1.1 Introduction
Operational Risk Management (ORM) is playing a new role in the field of Risk Management, as it has undergone a radical change. Indeed, the only regulatory definition of operational risk has experienced a major evolution. In fact, in the Basel Committeeās early work (BCBS 1998) 1 it had a ānegativeā meaning, as operational risk was everything that did not fall within the better known and classified categories of credit risk and market risk. Subsequently, the BCBS developed a āpositiveā notion (BCBS 2001a) 2 defining operational risk as āthe risk of direct or indirect loss resulting from inadequate internal processes, human errors, system failures or related causes. Strategic and reputational risk is not included in this definition for the purpose of a minimum regulatory operational risk capital charge. This definition focuses on the causes of operational risk and the Committee believes that this is appropriate for both risk management and, ultimately, measurementā. 3
The concept of operational risk has been at the centre of increasing debate also in the ORM literature over the years (see for example, Klugman, S. A. et al. (1998) 4 ; King J. L. (2001)5; Cruz M. G. (2002)6; Cruz M. (2003a, b) 7 ; Chapelle et al. (2004) 8 ; Giudici P. (2004) 9 ; Giudici P., Stinco G. (2004) 10 ; Moscadelli M. (2005, 2005b) 11 ; Cosma S. (2006, 2014) 12 ; Moosa (2007a, 13 2007b, 2007c); Birindelli G., Ferretti P. (2009, 2017) 14 ; Girling P. X. (2013) 15 ; Cruz et al. (2015) 16 ; Franzetti C. (2016) 17 ; Robertson D. (2016)). 18
In the current market, Authorities have emphasized the importance to find an āinternalā definition of operational risk, integrated in the bankās specific business and typical operational losses of its production process. Moreover, Authorities and the Basel Committeeās Task Force have expanded the set of information on AMA methodologies (qualitative and quantitative requirements) regarding procedures for estimating distributions (frequency and severity). However, the efficiency of the measures on operational losses is directly related to loss data collection and, therefore, to the quality of the data available. In this perspective, one of the most critical aspects of Operational Risk Management is the measurement or quantitative assessment of operational risk. As known, the Loss Distribution Approach (LDA) is the most popular method for calculating capital charges starting from a quantitative source (integration of internal/external losses and scenario data). The methodology to analyse a quantitative source is very complex but well defined, and there is much literature available on the various quantitative aspects, different methodologies (see Chap. 2) to integrate qualitative and quantitative data and internal and external data. In this perspective, this work wants to emphasize the importance to adopt and integrated risk approach in measurement, management, monitoring and reporting operational risk. In this perspective, the implementation of said methodologies was extended to institutions that operate in financial intermediation where this typology of risk assumes particular relevance.
To manage operational risk, financial intermediariesāand, in particular, those for which the issue of operational losses is quite complex or has a specific weight on overall riskinessāmust develop detailed strategies in their business plans. In order to formulate said strategies, though, it is first of all necessary to be provided with and be knowledgeable of a series of informative elements which enable to carry out comparative analyses of the different types of criticalities. This is a necessary condition for defining priority areas of possible interventions. In other words, the āintegrated assessmentā of operational losses constitutes a fundamental step in order to identify criticalities, to estimate operational risk events more precisely, as well as their causes and consequences, and thus for banksā Risk Management to plan preventive and protective actions.
In this perspective, the objectives of this study are as follows:
- To analyse the evolution of the regulatory framework on ORM and its impacts on the banking system (measurement, management, monitoring and reporting) and on the new Supervisory Review Process (SREP). In the new SREP, measurement is a relevant topic but not the main one. It is a topic also presented for comparison the regulatory framework on operational capital requirement and to further emphasize the importance of the operational process and not only the measurement process (see Chap. 2);
- To explore the measurement framework that attempts to integrate qualitative and quantitative data or different measurement approaches in relation to the regulatory measurement approach (see Chap. 3);
- To explain the methodological framework, assumptions, statistical tools, main results of an operational risk model projected by intermediaries whose business model produces a large amount of operational losses (see Chap. 4);
- To make comparative analysis between the new regulatory Standard Measurement Approach (SMA model) and an Advanced Measurement Approach (AMA); (b) a risk factor sensitivity analysis of the two approaches with the purpose to finally underline the importance to give a regulatory relevance to measurementās tools directly connected to operational risk level. All that (as we underline in the Chap. 5) try to demonstrate that without a capital requirement calculated with a risk sensitive tool, banking system could lose the boost to invest in the management of operational risk issues.
As known, Supervisory Authorities allow financial intermediaries to calculate their capital requirement through internal approaches (AMA). From a structural viewpoint, the AMA, as established by the BCBS (2001), is divided into three different approaches: the Internal Measurement Approach (IMA); the Loss Distribution Approach; the Scorecard Approach. This paperās case study is based on the Loss Distribution Approach, as said approach better identifies the actual risk incurred by a bank. In fact, the Value at Risk (as we underline in the second and third chapter) is calculated on the basis of a cumulated distribution of operational losses estimated for each business line and for each loss event. This measurement methodology attempts to include the existing relationship between risk events and the external economic context. In this perspective, it represents a novelty (still in experimental phase) compared to what described in the literature which fully considers an integrated measurement logic, as this paper will further highlight. At the same time, the methodology presented throughout this paper was developed by a financial intermediary whose business model, as underlined before, is characterized by the absence of credit intermediation and by a relevant weight of operational losses over the total losses.
1.2 Operational Risk: Transversal, Pure, Multidimensional
The definition of Operational Risk has evolved over the years in parallel with the changes occurred in the market and in the regulatory framework. Across the years, academics, researchers and Supervisory Authorities have attempted to provide a specific definition of the mentioned risk, reaching various conclusions, as specified in the following Table 1.1.
Table 1.1
Several definitions of operational risk.
Source Authorsā elaboration on Moosa (2007d)
Year | Author | Definition |
|---|---|---|
1993 | The Group of Thirty | āUncertainty related to losses resulting from... |