Presentation on theme: "Table of Contents 1. Point of view 2 2. Why firms are concerned 4"— Presentation transcript:
0 DateCurrent Challenges in Counterparty Collateral Management Informational Presentation for our Clients April 2008PwC
1 Table of Contents 1. Point of view 2 2. Why firms are concerned 4 Page1. Point of view 22. Why firms are concerned 43. Key issues & opportunities 94. Industry environment 105. Likely regulatory response 116. Suggested approach 127. Case studies 138. Summary 159. Appendix 1710. PwC contacts 24
2 DatePoint of viewThe recent turmoil in the credit markets has highlighted significant errors and shortfalls in CM operations. These errors have translated into material actual losses and sizable additional exposure which is under-reported to management, hence undermining the risk management benefits of collateral management.Significant operational challenges persistAlthough the role of collateral is straightforward, the volume, diversity and complexity of collateralized transactions have surpassed the scalability and flexibility of processes, people and technology that support the function.Credit and operational risks are significantBesides the direct impact of increased counterparty default exposure, underperforming CM functions may also cause or mask significant hidden risks such as portfolio concentration, flawed credit and customer data, and substandard or missing legal documentation – creating potentially dangerous latent exposures.The benefits of technology advances and the adoption of industry standards have been limitedBullish statements from Industry groups such as ISDA may over-state the degree to which derivatives-related CM operational issues have been reduced or eliminated by technology, e.g., the adoption of uniform confirmation and call practices. Our experience confirms that some large banks continue to experience high exception rates and difficulty processing collateral calls in a timely manner, and that root-cause remediation of these on-going challenges is difficult and costly.Many banks’ CM functions have not sufficiently evolved to support complex OTC derivativesA primary cause of substandard CM performance may lie in the historically low-profile role this cross-departmental function played in most investment banks, prior to the widespread use of complex OTC derivatives. The function may have been designed to support activities such as FX forwards and vanilla repos, where collateral movements were straightforward, products were simple, and there was a relatively small and static base of well-known customers.Management’s attention was distracted during market expansionThe boom market for OTC derivatives and credit risk transfer products from saw dramatic revenue growth and constant competitive pressures to deliver innovative products and to increase leverage for hedge fund clients. This may have distracted management’s attention from the growing insufficiency of CM resources and operating models to service the rapidly increasing counterparty exposure.
3 DatePoint of viewCM operations are challenged to keep pace with product volume and diversity growthFaced with myriad new and different derivative transactions and a continuous flow of new hedge fund counterparties, CM organizations and IT systems proved unable to change and scale quickly enough to keep up with marketplace demands. This has resulted in backlogs of tasks and documentation, significant data quality issues, and bottom line underperformance and unwanted counterparty default exposure, in the form of insufficiently called and/or ineligible collateral.Recent market events have led to greater management scrutiny of operational practicesThe credit crunch and market turmoil which began in 2007 have cast a harsh light on the requirement to measure, manage and mitigate counterparty exposure, particularly with respect to highly leveraged counterparties and/or less liquid underlying reference securities. Many financial services firms are aggressively seeking to remedy previous oversights and rapidly mitigate excess counterparty exposure – and to get better management intelligence on all credit risks.Regulatory focus is inevitableRegulators are aware of the operational weaknesses in collateralized derivative transactions and are likely to scrutinize these functions closely during financial soundness examinations – or on a targeted basis, if a major default event occurs.Sustainable operation model changes will bring benefitsA focus on end-to-end data management and data quality assurance – not only fixing errors in the current CM data environment, but equally importantly, developing sustainable changes to the operating model to maintain data integrity moving forward – can offer significant benefits as banks seek to overhaul and transform their CM operations.Scalability and adaptability are key in responding to the complexity of collateralized transactionsLonger term, firms that participate in large volumes of collateralized transactions are seeking to restructure their CM operating models – including people, processes, enabling IT systems and data management practices – to achieve scalability and adaptability appropriate to the elevated complexity of collateralized transactions in today’s capital markets. At the same time, firms are beginning to assess the need for more disciplined new product approval processes in order to make better informed decisions about the total lifecycle costs to support the exotic derivative or credit risk product du jour, instead of assuming ‘all new products are good new products.’Bottom Line: Often the risk is not apparent until it’s too late to react (e.g., the counterparty has defaulted). Strong risk managers are placing the spotlight on their CM operations to ensure they are adequately protected and to prevent further actual dollars being lost.
