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|Title:||Operational Risk Management|
|Format:||Online PDF (324 pages, 2.2MB)|
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Operational risk management: a practical approach to intelligent data analysis provides practical and experimental method combining structured and non-structured, semantic-based on data, and digital data, in risk management activities (OPR) data analysis.It offers a unique multidisciplinary perspective on important topics and development of risk management activities. The book will be useful to learners active risk, risk management in banks, hospitals and industries looking for a modern approach to risk management combines analysis of structured data and unstructured.
Table of Contents PART I INTRODUCTION TO OPERATIONAL RISK MANAGEMENT 1 1 Risk management: a general view 3 2 Operational risk management: an overview 19 PART II DATA FOR OPERATIONAL RISK MANAGEMENT AND ITS HANDLING 39 3 Ontology-based modelling and reasoning in operational risks 41 4 Semantic analysis of textual input 61 5 A case study of ETL for operational risks 79 6 Risk-based testing of web services 99 PART III OPERATIONAL RISK ANALYTICS 125 7 Scoring models for operational risks 127 8 Bayesian merging and calibration for operational risks 137 9 Measures of association applied to operational risks 149 PART IV OPERATIONAL RISK APPLICATIONS AND INTEGRATION WITH OTHER DISCIPLINES 169 10 Operational risk management beyond AMA: new ways to quantify non-recorded losses 171 11 Combining operational risks in financial risk assessment scores 199 12 Intelligent regulatory compliance Marcus Spies, Rolf Gubser and Markus Schacher 215 13 Democratisation of enterprise risk management 239 14 Operational risks, quality, accidents and incidents 253
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