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Operational Risk Management: A Practical Approach to Intelligent Data Analysis
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About Operational Risk Management: A Practical Approach
Models and methods for operational risks assessment and mitigationare gaining importance in financial institutions, healthcareorganizations, industry, businesses and organisations in general.This book introduces modern Operational Risk Management anddescribes how various data sources of different types, both numericand semantic sources such as text can be integrated and analyzed.The book also demonstrates how Operational Risk Management issynergetic to other risk management activities such as FinancialRisk Management and Safety Management. Operational Risk Management: a practical approach tointelligent data analysis provides practical and testedmethodologies for combining structured and unstructured,semantic-based data, and numeric data, in Operational RiskManagement (OpR) data analysis.Key Features:The book is presented in four parts: 1) Introduction to OpRManagement, 2) Data for OpR Management, 3) OpR Analytics and 4) OpRApplications and its Integration with other Disciplines.Explores integration of semantic, unstructured textual data, inOperational Risk Management.Provides novel techniques for combining qualitative andquantitative information to assess risks and design mitigationstrategies.Presents a comprehensive treatment of "near-misses" data andincidents in Operational Risk Management.Looks at case studies in the financial and industrialsector.Discusses application of ontology engineering to modelknowledge used in Operational Risk Management.Many real life examples are presented, mostly based on theMUSING project co-funded by the EU FP6 Information SocietyTechnology Programme. It provides a unique multidisciplinaryperspective on the important and evolving topic of Operational RiskManagement. The book will be useful to operational riskpractitioners, risk managers in banks, hospitals and industrylooking for modern approaches to risk management that combine ananalysis of structured and unstructured data. The book will alsobenefit academics interested in research in this field, looking fortechniques developed in response to real world problems.
