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Scaling Models for the Severity and Frequency of External Operational Loss Data

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  • Hela Dahen
  • Georges Dionne

Abstract

According to Basel II criteria, the use of external data is absolutely indispensable to the implementation of an advanced method for calculating operational capital. This article investigates how the severity and frequencies of external losses are scaled for integration with internal data. We set up an initial model designed to explain the loss severity. This model takes into account firm size, location, and business lines as well as risk types. It also shows how to calculate the internal loss equivalent to an external loss, which might occur in a given bank. OLS estimation results show that the above variables have significant power in explaining the loss amount. They are used to develop a normalization formula. A second model based on external data is developed to scale the frequency of losses over a given period. Two regression models are analyzed: the truncated Poisson model and the truncated negative binomial model. Variables estimating the size and geographical distribution of the banks' activities have been introduced as explanatory variables. The results show that the negative binomial distribution outperforms the Poisson distribution. The scaling is done by calculating the parameters of the selected distribution based on the estimated coefficients and the variables related to a given bank. Frequency of losses of more than $1 million are generated on a specific horizon.

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Bibliographic Info

Paper provided by CIRPEE in its series Cahiers de recherche with number 0702.

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Date of creation: 2007
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Handle: RePEc:lvl:lacicr:0702

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Keywords: Operational risk in banks; scaling; severity distribution; frequency distribution; truncated count data regression models;

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Cited by:
  1. Gilbert Colletaz & Christophe Hurlin & Christophe Pérignon, 2012. "The Risk Map: A New Tool for Validating Risk Models," Working Papers halshs-00746273, HAL.
  2. Cope, Eric W. & Piche, Mark T. & Walter, John S., 2012. "Macroenvironmental determinants of operational loss severity," Journal of Banking & Finance, Elsevier, vol. 36(5), pages 1362-1380.
  3. Rangga Handika & Chi Truong & Stefan Trueck & Rafal Weron, 2014. "Modelling price spikes in electricity markets - the impact of load, weather and capacity," HSC Research Reports HSC/14/08, Hugo Steinhaus Center, Wroclaw University of Technology.
  4. Jose Manuel Feria-Dominguez & Enrique Jimenez-Rodriguez & Pilar Camacho-Rubio, 2014. "People Value at Risk: A Key Indicator for Sound Management," Working Papers 14.03, Universidad Pablo de Olavide, Department of Financial Economics and Accounting (former Department of Business Administration).
  5. Fiordelisi, Franco & Soana, Maria-Gaia & Schwizer, Paola, 2013. "The determinants of reputational risk in the banking sector," Journal of Banking & Finance, Elsevier, vol. 37(5), pages 1359-1371.

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