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?