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 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 Business Knowledge 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 Buildings One Dimensional

Current Rating for BOP Property Base loss costs by state/territory for buildings & personal property Multi-state Relativities – Rate number – Sprinkler – Protection – Construction

Current Rating for BOP Liability 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