Loss Distribution Approach for Operational Risk Capital Modelling Under Basel II: Combining Diierent Data Sources for Risk Estimation

2013 ◽  
Author(s):  
Pavel V. Shevchenko ◽  
Gareth William Peters
Keyword(s):  
Risk Estimation ◽  
Operational Risk ◽  
Basel Ii ◽  
Data Sources ◽  
Risk Capital ◽  
Loss Distribution ◽  
Loss Distribution Approach

scholarly journals Loss distribution approach for operational risk capital modelling under Basel II: Combining different data sources for risk estimation

2013 ◽  
Vol 2 (3) ◽  
pp. 33-57 ◽  
Author(s):  
Pavel Shevchenko ◽  
Gareth Peters
Keyword(s):  
Operational Risk ◽  
Capital Requirements ◽  
Basel Ii ◽  
Data Sources ◽  
Risk Category ◽  
Risk Environment ◽  
Risk Capital ◽  
Regulatory Requirement ◽  
Loss Distribution ◽  
Loss Distribution Approach

The management of operational risk in the banking industry has undergone significant changes over the last decade due to substantial changes in operational risk environment. Globalization, deregulation, the use of complex financial products and changes in information technology have resulted in exposure to new risks very different from market and credit risks. In response, Basel Committee for banking Supervision has developed a regulatory framework, referred to as Basel II, that introduced operational risk category and corresponding capital requirements. Over the past five years, major banks in most parts of the world have received accreditation under the Basel II Advanced Measurement Approach (AMA) by adopting the loss distribution approach (LDA) despite there being a number of unresolved methodological challenges in its implementation. Different approaches and methods are still under hot debate. In this paper, we review methods proposed in the literature for combining different data sources (internal data, external data and scenario analysis) which is one of the regulatory requirement for AMA.

scholarly journals A Nonparametric Operational Risk Modeling Approach Based on Cornish-Fisher Expansion

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Xiaoqian Zhu ◽  
Jianping Li ◽  
Jianming Chen ◽  
Yingqi YangHuo ◽  
Lijun Gao ◽  
...  
Keyword(s):  
Operational Risk ◽  
Risk Modeling ◽  
Parametric Approach ◽  
Risk Capital ◽  
Loss Distribution ◽  
Modeling Approach ◽  
Loss Distribution Approach ◽  
Operational Risk Modeling ◽  
Chinese Banking ◽  
Distribution Assumption

It is generally accepted that the choice of severity distribution in loss distribution approach has a significant effect on the operational risk capital estimation. However, the usually used parametric approaches with predefined distribution assumption might be not able to fit the severity distribution accurately. The objective of this paper is to propose a nonparametric operational risk modeling approach based on Cornish-Fisher expansion. In this approach, the samples of severity are generated by Cornish-Fisher expansion and then used in the Monte Carlo simulation to sketch the annual operational loss distribution. In the experiment, the proposed approach is employed to calculate the operational risk capital charge for the overall Chinese banking. The experiment dataset is the most comprehensive operational risk dataset in China as far as we know. The results show that the proposed approach is able to use the information of high order moments and might be more effective and stable than the usually used parametric approach.

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.

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