Credit Scoring John Wilson, Director Analytics CAS Ratemaking and Product Management Spring 2012 – March 20 1.

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Credit Scoring John Wilson, Director Analytics CAS Ratemaking and Product Management Spring 2012 – March 20 1

2 What are Credit-based Insurance Scores?  A numeric representation of relative insurance claim risk based on consumer credit details  Most are “bowling” scores (higher scores indicate lower risk) but some are “golf” scores  An objective, consistent, and effective tool used with other risk factors (ex. prior claims) to better estimate future claims risk and cost

3 What Data is Considered?  How long you’ve had credit established  The numbers and types of accounts you hold  Indications of recent activity, such as inquiries and newly opened accounts  The degree of utilization on accounts, and  Payment history, including timeliness as well as adverse public records or collection items

4 What’s Not Considered?  Factors such as gender, marital status, age, address, occupation, or education  Inquiries made for account review, promotional, or insurance or consumer disclosure purposes  Multiple inquiries for auto finance or mortgage finance when made within a 30 day period  Collection items designated as medical on the credit report

5 How Do They Differ From Lending Scores?  Insurance Models ≠ Financial Models  Insurance Models are developed on historical insurance losses  Insurance Scores rank order claim frequency or a similar metric  Insurance scores are not as dependent on derogatory behavior  Financial Models are developed on bad debts or 90+ delinquencies  Financial Scores rank order the odds of credit “bads”  Financial scores are more sensitive to credit delinquencies

6 How is Their Use Regulated?  LexisNexis is a Consumer Reporting Agency under the federal FCRA and state analogues  We provide disclosure and facilitate dispute resolution  Because insurance is regulated at the state level, we conform to specific state statutes, guidelines, and regulations (ex. NCOIL)  We work with state insurance departments to explain our models and try to gain approval for their use  We are not an insurance company; we don’t set rates or provide advisory services

7 Insurance Credit Score Trends We track two different populations Activity in the Market (drawn from our NCF transactions), and A large retro sample (proxy for existing business) What changes are we seeing? 7

National Attract Auto Score Trends – New Business 8 All regions are seeing small, gradual score improvements Western and Southern regions improved more from 2009 to 2010

Attract Auto 3.0 Scores on this large retro sample get slightly better each year Adverse Public Records are up overall, but annual increase is relatively small Attribute Trends – Existing Business 9 9

Inquiry counts have dropped dramatically, while average trade age has increased Revolving utilization has steadied after an initial drop; bank / consumer changes Attribute Trends – Existing Business 10