1 / 42

Data Management in Banking

Data Management in Banking . The key to revenue growth, compliance, and risk management. Mona Leung, Chief Financial Officer, Alliant Credit Union David M. Wallace, Global Financial Services Marketing Manager, SAS. Agenda. Data and Information Management Analytics and Big Data

annelise
Download Presentation

Data Management in Banking

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Data Management in Banking The key to revenue growth, compliance, and risk management Mona Leung, Chief Financial Officer, Alliant Credit Union David M. Wallace, Global Financial Services Marketing Manager, SAS

  2. Agenda • Data and Information Management • Analytics and Big Data • Best Practices and Recommendations • Alliant Credit Union Perspective

  3. Data Management

  4. Data Management Information

  5. What is Information Management? • Strategy • STRATEGY & IMPLEMENTATION SUPPORT • Governance • INFORMATION GOVERNANCE • ANALYTICS MANAGEMENT • DATA MANAGEMENT • DECISION • MANAGEMENT • Capabilities Unified data management capabilities that include data governance, data integration, data quality and MDM Decision management services that include business rules and workflow that facilitates integration of the information services into the business systems Analytics management that includes model management, deployment, monitoring and governance of the analytics information asset

  6. Information Management Landscape IT PROJECTS OPERATIONAL SOLUTIONS BUSINESS SOLUTIONS Deposits, Lending, Bill Pay Brokerage & Wealth Treasury Risk & Fraud Finance & ALM SalesforceAutomation Customer Service Optimization Predictive Modeling Forecasting Statistical Analysis Drilldown Reporting Data Migration Data Consolidation Data Synchronization Data Quality Data Services Data Governance Master Data Management Data Quality Data Integration, Connectivity, Federation Broader Data Foundation Customer Data Customer Hub Customer Data Product Hub Unstructured Unstructured Risk Hub Cloud Big Data EDW ERP

  7. Data Management and Business Analytics “…the broad use of data andquantitative analysis for decision-making within organizations. It encompasses query and reporting, but aspires to greater levels of mathematical sophistication. It includes analytics, of course, but involves harnessing them to meet defined business objectives. Business analytics empowers people in the organization to makebetter decisions, improve processes and achieve desired outcomes. It brings together the best of data management, analytic methods, and the presentation of results—all in a closed-loop cycle for continuous learning and improvement.” Source: Thomas H. Davenport, The New World of Business Analytics, March, 2010

  8. Analytics and Big Data

  9. Our Perspective: Big Data is RELATIVE not ABSOLUTE OUR PERSPECTIVE Big Data When volume, velocity and variety of data exceeds an organization’s storage or compute capacity for accurate and timely decision-making

  10. The Four V’s of Big Data

  11. Analytics: Solving the Big Issues Source: Bloomberg Business Week, The Current State of Business Analytics: Where Do We Go From Here? August 2011. n = 930.

  12. Challenges: Too Much Data, Resources, Skills, Right Data What are your organization’s two biggest challenges in extracting value from data? Select up to two. (% respondents) Source: Economist Intelligence Unit, Big data: Harnessing a game-changing asset, September 2011. n = 586. Graph shows only financial services responses.

  13. Concerns: Customer Data Consolidation, Real-time Data, Data Privacy TDWI Research, Customer Analytics in the Age of Social Media, Q3 2012. n = 390

  14. Value of Speed Where has your organization benefited from increases in the speed at which data can now be processed? Where could it see benefits? Source: Economist Intelligence Unit, Big data: lessons from the leaders, September 2012. n = 752. Graph shows only financial services responses.

  15. Value of New Data Sources: Email, Mobile, Web, Social Media Source: Economist Intelligence Unit, Big data: Harnessing a game-changing asset, September 2011. n = 586.

  16. Ready Access to Data and Analytics Tools Source: Bloomberg Business Week, Making Business Analytics Work: Lessons from Effective Analytics Users, May 2012. n = 930.

  17. Key Findings: The State of Big Data Management • There is a strong link between effective data management strategy and financial performance. • Extracting value from big data remains elusive for many organizations. • Many companies struggle with the most basic aspects of data management, such as cleaning, verifying or reconciling data across the organization. • Companies that are furthest along the data management competency continuum—strategic data managers—provide a useful model for how organizations will need to evolve if they are to extract and utilize valuable data-driven insights. Source: Economist Intelligence Unit, Big data: Harnessing a game-changing asset, September 2011. n = 586.

