Financial Services. Flexing Data Muscles for New Challenges The Financial Services Data Warehouse Oracle Open Day, Istanbul Nov 1, 2011

Transcription

1 Financial Services Flexing Data Muscles for New Challenges The Financial Services Data Warehouse Oracle Open Day, Istanbul Nov 1, 2011

2 The following is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions. The development, release, and timing of any features or functionality described for Oracle s products remains at the sole discretion of Oracle.

3 Agenda FSDWH History New/old issues, new approach The Oracle answer

4 FSDWH History <Insert Picture Here>

5 Experience from the past Many financial institutions-particularly in this region-have already significant DWH experiences, not necessarily positive, due to a series of reasons: Inadequate offering DWH provided without physical data model DWH not tested in existing business environment Products still under development Poor planning Limited understanding of the concept of phased approach Unrealistic expectations with limited fall back plan Technical and HR constraints Common spaghetti architecture Limited amount of available data and of poor quality Lack of project management and core technical skills Data knowledge limited and application documentation incomplete or not updated 2011 Oracle Corporation - Proprietary 5

6 First Generation DW Design for FSI - Concept Warehouse as a Central Store of all Business Data 1 Develop/source Enterprise Logical Data Model Repeat these steps for each data source or new requirement. Banking Trading 2 Map to Source and Physicalize Hardware, middleware, database software, management and administration tools, and supporting software will also need to be acquired and integrated along the way Wealth 3 Inbound ETL ERP Account Txns CRM Contract Account Product HCM Customer Customer Product Org Data Warehouse 2011 Oracle Corporation - Proprietary 6

7 First Generation DW Design for FSI Reality 1 Develop/source Most logical data models are overly Enterprise abstract and Logical conceptual Data Model with no defined end use 5 ETLs to marts may bypass the warehouse entirely Risk Report1 RAPM? Banking Trading Wealth 2 3 Mapping to Source exercises and Physicalize often become a boiling of the ocean exercise Source Inbound ETL can be overly complex with data quality often focused only on technical checks 7 Profitability Inconsistencies appear data no longer trustworthy Customer Report1 Report2 Report3?? ERP Account Txns Report4 CRM HCM Customer Product Org Contract 4 Product Customer Account Ad-hoc ETL s needed to get data to analytical applications traceability can be broken Data Warehouse 6 Compliance Capital? Report5?? Report6 Proliferation of ETL and data mart silos as new needs appear more cost, complexity and overhead 2011 Oracle Corporation - Proprietary 7

8 Where is the industry today? A Shift in Thinking Dbms2.com (Monash Research) TDWI Research Report Next Generation Data Warehouse Platforms Information Week 2011 Oracle Corporation - Proprietary 8

9 New/Old issues, new approach <Insert Picture Here>

10 Analytical Applications Infrastructure Challenges Current Situation Inability to easily combine analytics from Risk, Performance Management and Finance functions resulting in fragmented views of bank health Stovepipe analytical solutions with inflexible, non-modular infrastructure are unable to scale in response to increasing internal and external demands Lack of transparency and traceability within analytical processes resulting in reduced trust in analytical results Lack of a centralized, consistent operations and security model across analytical applications 2011 Oracle Corporation - Proprietary 10

11 Analytical Transformation in FSI Today s reality Managing to Financial Performance Driving to a profitability culture Traditional performance measures not enough More detailed and transparent understanding of profitability Risk Adjusted Performance Mandatory Understanding compliance in the context of risk and performance key to increasing regulatory demands and competitive advantage Increasing Regulatory Pressure Shift from timeliness and quality of submissions to how business operates Increasing frequency of regulatory involvement i.e. stress testing Deeper and deeper understanding of what goes into the submissions 2011 Oracle Corporation - Proprietary 11

