Introduction to DCAM, the Data Management Capability Assessment Model - Edition 2

DCAM stands for Data management Capability Assessment Model. DCAM is a model to assess data management capabilities within the financial industry. It was created by the EDM Council in collaboration with over 100 financial institutions. This presentation provides an overview of DCAM and how financial institutions leverage DCAM to improve or establish their data management programs and meet regulatory requirements such as BCBS 239. Also the benefits of DCAM are described as part of this presentation.

1. Strategic Planning for Data Management Introduction to DCAM (Data Management Capability Assessment Model) July 2018

2. Introduction – About DCAM and EDM Council Benefits of DCAM General Benefits Comparability and DCAM Benchmark 360° view on data management Backup Company Snapshot of Element22 and DCAM related services and products Reference Information and Links for DCAM relevant information Contents T able of Contents 2

3. DCAM is a formal framework for data management in the financial industry developed by the EDM Council 3 Data Management Strategy Data Management Business Case Data Management Program Data Governance Data Architecture Technology Architecture Data Quality Data Control Environment Components (8) Capabilities (36) Sub-capabilities (112) Objectives (306) The Data Management Capability Assessment Model (DCAM) is a formal framework against which current data management capabilities are assessed using a consistent scoring model. 1 2 3 4 5 6 7 8 1: Not Initiated 2: Conceptual 3: Developmental 4: Defined 5: Achieved 6: Enhanced  Capabilities are disorganized and performed on an ad hoc basis  Initiated at the planning stages. Data Management Practices are Instance-based Engagement model being implemented. Data management practices are linked to organizational objectives   Business users taking active role. Data management practices are linked to organizational objectives Data management capabilities are embedded into operations Data management capabilities are embedded into the culture of the organization Created based on practical experience from 150 participants from leading institutions and CDOs Capabilities orientation : Not done In process Capability achieved Capability enhanced Each Component is defined by a set of Capabilities and Sub-Capabilities Each Sub-capability is assessed by a series of capability objectives Introduction What is DCAM?

4. Component Scope of Coverage Data Management Strategy Defines the elements of a sound data strategy, why it is important and how the firm needs to be organized for sustainable implementation Business Case/Funding Model Addresses the creation of the business case, its accompanying funding model and the importance of engaging senior executive stakeholders Data Management Program Identifies the organizational requirements needed to stand up a sustainable data management program Data Governance Defines the operating model and the importance of policies, procedures and standards as the mechanisms for alignment among stakeholders Data Architecture Focuses on the core concepts of “data as meaning” and how data is defined, described and related (d ata domains, metadata, critical data elements, taxonomies, common language/ontology) Technology Architecture Addresses the relationship of data with the physical IT infrastructure needed for operational deployment (integration into operational environments) Data Quality Establishes the concept of fit-for-purpose data and defines the processes associated with establishing both data control and supply chain management Data Control Environment The Data Control Environment refers to the process by which the data assets of a firm are managed in order to realize their maximum value. There are three elements of the control environment: DCAM has been organized into 8 components (categories), 36 capabilities and 112 sub-capabilities 4 Introduction What is DCAM?

5. DCAM is defined and managed by the EDM Council, which was formed by the Global Financial Industry to Elevate the Practice of Data Management Membership 1 60+ global member firms with over 6000 professionals Mission Elevate the practice of data management through best practices and data standards, and through industry and regulatory engagement Formation Established in 2005 as a 501(c)(6) non-profit trade association Neutrality Neutral business forum for all segments of the industry (financial institutions, vendors, consultants and regulators) Coverage Global coverage across major financial centers in North America, Europe and Asia EDM Council Affiliations FRAC - Financial Research Advisory Committee Member ISO TC68/Working Group 5 OFR - Chair of the Data & Technology Subcommittee of the US Treasury’s Office of Financial Research LEI Steering Committee CFTC - Member of the Technical Advisory Committee (TAC) for the Commodity Futures Trading Commission Financial Stability Board - Member of the Private Sector Advisory Group OMG - Member of the Board of Advisors for the Co-Chair of the Object Management Group’s (OMG) Financial Domain Task Force and Chair of the OMG Finalization Task Force Open Financial Data Forum - Chair Data Transparency Coalition Ontolog Forum - Board of Trustees 5 Introduction Who is EDM Council?

