Data-driven Operational Risk Management
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Data-driven Operational Risk Management

Data-driven Operational Risk Management


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About the Book

Table of Contents:
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.

About the Author :
Robert Scott Levine is an independent risk consultant and writer currently focusing on risk systems deployments, risk infrastructure design and building assurance and oversight processes. Before becoming a consultant, Robert was a vice president in charge of information protection at Bank of Tokyo-Mitsubishi North America. Prior to that he has worked with risk, trading, and financial systems design, control, and implementation at Reuters in New York, London, and Tel Aviv. Robert has also held audit management and senior staff positions at Deutsche Bank North America, Barclays Bank Plc, and other large financial institutions. Robert publishes widely in business and technology journals. His current research interests include operational risk data sources, risk management in personal finance, and early warning indicators. Robert Scott Levine holds an MBA from Baruch College, City University of New York, a BS from New York University and is completing a doctorate in finance


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Product Details
  • ISBN-13: 9781906348052
  • Publisher: Risk Books
  • Publisher Imprint: Risk Books
  • Height: 297 mm
  • ISBN-10: 1906348057
  • Publisher Date: 29 Feb 2008
  • Binding: Paperback
  • Width: 210 mm


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