A critique of the advanced measurement approach to regulatory capital against operational risk

2008 ◽  
Vol 9 (3) ◽  
pp. 151-164 ◽  
Author(s):  
Imad A Moosa
Keyword(s):  
Operational Risk ◽  
Regulatory Capital ◽  
Measurement Approach

scholarly journals Calculating operational value-at-risk (OpVaR) in a retail bank

2012 ◽  
Vol 11 (1) ◽  
pp. 1-16 ◽  
Author(s):  
Ja'nel Esterhuysen ◽  
Paul Styger ◽  
Gary Wayne Van Vuuren
Keyword(s):  
At Risk ◽  
Financial Institutions ◽  
Value At Risk ◽  
Operational Risk ◽  
Economic Capital ◽  
Clear Distinction ◽  
Regulatory Capital ◽  
Calculation Technique ◽  
Measurement Approach ◽  
The Way

The management of operational value-at-risk (OpVaR) in financial institutions is presented by means of a novel, robust calculation technique and the influence of this value on the capital held by a bank for operational risk. A clear distinction between economic and regulatory capital is made, as well as the way OpVaR models may be used to calculate both types of capital. Under the Advanced Measurement Approach (AMA), banks may employ OpVaR models to calculate regulatory capital; this article therefore illustrates the differences in regulatory capital when using the AMA and the Standardised Approach (SA), by means of an example. Economic capital is found to converge with regulatory capital using the AMA, but not if the SA is used.

A PIECEWISE-DEFINED SEVERITY DISTRIBUTION-BASED LOSS DISTRIBUTION APPROACH TO ESTIMATE OPERATIONAL RISK: EVIDENCE FROM CHINESE NATIONAL COMMERCIAL BANKS

2009 ◽  
Vol 08 (04) ◽  
pp. 727-747 ◽  
Author(s):  
JIANPING LI ◽  
JICHUANG FENG ◽  
JIANMING CHEN
Keyword(s):  
Commercial Banks ◽  
Public Information ◽  
Generalized Pareto Distribution ◽  
Operational Risk ◽  
Regulatory Capital ◽  
Loss Distribution ◽  
Generalized Pareto ◽  
Loss Distribution Approach ◽  
Indicator Approach ◽  
International Banks

Following the Basel II Accord, with the increased focus on operational risk as an aspect distinct from credit and market risk, quantification of operational risk has been a major challenge for banks. This paper analyzes implications of the advanced measurement approach to estimate the operational risk. When modeling the severity of losses in a realistic manner, our preliminary tests indicate that classic distributions are unable to fit the entire range of operational risk data samples (collected from public information sources) well. Then, we propose a piecewise-defined severity distribution (PSD) that combines a parameter form for ordinary losses and a generalized Pareto distribution (GPD) for large losses, and estimate operational risk by the loss distribution approach (LDA) with Monte Carlo simulation. We compare the operational risk measured with piecewise-defined severity distribution based LDA (PSD-LDA) with those obtained from the basic indicator approach (BIA), and the ratios of operational risk regulatory capital of some major international banks with those of Chinese commercial banks. The empirical results reveal the rationality and promise of application of the PSD-LDA for Chinese national commercial banks.

scholarly journals A Framework for Analysis and Prediction of Operational Risk Stress

2021 ◽  
Vol 26 (1) ◽  
pp. 19
Author(s):  
Peter Mitic
Keyword(s):  
Risk Factors ◽  
Financial Risk ◽  
Time Window ◽  
Operational Risk ◽  
Specific Reference ◽  
Mild Stress ◽  
Regulatory Capital ◽  
Regulatory Requirements ◽  
Extreme Stress ◽  
Loss Data

A model for financial stress testing and stability analysis is presented. Given operational risk loss data within a time window, short-term projections are made using Loess fits to sequences of lognormal parameters. The projections can be scaled by a sequence of risk factors, derived from economic data in response to international regulatory requirements. Historic and projected loss data are combined using a lengthy nonlinear algorithm to calculate a capital reserve for the upcoming year. The model is embedded in a general framework, in which arrays of risk factors can be swapped in and out to assess their effect on the projected losses. Risk factor scaling is varied to assess the resilience and stability of financial institutions to economic shock. Symbolic analysis of projected losses shows that they are well-conditioned with respect to risk factors. Specific reference is made to the effect of the 2020 COVID-19 pandemic. For a 1-year projection, the framework indicates a requirement for an increase in regulatory capital of approximately 3% for mild stress, 8% for moderate stress, and 32% for extreme stress. The proposed framework is significant because it is the first formal methodology to link financial risk with economic factors in an objective way without recourse to correlations.

scholarly journals Should the advanced measurement approach be replaced with the standardized measurement approach for operational risk?

2016 ◽  
Vol 11 (3) ◽  
pp. 1-49 ◽  
Author(s):  
Gareth Peters ◽  
Pavel Shevchenko ◽  
Bertrand Hassani ◽  
Ariane Chapelle
Keyword(s):  
Operational Risk ◽  
Standardized Measurement ◽  
Measurement Approach
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