12 Need for Speed Analytical Use cases in Financial Services Trading Desk Analytics Fraud, AML Trade Surveillance Riskbased pricing Real-time Marketing and offers Instrumen t Pricing Algorithmic Trading, HFT The general trend here is clear Far more data Subject to far more complex analytical Spanning processing the With far greater spectrum of speed accuracy In rapidly reducing time windows and complexity Performance Measurement Enterprise-wide Risk Computations and Stress Testing Regulatory Reporting Retail Customer Behavior Analysis Analytical Complexity 2011 Oracle Corporation - Proprietary 12

13 How would your data warehouse manage If your users started running more adhoc queries If you needed to use more complex analytics against bigger datasets? If your users demanded better performance? 2011 Oracle Corporation - Proprietary 13

14 How would your data warehouse manage If you wanted to store 15 years worth of detailed data? If you needed to better manage your storage requirements? If you needed to reduce your total data center costs? 2011 Oracle Corporation - Proprietary 14

15 Architectural evolution PROLIFERATION OF SILOS Applications spring up throughout the institution, serving specific functions Manual or limited sharing of data and lack of consistency become big headaches. INTEGRATION TO THE RESCUE? Integration within and across common functions, like Risk, Performance, Compliance and CRM becomes business as usual, but to this day remains rigid, costly, hard to trace and audit, not future proof and easily broken A UNIFIED PLATFORM More than integrated a UNIFIED platform, built on common infrastructure, data models, technologies and components engineered and designed to work together now and into the future 2011 Oracle Corporation - Proprietary 15

16 The quest for performance Liquidity Risk Regulatory Capital Profitability New mandates like Basel III are driving need for ondemand answers Global events or crises have near instantaneous impact Banks need to calculate stressed results in minutes not hours Contingency funding strategies need to be iteratively tested in a practical timeframe Reporting is stressful and time consuming with little time for analysis Performance bottlenecks leave little margin for error Demand for additional submissions with modified assumptions and calculations Demand for advanced analytical practices like stress testing and what-if analyses Tighter controls, laws limiting bank fees and slower revenue growth driving need for efficiency and cost controls Need for on-demand view of costs and profitability move beyond monthly reporting requirements. Need for faster and more granular review of product performance Need to quickly response to market shifts and changing rates. Senior executives are left scrambling to bridge key limitations in Performance & Scalability Responsiveness Simulation & What-If Capabilities 2011 Oracle Corporation - Proprietary 16

17 The Oracle answer <Insert Picture Here>

18 Oracle Is Changing the Rules of the Game Unmatched Solutions Offering for FS in the Applications and Technology Vendor Landscape Unified results and metrics across dimensions. Designed for Global banks-multiple jurisdictions support. Data-quality specific to business ideas not just formats Formal GL reconciliation process. Pre-built integration with operational finance flow Mixed workload handling our structures allow this Pre-built BI apps results handling expertise (app space) Unified active metadata through entire data life cycle Complete pre-built metadata covering all analytical disciplines from day one. Hierarchies and reference data are consistent across processing and results areas. One unified warehouse covering all relevant financial services business areas. Ability for customers to use a common AAI framework to modify or create new calculation/application logic Ability to host externally developed models and execute them on GL reconciled production data for consistent outputs under base lined and stress conditions ON the DWH Extreme Performance with greater value Oracle Corporation - Proprietary 18

19 Oracle's Strategy for Financial Services Industry Delivering Complete, Open, Integrated Solutions Complete Open Integrated Comprehensive Offering Standards-Based Architecture Designed to Work Together Broad & Deep Offering Lower Cost, Lower Risk More Choice Maximizes Existing Investments Less Effort More Value 2011 Oracle Corporation - Proprietary 19

