Post on 09-May-2018
© 2013 IBM Corporation
Benefits of Industry DWH Models -Insurance Information Warehouse
Roland Bigge
02.11.2013
© 2013 IBM Corporation2
Agenda
Introduction to Industry DWH Models
Business Drivers, Challenges and Opportunities
Insurance Information Warehouse (IIW) Details
IIW Value Proposition
Annex
© 2013 IBM Corporation3
Core Components of Industry Models
Data Models provide a structured data dictionary that defines the business terms and the resulting Business Intelligence data structures
IndustryData Models
Process Models provide pre-defined analysis-level processes, used to ensure consistency and reuse of processes and activities within the Financial Institution
IndustryProcess Models
Service Models provide the pre-defined analysis and design level structures to enable more consistency and reuse in the creation of Services
IndustryService Models
© 2013 IBM Corporation4
� 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.
Business Value of Industry Models
© 2013 IBM Corporation5
Agenda
Introduction to Industry DWH Models
Business Drivers, Challenges and Opportunities
Insurance Information Warehouse (IIW) Details
IIW Value Proposition
Annex
© 2013 IBM Corporation6
Lower Cost of Data� The costs of
managing and
providing data are
high and growing
Worker Productivity
� Cost cutting is
reducing staffs to a
level that puts
pressure on meeting
requirements
Prioritization
� Carriers need to focus
attention on the most
profitable customers,
agents, channels
Know the customer� Carriers lack a unified
view of their customers across divisions, subsidiaries, etc.
Optimized Access
� Carriers need to provide a personalized blend of access points to support customers needs
Take Proactive Action
� Carriers can gain an advantage by being able to predict customers needs and actions.
Advanced Analytics� Across the industry,
analytics is being applied. Take it to the next level
Product Management
� Lower premiums may not be enough to secure customers in today’s market
Optimize Distribution� Today’s customers
and agents want access on their terms – not the carriers
Solvency II� Enforcement of new
regulations such as Solvency II and other Risk Management Initiatives
Compliance & Reporting
� Regulatory reforms are creating an increasingly complex reporting & compliance landscape
Fraud & Abuse
� Reducing fraud, subro-gating losses, and avoiding errors improves results
Business Challenges Facing Insurers
1 2 3 4
© 2013 IBM Corporation7
Technical and Logistical Challenges facing Insurer’s Implementation Teams
1 2 3Terminology� Inconsistent use of
terminology across organization
� No Reference to guide requirements
Documentation
� Lack of information on data flows / reporting processes
Audit & Compliance� Requirements and
data now need to be auditable, traceable and repeatable
Changing Business Needs
Lack of Standards
More Data� More frequent
reporting without data quality issues
� Increased granularity not available with current infrastructures
Legacy Modernization� History of deferred IT
investment provides challenges as new requirements emerge
Better Design� Drive for more
reusable components rather than one off solutions
ChangingInformation
Needs 4Project expertise� Projects (e.g. SII)
require expertise in limited supply
� Limited access to business resources to define requirements
Cost Management
� Making efficient use of scarce resources
� Leveraging IT spend for multiple projects
Lack of Resources
Business Engagement� Need for greater
business validation and engagement during requirements definition
� Business and IT led projects
Faster Deployment
� Pressure for early deliverables to meet tight deadlines
Competing Projects� Ever increasing range
of projects (regulations, operational efficiencies, customer insight)
© 2013 IBM Corporation8
Agenda
Introduction to Industry DWH Models
Business Drivers, Challenges and Opportunities
Insurance Information Warehouse (IIW) Details
IIW Value Proposition
Annex
© 2013 IBM Corporation9
What is IBM Insurance Information Warehouse (IIW) ?
� IBM’s Comprehensive Enterprise Data Warehouse 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 (Business Vocabulary, Business Data Model, Atomic and
Dimensional Warehouse 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)
© 2013 IBM Corporation10
IIW core components includes� Business 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.
� Analytical Requirements– Structured requirements covering
management information and regulatory needs.