4 DateWhy firms are concernedHow we got here…Collateral management effectively reduced credit losses during the Asia, Russia and Hedge Fund ‘crisis’ in 1997/98.The complexity of unraveling the complex web of trades in a crisis today would be unprecedented and may have been one of the prompts for government intervention in the market recently.19982008Market characteristics at that time:International Swaps and Derivatives Association (ISDA) estimated $200bn collateral assetsHigh thresholds linked to credit worthinessCalendar driven MTM margin calls – straightforward calculationsWeekly/monthly margin frequencySingle product marginingStandard ISDA/Global Master Repo Agreement contract termsCollateral types: cash, govt bondsMarket characteristics currently:ISDA estimates >$1 trillion in collateral assetsWide range of CP creditworthiness and thresholdsMarket driven margin calls – complex formulasDaily/intra-day margin callsPortfolio marginingClient driven contract termsCollateral securities include corporate bonds, equitiesSources: ISDA, PwC research
5 DateWhy firms are concernedOvertaxed operations and collateral management processes have led to many millions of dollars in collateral deficienciesExplosive growth of derivative volumes, cheap funding and upward biased asset prices drove a period where core risk mitigation received less focus than revenue and market share growth.In such a climate, front office focused on product innovation and market share – there was minimal incentive to follow a disciplined new product approval and rollout process which would have better assured that support functions like CM could accommodate structures and meet volume expectations.Key data like collateral agreement terms & conditions and trade upfront amounts have been captured incorrectly, late, or not at all.Automation and straight through processing (STP) tools for CM and associated trade types are not as mature as those for cash trade processing and most firms choose to build in-house tools which may lack technical flexibility and may become overly dependent upon the key personnel who support and maintain them.Growth of value of estimated collateral 2000 to 200720040060080010001200140020002001200220032004200520062007YearBillions of US$Average reported monthly deal volume 2005 to 20072000400060008000100001200014000160001800020000200520062007YearNumber of tradesSource: ISDA Margin Survey 2007Source: ISDA Operations Survey 2007
6 The landscape has changed significantly in the last ten years DateWhy firms are concernedThe landscape has changed significantly in the last ten yearsDimensionThen (FX, repos, IRS were dominant collateralized transactions)Now (Complex OTC derivatives dominant; larger volumes of all collateralized transactions)Margin CalculationsVanilla – Single product marginingMature, standardized affirmation, comparison and settlement processSingle product marginingComplex – portfolio marginingNon Standard – Model/market drivenPortfolio margining/cross marginingData ManagementNarrow range of asset types on handful of front office systemsRelatively simple data managementLimited DependenciesUpstream Dependencies – capture of non-standard termsProduct innovation has led to multiple asset types on wide range of front office systemsMultiple agreement typesFront office modification of standard T’s & C’sPortfolio Risk ManagementHedged products were largely cash/FX basedCollateral was cash and short duration government debtRapid, unbounded product diversificationCross border activityWide range of security types, quality and maturities accepted as collateralCustomer ExperienceConsistent experienceLow employee turnoverInfrequent customer/broker relationship changesInconsistent experience – high staff turnoverStaff skill level exceeded in some areasInadequate training given complexity of productsConstant flow of new clients
7 DateWhy firms are concernedIncreased complexity has led to breakdowns throughout the operations and collateral management life cycle and…Missing AgreementsInefficient processesStandardize process Establish or clarify data ownershipSet up legal frameworkPeople: Training, Standardization, Quality AssuranceTechnology: Efficient document management and indexingTrades notTimely capturedInitiate the transactionFront office system rationalization and >99% day one captureEliminate IT bottlenecks which inhibit timely upfront callsUpfronts notcalledSettle the collateralPerformance metrics and real-time risk managementLeverage industry tools, messaging protocols (FpML) and settlement utilitiesPoor upstream data = Inaccurate margin calcsManage collateral (margin calls, reconciliation, substitutions, etc.)Improved STP technology – designed to support the business objectives end-to-endCollateral not returned by deadline on closed transactions = poor client experienceClose the transactionSources: SWIFT, PwC
