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Assessing Systemic Importance With a Fuzzy Logic Inference System

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  • Carlos León
  • Clara Machado
  • Andrés Murcia

Abstract

Three metrics are designed to assess Colombian financial institutions' size, connectedness and non‐substitutability as the main drivers of systemic importance: (i) centrality as net borrower in the money market network; (ii) centrality as payments originator in the large‐value payment system network; and (iii) asset value of core financial services. An aggregated systemic importance index is calculated based on expert knowledge by using a fuzzy logic inference system. We use principal component analysis to calculate a benchmark index for comparison purposes. Overall similarities between both indexes put forward that expert knowledge aggregation is consistent with that based on a purely quantitative standard approach. Specific non‐negligible differences concur with the nonlinear features of an approach whose intention is to replicate human reasoning. Both indexes are complementary and provide a comprehensive relative assessment of each financial institution's systemic importance in the Colombian case, in which the choice of metrics pursues the macroprudential perspective of financial stability. Copyright © 2015 John Wiley & Sons, Ltd.

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  • 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.
    • Handle: RePEc:wly:isacfm:v:23:y:2016:i:1-2:p:121-153
    DOI: 10.1002/isaf.1371
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