[en] This paper analyzes the implications of the Advanced Measurement Approach (AMA) for the assessment of operational risk. Through a clinical case study on a matrix of two selected business lines and two event types of a large financial institution, we develop a procedure that addresses the major issues faced by banks in the implementation of the AMA. For each cell, we calibrate two truncated distributions functions, one for “normal” losses and the other for the “extreme” losses. In addition, we propose a method to include external data in the framework. We then estimate the impact of operational risk management on bank profitability, through an adapted measure of RAROC. The results suggest that substantial savings can be achieved through active management techniques.
Disciplines :
Finance
Author, co-author :
Chapelle, Ariane
Crama, Yves ; Université de Liège - ULiège > HEC - École de gestion de l'ULiège > Recherche opérationnelle et gestion de la production - HEC-Ecole de gestion - HEC - Ecole de gestion de l'ULG : Direction générale
Hübner, Georges ; Université de Liège - ULiège > HEC - École de gestion de l'ULiège > Gestion financière
Peters, Jean-Philippe
Language :
English
Title :
Practical methods for measuring and managing operational risk in the financial sector: A clinical study
Alexander C. Operational Risk: Regulation, Analysis and Management (2003), FT Prentice Hall, London
Allen, L., Bali, T.G., 2005. Cyclicality in catastrophic and operational risk measurements. Working paper.
Balkema A.A., and de Haan L. Residual life time at great age. Annals of Probability 2 (1974) 792-804
Basel Committee on Banking Supervision. 2004. Basel II: International convergence of capital measurement and capital standards - A revised framework. Basel Committee Publications No. 107. The Bank for International Settlements, Basel.
Baud, N., Frachot, A., Roncalli, T., 2002. Internal data, external data and consortium data for operational risk measurement: How to pool data properly. Working paper. Groupe de Recherche Opérationnelle, Crédit Lyonnais.
Chavez-Demoulin V., Embrechts P., and Neslehova J. Quantitative models for operational risk: Extremes, dependence and aggregation. Journal of Banking and Finance 30 (2006) 2635-2658
Cherubini U., Luciano E., and Vecchiato W. Copula Methods in Finance (2004), Wiley & Sons, New York
Clayton D.G. A model for association in bivariate life tables and its application in epidemiological studies of familial tendency in chronic disease incidence. Biometrika 65 (1978) 141-151
Cruz M.G. Modeling, Measuring and Hedging Operational Risk (2002), Wiley & Sons, New York
In: Cruz M.G. (Ed). Operational Risk Modelling and Analysis: Theory and Practice (2004), Risk Waters Group, London
de Fontnouvelle, P., Jordan, J., Rosengren, E., 2003. Using loss data to quantify operational risk. Working paper. Federal Reserve Bank of Boston.
de Fontnouvelle, P., Rosengren, E., Jordan, J., 2004. Implications of alternative operational risk modeling techniques. Working paper. Federal Reserve Bank of Boston.
Di Clemente A., and Romano C. A copula - Extreme value theory approach for modelling operational risk. In: Cruz M. (Ed). Operational Risk Modelling and Analysis: Theory and Practice (2004), Risk Waters
Drees H., and Kaufmann E. Selecting the optimal sample fraction in univariate extreme value estimation. Stochastic Processes and their Applications 75 (1998) 149-172
Dupuis D.J. Exceedances over high thresholds: A guide to threshold selection. Extremes 1 (1999) 251-261
Embrechts, P., Furrer, H., Kaufmann, R., 2003. Quantifying regulatory capital for operational risk. Working paper, RiskLab, ETH Zürich.
Embrechts P., Klüppelberg C., and Mikosch T. Modelling Extremal Events for Insurance and Finance (1997), Springer-Verlag, Berlin
Embrechts P., McNeil A., and Strautmann D. Correlation and dependence in risk management: Properties and pitfalls. In: Dempster M.A.H. (Ed). Risk Management: Value at Risk and Beyond (2002), Cambridge University Press, Cambridge
Frachot, A., Roncalli, T., 2002. Mixing internal and external data for managing operational risk. Working paper. Groupe de Recherche Opérationnelle, Crédit Lyonnais.
Frachot, A., Georges, P., Roncalli, T., 2001. Loss distribution approach for operational risk. Working paper. Groupe de Recherche Opérationnelle, Crédit Lyonnais.
Frachot, A., Moudoulaud, O., Roncalli, T., 2003. Loss distribution approach in practice. Working paper. Groupe de Recherche Opérationnelle, Crédit Lyonnais.
Frachot, A., Roncalli, T., Salomon, E., 2004. The correlation problem in operational risk. Working paper. Groupe de Recherche Opérationnelle, Crédit Lyonnais.
Frank M.J. On the simultaneous associativity of F(x, y) and x + y - F(x, y). Aequationes Mathematicae 19 (1979) 194-226
Genest C., and McKay J. The joy of copulas: Bivariate distributions with uniform variables. The American Statistician 40 (1986) 280-283
Gumbel E.J. Distributions des valeurs extrêmes en plusieurs dimensions. Publications de Institut de Statistique de l'Université de Paris 9 (1960) 171-173
Hartung, T., 2003. Considerations to the quantification of operational risks. Working paper. University of Munich.
Huisman R., Koedijk K.G., Kool C.J., and Palm F. Tail-index estimates in small samples. Journal of Business & Economic Statistics 19 (2001) 208-216
Hürlimann W. Fitting bivariate cumulative returns with copulas. Computational Statistics and Data Analysis 45 (2004) 355-372
Hürlimann W. Multivariate Fréchet copulas and conditional value-at-risk. International Journal of Mathematics and Mathematical Sciences 7 (2004) 345-364
Joe H. Multivariate Models and Dependence Concepts (1997), Chapman & Hall, London
King J.L. Operational Risk, Measurement and Modelling (2001), Wiley & Sons, New York
Longin F., and Solnik B. Extreme correlation of international equity markets. Journal of Finance 56 (2001) 649-676
Matthys G., and Beirlant J. Estimating the extreme value index and high quantiles with exponential regression models. Statistica Sinica 13 (2003) 853-880
McNeil A.J. Extreme value theory for risk managers. In: Embrechts P. (Ed). Extremes and Integrated Risk Management (2000), Risk Books, London
Moscadelli, M., 2004. The modelling of operational risk: Experience with the analysis of the data collected by the Basel Committee, Banca d'Italia. Working Paper 517.
Nelsen R.B. An Introduction to Copulas (1999), Springer, New York
Pickands J. Statistical inference using extreme order statistics. Annals of Statistics 3 (1975) 119-131
Shih J., Samad-Khan A.H., and Medapa P. Is the size of an operational risk related to firm size?. Operational Risk January (2000)
Theil H. Applied Economic Forecasting (1971), North Holland, Amsterdam
