Benefits of Industry DWH Models - Insurance Information Warehouse

Transcription

1 Roland Bigge Benefits of Industry DWH s - Insurance Information

2 Agenda Introduction to Industry DWH s Drivers, Challenges and Opportunities Insurance Information (IIW) Details IIW Value Proposition Annex 2

3 Core Components of Industry s Industry Data s Data s provide a structured data dictionary that defines the business terms and the resulting Intelligence data structures Industry Process s Process s provide predefined analysis-level processes, used to ensure consistency and reuse of processes and activities within the Financial Institution Industry Service s Service s provide the pre-defined analysis and design level structures to enable more consistency and reuse in the creation of Services 3

4 Value of Industry s Reduces analysis and design of functional requirements by more than 40% Accelerates stakeholder approval by 50% Supports on average 85% of data requirements Reduces time and addresses risk compared to custom-built projects by helping to reengineer processes to comply with regulatory requirements. Increases ROI by Identify opportunities to streamline and outsource processes and be more responsive to customers. Reduce time-to-market with new products, such as online portfolio management. Integrates a merger and legacy systems more quickly. Facilitates a reliable mechanism for information availability across the organization such as customer data integration. 4

5 Agenda Introduction to Industry DWH s Drivers, Challenges and Opportunities Insurance Information (IIW) Details IIW Value Proposition Annex 5

6 Challenges Facing Insurers Solvency II Enforcement of new regulations such as Solvency II and other Risk Management Initiatives Lower Cost of Data The costs of managing and providing data are high and growing Know the customer Carriers lack a unified view of their customers across divisions, subsidiaries, etc. Advanced Analytics Across the industry, analytics is being applied. Take it to the next level Compliance & Reporting Regulatory reforms are creating an increasingly complex reporting & compliance landscape Worker Productivity Cost cutting is reducing staffs to a level that puts pressure on meeting requirements Optimized Access Carriers need to provide a personalized blend of access points to support customers needs Product Management Lower premiums may not be enough to secure customers in today s market Fraud & Abuse Reducing fraud, subrogating losses, and avoiding errors improves results Prioritization Carriers need to focus attention on the most profitable customers, agents, channels Take Proactive Action Carriers can gain an advantage by being able to predict customers needs and actions. Optimize Distribution Today s customers and agents want access on their terms not the carriers 6

7 Technical and Logistical Challenges facing Insurer s Implementation Teams 1 Changing 2 Lack of 3 Needs Standards Changing 4 Information Needs Lack of Resources Engagement Need for greater business validation and engagement during requirements definition and IT led projects Terminology Inconsistent use of terminology across organization No Reference to guide requirements More Data More frequent reporting without data quality issues Increased granularity not available with current infrastructures Project expertise Projects (e.g. SII) require expertise in limited supply Limited access to business resources to define requirements Faster Deployment Pressure for early deliverables to meet tight deadlines Documentation Lack of information on data flows / reporting processes Legacy Modernization History of deferred IT investment provides challenges as new requirements emerge Cost Management Making efficient use of scarce resources Leveraging IT spend for multiple projects Competing Projects Ever increasing range of projects (regulations, operational efficiencies, customer insight) Audit & Compliance Requirements and data now need to be auditable, traceable and repeatable Better Design Drive for more reusable components rather than one off solutions 7

8 Agenda Introduction to Industry DWH s Drivers, Challenges and Opportunities Insurance Information (IIW) Details IIW Value Proposition Annex 8

9 What is IBM Insurance Information (IIW)? IBM s Comprehensive Enterprise Data model for the Insurance Industry Built through client engagements over 15 years Covers All of Insurance including both Life and P&C/General Insurance content Complete set of related models ( Vocabulary, Data, Atomic and Dimensional models) Facilitates rapid scoping and specifying of requirements Customizable to meet company specific requirements Start with one project e.g. Solvency II and then extend to other solutions areas (e.g., SOX, IFRS) 9

10 IIW core components includes Terms Enterprise-wide vocabulary of business concepts that provides an organization's view of itself and its industry. Supportive Content Grouping of terms incorporating any terminology originating from an internal or external source. Vocabulary Supportive Content IIW Data s Terms Analytical Requirements Analytical Requirements Structured requirements covering management information and regulatory needs. Data (BDM) Reference data model,normalized view of insurance business Data s Data Atomic Dimensional Atomic Data Enterprise-wide data model defines how multiple sources of data should be consolidated into a single logical data structure Dimensional Enterprise-wide repository for analytical data with star schema style dimensional data structures organized around fact entities 10

