Download - Benefits of Industry DWH Models - Insurance Information ... · © 2013 IBM Corporation Benefits of Industry DWH Models - Insurance Information Warehouse Roland Bigge 02.11.2013

© 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


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


� 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


Agenda





Annex


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


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)


Agenda





Annex


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)


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


Data Models

Vocabulary

AtomicWarehouse

Model


Model

Business Data Model

Business Terms


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.


� 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).


Data Models

Vocabulary

AtomicWarehouse

Model


Model

Business Data Model

Business Terms


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


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


Model

Business Data Model

Business Terms


SupportiveContent

IIW Data Models


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


Model

Business Data Model

Business Terms


SupportiveContent

IIW Data Models


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


Model

Business Data Model

Business Terms


SupportiveContent


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 +

+


IIW Requirements ModelBusiness Solution Templates (BSTs)


Agenda





Annex


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


Agenda





Annex