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.

4.4.1 Document structure identification -- 4.4.2 Tokenisation -- 4.4.3 Sentence identification -- 4.4.4 Part of speech tagging -- 4.4.5 Morphological analysis -- 4.4.6 Stemming -- 4.4.7 Gazetteer lookup -- 4.4.8 Name recognition -- 4.4.9 Orthographic co-reference -- 4.4.10 Parsing -- 4.5 Ontology support -- 4.6 Ontology-based information extraction -- 4.6.1 An example application: market scan -- 4.7 Evaluation -- 4.8 Summary -- References -- 5 A case study of ETL for operational risks -- 5.1 Introduction -- 5.2 ETL (Extract, Transform and Load) -- 5.2.1 Related work -- 5.2.2 Modeling the conceptual ETL work -- 5.2.3 Modeling the execution of ETL -- 5.2.4 Pentaho data integration -- 5.3 Case study specification -- 5.3.1 Application scenario -- 5.3.2 Data sources -- 5.3.3 Data merging for risk assessment -- 5.3.4 The issues of data merging in MUSING -- 5.4 The ETL-based solution -- 5.4.1 Implementing the 'map merger' activity -- 5.4.2 Implementing the 'alarms merger' activity -- 5.4.3 Implementing the 'financial merger' activity -- 5.5 Summary -- References -- 6 Risk-based testing of web services -- 6.1 Introduction -- 6.2 Background -- 6.2.1 Risk-based testing -- 6.2.2 Web services progressive group testing -- 6.2.3 Semantic web services -- 6.3 Problem statement -- 6.4 Risk assessment -- 6.4.1 Semantic web services analysis -- 6.4.2 Failure probability estimation -- 6.4.3 Importance estimation -- 6.5 Risk-based adaptive group testing -- 6.5.1 Adaptive measurement -- 6.5.2 Adaptation rules -- 6.6 Evaluation -- 6.7 Summary -- References -- PART III OPERATIONAL RISK ANALYTICS -- 7 Scoring models for operational risks -- 7.1 Background -- 7.2 Actuarial methods -- 7.3 Scorecard models -- 7.4 Integrated scorecard models -- 7.5 Summary -- References -- 8 Bayesian merging and calibration for operational risks -- 8.1 Introduction -- 8.2 Methodological proposal.

8.3 Application -- 8.4 Summary -- References -- 9 Measures of association applied to operational risks -- 9.1 Introduction -- 9.2 The arules R script library -- 9.3 Some examples -- 9.3.1 Market basket analysis -- 9.3.2 PBX system risk analysis -- 9.3.3 A bank's operational risk analysis -- 9.4 Summary -- References -- PART IV OPERATIONAL RISK APPLICATIONS AND INTEGRATION WITH OTHER DISCIPLINES -- 10 Operational risk management beyond AMA: new ways to quantify non-recorded losses -- 10.1 Introduction -- 10.1.1 The near miss and opportunity loss project -- 10.1.2 The 'near miss/opportunity loss' service -- 10.1.3 Advantage to the user -- 10.1.4 Outline of the chapter -- 10.2 Non-recorded losses in a banking context -- 10.2.1 Opportunity losses -- 10.2.2 Near misses -- 10.2.3 Multiple losses -- 10.3 Methodology -- 10.3.1 Measure the non-measured -- 10.3.2 IT events vs. operational loss classes -- 10.3.3 Quantification of opportunity losses: likelihood estimates -- 10.3.4 Quantification of near misses: loss approach level -- 10.3.5 Reconnection of multiple losses -- 10.4 Performing the analysis: a case study -- 10.4.1 Data availability: source databases -- 10.4.2 IT OpR ontology -- 10.4.3 Critical path of IT events: Bayesian networks -- 10.4.4 Steps of the analysis -- 10.4.5 Outputs of the service -- 10.5 Summary -- References -- 11 Combining operational risks in financial risk assessment scores -- 11.1 Interrelations between financial risk management and operational risk management -- 11.2 Financial rating systems and scoring systems -- 11.3 Data management for rating and scoring -- 11.4 Use case: business retail ratings for assessment of probabilities of default -- 11.5 Use case: quantitative financial ratings and prediction of fraud -- 11.6 Use case: money laundering and identification of the beneficial owner -- 11.7 Summary -- References.

12 Intelligent regulatory compliance Marcus Spies, Rolf Gubser and Markus Schacher -- 12.1 Introduction to standards and specifications for business governance -- 12.2 Specifications for implementing a framework for business governance -- 12.2.1 Business motivation model -- 12.2.2 Semantics of business vocabulary and business rules -- 12.3 Operational risk from a BMM/SBVR perspective -- 12.4 Intelligent regulatory compliance based on BMM and SBVR -- 12.4.1 Assessing influencers -- 12.4.2 Identify risks and potential rewards -- 12.4.3 Develop risk strategies -- 12.4.4 Implement risk strategy -- 12.4.5 Outlook: build adaptive IT systems -- 12.5 Generalization: capturing essential concepts of operational risk in UML and BMM -- 12.6 Summary -- References -- 13 Democratisation of enterprise risk management -- 13.1 Democratisation of advanced risk management services -- 13.2 Semantic-based technologies and enterprise-wide risk management -- 13.3 An enterprise-wide risk management vision -- 13.4 Integrated risk self-assessment: a service to attract customers -- 13.5 A real-life example in the telecommunications industry -- 13.6 Summary -- References -- 14 Operational risks, quality, accidents and incidents -- 14.1 The convergence of risk and quality management -- 14.2 Risks and the Taleb quadrants -- 14.3 The quality ladder -- 14.4 Risks, accidents and incidents -- 14.5 Operational risks in the oil and gas industry -- 14.6 Operational risks: data management, modelling and decision making -- 14.7 Summary -- References -- Index.