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Too-connected-to-fail Institutions and Payments System´s Stability: Assessing Challenges for Financial Authorities


  • Carlos León
  • Clara Machado
  • Freddy cepeda
  • Miguel Sarmiento


The most recent episode of market turmoil exposed the limitations resulting from the traditional focus on too-big-to-fail institutions within an increasingly systemic-crisis-prone financial system, and encouraged the appearance of the too-connected-to-fail (TCTF) concept. The TCTF concept conveniently broadens the base of potential destabilizing institutions beyond the traditional banking-focused approach to systemic risk, but requires methodologies capable of coping with complex, cross-dependent, context-dependent and non-linear systems. After comprehensively introducing the rise of the TCTF concept, this paper presents a robust, parsimonious and powerful approach to identifying and assessing systemic risk within payments systems, and proposes some analytical routes for assessing financial authorities´ challenges. Banco de la Republica´s approach is based on a convenient mixture of network topology basics for identifying central institutions, and payments systems simulation techniques for quantifying the potential consequences of central institutions failing within Colombian large-value payments systems. Unlike econometrics or network topology alone, results consist of a rich set of quantitative outcomes that capture the complexity, cross-dependency, context-dependency and non-linearity of payments systems, but conveniently disaggregated and dollar-denominated. These outcomes and the proposed analysis provide practical information for enhanced policy and decision-making, where the ability to measure each institution´s contribution to systemic risk may assist financial authorities in their task to achieve payments system´s stability.

Suggested Citation

  • Carlos León & Clara Machado & Freddy cepeda & Miguel Sarmiento, 2011. "Too-connected-to-fail Institutions and Payments System´s Stability: Assessing Challenges for Financial Authorities," Borradores de Economia 8155, Banco de la Republica.
  • Handle: RePEc:col:000094:008155

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    Cited by:

    1. Carlos León & Clara Machado & Andrés Murcia, 2013. "Macro-prudential assessment of Colombian financial institutions’ systemic importance," Borradores de Economia 800, Banco de la Republica de Colombia.
    2. Carlos León & Clara Machado & Andrés Murcia, 2016. "Assessing Systemic Importance With a Fuzzy Logic Inference System," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 23(1-2), pages 121-153, January.
    3. Carlos Castro & Juan Sebastian Ordonez, 2012. "A Network model of systemic risk: identifying the sources of dependence across institutions," Documentos de Trabajo 9651, Universidad del Rosario.
    4. Carlos León, 2012. "Estimating financial institutions’ intraday liquidity risk: a Monte Carlo simulation approach," Borradores de Economia 703, Banco de la Republica de Colombia.
    5. Rincón, Hernán & Velasco, Andrés M. (ed.), 2013. "Flujos de capitales, choques externos y respuestas de política en países emergentes," Books, Banco de la Republica de Colombia, number 2013-09, December.
    6. Lu, Shan & Zhao, Jichang & Wang, Huiwen & Ren, Ruoen, 2018. "Herding boosts too-connected-to-fail risk in stock market of China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 945-964.
    7. Jacob Kleinow & Andreas Horsch & Mario Garcia-Molina, 2017. "Factors driving systemic risk of banks in Latin America," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 41(2), pages 211-234, April.
    8. Clara Machado & Carlos León & Miguel Sarmiento & Freddy Cepeda & Orlando Chipatecua & Jorge Cely, 2011. "Riesgo Sistémico Y Estabilidad Del Sistema De Pagos De Alto Valor En Colombia: Análisis Bajo," Revista ESPE - Ensayos sobre Política Económica, Banco de la Republica de Colombia, vol. 29(65), pages 106-175, June.
    9. Joaquin Bernal & Freddy Cepeda L. & Fabio Ortega C., 2011. "Cuantificación de la contribución de las fuentes de liquidez en el Sistema de Pagos de Alto Valor en Colombia: una aproximación preliminar," Borradores de Economia 683, Banco de la Republica de Colombia.
    10. Carlos León & Ron J. Berndsen, 2013. "Modular scale-free architecture of Colombian financial networks: Evidence and challenges with financial stability in view," Borradores de Economia 11104, Banco de la Republica.
    11. Carlos Léon, 2012. "Estimating financial institutions´ intraday liquidity risk: a Monte Carlo simulation approach," Borradores de Economia 9441, Banco de la Republica.
    12. Constanza Martínez & Freddy Cepeda, 2016. "Free-riding on Liquidity in the Colombian LVPS," Borradores de Economia 977, Banco de la Republica de Colombia.
    13. George Halkos & Shunsuke Managi & Kyriaki Tsilika, 2021. "Ranking Countries and Geographical Regions in the International Green Bond Transfer Network: A Computational Weighted Network Approach," Computational Economics, Springer;Society for Computational Economics, vol. 58(4), pages 1301-1346, December.

    More about this item


    Payments systems; too-connected-to-fail; too-big-to-fail; systemic risk; network topology; simulation; central bank liquidity.;
    All these keywords.

    JEL classification:

    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation

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