2006 cas ratemaking seminar considerations for small businessowners policies (com-3) beth...
TRANSCRIPT
2006 CAS RATEMAKING SEMINAR
CONSIDERATIONS FOR SMALL BUSINESSOWNERS POLICIES
(COM-3)Beth Fitzgerald, FCAS, MAAA
Agenda
•Definition of Risks
•Market Needs
•Use of Statistical Modeling
•Scoring Model Development
•Amount of Insurance Relativity Factors
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
Growth in Small Businesses
18,000,000
19,000,000
20,000,000
21,000,000
22,000,000
23,000,000
24,000,000
25,000,000
1992 1997 2000 2003
Establishmentswith less than 10Employees
Source: Office of Advocacy, U.S. Small Business Administration
Market Needs
•Efficient use of technology to allow for faster, more consistent underwriting decisions
•Add intelligence to the policywriting process
•Low-cost solution due to low premium size
What Makes Statistical Modeling Possible?
•Advanced computer capabilities
•Advanced statistical data mining tools
Uses of Statistical Modeling
•Scoring of small commerical risks– Improve loss predictability of risks– Increase accuracy of pricing decisions– Cost effective, consistent underwriting
• Improve manual rating of risks
Development of Scoring Models
•Analyze historical policy and loss data
•Link policy and loss data with external data:– Business financial data– Weather – Demographics
•Use statistical data mining software and techniques
Modeling Process
BusinessKnowledge
Data Linking
Data Cleansing
Analyze Variables
Determine Predictive Variables
Evaluation
Data Gathering
Modeling
Statistical Modeling Techniques
Balance good fit with explanatory power
•Generalized Linear Models
•Classification Trees
•Regression Trees
•Multivariate Adaptive Regression Splines
•Neural Networks
Benefits of Scoring Model
•Fast, cost-effective tool to help you determine which risks to insure
•More accurate pricing decisions
•Reduce underwriting expense through automated scoring process efficiencies
•Expand your markets
Risks of Not Scoring
•Lost market share
•Greater risk of adverse selection
Use of Statistical Modeling in Manual Rating
• Improve rating relativities of current rating factors
•Add new rating factor to manual using a multi-variate statistical model
Amount of Insurance Relativities
• Amount of Insurance identified as important variable in BOP Scoring analysis
• Partially handled by insurers
• Decision to include as variable in manual and not in scoring model
Property BuildingsOne Dimensional
0
0.5
1
1.5
2
2.5
Amount of Insurance in 000's
Exp
eri
en
ce R
ati
o
Current Rating for BOPProperty
•Base loss costs by state/territory for buildings & personal property
•Multi-state Relativities– Rate number– Sprinkler– Protection– Construction
Current Rating for BOPLiability
•Base loss costs by state/territory for occupants & lessors– Occupants vary by AOI, Payroll or Sales
exposure base
•Multi-state rating relativities– Class group
Multivariate Analysis for Amount of Insurance Relativities
•Variables used for Property– Rate number– Sprinkler– Protection– Construction
•Variables used for Liability– Class group
BOP Implementation of AOI Relativities
• Incorporation into manual – Definition of base amount of insurance– Building - vary by state/region
•Timeline– 12 month lead time – Interaction with other possible changes– Filing late 2006