EDM Council General Meeting New York City February 16, 2006

1. EDM Council General Meeting New York CityFebruary 16, 2006

2. Business Case Working Group Status Report on Progress February 16, 2006 • Working Group Leaders • AIG - Frank Duquette • Credit Suisse - John Bottega • UBS - David Goldberg • IBM Facilitators • Steve Mckenna, Con Crowley, David Gertler, Andrea Ianniello

3. Agenda – Model Business Case • Mission and Investigation Methodology • Key Findings and Core Challenges • Top Five Issues • The Governance Mandate • Business Case Summary (example) • Next Steps for Consideration

4. Initial Charter From theInaugural EDM Council Meeting (June ’05) … • Current Status • No consistent business case framework • Little relevant benchmark data on cost or ROI • Elusive and anecdotal metrics to quantify value • Proposed Deliverables • Framework for Business Case Analyses (multiple) • Benchmark data on strategic, operational, risk, CRM and monetary metrics • Value to EDM Council Members • Framework for composite EDM prioritization • Valid benchmarks with verifiable metrics • Support objectives of access, consistency, transparency and workflow integration • Leverage with suppliers on data quality and components of added value • Faster business case development and time-to-market for EDM solutions

5. Working Group Mission Collect and share experiences of data practitioners on how to elevate EDM as a business requirement, justify it in the face of other competing priorities and sustain it as an ongoing corporate initiative

6. Scope of Initial Investigation • Area: Client, counterparty, legal entities and business hierarchies • Rationale: Access to consistent data across multiple functions is a big challenge and required to meet regulatory obligations and financial risk mitigation • Objectives • Define the business case template for CCP as a component of a firm’s overall EDM portfolio • Identify key issues and drivers needed to build the business case template (with supporting evidence) • Present the template back to EDM Council members for use in their internal initiatives

7. Interview Process and Guide • 12 interviews including representatives from buy-side, sell-side, and asset servicing 1. List the type of CCP Data projects: • Other Relevant Areas of Discussion • Quantitative business case metrics • Anecdotal evidence • CCP sponsors, funding sources and governance structures • Business unit support mechanisms • Implementation/roll-out approach • Impact on downstream applications • Use of 3rd parties and consultants • Regional versus global considerations • Metrics for evaluating implementation value • Lessons learned B. Assessment of current pain point and emerging industry drivers. What caused you to initiate EDM CCP Data projects(s)? What was broken?:

8. Composite view is essential. Priorities differ among firms and business functions. Challenges are not homogenous. Key Evidence from the Interviews From the interview – Issues and drivers…. Never the driver but always a consideration Technological limitations/challenges of managing multiple systems Existing infrastructure hard to reconcile Not the critical driver – usually charged with implementation Contract negotiation mentioned consistently as a residual benefit Can centralized service meet or exceed the business service objectives Data content and format normalization is high priority More important when viewed as KYC objective. High priority and consistent driver Essential to meet KYC/AML objectives High priority for product/price master files not CCP Requirement to synchronize systems post merger is a core objective Risk evaluation and exposure measurement is a huge driver Inefficient use of resources needed to reconcile data Internal client frustration with bad, missing and late data - a clear driver Consistent data set is the number one business objective Internal consistency and ability to share data between functions is essential Mandatory objective and clear pathway to project funding

9. Data quality Consistency across lines of business and multiple master files • Reconciliation and validation processes (beyond “find and fix”) • Comparison between sources • Granularity and precision • Maintenance (particularly corporate actions) • Naming conventions and identifiers Sparsely populated within master files • Consolidation of trade hierarchies • Naming conventions and identifiers • Methodology for linking/aligning multiple investment programs to common legal entity • Precise terminology and classification system • Structure and cross-referencing for functional applications (I.e. risk, collateral management, legal agreements, transactions, regulatory reporting) • Automated delivery and account management instructions Hierarchies and relationships Compliance with regulation Proof of best execution • Price and transactions transparency • KYC/AML verification • Audit trails to justify data decisions • Reporting accuracy and deadlines • Full disclosure • Capital adequacy requirements and risk weighting KYC requirement (due diligence) • Streamline client “on-boarding” process • Consolidate, clean and align multiple account databases • “Know your customers business” (for product innovation, up-selling, data asset leverage, new revenue streams) • Pinpoint customer support ROI • Business unit requirements alignment and cross-referencing • Evaluate coverage models (risk disclosure, investment transition strategy, reconciliation to balance sheet) Account set-up process Operational Commitment Manage market/product complexity • Accurate performance benchmarking • Integrate acquisitions and mergers • Compress clearing and settlement cycles • Minimize FO/BO breaks • Promote business process automation • Reduce internal client frustration • Reduce data/system redundancy Research and metrics needed to determine … Evidence and implications Options and Remediation Measuring Success Top Five CCP Issues

10. Risk:Operational risk from interdependent markets and processes. P&L risk from bad data and convoluted trading models. Reputation risk from poor client reporting, fines and avoidable errors. • Regulation: Data management is essential in order to efficiently extract information, justify data decisions, provide transparent audit trails, identify hierarchical relationships and meet reporting deadlines. • Operational Commitment: Meeting the service objectives of LOBs by shortening clearing and settlement cycles, linking front and back office operations, managing costs and operating in complex global environments require automation which depend on accurate, consistent, precise, accessible and transparent data. • Composite View: Managing the requirements of sophisticated customers means access to data from multiple repositories across product lines. KYCB means opportunities for product innovation, up-selling, data asset leverage and new revenue opportunities Four Implications - Summation The issues and drivers can be grouped into four broad categories. Significant consensus on issues and drivers. Challenge is how to reconcile short-term (no immediate crisis) orientation with long-term (building block for doing business) objectives.

11. The Governance Mandate In the Words of the Members … "Keeping that interest and sense of urgency" “Need a champion – an active and influential executive sponsor” “Senior level Board member to manage selling business units and lobbying peers” “Can’t be driven by individual units because there is no alignment on business agenda” “Priorities and funding done by centralized strategic management” “Vision came from top management “this is the way we will operate” “Must have senior management attention for stability” “Reference data is back on the senior management radar” “Senior management recognized value – otherwise this project wouldn’t have moved forward”

12. CCP Business Case Summary

13. Ongoing Steps • EDM Council Research • Publish framework documents for composite, monetary, operational evaluation • Publish strategy papers on business case details by objective, application area, business function, data type and industry segment • Quantitative analysis of data management challenges and priorities (component-by-component) • Collect and normalize metrics for benchmarking (i.e. costs to fix problems, root cause analysis, risks associated with implementation) • Website Repository • Collect and post sample heat maps, templates and guides • Build network of member expertise • Leverage Influence • Create and verify requirements definition for standards bodies • Push data manufacturing envelope with originators and vendors