, operational research,
and statistics to support decision
making
Katsushika Hokusai. The great wave off
Kanagawa ~1830

16. Eratosthenes' map of the known world
c. 194 BC

17. Network maps
• Natural way to visualize the financial system
• Network visualizations are intuitive
• Maps aid decision making
• Mapping of the financial system
has only begun
Eratosthenes' map of the known
world, c. 194 BC.

18. Go is a board game that originated in
China more than 2,000 years ago.

19. Intelligence Amplification
• Technology, products and
practices change constantly
• Data is not clean, actions are not
„rational‟
• Algorithms don‟t fare well in
periods of abrupt change
• Algorithms do not think outside
the box
• A solution is to augment human
intelligence
• Intelligence Amplification vs
Artificial Intelligence

20. Financial Network Analytics

21. Financial Network Analytics (FNA)
FNA is an analytics platform that helps banks and financial
regulators manage and understand financial data with network
analysis
• Web Service (www.fna.fi) and Enterprise Software
• Modular design, current modules for:
– Financial Stability
– Payment System Oversight
– Macroprudential Supervision and
– Cross Asset Analysis
• Designed for operationalizing latest research

22. Financial Network Analytics Platform
Develop Monitor

23. Demos
• Bilateral banking sector exposures by country (2005-
2011)
– Node = country, Link = banking system exposure
– Force-Directed layout of network
• Asset correlation data for DAX stocks (January 2012)
– Node = asset, Link = coupling via correlations
– Dynamic Force-Directed layout of spanning tree
• Dashboards

24. Banking sector exposures by country
Chord Force-
24 directed

25. 25 Dashboard

26. Spanning Tree of
German DAX index stock correlations
January 2012
26

27. www.fna.fi
27
for more information

28. • http://trunk.fna.fi/fna/data/canemtest/cha
rts/public/canem.html