20 Analytics Analytics Oracle s Banking Footprint Oracle Third Party Governance, Risk & Compliance Risk Based Decisioning Risk Based Pricing Economic Capital/RAPM Risk Management Operational Risk Market Risk Credit Risk ALM Compliance BASEL II & 1A AML SOX Regulatory Reporting Lifecycle Management Marketing Retail Platform Internet Banking Deposits Loans Investments Payments Master Data Management Customer Data Hub Corporate Administration Enterprise GL Rich Client F/W AJAX, Web 2.0 Systems Mgmt Teller Kiosk Leasing Human Capital Mgmt Savings Call Center EBPP Mortgages Cards (Credit / Debit) Core Banking Ledger Product Hub Org Hierarchy Hub Accounting Hub Payments Hub Consolidation Projects Enterprise Technology Selling Commercial Team Selling Security Trading Customer Experience Order Mgmt Client Servicing Originating Internet Banking Derivative Pricing Channels Budgeting Profitability Mgmt Analytics Procurement Fixed Assets Private Wealth Mgmt CRM & Marketing Order Entry Platform Servicing Product and Transaction Processors Deposits Cash Integration Mgmt Loans Market Data Trade Finance Treasury Payments Portfolio Mgmt Asset Mgmt Syndicated Loans Structured Core Banking Derivatives Compliance Investor Nostro Services Recon Lock Box & Limits Leasing Custody Core Banking Trade Ledger Processing Lead Mgmt On Demand Incentive Comp Call Center Performance Mgmt Balance & Positions Fees & Commissions Compensation Clearing & Settlement Real Estate Financial Planning Database (Grid, Enterprise Content Web Services J2EE Services, ESB Memory, Embed) Mgmt Orchestration (BPEL) and Rules Engine Technology & Operations Directory Services Web Services Mgmt Identity Mgmt Access Mgmt Customer & Business Insight Customer Insight Customer Analytics Channel Analytics Marketing Analytics Performance Management Exec Analytics Profitability Analytics/RAPM Funds Transfer Pricing Operational Excellence Op Intelligence HR Analytics Analytics Platform Portal & Dashboards Business Activity Monitoring Business Process Analytics 2011 Oracle Corporation - Proprietary 20 Reconc iliation External Interfaces OFAC Check Order Market Feeds Fed Wire SWIFT POS Credit Rating ACH Other Systems

21 Oracle Financial Services Analytical Applications Performance Management and Finance Profitability Funds Transfer Pricing Consolidation Accounting Hub Credit Risk Activity-Based Costing Budgeting and Forecasting Reconciliation Analytical CRM Retail Credit Risk Corporate Credit Risk Treasury Risk Loan Loss Forecasting Hedge Management IFRS 9 IAS 32/39 RAPM Performance Management Pricing Management Customer Profitability Portfolio Analytics Marketing Analytics Service Analytics Market Risk Balance Sheet Planning Asset Liability Management Liquidity Risk Regulatory Capital Basel II Retail Portfolio Risk Models and Pooling Economic Capital Economic Capital Advanced (Credit Risk) Operational Risk Economic Capital Stress Testing ICAAP Risk Management Regulatory Compliance (Financial Crime) Anti-Money Laundering Broker Compliance Financial Services Data Warehouse Fraud Detection Trading Compliance Governance & Compliance Customer Insight Know Your Customer Channel Insight Channel Usage Channel Performance Comprehensive coverage, derived from deep core banking domain expertise, provides best of breed capabilities in key disciplines. Unified platform supports analytical intersections to address emerging Governance or and overlapping Compliance analytical needs without extensive re-wiring and rebuilding of supporting data infrastructure. Operational Risk 2011 Oracle Corporation - Proprietary 21

22 Oracle Financial Services Meets Today s Demands Financial Services Data Warehouse Analytical Applications Infrastructure (Data Quality., ETL, Metadata, Stress Testing, Modeling, Execution, etc) Oracle Calculation Engines & Statistical Models Analytical Application Processing (Within Warehouse) Hosted Statistical Models External Calculation Engines The foundation for a comprehensive analytical processing platform Can readily host both Oracle Financial Services Analytical Applications and other custom built or 3 rd party engines Sourcing Common input area for analytical processing Results Results for consumption Capabilities: Pre-built business oriented data quality and reconciliation processes Pre-built, readily deployable, end-use proven, physical data model for FSI Industry leading FS analytical applications pre-built and ready to run IN the Data Warehouse Unified and conformed model for reporting and business intelligence across all functional domains Optimized to leverage the power of EXADATA to ensure support for new analytical use cases 2011 Oracle Corporation - Proprietary 22

