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Algorithm for identifying systemically important banks in payment systems

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  • Soramäki, Kimmo
  • Cook, Samantha

Abstract

The ability to accurately estimate the extent to which the failure of a bank disrupts the financial system is very valuable for regulators of the financial system. One important part of the financial system is the interbank payment system. This paper develops a robust measure, SinkRank, that accurately predicts the magnitude of disruption caused by the failure of a bank in a payment system and identifies banks most affected by the failure. SinkRank is based on absorbing Markov chains, which are well-suited to model liquidity dynamics in payment systems. Because actual bank failures are rare and the data is not generally publicly available, the authors test the metric by simulating payment networks and inducing failures in them. The authors use two metrics to evaluate the magnitude of the disruption: the duration of delays in the system (Congestion) aggregated over all banks and the average reduction in available funds of the other banks due to the failing bank (Liquidity dislocation). The authors test SinkRank on Barabasi-Albert types of scale-free networks modeled on the Fedwire system and find that the failing bank's SinkRank is highly correlated with the resulting disruption in the system overall; moreover, the SinkRank technology can identify which individual banks would be most disrupted by a given failure. --

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Bibliographic Info

Paper provided by Kiel Institute for the World Economy in its series Economics Discussion Papers with number 2012-43.

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Date of creation: 2012
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Handle: RePEc:zbw:ifwedp:201243

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Keywords: Systemic risk; interbank payment system; liquidity; Markov chains; simulation;

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References

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  1. Soramäki, Kimmo & Bech, Morten L. & Arnold, Jeffrey & Glass, Robert J. & Beyeler, Walter E., 2007. "The topology of interbank payment flows," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 379(1), pages 317-333.
  2. Morten L. Bech & Christine Preisig & Kimmo Soramäki, 2008. "Global trends in large-value payments," Economic Policy Review, Federal Reserve Bank of New York, issue Sep, pages 59-81.
  3. Galbiati, Marco & Soramäki, Kimmo, 2011. "An agent-based model of payment systems," Journal of Economic Dynamics and Control, Elsevier, vol. 35(6), pages 859-875, June.
  4. Schulz, Christian, 2011. "Liquidity requirements and payment delays - participant type dependent preferences," Working Paper Series 1291, European Central Bank.
  5. Galos, Peter & Soramäki, Kimmo, 2005. "Systemic risk in alternative payment system designs," Working Paper Series 0508, European Central Bank.
  6. Docherty, Peter & Wang, Gehong, 2010. "Using synthetic data to evaluate the impact of RTGS on systemic risk in the Australian payments system," Journal of Financial Stability, Elsevier, vol. 6(2), pages 103-117, June.
  7. Walter E. Beyeler & Robert J. Glass & Morten L. Bech & Kimmo Soramaki, 2006. "Congestion and cascades in payment systems," Staff Reports 259, Federal Reserve Bank of New York.
  8. Angelini, P. & Maresca, G. & Russo, D., 1996. "Systemic risk in the netting system," Journal of Banking & Finance, Elsevier, vol. 20(5), pages 853-868, June.
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