8. Bayesian Merging and Calibration for Operational Risks

  1. Ron S. Kenett PhD, BSc Chairman CEO Research Professor Professor Associate Director Editor in Chief President2,3 and
  2. Yossi Raanan PhD, BSc Senior Consultant Strategic Partner Senior Lecturer former dean head chairman director4,5
  1. Silvia Figini PhD member

Published Online: 19 AUG 2010

DOI: 10.1002/9780470972571.ch8

Operational Risk Management

Operational Risk Management

How to Cite

Figini, S. (2010) Bayesian Merging and Calibration for Operational Risks, in Operational Risk Management (eds R. S. Kenett and Y. Raanan), John Wiley & Sons, Ltd, Chichester, UK. doi: 10.1002/9780470972571.ch8

Editor Information

  1. 2

    KPA Ltd, Raanana, Israel; University of Turin, Italy

  2. 3

    NYU-Poly, Center for Risk Engineering, New York, USA

  3. 4

    KPA Ltd, Raanana, Israel

  4. 5

    College of Management, Academic Studies, Rishon Lezion, Israel

Author Information

  1. Bocconi University in Milan, Italy

Publication History

  1. Published Online: 19 AUG 2010
  2. Published Print: 22 OCT 2010

ISBN Information

Print ISBN: 9780470747483

Online ISBN: 9780470972571

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Keywords:

  • credit risk;
  • financial data;
  • operational risk management;
  • XBRL

Summary

This chapter is to describes with a real case study, how to properly integrate financial quantitative data with operational data. The objective is to generate an integrated risk score from two different data sources: financial data represented by XBRL balance sheets and operational loss data. XBRL is a language for the electronic communication of business and financial data, which is revolutionizing business reporting. In the case study, starting from XBRL balance sheets, it is possible to derive quantitative information such as financial ratios that are useful for measuring credit risk. The chapter presents a methodological proposal followed by a description of the application and the main results achieved. It shows how to integrate financial and operational risk management and, more precisely, credit risk with operational risk, following a two-step approach.

Controlled Vocabulary Terms

credit risk