With more than 30 years of experience in the insurance industry, SAS can help you achieve long-term success and obtain peace of mind. Integrated and extensible insurance solutions built on a flexible business analytics framework and insurance-specific data model speed up both implementation and results, giving you a fast track to significant ROI.

1. SAS FOR INSURANCE
MORE INFORMATION
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2. SAS & INSURANCE
• 1200+ insurance companies worldwide use SAS within
these areas:
• Actuarial
• Underwriting
• Claims
• Marketing
• Corporate Information
• Reporting
• Financial
• IT
• Risk
C op yr i g h t © 2 0 1 2 , S A S I n s t i t u t e I n c . A l l r i g h t s r es er v e d .

3. SAS & INSURANCE INSURANCE SOLUTIONS
 SAS Risk Management for
Insurance
 SAS Fraud Framework for
Insurance
 SAS Insurance Analytics
Architecture
 SAS Customer Analytics for
Insurance
C op yr i g h t © 2 0 1 2 , S A S I n s t i t u t e I n c . A l l r i g h t s r es er v e d .

4. ANALYTICAL
QUESTIONS INSURANCE EXECUTIVES ARE ASKING
INSURER
 Who are my profitable customers & agents?
 What claims can I recover?
 Where are my expenses increasing?
 How can I increase market share?
 What are my customers saying about us?
 Who is committing fraud?
 Are our products competitively priced?
 …..
C op yr i g h t © 2 0 1 2 , S A S I n s t i t u t e I n c . A l l r i g h t s r es er v e d .

5. ANALYTICAL
INSURER
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6. ACTUARIAL
CHALLENGES
ANALYTICS
 Rising underwriting expenses
 Increased competition
 Data integrity
 Frequent rate revisions
 Catastrophe forecasting
 Long-tail liabilities
 New risk classification
 Telematics data
C op yr i g h t © 2 0 1 2 , S A S I n s t i t u t e I n c . A l l r i g h t s r es er v e d .

7. ACTUARIAL
HOW TO OPTIMIZE PRODUCT PROFITABILITY
ANALYTICS
 Multi-variant pricing using advanced analytical tools
 GLM, Neural Networks, Loss Triangles
 Straight through processing for underwriting
 Real-time pricing
 Data integrity
 Renewal impact analysis
 Catastrophe evaluation
 Reinsurance analysis
C op yr i g h t © 2 0 1 2 , S A S I n s t i t u t e I n c . A l l r i g h t s r es er v e d .

8. CUSTOMER STORY ONE BEACON (US)
Business Problem
• Price insurance to improve bottom line
Customer Quote
• Choose polices to underwrite
The models that we
use and build with • Select claims for investigation vs. fast resolution
SAS give us a
competitive Solution
advantage.
• SAS Enterprise Miner
Todd Lehman, Vice
President, Corporate
Research Results
• Loss ratio up by 2 to 4 points
• Operational projects see 10 times ROI
• Successful move into hard to price speciality lines
C op yr i g h t © 2 0 1 2 , S A S I n s t i t u t e I n c . A l l r i g h t s r es er v e d .

9. CUSTOMER STORY FCCI (US)
Business Problem
• Reduce Churn
Customer Quote • Compete in deregulated market
SAS has speed,
sophistication and
power Solution
• SAS Enterprise Miner
Ned Wilson, Vice
President Treasury &
Planning
Results
• 1.5 percentage-point improvement in combined ratio
from choosing whom to insure and from pricing products
appropriately
C op yr i g h t © 2 0 1 2 , S A S I n s t i t u t e I n c . A l l r i g h t s r es er v e d .

10. CLAIMS ANALYTICS CHALLENGES
 Increasing Fraud
 Inaccurate loss reserving
 Rising settlement costs
 Spiralling litigation costs
 Catastrophe resource planning
 Ineffective salvage & subrogation processes
 Limited Resources
 Unstructured data
C op yr i g h t © 2 0 1 2 , S A S I n s t i t u t e I n c . A l l r i g h t s r es er v e d .

11. CLAIMS ANALYTICS PREDICTIVE ANALYTICS ACROSS THE CLAIMS LIFECYCLE
Set-Up & Negotiation / Medical Litigation
Notification Assignment Investigation Evaluation
Coverage Disposition Management Management
Predictive Claims Opportunities.
Fraud Propensity
Subrogation / Recovery Identification / Propensity to Recover
Customer Attrition Propensity
Workforce Productivity / Performance
Attorney Representation / Litigation Propensity
Injury / Treatment
Segmentation &
Loss Reserving
Management
Assignment
Claim
Process Adherence / Compliance
C op yr i g h t © 2 0 1 2 , S A S I n s t i t u t e I n c . A l l r i g h t s r es er v e d .

12. CUSTOMER STORY CNA (US)
Business Problem
• Detect and prevent fraud in four separate commercial
lines of business
Customer Quote • Optimally direct its investigation resources on cases with
higher likelihood of fraud
We have an excellent
partnership with SAS.
They took the time to Solution
meet with us and truly
understand the nuances • SAS Fraud Framework for Insurance
of CNA so that we could
build effective predictive
models for each line of
our business Results
• $1.6m in fraud recovery / prevention within the first 6
Tim Wolfe, SIU Director months of implementation
• Detection and investigation of 15 potentially fraudulent
provider networks – four times what CNA anticipated
C op yr i g h t © 2 0 1 2 , S A S I n s t i t u t e I n c . A l l r i g h t s r es er v e d .

