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Operational risk management : a practical approach to intelligent data analysis / ed. by Ron S. Kenett ...
Mitwirkende(r): Resource type: Ressourcentyp: Buch (Online)Buch (Online)Sprache: Englisch Reihen: Statistics in Practice Ser ; v.106Verlag: Chichester ; [Hoboken, N.J.] : John Wiley & Sons, 2011Auflage: Online-AusgBeschreibung: Online-Ressource (1 online resource (xxxvii, 285 p.)) : illISBN:- 9781282774469
- 1282774468
- 9780470972564
- 9780470747483
- 658.155
- 658.15/5 22
- HD61
Inhalte:
Zusammenfassung: 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 industryZusammenfassung: Intro -- Operational Risk Management -- Contents -- Foreword -- Preface -- Introduction -- Notes on Contributors -- List of Acronyms -- PART I INTRODUCTION TO OPERATIONAL RISK MANAGEMENT -- 1 Risk management: a general view -- 1.1 Introduction -- 1.2 Definitions of risk -- 1.3 Impact of risk -- 1.4 Types of risk -- 1.5 Enterprise risk management -- 1.6 State of the art in enterprise risk management -- 1.6.1 The negative impact of risk silos -- 1.6.2 Technology's critical role -- 1.6.3 Bringing business into the fold -- 1.7 Summary -- References -- 2 Operational risk management: an overview -- 2.1 Introduction -- 2.2 Definitions of operational risk management -- 2.3 Operational risk management techniques -- 2.3.1 Risk identification -- 2.3.2 Control assurance -- 2.3.3 Risk event capture -- 2.3.4 Risk and control assessments -- 2.3.5 Key risk indicators -- 2.3.6 Issues and action management -- 2.3.7 Risk mitigation -- 2.4 Operational risk statistical models -- 2.5 Operational risk measurement techniques -- 2.5.1 The loss distribution approach -- 2.5.2 Scenarios -- 2.5.3 Balanced scorecards -- 2.6 Summary -- References -- PART II DATA FOR OPERATIONAL RISK MANAGEMENT AND ITS HANDLING -- 3 Ontology-based modelling and reasoning in operational risks -- 3.1 Introduction -- 3.1.1 Modules -- 3.1.2 Conceptual model -- 3.2 Generic and axiomatic ontologies -- 3.2.1 Proton extension -- 3.2.2 Temporal ontologies -- 3.3 Domain-independent ontologies -- 3.3.1 Company ontology -- 3.4 Standard reference ontologies -- 3.4.1 XBRL -- 3.4.2 BACH -- 3.4.3 NACE -- 3.5 Operational risk management -- 3.5.1 IT operational risks -- 3.6 Summary -- References -- 4 Semantic analysis of textual input -- 4.1 Introduction -- 4.2 Information extraction -- 4.2.1 Named entity recognition -- 4.3 The general architecture for text engineering -- 4.4 Text analysis components.PPN: PPN: 807316431Package identifier: Produktsigel: ZDB-26-MYL | ZDB-38-EBR | ZDB-30-PAD | ZDB-30-PBE | ZDB-30-PQE
Operational Risk Management; Contents; Foreword; Preface; Introduction; Notes on Contributors; List of Acronyms; PART I INTRODUCTION TO OPERATIONAL RISK MANAGEMENT; 1 Risk management: a general view; 2 Operational risk management: an overview; PART II DATA FOR OPERATIONAL RISK MANAGEMENT AND ITS HANDLING; 3 Ontology-based modelling and reasoning in operational risks; 4 Semantic analysis of textual input; 5 A case study of ETL for operational risks; 6 Risk-based testing of web services; PART III OPERATIONAL RISK ANALYTICS; 7 Scoring models for operational risks
8 Bayesian merging and calibration for operational risks9 Measures of association applied to operational risks; PART IV OPERATIONAL RISK APPLICATIONS AND INTEGRATION WITH OTHER DISCIPLINES; 10 Operational risk management beyond AMA: new ways to quantify non-recorded losses; 11 Combining operational risks in financial risk assessment scores; 12 Intelligent regulatory compliance Marcus Spies, Rolf Gubser and Markus Schacher; 13 Democratisation of enterprise risk management; 14 Operational risks, quality, accidents and incidents; Index
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