  18. A flexible enterprise architecture that supports many data types and usage patterns • Upstream use of analytics to optimize data relevance • Real-time visualization and advanced analytics to accelerate understanding and action • Common analytical framework across the enterprise Innovative Strategies for Big Data Analytics

  19. IMPACT SPANS THE ENTIRE ORGANIZATION Trusted, analytical-based decisions are needed across the organization Trusted, analytical-based decisions are needed across the organization

  20. Integrated Marketing Management: Data is the Foundation Consistent Customer Experience Channels Departments In Person Call Center Merchandising Finance Marketing Social Mobile Online Risk Customer Service Direct Mail Optimization Radio TV Corporate Affairs Operations ? ? ? ? ? ? Performance Management Marketing Communications Mix MarketingDecisions Operations Management & Strategy Descriptive CustomerAnalytics Predictive CustomerAnalytics CustomerExperience & Events Customer Profitability & LTV Customer Risk / Credit Social & NetworkAnalytics Insights Marketing Analytics DataManagement Information Management Other ERP CRM EDW Online Social

  21. Risk Management Modernization RISK REPORTING MEASUREMENT AND MONITORING INTEGRATION RISK INFRASTRUCTURE MODEL MANAGEMENT RISK DATA

  22. Risk and Finance Integration RISK AND FINANCE INTEGRATION • Last Reported/Actuals • Available Capital • Required Capital • PDs, LGDs, EaDs • Balance Sheet Items • Bond & Equity • Funds • Business Plan • Decided Expansion • Market Growth • Market Share Growth • Product Mix • …. • Macro-scenarios • Calculation • Sensitivities • Regression • Consolidation • Risk Aggregation • Reports • Full P&L • Available Capital • Regulatory Cap • Economic Cap • Capital Ratios

  23. Best Practices and Recommendations

  24. Key Recommendations: Data Management Optimize decision making to gain competitive advantage Manage data as a strategic information asset for business value

  25. Strategy Recommendations: High-PerformanceData Management for Advanced Analytics • Apply advanced analytics to enable more intelligent decisions. • Enable BI systems and other applications to consume analytics. • Reduce latency between data capture, analysis, and business execution. • Evaluate in-database and in-memory analytics and grid computing to increase scale and performance. • Decrease data movement to save steps in preparing data for analysis. • Understand workloads so you can match technology options with performance requirements for analytics. TDWI Research, Seven Keys to High-Performance Data Management for Advanced Analytics , December 2011.

  26. Lessons from Strategic Data Managers • They select the most appropriate data to make decisions, and use a high percentage of the data they collect. • A C-level executive runs their data operations. • They invest heavily in all aspects of data management, especially ensuring accurate, complete and integrated data. • They explore emerging data sets for potential value. Source: Economist Intelligence Unit, Big data: Harnessing a game-changing asset, September 2011. n = 586.

  27. 5 Stages of Maturity Source: Thomas H. Davenport, Competing on Analytics

  28. Alliant Credit Union Perspective

  29. Realities of Data Management Application Infrastructure Revenue Performance Management IT Strategy Revenue Productivity Risk Management Productivity Decision Making Culture Talent Risk Management

  30. Data ManagementRevenue and Productivity Customer Acquisition and Penetration Tools Results Revenue Productivity Risk Management

  31. Data ManagementRevenue and Productivity Customer Acquisition and Penetration Tools Results Revenue Productivity Risk Management

  32. Data ManagementRevenue and Productivity Asset Optimization and Cost Efficiency Tools Results Revenue Productivity Risk Management

  33. Data ManagementRisk Management Credit Risk Enterprise Risk Management Revenue Productivity Risk Management Process Quantification Market Risk Operation Risk

  34. Data ManagementRisk Management Credit Risk Expected Loss Unexpected Loss Revenue Productivity Risk Management Forecasting Planning

  35. Data ManagementRisk Management Market Risk Expected Loss Unexpected Loss Revenue Productivity Risk Management Forecasting Planning

  36. Data ManagementRisk Management Operation Risk Expected Loss Unexpected Loss Revenue Productivity Risk Management Forecasting Planning

  37. Realities of Data Management Application Infrastructure Revenue Performance Management IT Strategy IT Strategy Talent Decision Making Culture Performance Management Productivity Decision Making Culture Talent Risk Management

  38. Data Management InfrastructureIT Strategy Defined RoadmapHuman Capital PlanHardware/Software Solutions Capital Plan Systems Core 3rd Party Processors External Customer Data Operational Data Store Operating Data Marts Business Users IT Strategy Talent Decision Making Culture Performance Management Customer Accounting User Interface Data Warehouse Transaction Dashboard

  39. Data Management InfrastructureTalent At All Levels Recruitment and Retention IT Strategy Talent Decision Making Culture Performance Management

  40. Data Management InfrastructureDecision-Making Culture Hierarchical Open What’s Your Culture? IT Strategy Talent Decision Making Culture Performance Management

  41. Data Management InfrastructurePerformance Management What’s Your Practice? Shared Objectives Revenue & Risk Line & Staff IT Strategy Talent Decision Making Culture Performance Management Incentive Programs Scoreboards Aligned across different groups Balanced Scorecard Integrated Goal Setting Operational Financial Strategic

  42. Questions?

More Related