Designing an expert knowledge-based Systemic Importance Index for financial institutions
AbstractDefining whether a financial institution is systemically important (or not) is challenging due to (i) the inevitability of combining complex importance criteria such as institutions´ size, connectedness and substitutability; (ii) the ambiguity of what an appropriate threshold for those criteria may be; and (iii) the involvement of expert knowledge as a key input for combining those criteria. The proposed method, a Fuzzy Logic Inference System, uses four key systemic importance indicators that capture institutions´ size, connectedness and substitutability, and a convenient deconstruction of expert knowledge to obtain a Systemic Importance Index. This method allows for combining dissimilar concepts in a non-linear, consistent and intuitive manner, whilst considering them as continuous -non binary- functions. Results reveal that the method imitates the way experts them-selves think about the decision process regarding what a systemically important financial institution is within the financial system under analysis. The Index is a comprehensive relative assessment of each financial institution´s systemic importance. It may serve financial authorities as a quantitative tool for focusing their attention and resources where the severity resulting from an institution failing or near-failing is estimated to be the greatest. It may also serve for enhanced policy-making (e.g. prudential regulation, oversight and supervision) and decision-making (e.g. resolving, restructuring or providing emergency liquidity).
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Bibliographic InfoPaper provided by BANCO DE LA REPÚBLICA in its series BORRADORES DE ECONOMIA with number 008953.
Date of creation: 01 Sep 2011
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Systemic Importance; Systemic Risk; Fuzzy Logic; Approximate Reasoning; Too-connected-to-fail; Too-big-to-fail.;
Other versions of this item:
- Carlos León & Clara Machado, . "Designing an expert knowledge-based Systemic Importance Index for financial institutions," Borradores de Economia 669, Banco de la Republica de Colombia.
- D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
- C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
- E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies
- G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation
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- 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
799, Banco de la Republica de Colombia.
- 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 011104, BANCO DE LA REPÚBLICA.
- Constanza Martínez & Carlos León, 2014.
"The Cost of Collateralized Borrowing in the Colombian Money Market: Does Connectedness Matter?,"
BORRADORES DE ECONOMIA
011123, BANCO DE LA REPÚBLICA.
- Constanza Martínez & Carlos León, 2014. "The Cost of Collateralized Borrowing in the Colombian Money Market: Does Connectedness Matter?," Borradores de Economia 803, Banco de la Republica de Colombia.
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