THE SECRETS TO SUSTAINABLE REGULATORY COMPLIANCE

Transcription

1 THE SECRETS TO SUSTAINABLE REGULATORY COMPLIANCE Realizing value from data governance Simon Hankinson Market Manager, Financial Services May 3, Collibra Collibra Inc

2 Value is in the Eye of the (Issue) Beholder Financial services companies are prioritizing regulatory reporting data governance business cases Data governance alone rarely makes a compelling business case Data governance must be aligned to business priorities and sponsored by the business Most common current financial services business case is to achieve relief from regulatory pressure, especially CCAR Increased need to improve operational efficiency 2 Collibra 2017

3 Value is in the Eye of the (Issue) Beholder Financial services companies are prioritizing regulatory reporting data governance business cases The biggest value is often enabling self-service analytics and reporting Financial services rarely recognize the need for governance for data lake, data warehouse, and other big data initiatives 3 Collibra 2017

4 Organizations Want to Reduce the Time to Find Data They Can Trust BI analytics is the top priority for nearly 80% of CFOs. Their needs are: More accurate reports Saving time and money Being able to easily share data Despite spending more than $2bn per year, CFOs report that most BI projects are: Too tactical Focus too much on technology Do not address the fundamental issue of data quality and consistency 4 Collibra 2017

5 Illustration: Time Wasted Finding Data Example: 15 s involving 12 people over nearly 31 hours 11:18am 2:08pm 2:40pm 3:52pm 8:48pm 10:59am 1:37pm 6:02pm 2:03pm 2:29pm 2:52pm 4:54pm 8:25am 11:27am 5:30pm How do we define Customer Lifetime Value Metric? Here is how we define Customer Lifetime Value A Customer is someone we have done business with In Finance, Customer Lifetime Value is calculated based on who creates the report There is a new focus in creating definitions through the Data Governance Council There is no single source of truth, here s a recommendation for defining the Customer Lifetime Value Metric Forward to an analyst Analyst provides a calculation for Customer Lifetime Value in 1 Business Lead Analyst Analyst Business Lead Analyst Analyst Analyst Analyst Concurrence on the recommendation in 6 Reiterating the need for a certified definition of the calculation Business leads coordinating Explanation on where the business is with defining how customer lifetime value should be calculated Business lead contacts Enterprise Data Governance Office Detailed explanation of the definition of customer lifetime value calculation Align this to the Data Governance POC Analyst Business Lead Business Lead Business Lead Business Lead Analyst Business Lead 5 Collibra 2017

6 Information Governance Maximizes the Value of Data High Find Earnings Trust Growth Value Low Understand Data Management (IT) Documentation lineage, glossary, dictionary, etc. Data Governance (IT, Business) Working groups agree standards, definitions, etc. Report Governance (IT, Business, Executives) Share easy to find, trustworthy information to make decisions Regulatory Risk management 6 Collibra 2017 Business Involvement

7 Be Realistic about the Challenges to be Successful No one wants to own data Skepticism that this time its different Information and reports are valuable, not data Solving process - not technology - issues Requires process change 7 Collibra 2017

8 Adoption is Critical: Organizations still Struggle to Sustain Programs Govern what matters Establish path of least resistance Easy to use Reliable results Build peer pressure certification/watermark Right-size governance Minimize manual steps Integrate data governance data sources 8 Collibra 2017

9 What are the Keys to Sustaining Data Governance? Data governance needs to be adopted as business-as-usual by the business There are recurring characteristics of successful data governance programs. They: Have authority Are sponsored and owned by the business Use technology that is easy to use by business and IT Integrate processes, tools, and documentation to each other and to an operating model Automate workflow and issue management, replacing SharePoint, excel, Word, etc. Measure and report progress Provide transparency to data, metric, and report users on the data that matters 9 Collibra 2017

10 Value is in the Eye of the (Issue) Beholder so Focus on the Data that Matters The framework aligns information needs to organization strategy Ties the value and priority of data to strategic objectives Promotes business sponsorship and adoption of data governance by aligning data governance to organization priorities Strategy Objective Objective Activities/projects Required information, reports, metrics and data 10 Collibra 2017

11 Prioritized Information Aligns to Business Strategy and Objectives Strategy Objective Activities/Projects Reports/Metrics/Data Growth/Market Share Grow transaction income and fees Integrate delivery channels Optimize customer experience Increase accessibility (branches, internet/digital) Develop high-performing, customer-centric culture Customer 360 Product analysis Digital/Big data analytics Earnings Increase EPS Maintain return on equity Improve efficiency ratio Grow cost-effective, sustainable deposit base Tightly manage expense base Fees, margin, revenue, and expenses reports and metrics Asset and Capital Management Capital and resource allocation Strong balance sheet Align and manage capital, liquidity, and risk appetite Balance business mix Grow loan book responsibly Balances, ALM, liquidity reports and metrics Risk and Regulatory 11 Collibra 2017 Responsible management of reg and compliance risk Enhance regulator/ legislature communications Embed risk management throughout the organization Build strong relationships with regulators Risk and Regulatory Reports and metrics

12 Capabilities to Enable Information Governance Find Report Governance Catalog Data sharing agreements/slas Data governance/quality reporting Data/reporting certification and attestation Data helpdesk Scorecards Trust Data Governance Reporting Roles and responsibilities Policies Operating model Data sharing agreements/slas Issue management workflows Authority and voting/approval Data/report certification and attestation Data governance process flows Data ownership Data helpdesk Data governance/quality reporting Integration / Collibra Connect Collibra Understand Data Management Data glossary Data dictionary Critical data elements Data lineage & traceability Controls Metadata (business & technical) Reference data Report catalog KPI & metrics catalogs 12 Collibra 2017

13 Collibra for Enterprise Analytics & BI Report & Data Catalog One stop, searchable access to find reports across existing BI and reporting silos Track and automatically maintain lineage from source to target, transformation logic, etc. Data Lineage and Metadata Document business and technical lineage, metadata, enterprise systems, and data flows Track and automatically maintain lineage from source to target, transformation logic, etc. Data Quality Data quality results link data quality scores with reports and business views of data Business rules track quality scoring and on boarding of business rules Reference Data Management Manage, govern, and deploy enterprise reference data, lists, and cross maps Issue management, tracking, and remediation plan workflows Issue Management Operating Model Initiate workflows and monitor issue resolution for enterprise data with automatic escalation Issue management, tracking, and remediation plan workflows Defined data governance roles & responsibilities Integration across existing data management tools (including Excel, EDW, and BI) Process flows tied to working groups by report/domain/data elements with automated workflows 13 Collibra 2017

14 Getting a Data Governance Program Started Principles Scope: Start small Relevance: Identify one critical report/process Approach 1. Target Operating Model 2. Data Domains Activities Define enterprise roles & responsibilities Define LOB roles & responsibilities Design governance structure Define data domains Assign prioritized domain owners Value: Prove value of data governance prior to issuing policy and standards Operating Model: Establish roles, responsibilities, and authority Optimization: Consolidate data sources; automate 14 Collibra End to End Supply Chain 4. Controls Measurement 5. Authoritative Data Sources 6. Policy & Standards Identify key report inventory Identify critical data elements Document CDE supply chain Define key controls, metrics, and thresholds Develop reporting and feedback processes Execute controls and data measurement Identify key data and controls Identify target ADS for key data Assess target ADS against controls and requirements Develop ADS adoption roadmap Document roles and responsibilities Facilitate alignment with data management strategy Execute enterprise roll-out