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Presentation at Delft University's Mathematics and Computer Science department on Financial Networks, on analyzing and modeling them and on the www.fna.fi service.
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“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
We are talking about systemic risk ≠ systematic risk
• The risk of disruption to a financial entity with spillovers to the real economy
• Risk of a crisis that stresses key intermediation markets and leads to their breakdown, which impacts the broader economy and requires government intervention
• Risk that critical nodes of a financial network cease to function as designed, disrupting linkages
-> some chain of events that starts or gets magnified in the finance sector and makes us all worse off
News articles mentioning “systemic risk”, Source: trends.google.com
• Three components of models
– Topology of financial networks– System mechanics– Behavioral dynamics
• How to bring research to policy?
• Financial Network Analytics -software
Agenda
Payment systems
Annual value (euros) Liquidity need Age of the universe (hours)0.00E+00
5.00E+14
1.00E+15
1.50E+15
2.00E+15
2.50E+15
Annual value (euros) Liquidity need0.00E+00
5.00E+14
1.00E+15
1.50E+15
2.00E+15
2.50E+15
Annual value (euros)0.00E+00
5.00E+14
1.00E+15
1.50E+15
2.00E+15
2.50E+15
Annual value (euros) Liquidity need Age of the universe (days)0.00E+00
5.00E+14
1.00E+15
1.50E+15
2.00E+15
2.50E+15
~1939 tr
~194 tr ~120 tr ~5 tr
Bech, Preisig and Soramäki (2008), FRBNY Economic Review, Vol. 14, No. 2.
Topology of interactions
Total of ~8000 banks66 banks comprise 75% of value25 banks completely connected
Degree distribution
Soramäki, Bech, Beyeler, Glass and Arnold (2006), Physica A, Vol. 379, pp 317-333.
System mechanics
Bank i Bank j
Payment system
1 Agent instructs bank to send a payment
2 Depositor account is debited
Di Dj
5 Payment account is credited
4 Payment account is debited
Productive Agent Productive Agent
6 Depositor account is credited
Qi
3 Payment is settled or queued
Bi > 0 Qj
7 Queued payment, if any, is released
Qj > 0
Bi Bj
Central bank
Beyeler, Glass, Bech and Soramäki (2007), Physica A, 384-2, pp 693-718.
LiquidityMarket
5 5 0 0
5 6 0 0
5 7 0 0
5 8 0 0
5 9 0 0
6 0 0 0
6 1 0 0
5 5 0 0 5 7 0 0 5 9 0 0 6 1 0 0
Instructions
Pay
men
ts
0
2 0 0 0
4 0 0 0
6 0 0 0
8 0 0 0
1 0 0 0 0
1 2 0 0 0
1 4 0 0 0
1 6 0 0 0
1 8 0 0 0
2 0 0 0 0
0 2 0 0 4 0 0 6 0 0 8 0 0 1 0 0 0 1 2 0 0 1 4 0 0 1 6 0 0 1 8 0 0 2 0 0 0
Time
0
2 0 0 0
4 0 0 0
6 0 0 0
8 0 0 0
1 0 0 0 0
1 2 0 0 0
1 4 0 0 0
1 6 0 0 0
1 8 0 0 0
2 0 0 0 0
0 2 0 0 4 0 0 6 0 0 8 0 0 1 0 0 0 1 2 0 0 1 4 0 0 1 6 0 0 1 8 0 0 2 0 0 0
Time
PaymentSystem
When liquidity is high payments are submitted promptly and banks process payments independently of each other
Instructions Payments
Summed over the network, instructions arrive at a steady rate
Liquidity
0
2 0 0 0
4 0 0 0
6 0 0 0
8 0 0 0
1 0 0 0 0
1 2 0 0 0
1 4 0 0 0
5 5 0 0 5 7 0 0 5 9 0 0 6 1 0 0
Instructions
Pay
men
ts
0
2 0 0 0
4 0 0 0
6 0 0 0
8 0 0 0
1 0 0 0 0
1 2 0 0 0
1 4 0 0 0
1 6 0 0 0
1 8 0 0 0
2 0 0 0 0
0 2 0 0 4 0 0 6 0 0 8 0 0 1 0 0 0 1 2 0 0 1 4 0 0 1 6 0 0 1 8 0 0 2 0 0 0
Time
Reducing liquidity leads to episodes of congestion when queues build, and cascades of settlement activity when incoming payments allow banks to work off queues. Payment processing becomes coupled across the network
PaymentSystem
