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The optimal operational risk capital requirement by applying the advanced measurement approach

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  • Tyrone Lin
  • Chia-Chi Lee
  • Yu-Chuan Kuan

Abstract

The purpose of this paper is to construct a risk quantification model to achieve the accurate operational risk management and gain the satisfying estimation and control of future possible extreme losses by using capital charges to assess operational risk. The paper takes a case bank as the research object and compares the differences under various circumstances engaging the Basic Indicator Approach, the Standardized Approach, and the Advanced Measurement Approach for the operational risk capital requirement of a bank. The results indicate that it is more appropriate to adopt the Advanced Measurement Approach to estimate the operational risk capital requirement; this way can help a bank enjoy a much lessened capital charge required and subsequently its available capital increases. Hence, it allows a bank to have sufficient funds in operations and reduce the burden of capital costs. Therefore, it will bring the positive benefits to the whole banking industry when enforcing the Advanced Measurement Approach. Copyright Springer-Verlag 2013

Suggested Citation

  • Tyrone Lin & Chia-Chi Lee & Yu-Chuan Kuan, 2013. "The optimal operational risk capital requirement by applying the advanced measurement approach," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 21(1), pages 85-101, January.
    • Handle: RePEc:spr:cejnor:v:21:y:2013:i:1:p:85-101
    DOI: 10.1007/s10100-011-0206-7
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    1. Andrew Sheen, 2005. "Implementing the EU Capital Requirement Directive – key operational risk elements," Journal of Financial Regulation and Compliance, Emerald Group Publishing, vol. 13(4), pages 313-323, November.
    2. Ines Drumond, 2009. "Bank Capital Requirements, Business Cycle Fluctuations And The Basel Accords: A Synthesis," Journal of Economic Surveys, Wiley Blackwell, vol. 23(5), pages 798-830, December.
    3. Silvia Figini & Paolo Giudici & Pierpaolo Uberti, 2010. "A threshold based approach to merge data in financial risk management," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(11), pages 1815-1824.
    4. Robert Jarrow, 2017. "Operational Risk," World Scientific Book Chapters, in: THE ECONOMIC FOUNDATIONS OF RISK MANAGEMENT Theory, Practice, and Applications, chapter 8, pages 69-70, World Scientific Publishing Co. Pte. Ltd..
    5. McNeil, Alexander J. & Frey, Rudiger, 2000. "Estimation of tail-related risk measures for heteroscedastic financial time series: an extreme value approach," Journal of Empirical Finance, Elsevier, vol. 7(3-4), pages 271-300, November.
    6. Michael Foot, 2002. "Operational risk management for financial institutions," Journal of Financial Regulation and Compliance, Emerald Group Publishing Limited, vol. 10(4), pages 313-316, December.
    7. Gabriela ANGHELACHE & Ana-Cornelia OLTEANU (PUIU) & Alina-Nicoleta RADU, 2010. "Operational Risk Measurement," European Research Studies Journal, European Research Studies Journal, vol. 0(1), pages 215-223.
    8. Chapelle, Ariane & Crama, Yves & Hübner, Georges & Peters, Jean-Philippe, 2008. "Practical methods for measuring and managing operational risk in the financial sector: A clinical study," Journal of Banking & Finance, Elsevier, vol. 32(6), pages 1049-1061, June.
    9. Bertrand Rime, 2005. "Will Basel II Lead to a Specialization of Unsophisticated Banks on High‐Risk Borrowers?," International Finance, Wiley Blackwell, vol. 8(1), pages 29-55, March.
    10. Cummins, J. David & Lewis, Christopher M. & Wei, Ran, 2006. "The market value impact of operational loss events for US banks and insurers," Journal of Banking & Finance, Elsevier, vol. 30(10), pages 2605-2634, October.
    11. K. Kosmidou & F. Pasiouras & M. Doumpos & C. Zopounidis, 2006. "Assessing performance factors in the UK banking sector: A multicriteria methodology," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 14(1), pages 25-44, February.
    12. de Fontnouvelle, Patrick & Dejesus-Rueff, Virginia & Jordan, John S. & Rosengren, Eric S., 2006. "Capital and Risk: New Evidence on Implications of Large Operational Losses," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 38(7), pages 1819-1846, October.
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    Cited by:

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    2. Kamil J. Mizgier & Joseph M. Pasia, 2016. "Multiobjective optimization of credit capital allocation in financial institutions," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 24(4), pages 801-817, December.

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