Business Intelligence for Insurance

AMIS

May 25, 2010

2 > 5/21/2010

Insurance Environment

• Industry is fundamentally strong… but the residual impact of the economy and soft insurance market will put extraordinary pressure on financial results, driving further need for operational efficiency.

• Regulatory requirements and increased focus on risk management will drive adoption of analytics and models, data management, and integration.

• Technology initiatives in Business Intelligence (BI) and process improvement are imperative for all customer and agent management initiatives.

• Distribution…changes in distributor requirements and emerging need to develop multiple distribution capabilities will escalate the importance of self-service technologies and mobile application development.

• Globally, markets will be in transition as some insurers execute merger and acquisition (M&A) strategies and others retract from geographies and product lines that are not performing well.

• Optimizing employee performance through technology adoption and integrating familiar social media will create a positive atmosphere.

3 > 5/21/2010

Implications for Insurance Companies

• Industry is fundamentally strong… but residual impact of economy and soft market will put extraordinary pressure on financial results, driving further need for operational efficiency.

Need for better, more timely operational/financial metrics

• Regulatory requirements and increased focus on risk management will drive adoption of analytics and models, data management, and integration.

Need holistic approach to risk management

• Technology initiatives in BI and process improvement are imperative for all customer management initiatives.

Adopt next generation CRM tools and approaches

• Distribution…changes in distributor requirements and need to develop multiple distribution capabilities will escalate self-service technologies and mobile application development.

Need for better analytics on agents/brokers/direct channels

• Globally, markets in transition as some insurers execute M&A strategies and others retract from geographies and product lines that are not performing well.

Need to integrate/analyze data from new sources

• Optimizing employee performance through technology adoption, “information democratization.”

Need to push Business Intelligence to front lines, “pervasive BI”

4 > 5/21/2010

“Five Stages of an Active Data Warehouse Evolution”, Stephen Brobst and Joe Rarey, Teradata Magazine Online

OPERATIONALIZINGWHAT IS

happening now?

ACTIVATINGMAKE it happen!

Link to Operational Systems

Automated Linkages

REPORTINGWHAT

happened?

PREDICTINGWHAT WILL happen?

ANALYZINGWHY

did it happen?

Batch Reports

Ad Hoc, BI Tools

Predictive Models

Batch

Ad Hoc

Analytics

Continuous Update/

Short Queries

Event-Based

Triggering

Business is driven by need for actionable information

Workload Complexity

Data Sophistication

5 > 5/21/2010

The Data Drivers

• Enhanced Customer & Agent Intelligence> Single view of the Customer

> Move from Product to Customer View

• Increased / Improved Risk Analysis– Improved Underwriting / Pricing Segmentation

– Catastrophe Modeling

– Global climate change issues

– Enterprise Risk Management & Solvency II

– New programs and products

• Increased reliance on Predictive Modeling Capabilities> Customer Segmentation

> Fraud & Abuse (proactive reduction)

• Protection / Growth of Market Share> Analysis of distribution channels and pipeline activity

6 > 5/21/2010

Situation Analysis – How organizations are responding

Building out a flexible and robust data warehouse infrastructure that:

> Supports direct user and application access to a common set of data resources

– Application neutral, organized to reflect the business relationships of data

– Established to meet today’s needs as well as future growth

> Supports multiple types of data in one platform

> Leverages data reuse – “Source Once and Use Many”

> Allows quick response to new business data requirements

> Supports “Any question by any user, at any time”

> Is driven by business value

7 > 5/21/2010

Multiple/Custom

ETL

Typical Data Environment…

Large Numbers of Analysts

Disparate Reports

MultipleSourceSystems

Multiple Custom Data Marts/Cubes

Transaction Systems Data Management Analytics

End Users and Decision

Makers

ClaimsSystems

ERP

Policy Systems

CATSystems

Other

Sources

Customer

Information

System

Teradata Confidential and Proprietary-7-

8 > 5/21/2010

Standard Sourcing

EnterpriseData Warehouse

IntegratedData

Portals, Metrics

and Alerts

End Users and Decision Makers

Other tools(MicroStrategy, Cognos, SAS, Bus Objects, etc.)

…A Better Place to Be

Transaction Systems Data Management Analytics

ClaimsSystems

ERP

Policy Systems

CATSystems

OtherSources

CustomerInformationSystem

MultipleSourceSystems

Teradata Confidential and Proprietary-8-

Data Model

9 > 5/21/2010

+ 64 + 277 = 444

+ 43 + 189 = 292

+ 29 + 70 = 130

31

Functional +Cross-Functional

Questions Answered

EDW –Questions Answered

Functional Questions Answered

(from separate marts/depts)

+ 64 = 167+ Financial

+ 43 = 103+ Customer

+ 29 = 60+ Channel

31Claims

Data Mart –Questions Answered

Data Sources

$$$

$

Greatest Opportunity

Lowest Cost

$

$

<

>

$

$

$

$

Information Evolution

Comparing Data Marts and EDW

• Integrated, Enterprise Data Warehouse

> Enables incremental cross-functional business questions

> Enables data leverage; no need to re-acquire existing data

10 > 5/21/2010

Putting It Together into Action

S T R A T E G I C I N T E L L I G E N C E

O P E R A T I O N A L I N T E L L I G E N C E

ActiveEnterpriseIntelligence

Does this claim require a special investigation based on severity?