23 Oracle Financial Services Data Warehouse Standards Based LDM to extend Warehouse Model Core Subject Areas: Events (red): The recorded, time-stamped results of executing FS business processes Transaction is the primary concept State (grey): Current snapshot of FS organization Cumulative effect of events Contract, Account are primary concepts Party Organization Calendar The primary raw material for analytics Domain (FS)specific, and central part of the FSDM State (Contracts) Product Context Subject Areas: Related Dimensions for core data Who Party, Organization Subject Areas What Product Subject Area Where/When Geography, Calendar Subject Area Not FS specific, but customized for FS domain Transactions (Events) FS Logical Data Model Location 2011 Oracle Corporation - Proprietary 23

24 Oracle Financial Services Data Warehouse Financial Services Physical Data Model Pre-built, comprehensive and ready-to-deploy Covers all classes of FSI business data Pre-built and fully conformed to meet FS reporting needs Complete mapping between sourcing and results Analytical Applications Infrastructure (Data Quality., ETL, Metadata, Stress Testing, Modeling, Execution, etc) Analytical Application Processing (Within Warehouse) Oracle Calculation Engines & Statistical Models Hosted Statistical Models External Calculation Engines Sourcing Results Common input area for analytical processing Results for consumption 2011 Oracle Corporation - Proprietary 24

25 Oracle Financial Services Data Warehouse Common Sourcing Pre-built, comprehensive and ready to deploy One sourcing area shared across all analytical needs Segments data elements based on analytical needs Facts Financial Instrument Transaction Ledger Exposure Campaign Master Data Dimensions COA Product Org Customer Analytical Applications Infrastructure (Data Quality., ETL, Metadata, Stress Testing, Modeling, Execution, etc) Oracle Calculation Engines & Statistical Models Analytical Application Processing (Within Warehouse) Hosted Statistical Models External Calculation Engines Time Series Data (Rates, Indicators, risk factors etc) Display Codes/Master tables Sourcing Common input area for analytical processing Results Results for consumption 2011 Oracle Corporation - Proprietary 25

26 Oracle Financial Services Data Warehouse Unified Results Across All Key Analytical Areas Fully conformed dimensions for cross-functional analysis Pre-built, comprehensive and ready to deploy Eliminates data mart silos Multiple jurisdictions Results versioning Analytical Applications Infrastructure (Data Quality., ETL, Metadata, Stress Testing, Modeling, Execution, etc) Analytical Application Processing (Within Warehouse) End-use Specific Facts ALM, Basel II, Basel III RAPM, Profitability, Liquidity ICAAP, Economic Capital Shared BI Facts Oracle Calculation Engines & Statistical Models Hosted Statistical Models External Calculation Common Conformed Dimensions Engines COA Org Product Customer Sourcing Common input area for analytical processing Results Results for consumption Time Series Data (Rates, Indicators, risk factors etc) 2011 Oracle Corporation - Proprietary 26

27 OFSAA and Exadata Performance in Action What Could YOU Do With Extreme Performance Profitability on a daily basis Process (Rules Execution Across Different Rule Types) Elapsed Time Allocation Rules on Transactions (41) 1:02:01 Allocations from Ledger to Transactions (6) 14:42 Aggregation of Transactions to Ledger (6) 0:00:58 Aggregation from Transactions to Instrument (18) 1:08:00 Instrument level Allocations (42) 0:55:02 Ledger to Instrument Allocations (10) 0:25:40 Ledger level Allocations(30) 0:15:06 Instrument to Ledger Aggregations(19) 0:44:22 Total (172) 4:45:51 1 Billion Transactions. 250 Million Accounts. 172 Rules. OFSAA on Exadata Performance Test Results Confirm the Possibilities Regulatory capital in minutes not days Process ELAPSED TIME Data Load from Stage Tables to Basel Processing Tables 0:02:07 Pre-Processing of Data (for RWA Calculations) 0:16:24 Risk Parameter Estimation 0:19:49 Risk Weighted Assets (RWA) Computation 0:51:01 Total Elapsed Time 1:29:21 65 Million Exposures. Intraday liquidity analysis Process Elapsed Time Contractual Liquidity Run 0:59:42 Business As Usual Liquidity Run 0:09:19 Baseline Run 0:69:01 Stress Test Run 0:10:06 66 Million Exposures. 371 Million Cash Flows Oracle Corporation - Proprietary 27

