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2004 CAS RATEMAKING SEMINAR
CONSIDERATIONS FOR SMALL
BUSINESSOWNERS POLICIES
(C-5)
Beth Fitzgerald, FCAS, MAAA
Agenda
• Definition of Risks
• Current Underwriting Process
• Issues
• Market Needs
• Why Scoring?
• Model Development
• Benefits and Risks of Scoring
Underwriting Small Commercial Risks
Eligible for Businessowners
• Size
– Area
– Gross sales
• Type of risk
– Office, apartments, retail, service
– Contractors, restaurants, motels, self-storage
facilities
– Light manufacturing
• Rating
– Class-rated
– Low average premium
Current Underwriting Process
• Establish underwriting guidelines for
type of risk and size of risk
• Review application information
–
–
–
–
Number of years in business
Financial information
Age/Characteristics of building
Prior loss history
Underwriting Issues
• Low average premium does not allow for
expensive hands-on underwriting of each
risk; Experienced underwriters focused on
larger accounts
• Small businesses underwritten more as a
commodity
• Expansion of eligible risks leads to less
stringent underwriting of these risks
• Result
– Lower underwriting expenses
– Higher underwriting loss ratios
Market Needs
• Efficient use of technology to allow for
“hands-off” underwriting
• Added intelligence in the policywriting
process
• Low cost solution for underwriting risks
Growth in Small Businesses
21,500,000
21,000,000
20,500,000
20,000,000
Establishments
with less than 10
Employees
19,500,000
19,000,000
18,500,000
18,000,000
17,500,000
17,000,000
1992
1997
2000
Source: Office of Advocacy, U.S. Small Business Administration
Why Scoring for Small
Commercial Risks?
• Improve loss predictability of risks
• Increase accuracy of pricing decisions
• Cost effective, low-touch underwriting
• Acceptable use of scoring for personal
lines risks
What Makes Scoring Models
Possible?
• Advanced computer capabilities
• Advanced statistical data mining
tools
Development of Scoring Models
• Analyze historical policy and loss data
• Link policy and loss data with external
data:
– Business financial data
– Weather
– Demographics
• Use sophisticated statistical data mining
software and techniques
Data Mining Process
Data Linking
Data Gathering
Data Cleansing
Evaluation
Business
Knowledge
Determine
Predictive Variables
Analyze
Variables
Data Mining
Data Mining Techniques
Balance good fit with explanatory power
• Generalized Linear Models
• Classification Trees
• Regression Trees
• Multivariate Adaptive Regression
Splines
• Neural Networks
How Do Scoring Models Work?
• Access models via:
– Easy-to-navigate web-based interface
– High-volume batch option for ease of
integration into company processing
systems
• Models return score reflecting future
potential loss ratio for individual risks
• Models provide reason codes for score
Benefits of Scoring Model
• Fast, cost-effective tool to help you
determine which risks to insure
– Demonstrated by success of scoring in personal
lines
• More accurate pricing decisions
• Reduce underwriting expense through
automated scoring process efficiencies
• Expand your markets
Risks of Not Scoring
• Lost market share
• Higher loss ratios
• Greater risk of adverse selection
• Increase in acquisition costs
• Reduce profitability