Does the CSR have detail

information to make the

appropriate decisions?

CustomersFinancial

Management

Attaining overall

policyholder satisfaction

How does call center performance compare with last year?

How can we predict claims

severity and fraud?

Does the CSR have access to triggers, alerts, up-sell ops?

11 > 5/21/2010

Post Evolution Examples

Cross

Sell

(Customer)

(Household)

Customer

Value

(Customer)

(Household)

Renewal

Date

Product

SummaryGeographic

PenetrationOrganization

Penetration

Customer

Behavior

(Channel

Usage)

Cross

Channel

(Channel

Capacity)

Channel

Specific

(Producer)

Channel

Specific

(Branches)

Channel

Specific

(Call

Center)

Channel

Specific

(Web)

Product ViewAnalyze Product Holdings & Demographics

Transaction ViewAnalyze Events Across Channels & Products

12 > 5/21/2010

100%

82%

75%

63%

57%

74%

83%

53%

62%

54%

24%

100%

25%

11%

21%

56%

22%

10%

18%

9%

64%

71%

100%

47%

45%

64%

64%

49%

54%

38%

27%

17%

24%

100%

47%

26%

38%

36%

31%

47%

28%

35%

26%

53%

100%

52%

32%

39%

29%

57%

16%

41%

16%

13%

23%

100%

8%

6%

14%

11%

56%52%66%31%Customer Retention

50%32%65%17%Customer Communications Management

50%57%69%26%Customer Acquisition

58%83%78%62%Consistent ComplianceInfrastructure Assurance

44%79%65%67%Claims Payment Management

26%29%72%29%Channel Communications

100%71%65%45%Product and Customer Alignment

49%100%50%55%Underwriting Risk Analysis

40%45%100%30%Sales Reporting and PerformanceAnalysis

54%95%58%100%Risk Management Optimization

Risk M

anagement

Optimization

Underwriting Risk

Analysis

Product and

Customer Alignment

Sales Reporting and

Performance Analysis

Claim

s Payment

Management

Consistent Compliance

Infrastructure

Assurance

Customer Acquisition

Customer

Communications

Management

Customer Retention

If

Then

New Business Improvement Opportunities through Data Leverage

Insurance: Data Overlap Analysis

Channel

Communications

13 > 5/21/2010

Organizing All That Data –

What is the Purpose of a Data Model?

•A successful data model blueprint will allow you

to start small and grow your data warehouse

for different uses over time without having to re-

architect

•It provides discipline and structure to the

complexities inherent in data management

•Can you imagine building a house without

a blueprint?

•Or driving across the country without a

map?

•It facilitates communication within the

business (e.g. within IT and between IT and the

business)

•It facilitates arriving at a common understanding of important business concepts (e.g what is a customer?)

14 > 5/21/2010

Lots of Detail / Expertise Behind Models

15 > 5/21/2010

Sources of New Data Adding to the Mix

• Optical / Graphical & Geographic Information Systems (GIS):

> Satellite imagery, maps, photos

> Geo-spatial data

• Direct marketing & call centers

• Telephonic:

> Telematics

> RFIDs

> Cell Phone/PDA reporting and communication

• Internet

> Standard insurance functions

> Social media

16 > 5/21/2010

Types of New Data

• Geographic Information Systems (GIS):

