Project Management For Class Plan Projects CAS Special Interest Seminar on Predictive Modeling October 11-12, 2007 Jonathan White.

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Project Management For Class Plan Projects CAS Special Interest Seminar on Predictive Modeling October 11-12, 2007 Jonathan White

2 Hope Is Not a Strategic Plan

3 Project Management Basics  Set research project goal  Define project tasks  Organize – work breakdown structure (WBS) –Identify dependencies –Sequence of tasks –Resource requirements of tasks –Duration of tasks  Project schedule – Gant chart  Project milestones

4 Planning  Clear understanding of the business objectives –Where is the plan to be used – Channel/state/ –Marketing source –Product/business expectations –Current competitive position –Implementation strategy

5 Planning  Clear research objectives –Statistical methodology –Software –New data –New variables –Scope of analysis –Required research infrastructure  Research vision of end product  IT / Operations / U/W … integration Defines Research Scope

6 Balancing Triangle SCOPE RESOURCES TIME

7 Planning  Environmental changes –Business strategy –Regulatory  Vulnerabilities –Data –Methodology –Software  Research contingencies –What if xxxx does not work?

8 Phases of a Class Plan Project 1. Planning 2. Data 3. Equity Modeling 4. Selection 5. Implementation 6. Monitoring

9 Data  Internal –Previously used –New  External –Hit rate  Understand the data  Data quality  Significant potential for delays

10 Equity Modeling Equity Modeling  Many times the simplest phase  Modeling options –Regression –Classification trees –Neural nets  Dependent variable –Loss ratio –Claim frequency/claim severity –Pure premium

11 Equity Modeling Equity Modeling  Holdout sample  Threshold for variable inclusion  Statistical measures of overall model predictiveness  Deliverables –Structure –Indicated factors  Peer Review

12 Selection  Recent performance vs. Modeling indications  New plan vs. Old plan comparison –Dislocation –Conversations with the business –Percentage change vs. Observed loss ratio  Cost benefit conversations

13 Percentage Change Vs. Observed LR

14 Selection  Benefits analysis  Price optimization –Data requirements –Analysis requirements  Environmental changes –Internal –External

15 Benefits analysis  Loss ratio/issue rate  Requirements –Equity model (indicated class plan) –Quote data - Issue rate model –Retention data - Retention rate model (if applied to renewal business) –Re-rating capabilities –Competitor pricing data or proxy

16 Implementation  Off-balance –Traditional – static environment –Dynamic – reflect mix changes  Filing support –What do you do when loss ratios don’t mean very much?  State exceptions – personal auto –Credit, driving record, prior carrier info –Balance efficiency and accuracy

17 Monitoring  Key metrics –Loss performance –Issue rate –Operational metrics  Importance of early reads –Leading indicators  Benchmarks

18 Loss Performance Monitoring  Determine key variables/niches  Establish and calculate benchmarks  Look for leading indicators –Claim frequency –Stabile, quick settling coverages –Cap severity –Credibility weight observed with benchmarks

19 Issue Rate Monitoring  Leading indicator  Problem of quotes  Comparison points –Prior plan –Benchmark  Do you believe the market or your equity modeling?

20 Hope Is Not a Strategic Plan