scholarly journals Implementing loss distribution approach for operational risk

2009 ◽  
Vol 26 (3) ◽  
pp. 277-307 ◽  
Author(s):  
Pavel V. Shevchenko
Keyword(s):  
Operational Risk ◽  
Loss Distribution ◽  
Loss Distribution Approach

Operational risk measurement beyond the loss distribution approach: an exposure-based methodology

2018 ◽  
Vol 13 (2) ◽  
pp. 1-33
Author(s):  
Michael Einemann ◽  
Joerg Fritscher ◽  
Michael Kalkbrener
Keyword(s):  
Operational Risk ◽  
Risk Measurement ◽  
Loss Distribution ◽  
Loss Distribution 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.

scholarly journals Loss Distribution Approach for Operational Risk

2001 ◽  
Author(s):  
Antoine Frachot ◽  
Pierre Georges ◽  
Thierry Roncalli
Keyword(s):  
Operational Risk ◽  
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.

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