6. Introduction EDM Council is guided by a board comprised out of data executives throughout various types of institutions in the financial industry 6 Who is EDM Council?

7. The EDM Council has over 160 member firms with over 6000 professionals, ranging from financial institutions, service providers, consulting firms to data/technology vendors Introduction 7 Who is EDM Council?

8. DCAM is available via , a cloud-based platform to streamline the assessment and analytics, review progress through the time and benchmark against peers. https://dcam.pellustro.com/ 8 Introduction What is Pellustro ? Analyze Benchmark Define Assess 2 3 4 1

9. Benefits To understand current state of DM capabilities Firms use data management assessments based on industry standard models like the DCAM to clearly understand the current state of data management. Firms leverage the project to clearly communicate strengths and priorities to stakeholders (board members, CEOs, management, employees and regulators). Firms leverage the DCAM framework to establish common terminology for discussing data management within the organization and to help educate non data management professionals about data management capabilities. To have a Strategic Plan to improve data quality Firms undertake strategic planning based on DCAM to quickly build an actionable strategic plan that is grounded in a holistic understanding of strengths, weaknesses, best practices and enterprise priorities . To know which DM investments are most important Firms perform assessments based on DCAM to prioritize investments to improve data management with greater clarity on which investments will have the greatest impact on targeted capabilities and business goals and support the business case for funding. To baseline, measure, analyze and report progress Firms conduct regular assessments based on DCAM so they can monitor and report data management improvements to stakeholders, data consumers and regulators in a manner that is consistent and aligned to industry standards . Ongoing assessments are also used to objectively measure and demonstrate the impact of data management practices and programs . To benchmark against peers and within the firm Firms can utilize assessments based on the DCAM to benchmark specific capabilities, locations and organizational units against each other to understand internal leading and lagging practices. As the industry completes more assessments, firms will be able to leverage DCAM assessments to benchmark capabilities against peer organizations . Examples Common Reasons 9 There are several compelling reasons to leverage DCAM

10. DCAM enables Benchmarking against industry peers, the financial industry or your scores from previous assessments (capability & sentiment) to demonstrate current state & progress 10 Benefits Benchmark your firm’s capabilities against best practices and progress over time Industry Peer group assessment on data management capabilities Compare your firm to industry benchmark from EDM Council to see where your capabilities stand Analyze the state of data management in the financial industry online in Pellustro Comparability https:// benchmark.pellustro.com /

11. Benefits Statements Components Our organization has a defined and endorsed data management strategy The goals, objectives and authorities of the data management program are well communicated Stakeholders understand (and buy into) the need for the data management program Data Management Strategy 4. The funding model for the Data Management Program is established and sanctioned The costs of (and benefits associated with) the Data Management Program are being measure Business Case/Funding Model 6. The data management program is established and has the authority to enforce adherence The data management program is sufficiently resourced Data Management Program 8. Data governance structure and authority is implemented and communicated Governance “owners” and “stewards” are in place with clearly defined roles and responsibilities Data policies and standards are documented, implemented and enforced The “end user” community is adhering to the data governance policy and standards Data Governance 12. The business meaning of data is defined, harmonized across repositories and governed Critical data elements are identified and managed Logical data domains have been declared, prioritized and sanctioned Data Architecture 15. Technology standards and governance are in place to support data management objectives The data management program is aligned with internal technical and operational capabilities Technical architecture is defined and integrated Technology Architecture All data under the authority of the Data Management Program is profiled, analyzed and graded Procedures for managing data quality are defined, implemented and measured Root cause analysis is performed and corrective measures are being implemented Data Quality End-to-end data lineage has been defined across the entire data lifecycle Data management operates collaboratively with existing enterprise control functions Data Control Environment EDM Council defined 22 statements and aligned them with DCAM for the DCAM Benchmark 11