Instructions Payments0
2 0 0 0
4 0 0 0
6 0 0 0
8 0 0 0
1 0 0 0 0
1 2 0 0 0
1 4 0 0 0
1 6 0 0 0
1 8 0 0 0
2 0 0 0 0
0 2 0 0 4 0 0 6 0 0 8 0 0 1 0 0 0 1 2 0 0 1 4 0 0 1 6 0 0 1 8 0 0 2 0 0 0
Time
1 E -0 4
0 .0 0 1
0 .0 1
0 .1
1
1 1 0 1 0 0 1 0 0 0 1 0 0 0 0
Cascade Length
Fre
qu
ency
Liquidity
System mechanics
Bank i Bank j
Payment system
1 Agent instructs bank to send a payment
2 Depositor account is debited
Di Dj
5 Payment account is credited
4 Payment account is debited
Productive Agent Productive Agent
6 Depositor account is credited
Qi
3 Payment is settled or queued
Bi > 0 Qj
7 Queued payment, if any, is released
Qj > 0
Bi Bj
Central bank
Beyeler, Glass, Bech and Soramäki (2007), Physica A, 384-2, pp 693-718.
LiquidityMarket
• Example: How much liquidity to post?
• Cost for a bank in a payment system depends on – Choice of liquidity and – Delays of settlement
• Banks liquidity choice depends on other banks’ liquidity choice
• We develop ABM – payoffs determined by a
realistic settlement process – reinforcement learning– look at equilibrium
Galbiati and Soramäki (2011), JEDC, Vol. 35, Iss. 6, pp 859-875
Economic behavior
Liquidity demand curve
How to operationalize all this?
Data tsunami
• Digital information is doubling every 1.2 years. Open data, data science, …
• 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 policy”, i.e. the application of computer technology, operational research,and statistics to solve regulatory problems
Katsushika Hokusai. The great wave off Kanagawa ~1830
Network maps
• Recent financial crisis brought to light the need to look at links between financial institutions
• Natural way to visualize the financial system• ‘Network thinking’ widespread by regulators• Mapping of the financial system
has only begun
Eratosthenes' map of the known world, c.194 BC.
Intelligence
• Financial crisis are different and rare
• Technology, products and practices change
• Data is not clean, actions are not ‘rational’
• Hard to develop algorithms
• A solution is to augment human intelligence (in contrast to AI and algorithms)
Financial Network Analytics Platform
18
Explain screen
Screen elementsAccess via browser in intranet, internet
or desktop
Operation based on commands
Result panel shows command output
Submit commandEach command has
different parameters
And creates files (charts, data, etc)
Files and database connections are in
file panels
‘Visualize’ screen shows created
charts and layouts
Switch between ‘point-and-click’ and command line view
19
Tabs allow multiple visualisations open
All visualisations are html documents that
work also outside FNA
20
Dashboard (concept)The dashboard can combine multiple views to the data on a single screen
It can be available e.g. on the
intranet and updated daily
21
All commands can be submitted using command syntax
Command line
All commands submitted (also from point-and-click) are
shown in history
History provides an easy way to make
new scripts for research or for the
dashboard
22
Command line
Scripts can be run from the scripts panel or as regular jobs by
the server
Objectives
• Provide a tool for exploration, analysis and visualization of regulatory financial data
• Make online financial available for easy analysis
• Provide a extendible platform for custom functionality, agent based models and other simulation models
• Make advances in research available to policy
• 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
Technical details
