Designing an Expert Knowledge-Based Systemic Importance Index for Financial Institutions
Borradores de Economia, No. 669, 2011
41 Pages Posted: 7 Jul 2012
Date Written: September 1, 2011
Defining 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).
Keywords: systemic importance, systemic risk, fuzzy logic, approximate reasoning, too-connected-to-fail, too-big-to-fail
JEL Classification: D85, C63, E58, G28
Suggested Citation: Suggested Citation