scholarly journals A Tale of Tails: An Empirical Analysis of Loss Distribution Models for Estimating Operational Risk Capital

2006 ◽  
Author(s):  
Kabir Dutta ◽  
Jason Perry
Keyword(s):  
Empirical Analysis ◽  
Operational Risk ◽  
Risk Capital ◽  
Distribution Models ◽  
Loss Distribution

scholarly journals ANALISA PENGUKURAN BEBAN MODAL RISIKO OPERASIONAL METODE BASIC INDICATOR APPROACH (BIA) DAN ADVANCE MEASUREMENT APPROACH (AMA) DI BANK EFG

2020 ◽  
Vol 21 (1) ◽  
pp. 14-20
Author(s):  
Edian Fahmy
Keyword(s):  
Value At Risk ◽  
Goodness Of Fit ◽  
Geometric Distribution ◽  
Operational Risk ◽  
Risk Capital ◽  
Loss Distribution ◽  
Indicator Approach ◽  
External Events ◽  
Measurement Approach

This study aims to compare the magnitude of operational risk losses between the Basic Indicator Approach (BIA) method, and the loss distribution model in the Advanced Measurement Approach (AMA) approach so as to provide a more realistic picture for banks to determine the operational risk capital burden that must be provided based on the causes Operational risks are as follows Internal Process, Human and External Events. Measurement of operational risk capital burden by the AMA method is the determination of frequency of loss distribution, determination of severity of loss distribution, testing with goodness of fit test, then compilation of aggregated loss distribution, calculation of Operational Value at Risk (OpVar), testing the model with back testing and comparison of capital adequacy from the results of the calculation of the Basic Indicator Approach (BIA) and the Advance Measurement Approach (AMA). The results of research based on the BIA require an operational risk capital cost of Rp.291,652,000,000. The results of the research on the AMA approach use the frequency of loss distribution parameter for the internal causes of the process with a Geometric distribution of 0.17561, while for the human cause of 0.08511, for the cause of external events amounting to 0.83721. Determination of Frequency of Loss Distribution using Goodness of Fit for internal processes, people and external events. The results of the Operational Value at Risk (OpVar) with a geometric distribution pattern, then the maximum loss that can arise due to human factors is Rp.24,114,480,096, -, for internal process factors of Rp.6,010,929,367, whereas for external causes for Rp. 2,161,092,909. In total operational risk capital needs through the AMA method of Rp. 32,286,502,372.

scholarly journals Operational Risk Aggregation across Business Lines Based on Frequency Dependence and Loss Dependence

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Jianping Li ◽  
Xiaoqian Zhu ◽  
Jianming Chen ◽  
Lijun Gao ◽  
Jichuang Feng ◽  
...  
Keyword(s):  
Frequency Dependence ◽  
Operational Risk ◽  
Copula Function ◽  
Limited Attention ◽  
Risk Modeling ◽  
Risk Capital ◽  
Loss Distribution ◽  
Risk Aggregation ◽  
The Impact ◽  
Chinese Banking

In loss distribution approach (LDA), the most popular approach in operational risk modeling, frequency dependence and loss distribution dependence across business lines are two dependences which banks should consider. In practice, mainly for simplicity, many banks only model frequency dependence although they think that the impact of frequency dependence is insignificant. In this study, two approaches, respectively, models frequency dependence and loss distribution dependence, are introduced. Both approaches are modeled by copula function, which is capable of capturing nonlinear correlation. Based on the most comprehensive operational risk dataset of Chinese banking as far as we know, the operational risk capital charge of the overall Chinese banking is calculated by the two approaches. The results show that there is an obvious distinction between the capital calculated by modeling frequency dependence and the capital calculated by modeling loss dependence. The approach with very limited attention exactly yields a much larger capital result. So it is advised in this paper that banks should not just rely on the approach to modeling frequency dependence for it is natural and easy to deal with. A safer and more effective way for banks is to comprehensively take the results of the two kinds of approach into consideration.

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.

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