� Business Data Model (BDM)– Reference data model ,normalized view of
insurance business
� Atomic Data Warehouse Model– Enterprise-wide data model defines how
multiple sources of data should be consolidated into a single logical data structure
� Dimensional Warehouse Model– Enterprise-wide repository for analytical
data with star schema style dimensional data structures organized around fact entities
IIW Data Models
Data Models
Vocabulary
AtomicWarehouse
Model
Dimensional Warehouse
Model
Business Data Model
Business Terms
Analytical Requirements
SupportiveContent
© 2013 IBM Corporation11
Data Models
Vocabulary
AtomicWarehouse
Model
Dimensional Warehouse
Model
Business Data Model
Business Terms
Analytical Requirements
SupportiveContent
IIW Data Models
The Vocabulary includes
Business Terms
� 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 Business Model
� 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.
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, …)
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).
© 2013 IBM Corporation12
Data Models
Vocabulary
AtomicWarehouse
Model
Dimensional Warehouse
Model
Business Data Model
Business Terms
Analytical Requirements
SupportiveContent
IIW Data Models
The Business Data Model includes
� 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
© 2013 IBM Corporation13
The Atomic Warehouse Model includes
� 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
Data Models
Vocabulary
AtomicWarehouse
Model
Dimensional Warehouse
Model
Business Data Model
Business Terms
Analytical Requirements
SupportiveContent
IIW Data Models
© 2013 IBM Corporation14
The Dimensional Warehouse Model includes
� 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 Warehouse Model, from which it can be populated
� Can be used to populate data marts.
Data Models
Vocabulary
AtomicWarehouse
Model
Dimensional Warehouse
Model
Business Data Model
Business Terms
Analytical Requirements
SupportiveContent
IIW Data Models
© 2013 IBM Corporation15
Profile – Extract – Transform -
Load
Customer
Policy
Claim
Premiums
Reinsurance
Assets
Underwriting
General Ledger
etc.
Reporting & Analysis
IIW
Risk Applications
Data Marts / Cubes
Extract, Transform, and Load (ETL)
Enterprise Data Warehouse
Calculation Engines Data MartsDecision Support/
Reporting
Data Sources /Operational
Systems
Data Sources /Operational
Systems
IIW supports data warehouse and data mart deployments
Enterprise Data Warehouse
IIW for InfoSphere
Data Models
Vocabulary
AtomicWarehouse
Model
Dimensional Warehouse
Model
Business Data Model
Business Terms
Analytical Requirements
SupportiveContent
© 2013 IBM Corporation16
Business Analyst
Data Modeler
Developing a data warehouse with the Industry Models involves several tasks
Developing
Analytical
RequirementsSetting-up
ProjectDeveloping
Business
Terms
Developing
Supportive
Content
Developing
Business Data
Model
Developing Atomic
Warehouse Model
Developing
Dimensional
Warehouse Model
Data Architect
Project ManagerProject
Manager
Business Architect +
+
© 2013 IBM Corporation18
Agenda
Introduction to Industry DWH Models
Business Drivers, Challenges and Opportunities
Insurance Information Warehouse (IIW) Details
IIW Value Proposition
Annex
© 2013 IBM Corporation19
Technical and Logistical Benefits using IIW
1 2 3Consistent Approach� Leverage IIW methodology
and as a reference guide to develop consistent terminology
Better Documentation
� Common tooling/ methodology and vocabulary makes it easier to consolidate reporting across data marts
Audit & Compliance
� IIW analytical requirements/ mappings demonstrate traceability from source data to report
Engaging the Business� Tools and Industry content
makes it easier to meet business needs
� 85% of customers surveyed highlighted models as significant benefit
Faster Time to Value
� More than 50% of customers reported faster time to value when IIW model driven DWH in place
Cross Project Support
� IIW enterprise wide coverage supports wide variety of insurance related subject areas
Flexibility Standardisation
More Data� 85% of model customers
reported that IIW models granularity improved flexibility of DWH
Legacy Modernization
� IIW with IBM Information Management aids the recalibration of legacy data sources to meet new information needs
Better Design
� Significant benefits achievable after initial IIW project with the reuse of IIW modelling components
4Efficient Use of Resources
Resource Management� IIW models and
methodology accelerate requirements gathering and reduce resources required
Cost Management
� On Average, customers report 15-20% cost saving
� 77% reported that developer productivity significantly improved
Meeting Information Needs