8 DateWhy firms are concerned…Technology infrastructure supporting operations, including collateral management, is often inadequate to identify and/or control risks…LegalTrade WhseCreditCMSTrade input systems(numerous, inconsistent and not fungible)Other collateral systems for Prime Brokerage, Private Clients…Legal documentation system (CSA, ISDA)Credit system (CSA, ISDA)Trade data warehouseSettlementCollateral Management SystemTrade settlement systemCash ManagerCash Manager – Routes cash movements to payments systemCorrections of trades incorrectly routedIncomplete trade data causing inaccurate portfolio margin calculationsInaccurately captured terms, conditions, thresholds, currencies, MTAs, collateral types etcUntimely, inaccurate collateral requests Improper nettingTrades not timely input Trade terms not captured Upfront amounts never calculated
9 So what are the key issues and what can clients do DateKey issues & opportunitiesSo what are the key issues and what can clients doKey IssueImpactOpportunityPoorly controlled and/or inconsistently executed customer on-boarding/ legal/credit processesSignificant number of missing, outdated, incomplete, or legally ineffective documentsConduct a fast track, risk based remediation effort to inventory and resolve discrepanciesDocument management and indexing systems lack required flexibility to capture all relevant T’s &C’s; Contract amendments not consistently captured in terms databaseIncorrect downstream calculations leading to inaccurate collateral callsRe-align people, processes and technology resources to properly support the business going forward – a fancy document management solution won’t solve core process issues by itselfChanges negotiated to ISDA boilerplate language/non-standard variances to terms and parameters agreedUnnecessary process complexity to handle rare and/or marginally useful variances to standardized contractsStreamline document workflow and reduce number of routinely allowed changesIncomplete/inconsistent deal data flow to collateral management systems on Trade DateUpfront calls not timely issued; incorrect portfolio netting calculationsGet control over trade data flow; establish and use daily metrics to monitor process integrityUpfronts and MTMs not properly valued, leading to under-margined exposureExcess counterparty default riskImprove upstream data processes to drive accurate margin and collateral calls; identify and remedy shortfallsLack of visibility on actual risk of aggregate collateral pool, e.g. by asset class, rating, issuerPotentially unmanaged market and portfolio exposure if undue concentrations existMonitor and manage these types of exposure to reduce riskInconsistent customer experiences due to information quality and staff training issuesPoor client service, reputational riskRestructure customer –facing CM roles and functions to improve quality and consistency
10 Industry EnvironmentBecause the OTC Derivative space is mostly unregulated, there is a wide performance gap between the ‘best’ and the ‘worst’ firms.DimensionGlobal Investment Bank AGlobal Prime Broker BGlobal Investment Bank CConsistent and accurate terms & conditions data across multiple functional groups (e.g., Front Office, Legal, Credit, and Middle Office)Poor – 100% error rate, dozens of agreement templates, data quality not managedFewer standard forms , management limits non-standard languageProactive limits on non-standard language changes Sole source database with clear ownerAccurate and timely independent price verification of collateralMainly manual – some stale prices and marksSome automationUse of automated price feedsTimely collection of collateral including margin calls and upfrontsWidely variable by product typeMediumConsistent and measuredTime required to react to credit events and counterparty deteriorationSlow – multiple daysTypically next business daySame dayMonitoring and regulatory reporting capabilitiesSignificant gaps in all relevant data sets = inaccurate reports/metricsEnd-of-day batch process, fewer data issuesNear real time margin calculation abilitiesCollection of collateral types appropriate to counterparty and market risks being securedAware of issue, some manual reviewsPassive monitoring of correlation matching issuesDaily analysis of acceptable collateral types, prompt corrective actionEstimated annual technology spend in CM area>$5M$3-$5M>$15MClient Satisfaction RatingPoorGood – ExcellentA firm that is effective at collateral management is a firm which has the ability to match its risk objectives with the amount and type of collateral it pledges and receives.