13. CUSTOMER STORY TIER 1 INSURER (UK)
Business Problem
• Well established recoveries process
• Challenge was to see if analytics could improve recovery
rate
Solution
• SAS Enterprise Miner & SAS text Miner
Results
• Increased recovery rate by 4% to 6%
• Significant impact on Combined Ratio
• Analytics is now an integral part of the claims processes
C op yr i g h t © 2 0 1 2 , S A S I n s t i t u t e I n c . A l l r i g h t s r es er v e d .

14. CUSTOMER
CHALLENGES
ANALYTICS
 No single view of customer
 Increasing acquisition costs
 Lack of cross-channel integration
 Decreasing retention rates
 Ineffective segmentation and profiling
 Insufficient customer insight
 Ineffective agency performance measurement
 Poor conversion rates
C op yr i g h t © 2 0 1 2 , S A S I n s t i t u t e I n c . A l l r i g h t s r es er v e d .

15. CUSTOMER
HOW TO OPTIMIZE CUSTOMER INSIGHT
ANALYTICS
 Improve customer profitability
 Profile, segment & predict customer behavior
 Increase customer engagement
 Enhance marketing performance
 Multi-channel integration
 Recognize right channel for the right customer
 Distribution insight
 Highlight leading / lagging sales productivity KPIs
C op yr i g h t © 2 0 1 2 , S A S I n s t i t u t e I n c . A l l r i g h t s r es er v e d .

16. CUSTOMER STORY MAX NEW YORK LIFE (INDIA)
Business Problem
• Accurate data warehouse
• Increase customer retention
Customer Quote
• Improve cross-sell sales
In the first quarter after
implementing SAS, sales
to existing customers Solution
jumped to more than 20 • SAS Campaign Management & SAS Enterprise Miner
percent
Nagaiyan Karthikeyan,
Head of Business
Results
Intelligence and • Increase cross-sell sales opportunities by nearly 300%
Analytics
• 40 percent improvement in premium revenue
• Reduced sales expenses through shortened sales cycle
C op yr i g h t © 2 0 1 2 , S A S I n s t i t u t e I n c . A l l r i g h t s r es er v e d .

17. CUSTOMER STORY TOPDANMARK (DENMARK)
Business Problem
• Automate marketing campaigns to drive strong lead
Customer Quote management instead of spending large sums of money on
mass communication
With SAS as a strategic
partner, we ensure that • Prevent lapses in personal lines
we have the best
technology and
knowledge available. The Solution
vision of the data mining • SAS Marketing Automation
project is to find the
relevant customers far
more elegantly, and
ensure that they stay Results
with us
• Generate more campaigns with improved results from
the same amount of resources
Bjørn Verwohlt,
Marketing Director
• Annually target the ‘best’ 5,000 customers with highest
risk of lapsing
C op yr i g h t © 2 0 1 2 , S A S I n s t i t u t e I n c . A l l r i g h t s r es er v e d .

18. RISK ANALYTICS CHALLENGES
 New regulatory compliance
 Data availability and poor quality
 Unknown operational losses
 Incomplete view of risk
 Unreliable and inaccurate reporting
 Limited or non-sophisticated risk tools
 Lack of data transparency & auditability
C op yr i g h t © 2 0 1 2 , S A S I n s t i t u t e I n c . A l l r i g h t s r es er v e d .

19. RISK ANALYTICS BEYOND RISK COMPLIANCE WITH SAS
C op yr i g h t © 2 0 1 2 , S A S I n s t i t u t e I n c . A l l r i g h t s r es er v e d .

20. CUSTOMER STORY CHARTIS (US)
Business Problem
• Estimate risk of future losses
• Help underwriters access and price insurance risk
Customer Quote
• Estimate bad debt reserve funds for premium receivables
We are now much more
confident in making Solution
reinsurance decisions.
Today we have a daily, • SAS Analytics
real-time view of our risk
John Savage, Vice Results
President, Strategic Risk
Analysis • $14m in new, low-risk business, representing 100%
segment growth
• Avoided potential loss of $75m from certain executive
liability accounts
• Reduced requirement for bad-debt reserve funds
C op yr i g h t © 2 0 1 2 , S A S I n s t i t u t e I n c . A l l r i g h t s r es er v e d .

21. CUSTOMER STORY HDI ASSICURAZIONI (ITALY)
Business Problem
• Meet Solvency II requirements while improving data
quality and decision-making speed
Customer Quote
We have met the double
objective of improving Solution
data quality and
streamlining information • SAS Risk Management for Insurance
processes
Francesco Massari, Head Results
of Organization and
Information Systems • Improve data quality
• Timely information reaches business users, actuarial
scientists and senior management
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22. SAS FOR
VALUE PROPOSITION
INSURANCE
More granular
pricing = 2 to 4 %
improvement in
Combined Ratio
Avoid poor risks = 1
Capital allocation
to 3% improvement
decrease by 1%
in Loss Ratio
Reinsurance
Lapse rates reduced Analysis = 0.2 to
by 20 to 25% 0.5% improvement
in U/W Expenses
3 to 5 times
Fraud rates
increase in
reduction by 2 to 5%
response rates
Marketing
campaigns ROI Recoveries increase
increase by 10 to by 3 to 6%
15%
C op yr i g h t © 2 0 1 2 , S A S I n s t i t u t e I n c . A l l r i g h t s r es er v e d .

23. MORE
INFORMATION
• Contact information:
Stuart Rose, SAS Global Insurance Marketing Director
e-mail: Stuart.rose@sas.com
Blog: Analytic Insurer
Twitter: @stuartdrose
• White Papers:
Analytical P&C Insurer
Analytical Life Insurer
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24. THANK YOU
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