28 Oracle Data Warehouse Solution for Typical Bank 2011 Oracle Corporation - Proprietary 28

29 Requirements & Analysis Design, Build, & Test Production & Rollout Oracle Value Proposition Time & Risk Standard DW Implementation: significant time to design, build, implement & test. Requirements & Analysis Design, Build, & Test 2+ Years Production & Rollout Oracle FS Data Warehouse: drastically shortened time to value, significantly reduced implementation risk Weeks 2011 Oracle Corporation - Proprietary 29

30 Traditional Activities Related to DW Implementation Phase Activity Typical Duration Complexity Extent of Bank Resource Involvement Requirements Conduct Business Requirements Study and create BRD 3 months High. DW vendors start from a blank sheet High Analysis Map BRD to logical model, detailed source system analysis, build data requirements 6 months High. Use cases not considered during data sourcing. High Design Create extract specs, design data quality process, create source mappings to LDM, design reconciliation process, design metadata, design OLAP & BI structures 7 months High. BI report deliverables considered long after data model design necessitating multiple iterative changes. High Build Create ETL, create DQ checks and process, create metadata repository, build reports, build manual adjustment process 6 months High. From -scratch build of customer specific DQ, metadata and adjustment processes Medium 2011 Oracle Corporation - Proprietary 30

31 Beginning With the End in Mind Gets us the data we need Required Data Elements to Ensure Relevant Outputs Can be Generated Appropriate Data Quality Checks to Ensure Sanctity of Data for Outputs Needed Reconciliation Process to Ensure Results Tally to GL Needed Value-add Computations to Produce the Outputs Desired Use Cases (Outputs) in a Given Subject Area Corporate Credit Risk Retail Credit Risk Finance, Treasury Marketing 2011 Oracle Corporation - Proprietary 31

32 Accelerating New Business Requirements The Oracle Advantage Business Solution Requirement Corporate Credit Risk Analytics Retail Credit Risk Analytics Analytical CRM/ Marketing Analytics New Data Elements Needed to Address Requirement Data Elements Already Sourced & Needed for New Solution Net New Incremental Data Elements Required 360 N/A N/A Advantage Complete clarity up-front on all data requirements to address Business Requirements 40% reduction in Data Sourcing Effort for new Solution 25% reduction in Data Sourcing Effort for new solution 2011 Oracle Corporation - Proprietary 32

33 Typical Data Warehouse implementation vs Oracle Financial Services Data Warehouse Traditional Oracle Oracle Advantage: Bank can deploy future use cases without Oracle involvement Months Phase 1 - Corporate Credit Risk Phase 2 - Retail Credit Risk Phase 3 - Marketing, Finance 2011 Oracle Corporation - Proprietary 33

34 What Could You Do? With Extreme Performance Like This Liquidity Risk Regulatory Capital Profitability Address regulator requests in minutes rather than hours or days Understand impact of global economic events as they happen Tune contingency funding strategies as events unfold Run multiple stress scenarios to fully understand complex events Collapse regulatory reporting run times to hours instead of days Turnaround regulatory resubmissions or adjustments in minutes instead of days Easily and practically perform advanced analytical practices like stress testing and what-if analyses Capture a daily view of profitability and risk adjusted performance More proactively manage your business Quickly assess the profitability of new products and programs Run your institution based on today instead of last month 2011 Oracle Corporation - Proprietary 34

35 Alfonso Asaro Director Europe Analytical Solutions Initiatives Group (Office)