leveraging an enterprise-wide stress testing automation

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This presentation, from a seminar co-hosted with PRMIA on October 22, discusses the following: 1. Stress testing industry challenges, such as the main areas of focus from regulators, governance, technology, process and reporting, and data and models. 2. Best practices of efficient infrastructure and data management, such as workflows, automation, datamarts, and risk data aggregation principles. 3. End-to-end automation across models, scenarios, and reporting.

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  • 1. Leveraging an Enterprise-wideStress Testing AutomationOCTOBER 22, 2014

2. Agenda1. Stress Testing Industry Challenges2. Best Practices of Efficient Infrastructure and Data Management3. End-to-End Automation across Models, Scenarios, and Reporting4. Conclusion 3. Global regulatory radar: growing trends of stress testregulations and data integration3EMEABasel 3 (IRB)CRD IV/CRRFI/Riksbank STReview of trading book(market risk)ICAAPBoE/PRA ST (Top 8 banks +Mid sized + SIFIs)CRR LCR2B3/ CRDIVMIFID IISIFI surcharge& risk mgtCRDIV AM?ORSAVolker RuleCCAR/DFAST STEBA / ECB STLarge exposures/concentration riskVickers ReformReview ofICAAPSecuritization rulesLarge exposures/concentration riskReview ofSecuritization rulesInternal Ratings2017 2016 2015 2014 2013 2014 2015 2016 2017Source Moodys Analytics market research and own analysis as of April 2014LEIReview ofSecuritization rulesLCR frameworkBasel 2Basel 3Global systemicrisk report (FED)Basel 3UK FDSFBasel 3(STD)Stress testsFBOCover BondsRule 3Review of trading book(market risk)Large exposures/concentration riskReview of tradingbook (market risk)LEILEIBasel 3RBC 2/ ERMIns. Inv.reqCROSSIBASuperann. Req.Ins Prud. StandSAMFull Solvency IISolvencia IISII-likeBMA P1SSTORSA USAIFMDUCITS LiquidityStress TestMMF InternalRatings/STCCP EMIRG-SIIs rulesG-SIIs rulesG-SIIs rulesSIFI surcharge& risk mgtSIFI surcharge& risk mgtUK ICASNIMMNIMMCOREP/ FINREPECB CR4IFRS 4,9LCRLCRInsurance CapitalStandardInsurance CapitalStandardInsuranceCapitalStandardInterimMeasuresSII InterimMeasuresNIMMCCAR/DFASTSTCapital PlanSubmission1CRR LCR2Qatar InsurancePrudential rulesIRDA risk-basedsolvencyCapital Rules & FinalMarket Risk Rule)BoE / PRA ST(Top 8 banks)ICAAP / ILAAPICAAP / ILAAPICAAP / ILAAPCCAR/DFASTSTCCAR/DFASTSTICAAPICAAPRetail BanksSTFSA STFSA STFSA STBlue Stress Testing-related Regulatory RequirementsBlack Other Regulatory RequirementsBoE / PRA STICAAPEBA/ECBSTFI/Riksbank STFI/Riksbank STRetailBanks ST 4. Stress Testing Main Areas of Focus from Regulators Increased expectations for scenario design Firm-wide risk identification and assessment Auditing and automation Risk data aggregation (RDA)* Analytics: Granular models; challenger process Narrative: Validation, documentation, and calibration Road mapping: Show a commitment to building out processes,controls, and governance of/for the exercise*Principles for Effective Risk Data Aggregation and Risk Reporting; Basel Committee on Banking Supervision. January 2013 5. Stress Testing Industry ChallengesProcess &Reporting Integration of stress testing withforecasting processes and resources Increasing frequency of stress testing Lack of harmonization betweenregulatory stress testing methodologyand accounting Evaluation of banks on the basis of ex-ante/ ex-post analysis (i.e., backtesting) Auditability of results Publish reports in required format; fullyautomated process2Technology Spreadsheet-based infrastructure Manual processes constrain:- Frequency of stress testing- Reconciliation (FINREP, COREP) andcontrols- Ability to analyze results Competing priorities:- Need for long term infrastructureplanning and enhancements- Short-term stress tests timeline Existing infrastructure not well-suited forstress testing process3Governance Coordination efforts across finance,treasury, and risk groups Need for timely communication throughchain of command as C-suite and seniormanagement are engaged in scenariodefinition, results review Ongoing board education efforts Transparency of the process1Models &Data Methodologies continue to evolve Emphasis on greater granularity Consistency of loss estimation and newbusiness methodologies Quantifying unknown unknowns Event-driven scenarios need to usethorough and well-governed analysisrather than routine models4 6. The Industrys Response Focuses on Automating &Streamlining the Stress Testing Process across theEnterprise Data quality and integrity Harmonized NPLs and RWAs definitions Regulatory and internal drivenscenarios Strategic planning What-if analysis Inclusion on the living wills Quantify contingency planningmetrics Linkage stress testing to capital plan Dynamic balance sheet forecasting Pre-provision net revenue forecasting Margins & Volumes M&A activity Early warning indicators Growth strategy, M&As, deleverage Setting risk limits & RAROC pricing Capital allocation Forecasting dividendpolicies Reverse Stress Testing RoE/RoAanalysis/projectionsunderscenarios/strategies Budgeting planning ILAP LCR forecasting Funding projections Liquidity stress testing HQLA optimization strategiesAQR &BalanceSheetReviewsStress TestingStrategicPlanning &ForecastingCapitalPlanning &ICAAPRisk AppetiteDividendPlanning &BudgetingLiquidityPlanning &ManagementOne of the biggest challenges for banks is coordinating the stress testing process amongst the differentstakeholders in a way that is transparent, controlled, auditable, dynamic, and repeatableSource Moodys Analytics 7. How Are Institutions Using Stress Testing? CapitalPlanning & Risk Management is High on the agendas ofBanks and regulatorsRegulatoryComplianceCapitalAdequacyMeasurementand PlanningRisk AppetiteDefinitionRiskManagementandMeasurementFinancialPlanning /Budgeting,StrategicPlanningLimit SettingandMeasurementPortfolioStructuringPricingSource Moodys Analytics 8. Stress Testing Key Areas of Investment / ChangesPlanned for 2015 and BeyondProcess/Workflow Infrastructure Governance Structure OrganizationSource Moodys Analytics 9. Do Banks Have a Roadmap for Improving the StressTesting Results Over the Next Two Years?Yes 77%No 23%Key areas of enhancement in the roadmap Modeling / automation of the process / risk dataaggregation / staffing / reporting / governance.but it is a work in progress todefine the contents of theroadmap.Source Moodys Analytics 10. Agenda1. Stress Testing Industry Challenges2. Best Practices of Efficient Infrastructure and Data Management3. End-to-End Automation Across Models, Scenarios, and Reporting4. Conclusion 11. The Stress Testing WorkflowStructuredCorporate CRE C&I RetailPPNRForecastNon-InterestInc / ExpForecastNet InterestIncomeForecastNCO /ALLLForecastOther LossesChanges toAvailableCapitalForecastRWARequiredCapitalBusinessForecastingModelsForecastPositionsP & LModelsFinancial Planning &Analysis Other revenue Op losses Trading losses Counter-partylosses Other expensesTreasury / ALMForecastPositions Base Runoff New BusinessInterestIncome /ExpenseModelsMarket RiskStrategy /RiskAppetiteRegulatory ReportsKey PerformanceIndicators / BalancedScorecard VariablesStress Testing InputsRegulator Scenarios Current PositionsSourceDatabaseSourceDatabaseSourceDatabasePricingCurvesEconomic Variablesand AlternateScenariosC & ICreditModelsCREMortgagesCreditCardsAutoOtherMarket RiskForecastPositionsOp RiskRisk 12. 12Stress Test Infrastructures and Automation Leveragethe Effective Risk Data Aggregation PrinciplesOverarchinggovernanceandinfrastructureRisk dataaggregationcapabilitiesRisk reportingpracticesSupervisoryreview, tools,andcooperation3. Accuracyand Integrity4. Completeness5. Timeliness6. Adaptability1. Governance2. DataArchitecture andInfrastructure7. Accuracy8.Comprehensiveness9. Clarity10. Adaptability11. Distribution12. Review13. Remedialactions/supervisory14. Home/HostCooperationBIS will start to assess the above principles implementation starting 2013 and to comply by 2016Not enforceable, but APRA is aligned with core principles (validation, automation, timeliness, control, etc.) 13. Best Practice Infrastructure: a Centralized Datamart tointegrate Counterparty, Credit Risk, and Finance data13CentralHead OfficeDomesticCalculationRulesOverseasAU SGPortfolio3 Tier Infrastructure DatamartHistoricalViewsCalculationWorkspacesSource SystemsTreasury,Investments,Assets & Liabilities,Commitments,CounterpartiesResultsMarket DataBloomberg,ReutersGeneral LedgerGL Recon.CapitalItemsRisks & BehavioralModelsStressScenarioRegulationConfigurationmaintenanceLocal Reporting requirementsat each consolidation levelBusiness Rules & WorkflowsCalculation& ReportingRiskEnginesData Editing & QueryingData Patching ToolError CheckingGL reconciliationAdjustmentWorkflowsPublishable ReportsDashboard & AlertsGraphical AnalyticsRegulatory ReportsUpdated regularlyfor local complianceDomesticOverseas 14. Stress Test Data Completeness Requires a Bank-wideData Model for Instruments and Referential Management14 15. Fitness for Use: Data Quality, Correction, Validation, andAdjustments Can Be Automated at Data/Dataset Levels Data validation: format, type, valuerange, currency, presence,consistency, and completeness Cleansing: default value, patching,bulk-edit, adjustment, reload/upload Data set validation: control totaling,GL reconciliation, benchmarking,variance15 16. Agenda1. Stress Testing Industry Challenges2. Best Practices of Efficient Infrastructure and Data Management3. End-to-End Automation Across Models, Scenarios, and Reporting4. Conclusion 17. GL RECONCILIATION ACCOUNTING REPORTINGCard StructuredAutoResiCREC&IMuniOtherRetailTradingMSRFundingOtherA Stress Testing System Is Seen as Mission ControlStress Test solution: the backbone to automate and integrate for firm-wide stress testingWORKFLOWMODELMANAGEMENTINPUT/OUTPUT ANDASSUMPTIONMANAGEMENTETL SYSTEMACCOUNTSHIERARCHYMANAGEMENT Centralized management of all primary credit models Can be extended to challenger credit models and econometrically-based PPNR calculations Supports reconcilement across all legacy feeder production risk and finance systems Supports all required regulatory and internal reporting Single point-of-entry to compile all stress test submission elements (inputs, scenarios, results) Highly configurable to support each unique client business model and user requirements 18. Model Inventory: Banks rely on the Stress Test

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