Data-driven operational risk management
著者
書誌事項
Data-driven operational risk management
（Risk executive report）
Risk Books, c2008
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注記
Includes bibliographical references (p. 133-134) and index
内容説明・目次
内容説明
Most organisations currently rely on 'soft' subjective op risk data such as self assessments. But objective measurements reflect a truer picture of risk. Using primary research, this practical report demonstrates how you can use 'hard' data to improve your operational risk measurement. Robert Scott Levine tackles this data challenge based on in-depth knowledge gained as an experienced auditor, fraud examiner, data security manager and risk systems implementer. The core focus of the report is on how you can plan, implement and manage the available data sources for improved operational risk management. It also shows you how to maximise the rich internal and external data sources that are often overlooked.The practical examples given throughout the report clearly demonstrate the business benefits of operational risk management, beyond just the need for regulatory compliance. It also looks at the techniques that you can automate to produce early warning operational risk indicators.
This book is highly recommended for operational risk practitioners, auditors, examiners and compliance staff who will benefit from learning how to pull in the right operational data and how to automate the collection, cleansing, aggregation, correlation and analysis processes to do your job more effectively.
目次
1: Introduction and ChallengesWhat is Operational Risk?Processes and controlsDefinition of Operational RiskOperational Risk versus Other Risk TypesManaging Operational RiskOperational Risk MeasurementWhy a Data-Driven Approach?Challenges in the Data-Driven Approach2: Operational Risks and DriversWhy ORM?Risk and Loss CategoriesRisk-Type Classification - A Summary3: Approaches to Operational Risk ManagementThe Operational Risk LifecycleRisk FactorsRisk Assessment Tools and Measurement ApproachesLosses and Loss DistributionsImpact DataUse of CapitalUse of InsuranceActive Operational Risk ManagementLoss PreventionSummary of Methods4: Internal Incident Data Sources for Bottom-Up Operational Risk MeasurementInternal DataExternal DataChallenges with both Internal and External DataSummary of Data SourcesWrap-up5: External Incident Data Sources for Operational Risk MeasurementScalingTypes of External Loss DataExamples of External Data ServicesReputational RiskSummary6: The Operational Risk Management SystemOverall EnvironmentPerform AssessmentsAssess RisksTesting of ControlsAction TrackingTrack Events and LossesProcess Description, Mapping, and RedesignRisk Assessment HierarchyRisk and Control Data Capture and ManagementDocument ManagementRisk EngineEvents and LossesThe Risk View and Reporting CapabilityAdministration and Technical RequirementsOperational Risk Data Model EntitiesOperational Risk Data EntitiesOperational Risk Software Vendors7: Integration Challenges and ProcessesThe Implementation ProcessIntegration ChallengesUsing External Data to Compensate for Missing Internal DataAggregationDifferent Modelling ApproachesTracking LossesSummary8: Designing and Maintaining Data Cleansing, Improvement and Quality ProcessesThe Need for Data QualityDefinition of Data QualityThe Starting PointThe Quality Management ProcessData Quality ObjectivesHow Data Quality Can Be MaintainedStandardisationTechnical DesignData Cleansing and Validation RulesOperational Data ValidationReconciliationsMonitoring Job ExceptionsSummary9: Operational Risk Standards and MetricsWhy Standards?Operational Risk IndicatorsIndustry-Wide Risk Indicator InitiativesProcess Mapping, Control Identification and MetricsRisk Identifier DevelopmentMetricsMetric TypesDetermining the Quality of MetricsChallenges with Using MetricsMetrics and Risk ProxiesMetrics and Business Process OutsourcingSummary10: Enhanced Operational Risk Analysis and ReportingOperational Risk Reporting AreasSummary11: ConclusionNB - This table of contents is provisional until final publication of the book. Small changes to chapter titles and order may occur.
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