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Data Scaling for Operational Risk Modelling

Author

Listed:
  • Na, H.S.
  • Couto Miranda, L.
  • van den Berg, J.H.
  • Leipoldt, M.

Abstract

In 2004, the Basel Committee on Banking Supervision defined Operational Risk (OR) as the risk of loss resulting from inadequate or failed internal processes, people and systems or from external events. After publication of the new capital accord containing this dfinition, statistical properties of OR losses have attracted considerable attention in the financial industry since financial institutions have to quantify their exposures towards OR events. One of the major topics related to loss data is the non-availability of a suficient amount of data within the Financial Institutions. This paper describes a way to circumvent the problem of data availability by proposing a scaling mechanism that enables an organization to put together data originating from several business units, each one having its specific characteristics like size and exposure towards operational risk. The same scaling mechanism can also be used to enable an institution to include external data originating from other institutions into their own exposure calculations. Using both internal data from different business units and publicly available data from other (anonymous) institutions, we show that there is a strong relationship between losses incurred in one business unit respectively institution, and a specific size driver, in this case gross revenue. We study an appropriate scaling power law as a mechanism that explains this relationship. Having properly scaled the data from different business units, we also show how the resulting aggregated data set can be used to calculate the Value-at-OR for each business unit and present the principles of calculating the value of the OR capital charge according the minimal capital requirements of the Basel committee.

Suggested Citation

  • Na, H.S. & Couto Miranda, L. & van den Berg, J.H. & Leipoldt, M., 2006. "Data Scaling for Operational Risk Modelling," ERIM Report Series Research in Management ERS-2005-092-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    • Handle: RePEc:ems:eureri:7234
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    References listed on IDEAS

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    1. J-P. Bouchaud, 2001. "Power laws in economics and finance: some ideas from physics," Quantitative Finance, Taylor & Francis Journals, vol. 1(1), pages 105-112.
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    Cited by:

    1. Norbert Kozma, 2020. "Principles of Proportionality in Credit Institutions’ Operational Risk Management," Financial and Economic Review, Magyar Nemzeti Bank (Central Bank of Hungary), vol. 19(3), pages 78-101.
    2. Dániel Homolya, 2016. "Risk Management Approaches and Bank Size," Financial and Economic Review, Magyar Nemzeti Bank (Central Bank of Hungary), vol. 15(2), pages 114-128.
    3. Muhammad Yasran Rasheed & Asif Saeed & Ammar Ali Gull, 2018. "The Role of Operational Risk Management in Performance of Banking Sector: A Study on Conventional & Islamic Banks of Pakistan," Pakistan Journal of Humanities and Social Sciences, International Research Alliance for Sustainable Development (iRASD), vol. 6(1), pages :1-16, March.

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    More about this item

    Keywords

    Loss Distribution; Minimal Capital Requirements; Operational Risk; Power Law Scaling; Value at Operational Risk;
    All these keywords.

    JEL classification:

    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • L15 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Information and Product Quality
    • M - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D

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