Autori: Daniela Coluccia, Stefano Fontana, Elvira Anna Graziano, Matteo Rossi, Silvia Solimene

Tipologia: contributo in volume

Titolo volume: Corporate Ownership and Control

Volume/Numero/Pagine: 15, n.1, pp. 33-43

Editore: Virtus Interpress

ISSN – 1727-9232 (printed version)

ISSN – 1810-0368 (CD version)

ISSN – 1810-3057 (online version)

DOI: 10.22495/cocv15i1art3


The recent financial crisis highlights the weaknesses of the traditional measures of risk in the banking sector, as Banking Authorities have missed considering the behavioural aspect of the risk culture, which is an essential tool for the value creation process of risk management (Financial Stability Board, 2014; Carretta et al., 2015; Schwizer, 2013; Guiso, Sapienza and Zingales, 2015), usually measured using the survey method. Our paper addresses a central question: What is an alternative measure of risk that estimates the banking risk-taking behaviour, also considering their risk culture? By analysing a panel of the thirty Global Systematically Important Banks (G-SIBs) from 2006 and 2013, our paper provides empirical evidence that the presence of a Risk Committee, the size of the Risk Committee and the number of the Risk Committee’s meetings have a positive impact on a bank’s volatility. Using multiple regression analysis on panel data, we verify the relationship between the bank asset risk and explicative variables that measure risk governance, banks’ size and traditional banks’ risk indicators. Our study extends the literature by providing evidence that separates RCs as having a significant impact on reducing firms’ volatility and as being an important risk governance tool in the hands of boards. Moreover, given the recent emphasis of regulatory bodies on strengthening the risk management and risk reporting systems of financial firms and the overwhelming trend of firms to form a separate RC, our study responds to the opportunity to investigate this relationship.

Keywords: Risk Culture, Risk Measure, Risk Committee, Risk Management, Multiple Regression Analysis


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