Operational Risk Management: A Practical Approach to Intelligent Data Analysis

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Ron S. Kenett, Yossi Raanan
John Wiley & Sons, Jun 20, 2011 - Business & Economics - 324 pages
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Models and methods for operational risks assessment and mitigation are gaining importance in financial institutions, healthcare organizations, industry, businesses and organisations in general. This book introduces modern Operational Risk Management and describes how various data sources of different types, both numeric and semantic sources such as text can be integrated and analyzed. The book also demonstrates how Operational Risk Management is synergetic to other risk management activities such as Financial Risk Management and Safety Management.

Operational Risk Management: a practical approach to intelligent data analysis provides practical and tested methodologies for combining structured and unstructured, semantic-based data, and numeric data, in Operational Risk Management (OpR) data analysis.

Key Features:

  • The book is presented in four parts: 1) Introduction to OpR Management, 2) Data for OpR Management, 3) OpR Analytics and 4) OpR Applications and its Integration with other Disciplines.
  • Explores integration of semantic, unstructured textual data, in Operational Risk Management.
  • Provides novel techniques for combining qualitative and quantitative information to assess risks and design mitigation strategies.
  • Presents a comprehensive treatment of "near-misses" data and incidents in Operational Risk Management.
  • Looks at case studies in the financial and industrial sector.
  • Discusses application of ontology engineering to model knowledge used in Operational Risk Management.

Many real life examples are presented, mostly based on the MUSING project co-funded by the EU FP6 Information Society Technology Programme. It provides a unique multidisciplinary perspective on the important and evolving topic of Operational Risk Management. The book will be useful to operational risk practitioners, risk managers in banks, hospitals and industry looking for modern approaches to risk management that combine an analysis of structured and unstructured data. The book will also benefit academics interested in research in this field, looking for techniques developed in response to real world problems.

 

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Contents

Foreword
1951
Notes on Contributors
1960
List of Acronyms
1969
an overview
1989
PART I DA TA FOR OPERATIONAL RISK
2004
Ontologybased modelling and reasoning
Semantic analysis of textual input
A case study of E TL for operational risks
Scoring models for operational risks
References
Measures of association applied to operational
Combining operational risks in financial risk
Intelligent regulatory compliance
Democratisation of enterprise risk management
Operational risks quality accidents and incidents
Copyright

Riskbased testing of web services

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