12. Benefits Data management maturity in the financial industry is at maturity 3.23 as of July, 2017 Besides solid progress on Data Governance and Program, data is still not trustable About the Benchmark 150+ Institutions Biennial Study 22 Statements 209 Participants Started in 2015 Latest as of July, 2017 5 major problems areas Metrics 2.7 The costs of (and benefits associated with) the data management program are being measured Adherence   3.0 The end user community is adhering to the data governance policy and standards Meaning 3.0 The business meaning of data is defined, harmonized across repositories and governed Lineage 2.8 End-to-end data lineage has been defined across the entire data lifecycle Profiling 2.6 All data under the authority of the Data Management Program is profiled, analyzed and graded More information about the state of data management in the financial industry 12 Results of 2017 DCAM Benchmark

13. Benefits 13 DCAM provides a 360° view on data management by combining an expert, evidence-based capability assessment with sentiment index and an industry benchmark 360° view on data management 2017 Capability Assessment Sentiment Assessment Objectivized expert opinion about the state of Data Management Capabilities Data Management Capabilities perceived by the Stakeholders, Producers and Consumers 360° view on Data Management Capabilities Industry Perspective Data Capabilities benchmarked with industry and peers Management Assessment Objectivized stakeholder opinion about the state of Data Management Capabilities 112 Sub-Capabilities of DCAM 22 Statements of DCAM Benchmark 22 Statements of DCAM Benchmark 36 Capabilities of DCAM

14. 14 Reference Information Resource Title and Link Standstill in Data Management? Metrics, Adherence, Meaning, Lineage and Quality offset solid progress on Data Governance http://www.element-22.com/standstill-in-data-management-metrics-adherence-meaning-lineage-and-quality-offset-solid-progress-on-data-governance/ 2017 DCAM Data Management Benchmark Data Now Available In Pellustro http://www.element-22.com/2017-dcam-data-management-benchmark-data-now-available-in-pellustro/ Industry research finds significant progress in data governance, but major challenges in data quality remain http://www.element-22.com/industry-research-finds-significant-progress-in-data-governance-but-major-challenges-in-data-quality-remain/ Financial Institutions Making Progress on Data Objectives Associated with Regulatory Mandates http://www.element-22.com/financial-institutions-making-progress-on-data-objectives-associated-with-regulatory-mandates/ Glass Half Full: EDMC Benchmarking study indicates solid progress but a long road to robust data management lies ahead http://www.element-22.com/glass-half-full-edmc-benchmarking-study-indicates-solid-progress-but-a-long-road-to-robust-data-management-lies-ahead/ About DCAM Official Web Site of DCAM from the EDM Council http:// www.edmcouncil.org / dcam Data from the EDM Council’s 2015 Data Management Industry Survey that was based DCAM can now be accessed and analyzed at no cost in Pellustro https:// benchmark.pellustro.com /#/campaigns/ dcam About EDM Council Official Web Site of the EDM Council http://www.edmcouncil.org/edmcouncil About Pellustro Official Web Site of pellustro https://pellustro.com/dcam/ Qualitative assessments enable just-in-time policy adherence measurement and early issue detection http://www.element-22.com/qualitative-assessments-enable-just-in-time-policy-adherence-measurement-and-early-issue-detection/ Further Reading Material about the State of Data Management, DCAM and EDM

