The presentation looks at the importance topology of interactions in payment system and the behavior of banks in the system

1. New approaches for payment system simulation research Kimmo Soramäki www.soramaki.net www.financialnetworkanalysis.com TKK, Helsinki, 3.9.2007

5. Fedwire liquidity flows Fedwire liquidity flows share many of the characteristics commonly found in other empirical complex networks - scale-free (power law) degree distribution - high clustering coefficient - small world phenomenon - short paths (avg 2.6) in spite of low connectivity (0.3%) - structure of networks persistent from day to day - heavily impacted by the terrorist attacks of 9/11, disruption lasted for ~10 days 6600 banks, 70,000 links 66 banks comprise 75% of value 25 banks completely connected

7. Payment System 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 Influence of liquidity 1

8. 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 Payment System Instructions Payments Liquidity Influence of liquidity 2

9. Payment System Instructions Payments At very low liquidity payments are controlled by internal dynamics. Settlement cascades are larger and can pass through the same bank numerous times Liquidity Influence of liquidity 3

10. Payment System Instructions Payments A liquidity market substantially reduces congestion using only a small fraction (e.g. 2%) of payment-driven flow Liquidity Market Influence of a liquidity market

16. example: Fedwire around 9/11 2001 Topology and disruption 1