11 Likely regulatory response DateLikely regulatory responseFinancial Regulators are aware of the systemic risks presented by weak operational processes and practices:Immature state of OTC derivatives processing and collateral management processes industry-wide cited in US Treasury Dept report to President Bush as a key risk and area for attention (March 2008)We have strong indications that all risk management and operational functions are going to receive increased scrutiny in the current environmentRegulators are beginning to show interest in operational issues and how they impact the market/credit risk of an entitySpecial examinations, including operational processes, are likely to increase at top tier banks in 2Q08 and 3Q08, and we recommend clients be prepared
12 Suggested approach Date 3 – 12 months Remediation & Tactical Fixes Strategic SolutionScoping & DiagnosisData Clean-up& RemediationProcess AnalysisProcess Re-DesignImplementationContinuousImprovementPeopleEstablish Policy Board, Steering Committee and Working GroupsAgree on resourcing approachDeploy data remediation and project management resourcesDevelop current state view of organizational structure, roles and responsibilitiesExamine linkages of policies back to roles and responsibilitiesDefine organizational roles and responsibilitiesDraft and agree principles relating to interim changes to Operating Model, e.g. data, sourcing, technology, locationsUpdate procedures and training, including upstream procedures e.g. new product approval processes.Develop and train staff on new proceduresRefine enhanced operating model from a process, data, technical, functional and organizational perspectiveProcessConfirm project scopeDevelop project plan and define workstreamsDevelop workstream project chartersDevelop data remediation metrics and progress reportingInterpret and assess results and determine remediation prioritiesRemediate collateral positionsDevelop current state view of end to end processesAssess exception management and escalation procedures, including cross-departmental proceduresDrilldown on targeted areas causing problems and Identify key control breakpointsPerform gap analysis of policies and proceduresDefine manual and automated workarounds and associated control reporting toolsAssess compliance of policies/procedures with regulatory guidelines and identify changes requiredImplement manual and automated solutions and associated control reporting tools.Embed policies in processing environmentImplement exception reporting metrics:incorrect or stale valuation of exposurescommon CSA errorsratings based downgrade provisionsDefine future business service offering based on business and operational strategiesUtilizing process analysis work completed in earlier phases, identify gaps between current state and enhanced operating process modelTechnologyConfirm support required from technology teamsDefine initial data quality queriesRefine/tailor diagnostic query toolsRun targeted diagnostic queriesDevelop current state view of CM system architecture and datawarehousingAssess timeliness and accuracy of system feeds between front/middle/back officeDefine tactical and strategic IT upgradesManage “quick win“ and medium term implementation processes with ITEnhance use of automation, workflow and document management optionsDataReview existing documentation on data sources and reconciliationsConfirm data sources and data populationPerform standing data quality tests:- Counterparty data- CSA data- Credit risk dataRun scenarios/perform reconciliation on:- Marks- Trade level details- CollateralReview data integrity management processes and standardsDesign cross functional CM data integrity standards and controls, focusing on highest risk/return areas.Implement selected cross functional CM data integrity standards and controlsEnhance data warehousing architecture and data integrity management
13 DateCase StudyCollateral Management Data Remediation and Operational Process RedesignProblemThe client was a leading global financial institutionClient’s global Collateral Management (CM) group provides essential risk mitigation and client service functions to support the OTC derivatives and securities repurchase agreements (“repo”) businesses. The CM function was struggling with outdated enabling technology, major data management issues, and lack of mature and documented business processes. Collateral calls were not being properly issued, creating over $500 million in unnecessary risk exposure. Recognizing the urgency to address these challenges, the client created a global initiative involving PwC, internal resources and technical temporary resources in London and New York.ApproachWorking with the client, PwC developed over 50 multi-variable scenario queries to identify and prioritize collateral deficienciesThese scenarios were run against the client’s data to identify high impact quick wins as well as to develop a detailed understanding of the failures that were continuing to occur, leading to new defects appearing in the data on a daily basis.We also created an efficient, documented repeatable process to conduct a mass data clean-up effort in ISDA Credit Support Annex documentation.We worked with the client to develop and prioritize near and long-term process improvements to the day-to-day functioning of the global Collateral Management group.