> Latitude / Longitude, Flood Zone, Storm Surge

• GPS

> Turn by turn, speed, velocity, stop and starts

• Traffic & Weather

• Unstructured Text

• Health / Medical

> Electronic Health Records, Treatment Plans

> Prescriptions and outcomes

• Click Stream

> Web site activity

17 > 5/21/2010

Business and Financial Events Flow-through to Financial Performance Management

Financial Position

Income Expense

Assets

Liabilities

Equity

Balance Sheet

Income Statement

Financial Performance

Balance Sheet

• Cash

• Accounts Receivable

• Accounts Payable

• Unearned Premium

• Loss and Loss Adjustment Reserves

• Investments

• Capital and Surplus

• Dividends

Income Statement

• Premium Written

• Commissions

• Reinsurance

• Claims and Benefits

• Underwriting Expense

• Underwriting Profit/Loss

• Other Expense

• Investment Income and Expense

• Taxes

• Develop Products

• Sell Products and Services

• Price Products

• Underwrite Risk

• Write Premium

• Earn Premium

• Receive Payments

• Manage Reinsurance

• Pay Commissions

• Manage Claims

• Pay Claims/Benefits

• Recover Reinsurance

• Calculate IBNR

• Pay Expenses

• Manage Investments

• Pay Taxes

Business/Financial Events Financial ReportingData Warehouse

INTERNAL ORGANIZATION

LOCATIONCHANNEL

CONTACT/TRANSACTION EVENT

ACCOUNT

PARTY

Transparency = Detailed Data & Audit Trail

Data Warehouse

CAMPAIGN

PRODUCT

18 > 5/21/2010

GAAP/IFRS

Management

Statutory

Statistical

• Annual Report Government/Treasury

• SBU• Line of Business• Profit Center• Cost Center

• Annual Statement & Exhibits• Bureaus• Associations• Special Filings

• Statistical Plans• Actuarial

Combined Statistical, Statutory, and Management Reporting Integrated with GAAP

Consistency = Single Source of Data

Financial Position

Income Expense

Assets

Liabilities

Equity

Balance Sheet

Income Statement

Financial Performance

INTERNAL ORGANIZATION

LOCATIONCHANNEL

CONTACT/TRANSACTION EVENT

ACCOUNT

PARTY

Data Warehouse

CAMPAIGN

PRODUCT

19 > 5/21/2010

• Return on Equity• Return on Assets• Net Investment Yield• Earnings Per Share

• Shareholder Value Added• Measured Operating Income• Cumulative Discounted Cash Flow• Internal Rate of Return• Underwriting P&L

• Combined Ratio• Loss Ratio• Expense Ratio• Operating Ratio• Change in Surplus

• Change in Premium Written• Liabilities to Surplus• Leverage Net and Gross• Current Liquidity• Reserves to Surplus

• Premium Persistency• Mortality and Claims• Medical Trend

• Revenue Growth

• Earnings Growth

• Return on Capital

• Market Value Added

• Equity Earnings

• Yield on Investments

• Duration of Assets

• Credit Default

• New Business

• Mix of Business

• Premium/Asset per Customer

• Products per Customer

• Fixed and Variable Costs

• Acquisition Costs

• Capacity

• Sales by Distribution

• Agent/Policyholder Retention

• Catastrophes

• Reinsurance• Policy Class/Sub Class

• Peril

• Policy Term

• State

• Agent State

• Territory

• Price Target/Achieved

• Quotes Accepted/Declined

• Premium Persistence

• Expose Mix

• Exposure Units

Reporting Measures/KPIs Analysis

Comprehensiveness = Reporting, Analytics and Decision Support

GAAP

Management

Statutory

Statistical

• Annual Report Government/Treasury

• SBU• Line of Business• Profit Center• Cost Center

• Annual Statement & Exhibits

• Bureaus• Associations• Special Filings

• Statistical Plans• Actuarial

20 > 5/21/2010

New & Improved Tools and Analytics

• Integrated Master Data Management (MDM)

• Data Profiling

• Data and Text Mining

• Predictive Modeling and Scoring Engines

• Encryption for Privacy and Security

• Visualization Tools

• Usage-Based Rating / PAY-AS-YOU-DRIVE

20

21 > 5/21/2010

Value

Business event

Data captured

Intelligence delivered

• Policyholder requests additional auto liability coverage

• Based upon driving record, an umbrella policy should be offered

Missed Opportunity

• Increasing the policyholder’s coverage at a fraction of the price of modifying or replacing the policy with an umbrella policy

TDWI The Business Case for Real-Time BIBased on concept developed by Richard Hackathorn, Bolder Technology

Situation Gained Opportunity

• Policyholder gets more extensive coverage without replacing or modifying existing auto policy

• Umbrella policy sold by CSR after reviewing MVR records and client history

Action taken

Time

Accelerating Actions

22 > 5/21/2010

Data Management Services

•• Data GovernanceData Governance – The practice of organizing and implementing principles, policies, procedures, and standards for effective data use

•• Data StewardshipData Stewardship - Continual, day-to-day activities of creating, using, and retiring data

•• Data QualityData Quality – Ensure data is fit for its intended use

•• Data IntegrationData Integration – Includes Data Acquisition (ETL/ELT) processing to combine transaction and master data to provide a consistent, meaningful, trusted view of data across BUs and subject areas

•• Data Security and PrivacyData Security and Privacy – Information security, data privacy, and regulatory compliance across data subject areas, including monitoring/audit capabilities

•• Metadata ManagementMetadata Management – The people, processes, and technical components necessary to ensure that metadata is easily accessible, consistent, current, accurate, timely, and complete

•• Master Data ManagementMaster Data Management – Focus on reference and relationship data for product, customer, supplier, and organizational data to ensure data consistency

•• Data ArchitectureData Architecture – The logical and physical data modeling plus other activities needed to understand business information needs and design for effective database usage

Data Governance

Data Stewardship

Integrated/ Trusted

Information

People, Processes, and Technology

Data Integration

Data Architecture

Data Quality

Master Data Mgmt

Metadata Mgmt

Data Security

and Privacy

Your Path to Integrated, Trusted Information

Questions?