11 The Vocabulary includes Vocabulary Supportive Content IIW Data s Terms Data Analytical Requirements Analytical Requirements Structured requirements representing the answer to a particular business issue or goal that is identified at top-management level as a business opportunity, based on the analysis of business facts. By combining Measures and Dimensions, Analytical Requirements define a specific business opportunity context Allow business users to fully articulate the requirements for a piece of analysis using their business terminology. Includes regulatory requirements (e.g. Solvency II, IFRS, ) Data s Atomic Dimensional Terms Supportive Content Supportive Content is a grouping of terms incorporating any terminology originating from an internal or external source. It is used to support data structures such as regulatory reports (e.g. IAS/IFRS, Solvency II), industry standards (ACORD, HIPAA, SEPA, SEC US GAAP), business architecture standards (e.g. EPP), vendor interfaces (e.g. SAS, Fair Issac, Sendero, Oracle Financials), or legacy source systems (e.g. Underwriting systems). Industry concepts used from day to day in the running of business operations and analysis Expressed in plain business language, with no modeling or abstraction involved Mapped to the The option to link related terms with an alias to let you choose the most appropriate terms in your context Used as axes of analysis to define Analytical Requirements. 11

12 The Data includes IIW Data s Vocabulary Supportive Content Terms Analytical Requirements Data Data s Atomic Dimensional Unambiguous definition of business concepts and their relationships to insure communication across different IT projects and between the business users and the IT Conceptual view of the enterprise data with generic definitions to maximize applicability, flexibility, and reusability 12

13 The Atomic includes IIW Data s Vocabulary Supportive Content Terms Analytical Requirements Data Data s Atomic Dimensional The enterprise-wide repository of atomic data used for informational processing Fully defined logical design of data warehouse structures, with history management Partly de-normalized, for ease of navigation and performance 13

14 The Dimensional includes IIW Data s Vocabulary Supportive Content Terms Analytical Requirements Data Data s Atomic Dimensional The enterprise-wide repository of analytical data used for informational processing Star schemas supporting the Analytical Requirements Conformed Dimensions and Conformed Facts define consistency across fact tables and facilitate analysis techniques, such as drilling across Mapped to the Atomic, from which it can be populated Can be used to populate data marts. 14

15 IIW supports data warehouse and data mart deployments Vocabulary Reporting & Analysis Supportive Content Terms Analytical Requirements Data Marts / Cubes Data Data s Atomic Dimensional IIW Customer Policy Profile Extract Transform - Load Enterprise Data Claim Premiums Reinsurance Assets Underwriting Risk Applications General Ledger etc. Data Sources / Operational Systems Extract, Transform, and Load (ETL) Enterprise Data Calculation Engines Data Marts Decision Support/ Reporting 15 IIW for InfoSphere

16 Developing a data warehouse with the Industry s involves several tasks Architect + Analyst Setting-up Project Project Manager Developing Analytical Requirements Developing Terms Developing Supportive Content Developing Data Developing Atomic Developing Dimensional Data Architect + Data er 16

17 IIW Requirements Solution Templates (BSTs) 17

18 Agenda Introduction to Industry DWH s Drivers, Challenges and Opportunities Insurance Information (IIW) Details IIW Value Proposition Annex 18

19 Technical and Logistical Benefits using IIW 1 Flexibility 2 Standardisation 3 Meeting Information Needs 4 Efficient Use of Resources Engaging the Tools and Industry content makes it easier to meet business needs 85% of customers surveyed highlighted models as significant benefit Consistent Approach Leverage IIW methodology and as a reference guide to develop consistent terminology More Data 85% of model customers reported that IIW models granularity improved flexibility of DWH Resource Management IIW models and methodology accelerate requirements gathering and reduce resources required Faster Time to Value More than 50% of customers reported faster time to value when IIW model driven DWH in place Better Documentation Common tooling/ methodology and vocabulary makes it easier to consolidate reporting across data marts Legacy Modernization IIW with IBM Information Management aids the recalibration of legacy data sources to meet new information needs Cost Management On Average, customers report 15-20% cost saving 77% reported that developer productivity significantly improved Cross Project Support IIW enterprise wide coverage supports wide variety of insurance related subject areas Audit & Compliance IIW analytical requirements/ mappings demonstrate traceability from source data to report Better Design Significant benefits achievable after initial IIW project with the reuse of IIW modelling components 19

20 Agenda Introduction to Industry DWH s Drivers, Challenges and Opportunities Insurance Information (IIW) Details IIW Value Proposition Annex 20