14 DateCase StudyCollateral Management Data Remediation and Operational Process RedesignImpact and Benefits to the ClientWe helped the client gain a deep understanding of the population of risks and exposures that exist within its Collateral Management unit – a deep root cause analysis of how the client came to have substantial uncollateralized exposure and what needed to be done to fix it.We helped the client remediate thousands of key data elements in the Collateral Management contract terms system – enabling immediate, significant improvements to the functioning of the Collateral process and the rapid collection of several hundred million dollars in deficient collateral.The client further identified and fixed potential deficiencies (e.g., wrong credit limits, thresholds etc.) which carried aggregate potential exposure in the billions of dollars.Next StepsWe are beginning to assist the client in developing and implementing a fundamental re-design, including process re-design and an enhanced technology platform.
15 DateSummaryIn summaryCertain clients are experiencing significant error rates and exposures generated from broken operational processes and flawed data – leading to as much as hundreds of millions of dollars in margin deficiencies and untold billions in parameter errorsA root cause of the high levels of operational risk and/or actual operational failures can be traced to fragmented processes and siloed systems that can’t keep pace with product and volume growthWe recommend that organizations undertake end-to-end operational effectiveness assessments in highly complex product areasProcesses need to be re-designed to meet the current and future needs of business and large stores of critical data may need to be remediatedExperience shows millions (USD) or more may be at unnecessary risk and can be identified and collected in an early phase of the overall project
16 What does an effective collateral management operation look like DateAppendixWhat does an effective collateral management operation look likeCase Study – Detailed Project Approach
17 DateWhat are some characteristics of an effective collateral management operationEnsuring the right data is uploaded into systems in a timely manner.Maintaining the integrity of the data across various functional groups and their corresponding systems, e.g., reconciliation, data warehousing, data control/governance systemsUtilizing the data to price, collect, and track the collateral needed to stay within firm regulated exposure limits, i.e.Do we have enough collateral to cover our counterparties?Did we call the correct amount of collateral, based on counterparty ratings, loss given default, potential credit exposure, etc.?Are we pledging more collateral than is required?Escalating issues where exposure exceeds firms’ acceptable limits due to insufficient collateralAdjusting and responding appropriately to changes in market conditionsEnsuring execution aligns with collateral management business strategy, i.e.:What types of collateral are we holding?Is it appropriate for the counterparty, given the industry they are in?Are exposures or counterparty creditworthiness positively or negatively correlated with the type of collateral the counterparty is posting?
18 Suggested approach Date 3 – 12 months Remediation & Tactical Fixes Strategic SolutionScoping & DiagnosisData Clean-up& RemediationProcess AnalysisProcess Re-DesignImplementationOptimizationPeopleEstablish Policy Board, Steering Committee and Working GroupsAgree on resourcing approachDeploy data remediation and project management resourcesDevelop current state view of organizational structure, roles and responsibilitiesExamine linkages of policies back to roles and responsibilitiesDefine organizational roles and responsibilitiesDraft and agree principles relating to interim changes to Operating Model, e.g. data, sourcing, technology, locationsUpdate procedures and training, including upstream procedures e.g. new product approval processes.Develop and train staff on new proceduresRefine optimal operating model from a process, data, technical, functional and organizational perspectiveProcessConfirm project scopeDevelop project plan and define workstreamsDevelop workstream project chartersDevelop data remediation metrics and progress reportingInterpret and assess results and determine remediation prioritiesRemediate collateral positionsDevelop current state view of end to end processesAssess exception management and escalation procedures, including cross-departmental proceduresDrilldown on targeted areas causing problems and Identify key control breakpointsPerform gap analysis of policies vs proceduresDefine manual and automated workarounds and associated control reporting toolsAssess compliance of policies/procedures with regulatory guidelines and identify changes requiredImplement manual and automated solutions and associated control reporting tools.Embed policies in processing environmentImplement exception reporting metrics:incorrect