Presentation at Bank of Canada workshop on "Understanding financial markets and institutions - Theory and Data" on 2 June 2011 in Ottawa, Canada.

1. Presentation at Bank of Canada Workshop on Understanding Financial Institutions and Markets: Theory and Data 2 June 2011 Financial Network Analytics Kimmo Soramäki kimmo.soramaki@fna.fi

2. Perspective Understanding financial institutions and markets Theory Data Focus on the tools and processfor research and policy

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

4. Eratosthenes' map of the known world, c. 194 BC

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

6. Data deluge Data tsunami - digital information is doubling every 1.2 years 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 (public, commercial and regulatory) Data enables “Analytics based policy”, i.e. the application of computer technology, operational research, and statistics to solve problems

7. Network maps Recent financial crisis brought to light the need to look at links between financial institutions Way to present data. Mapping of the financial system has only begun Reduce uncertainty about interconnections Garrett, Mahadeva and Svirydenska (2011) Soramaki, Bech et al (2006)

8. Intelligence Financial crisis are different and rare Pattern recognition is hard for computers -> the best Go programs only manage to reach an intermediate amateur level The patterns to be recognized must be frequent enough for computers to learn A solution is to augment human intelligence (in contrast to AI)

9. Roots of the work Bof-PSS2 Bank of Finland, 1997- Payment system simulator used in ~60 central banks Loki Sandia National Laboratories, 2004- Toolkit for network analysis and ABM Sponsored by Norges Bank, collaborative efforts with other central banks

10. Method and features

11. Data tools in FNA

12. Network analysis in FNA

13. Network visualization in FNA

14. Demo

16. Cloud service

17. REST API (for accessing FNA engine from web applications)

18. Intranet

19. Operative use

20. Integration to databases and user management

21. Browser based GUI

22. Desktop

23. By demand, academic use

24. Command line version available

26. Vision Develop tool for explorativeanalysisof the financial system Provide a platform for building agent based and simulation models Make advances in research available to policy Integrate data feeds and available databases

27. Thank you More information www.financialnetworkanalysis.com Contact us kimmo.soramaki@fna.fi