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Predictive Modeling – Potentials and Pitfalls CAS Annual Meeting November, 2006 John R. Pedrick, FCAS, MAAA Ohio Department Of Insurance www.ohioinsurance.gov.

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Presentation on theme: "Predictive Modeling – Potentials and Pitfalls CAS Annual Meeting November, 2006 John R. Pedrick, FCAS, MAAA Ohio Department Of Insurance www.ohioinsurance.gov."— Presentation transcript:

1 Predictive Modeling – Potentials and Pitfalls CAS Annual Meeting November, 2006 John R. Pedrick, FCAS, MAAA Ohio Department Of Insurance www.ohioinsurance.gov

2 Predictive Modeling – Pitfalls and Potentials  Rate Regulation Basics – What’s the law?  Regulatory Pitfalls  The Future

3 What’s the Law? Insurers must file everything. “Every insurer shall file with the superintendent of insurance every form of a policy, endorsement, rider, manual of classifications, rules, and rates, every rating plan, and every modification of any of them which it proposes to use.” - Ohio Revised Code § 3937.03 (A)

4 What’s the Law? Insurers must support everything. “When … the superintendent does not have sufficient information to determine whether such filing complies with sections 3937.01 to 3739.17 of the Revised Code, he may require such insurer to furnish the information upon which it supports such filing.” - Ohio Revised Code § 3937.03 (A)

5 What’s the Law? Standards For Rates “Rates shall not be excessive, inadequate, or unfairly discriminatory.” - Ohio Revised Code § 3937.02 (D)

6 What’s the Law? Public Records “A filing and any supporting information shall be open to public inspection after the filing becomes effective.” - Ohio Revised Code § 3937.03 (A)

7 Regulatory Pitfalls The Public Record  Models are proprietary.  Model results are incorporated in rating plans.  Rating plans are public records.

8 Regulatory Pitfalls – Three Primary Questions 1.Are prohibited or controversial factors used? 2.Can we rate a policy from information on the record? 3.Are the rates actuarially sound?

9 Regulatory Pitfalls – Controversial Factors May Need More Support For Example:  Credit Score  Education  Occupation

10 Regulatory Pitfalls – Prohibited Factors? Characteristic:Categories Insurance Bureau Score:A1 … A12 Ratio of Drivers to Vehicles:B1 … B3 Number of Additional Policies:C1 … C3 Number of Married Drivers:D1 … D2 Years Policy in Force:E1... E3 Vehicle Count:F1 … F2 ::

11 Regulatory Pitfalls – Prohibited Factors? Characteristic:Categories Characteristic:Categories: Age of Youngest Driver:G1 … G8 Auto Losses ($) in Prior Term:H1 … H3 Ratio of Incidents to Drivers:I1 … I2 Frequency of Bill Payment:J1 … J2 HO Losses ($) in Prior Term:K1 … K3 43 Price Points (Tiers)

12 Regulatory Pitfalls – Can A Policy Be Rated?

13 12 x 3 x 3 x 2 x 3 x 2 x 8 x 3 x 2 x 2 x 3 At 21 Combinations per Page 17,774 Pages = 373,248 Combinations

14 Regulatory Pitfalls – Can A Policy Be Rated? 17,774 Pages = 36 Reams 17,774 Pages, end-to-end, stretch 16,293 feet. That’s 3.1 miles of paper!

15 Regulatory Pitfalls – Are Rates Actuarially Sound?  Past  Present / Recent Past  Future

16 Regulatory Pitfalls – Are Rates Actuarially Sound? The Past

17 Regulatory Pitfalls – Are Rates Actuarially Sound? The Present / Recent Past

18 Regulatory Pitfalls – Are Rates Actuarially Sound? The Future

19 Regulatory Pitfalls – Are Rates Actuarially Sound?  Principles of Ratemaking  Standards of Practice  ASOP 9 – Documentation and Disclosure  ASOP 12 – Risk Classification  ASOP 23 – Data Quality

20 Regulatory Pitfalls – Are Rates Actuarially Sound?  Regulators must adapt to new approaches.  Actuaries must be prepared to explain their work in understandable terms.  Both must work to show the market benefits of predictive models.

21 Predictive Modeling – Pitfalls and Potentials Contact Information: John Pedrick john.pedrick@ins.state.oh.us Ohio Department Of Insurance www.ohioinsurance.gov


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