or stale valuation of exposurescommon CSA errorsratings based downgrade provisionsDefine future business service offering based on business and operational strategiesUtilizing process analysis work completed in earlier phases, identify gaps between current state and optimal operating process modelTechnologyConfirm support required from technology teamsDefine initial data quality queriesRefine/tailor diagnostic query toolsRun targeted diagnostic queriesDevelop current state view of CM system architecture and datawarehousingAssess timeliness and accuracy of system feeds between front/middle/back officeDefine tactical and strategic IT upgradesManage “quick win“ and medium term implementation processes with ITOptimize use of automation, workflow and document management optionsDataReview existing documentation on data sources and reconciliationsConfirm data sources and data populationPerform standing data quality tests:- Counterparty data- CSA data- Credit risk dataRun scenarios/perform reconciliation on:- Marks- Trade level details- CollateralReview data integrity management processes and standardsDesign cross functional CM data integrity standards and controls, focusing on highest risk/return areas.Implement selected cross functional CM data integrity standards and controlsOptimize data warehousing architecture and data integrity management
19 Detailed project timeline DateCase StudyDetailed project timelineScoping, planning, stakeholder and key metric reporting definitionConfirm data sources and data populationPerform selective process mappingIdentify key control breakpointsScoping and PlanningDiagnosis and AssessmentData & Collateral Position RemediationRoot Cause AnalysisProcess RedesignRun diagnostic queriesPerform comparison of system data to source Credit Support Annex’s (CSA)Interpret and assess results and develop remediation priority listReview results and agree resolution activity with managementPerform updates to correct data errors (Manual or IT upload)Remediate collateral positionsReport progress and MI on issues identifiedDevelop tactical and strategic process redesign recommendationsTime
20 Diagnostics: Data Scenario Analysis DateCase studyDiagnostics: Data Scenario AnalysisWorking with the client, PwC developed over 50 multi-variable scenario queries to identify and prioritize collateral deficienciesWe also created an efficient, documented repeatable process to conduct a mass data clean-up effort in ISDA Credit Support Annex documentationScenarios were run against the client’s data to identify high impact quick wins - for example, customers with live trades and:No upfront call issuedStale MTMCredit MTM ≠ Trade MTMOut-of-range MTA and threshold valuesWrong call frequencyThe query results were also used to prioritize strategic (business re-design) objectives based on actual patterns and frequencies of particular kinds of errors and deficienciesA flexible resourcing plan – PwC, client, legal temporary staff – allowed the client to get immediate tangible results while limiting project costs
21 DateCase studyPwC’s diagnostic analysis enabled the client to collect several hundred million dollars in deficient collateralCall Frequency incorrect1,572 instances$52 mmIdentifyQuantifyCollectPwC’s Collateral Diagnostic Tools are designed to quickly and efficiently identify, quantify and help prioritize high impact collateral shortfalls and deficiencies by cause and by client. Outputs can be promptly verified and sent to Margin/Collateral for immediate action during the projectData in the graphic above are simulated and do not reflect any actual client information
22 Representative analysis approach and results Scenario analysis – Update & capture of CSA dataScenario analysis – Trade Data QualityAnalysis of instances of incorrect ‘roll up’ of collateral valueAnalysis of control risks and policy questions relating to counterparty Minimum Transfer AmountsDistribution of MTAs by Counterparties with no external credit rating:Source: Scenarios K5Decreasing Credit RatingDistribution of Thresholds Amongst Counterparties with no external rating and an internal rating of ‘No Rating’:Source: Scenarios Z5
23 Root cause analysis and process re-design DateCase studyRoot cause analysis and process re-designAssessment of type and frequency of errorsSelective process mapping to identify issues with:Data fundamentals – definition, ownership, controlOrganization design – roles, responsibilities and controlsProcesses – streamlining and improving scalabilityTechnology – use of automation, workflow and document management optionsAssessment of root cause analysis findingsStrategic recommendations based on global industry practicePhased approach including short-term tactical fixesAddresses organizational, process and technology issuesDevelop and implement enhanced future state
24 For further information, please contact DateFor further information, please contactJohn GarveyAndrew WilsonRichard PaulsonKaren Joyce
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