15. Experienced leadership Predrag Dizdarevic Edward Hawthorne Methea Tep Rohit Mathur Thomas Bodenski CEO of GoldenSource President of Capco Reference Data Services CTO and CIO at Capco External partner in Leading Fintech Private Equity Fund Founder and Lead of Capco Investment & Wealth Management Practice Operating Model Transformation and Strategy Consulting Partner at Capco EVP of Managed Data Services and Data Utility at SmartStream COO of Capco Reference Data Services COO of Iverson Global Lead of Enterprise Data Practice at Headstrong Architect of KYC utility platform Owner - Architect for Genpact’s 'Remediation as a Service' CEO/Founder of Foxeye (consultancy focused on trading, asset management and treasury) Global Head of Front Office Services at State Street IFS Leader of industry initiatives Leading participant in the design, execution and analysis of financial services i ndustry benchmarks and surveys on data management capabilities with the EDM Council. Leader of Data Quality industry survey , addressing all aspects of data quality from strategy to architecture. Leading industry initiative to create a standard approach to quantify and monitor data quality . Major contributor to the formulation of the CMMI Institute’s Data Management Maturity (DMM SM ) Model 1.0 and to the EDM Council’s next generation data management model – the Data Management Capability Assessment Model (DCAM) . One of the EDM Council’s first DCAM Authorized Partners and creator of the first cloud-based platform for DCAM assessments . Organizer and sponsor of industry Chief Data Officer forums and events to promote executive discourse on industry issues and solutions . Element22 overview We are the leading data management technology and advisory firm focused on the financial services industry. We empower institutions to achieve more with data by measuring data capabilities and delivering quantifiable improvements . We offer an array of specialized products and expert consulting services to help firm’s advance information management . We are the leading provider of data management assessments based on the EDM Council’s Data Capability Assessment Model (DCAM). Our founders and team offer deep domain expertise as recognized industry practitioners and executives. About Element22 15 Element22 – Unlocking the power of data

16. Solutions A focused solution to develop a strategic plan for enterprise data management in 6 weeks with prioritized recommendations to better service business needs that incorporates EDM Council DCAM capability and sentiment Assessments. A cloud-based platform for quantifying the views of stakeholder and SME communities using structured, domain-specific models (such as BCBS 239 preparedness) that yields detailed analytics and benchmarks to make better decisions . An innovative data quality measurement solution that combines uniform and easily comparable quality metrics and measurements with visualization and dynamic analysis of the results, supporting continual monitoring and benchmarks. It includes collaborative, curated cloud-based Data Rules Library based on the data quality rules of the ultimate source (e.g. exchange, issuer) with comprehensive rules search and grouping capabilities and intuitive rules design and script-based execution. Clients Asset Managers Pension Plans Hedge Funds Broker Dealers Investment Banks Wealth Managers Asset Servicing Firms Clearing Utilities Rating Agencies Data Vendors Index Providers Software Vendors Data Strategy, Governance and Stewardship Defined and implemented enterprise data management strategy and change programs . Defined and operationalized d ata governance organization structures, policies, procedures, roles & responsibilities. Operations Design and Optimization Built global data operations organizations : defining org structures, roles & responsibilities, processes and procedures. Optimized data operations organizations based on industry best practices to ensure ongoing compliance and quality. Business Glossaries, Data Dictionaries, Taxonomies and Ontologies Developed full methodology for initial build, maintenance and governance of business vocabulary and taxonomy. Established common languages and business glossaries; built data dictionaries and taxonomies. Defined Critical Data Element (CDE) selection criteria. Defined and led CDE selection processes. Selection of Data Management Tools and Data Feeds Defined and managed RFP process for data management technologies, i.e. Multi-Domain MDM selection including POC. Optimized data sourcing based on specific priorities, risk and business context. Architecture and Platform Design Developed target system architecture, transition and integration strategies for data management s olutions. Designed architectures detailing components, integrations and business processes for data management. Data Quality Strategy, Metrics and Rules Developed data quality strategy, metrics, rules and assurance processes by defining relevant dimensions of data quality, their measurement approach and CDEs. Applied specific data quality rules for CDEs and DQ dimensions. Monetization of data-related assets Assess and validate the value of services, technologies, and data offered by the organization to internal and external clients Define go-to-market strategies, approaches, and branding to monetize existing data-related assets Advise buyers or sellers on the acquisition or sale of data-related assets including software, content, or entire organizations About Element22 16 Innovative solutions for effective data management

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