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Presentation at European Central Bank 17 August 2011 Financial Network Analytics Kimmo Soramäki kimmo@soramaki.net
Katsushika Hokusai. The great wave off Kanagawa ~1830
Eratosthenes' map of the known world, c. 194 BC
Go is a board game that originated in China more than 2,000 years ago.
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 regulatory problems
Network maps Erastothenescreated the first known map of the world and is considered the father of geography and the concepts of latitude and longitude (i.e. ways to measure it) Recent financial crisis brought to light the need to look at links between financial institutions Network are a natural way to present financiallinkage data. Mapping of the financial systemhas only begun Maps reduce uncertainty about interconnections  Garrett, Mahadeva and Svirydenska (2011) Soramaki, Bech et al (2006)
Intelligence Pattern recognition is hard for computers -> the best Go programs only manage to reach an intermediate amateur level Financial crisis are different and rare  The patterns to be recognized must be frequent enough for computers to learn A solution is to augment human intelligence (in contrast to AI) Intelligence amplification (William Ross Ashby 1956)
Financial Network Analytics Platform
Objectives Provide a tool for exploration, analysis and visualization of regulatory financial data  Provide a extendible platform for custom functionality, agent based models and other simulation models Make advances in research available to policy
Situation around March 2010 Furfine algorithm Payment System Simulator FNA 1.1
Because analyzing financial microdata is difficult Files are large, content is difficult to understand Data is incomplete and messy Data is confidential Most analysis packages are opaque Error and trial Paradigm
Platform + modules + sharing
Current modules
The network model N3 Prop1=Aaa; Prop2=Bbb;….. N2 Prop1=Aaa; Prop2=Bbb;….. A1 Source=V1 Dest=V2 Props… Network 1 – N1 Prop1=Abc Prop2=Def … A2 Source=V2 Dest=V3 Props… 14 V2 Prop1=20 Prop2=Ab Prop3=Bc A3 Source=V2 Dest=V1 Props… V1 Prop1=20 Prop2=Ab Prop3=Bc V3 Prop1=20 Prop2=Ab Prop3=Bc Time Series
Explain screen Screen elements Result panel shows command output Access via browser in intranet, internet or desktop And creates files (charts, data, etc) Operation based on commands Submit command Each command has different parameters ‘Visualize’ screen shows created charts and layouts Switch between ‘point-and-click’ and command line view Files and database connections are in file panels 15
Tabs allow multiple visualisations open All visualisations are html documents that work also outside FNA 16
Dashboard (concept) The dashboard can combine multiple views to the data on a single screen 17 It can be available e.g. on the intranet and updated daily
Command line All commands can be submitted using command syntax   History provides an easy way to make new scripts for research or for the dashboard All commands submitted (also from point-and-click) are shown in history 18
Command line Scripts can be run from the scripts panel or as regular jobs by the server 19
FNA is available at www.fna.fi (as from 29 August 2011) Contact us kimmo@soramaki.net
Technical details Performance Client server architecture allows use of high performance servers, computer clusters and cloud computing High-performance graph engine (neo4j.org)  Fast client application (Google web toolkit e.g. as in gmail.com) Security Sensitivity and confidentiality of data creates addition constraints for analysis Data is stored on server where it can be protected better (vs analysts desktops) Each user accesses FNA with her own account SSL encryption of traffic Logging and analytics, audit trail Integration to corporate IT Integration to databases possible FNA accounts can be managed centrally by IT (integration to LDAP systems) Can run on most application servers Modular structure allows easier updates

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Financial Network Analytics @ ECB

  • 1. Presentation at European Central Bank 17 August 2011 Financial Network Analytics Kimmo Soramäki kimmo@soramaki.net
  • 2. Katsushika Hokusai. The great wave off Kanagawa ~1830
  • 3. Eratosthenes' map of the known world, c. 194 BC
  • 4. Go is a board game that originated in China more than 2,000 years ago.
  • 5. 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 regulatory problems
  • 6. Network maps Erastothenescreated the first known map of the world and is considered the father of geography and the concepts of latitude and longitude (i.e. ways to measure it) Recent financial crisis brought to light the need to look at links between financial institutions Network are a natural way to present financiallinkage data. Mapping of the financial systemhas only begun Maps reduce uncertainty about interconnections Garrett, Mahadeva and Svirydenska (2011) Soramaki, Bech et al (2006)
  • 7. Intelligence Pattern recognition is hard for computers -> the best Go programs only manage to reach an intermediate amateur level Financial crisis are different and rare The patterns to be recognized must be frequent enough for computers to learn A solution is to augment human intelligence (in contrast to AI) Intelligence amplification (William Ross Ashby 1956)
  • 9. Objectives Provide a tool for exploration, analysis and visualization of regulatory financial data Provide a extendible platform for custom functionality, agent based models and other simulation models Make advances in research available to policy
  • 10. Situation around March 2010 Furfine algorithm Payment System Simulator FNA 1.1
  • 11. Because analyzing financial microdata is difficult Files are large, content is difficult to understand Data is incomplete and messy Data is confidential Most analysis packages are opaque Error and trial Paradigm
  • 12. Platform + modules + sharing
  • 14. The network model N3 Prop1=Aaa; Prop2=Bbb;….. N2 Prop1=Aaa; Prop2=Bbb;….. A1 Source=V1 Dest=V2 Props… Network 1 – N1 Prop1=Abc Prop2=Def … A2 Source=V2 Dest=V3 Props… 14 V2 Prop1=20 Prop2=Ab Prop3=Bc A3 Source=V2 Dest=V1 Props… V1 Prop1=20 Prop2=Ab Prop3=Bc V3 Prop1=20 Prop2=Ab Prop3=Bc Time Series
  • 15. Explain screen Screen elements Result panel shows command output Access via browser in intranet, internet or desktop And creates files (charts, data, etc) Operation based on commands Submit command Each command has different parameters ‘Visualize’ screen shows created charts and layouts Switch between ‘point-and-click’ and command line view Files and database connections are in file panels 15
  • 16. Tabs allow multiple visualisations open All visualisations are html documents that work also outside FNA 16
  • 17. Dashboard (concept) The dashboard can combine multiple views to the data on a single screen 17 It can be available e.g. on the intranet and updated daily
  • 18. Command line All commands can be submitted using command syntax History provides an easy way to make new scripts for research or for the dashboard All commands submitted (also from point-and-click) are shown in history 18
  • 19. Command line Scripts can be run from the scripts panel or as regular jobs by the server 19
  • 20. FNA is available at www.fna.fi (as from 29 August 2011) Contact us kimmo@soramaki.net
  • 21. Technical details Performance Client server architecture allows use of high performance servers, computer clusters and cloud computing High-performance graph engine (neo4j.org) Fast client application (Google web toolkit e.g. as in gmail.com) Security Sensitivity and confidentiality of data creates addition constraints for analysis Data is stored on server where it can be protected better (vs analysts desktops) Each user accesses FNA with her own account SSL encryption of traffic Logging and analytics, audit trail Integration to corporate IT Integration to databases possible FNA accounts can be managed centrally by IT (integration to LDAP systems) Can run on most application servers Modular structure allows easier updates