1. 1 Deloitte Consulting LLP Predictive Modeling for Commercial Risks Cheng-Sheng Peter Wu, FCAS, ASA, MAAA CAS 2005 Special Interest Seminar Chicago September 19-20, 2005

2. 2 Deloitte Consulting LLP Fast technology development: –Fast computation and data processing capability –Powerful statistical modeling tools –Availability of wide range of internal and external information PM applications very successful for personal lines. So if personal lines can, why not commercial lines? Why Now for Commercial Lines PM?

3. 3 Deloitte Consulting LLP Intensified competition for commercial lines: –Hard market/good profit over the past years –Competition for “growth” intensified: Grow “profitably” the “mainstream” small and mid size business Better segmentation: how to go beyond class base underwriting? Lower expense ratio: more automation, less touch, and less paper work for UW process –Ready for the next cycle? “PM provides a tool for better segmentation of risks and lower expense ratios” Why Now for Commercial Lines PM?

4. 4 Deloitte Consulting LLP Lessons from PM for personal lines –Credit scores –GLM –Large scale multivariate analysis –Wide range of internal and external data –Strong segmentation/lifts –“First movers’ advantages” About 25% of small commercial risks are being modeled currently Predictive Modeling for Commercial Risks

5. 5 Deloitte Consulting LLP First Movers ’ Advantages – Personal Auto

6. 6 Deloitte Consulting LLP Segmentation - Loss Ratio Lift Curve 82 66 58 62 70 74 78 90 120 50 Credit Score Decile Loss Ratio

7. 7 Deloitte Consulting LLP Credit Score Power – Personal Auto

8. 8 Deloitte Consulting LLP Traditional Segmentation by Class Actual loss ratio Below average Average Above average 135% 125% 110% 115% 100% 90% 80% 70% 140% Internal data 63% 60% 65% 68% 72% 78% 75% 82% 90% 87% Roofers Florists Overall Loss Ratio of 75%

9. 9 Deloitte Consulting LLP PM Scoring – Go Beyond “Class Based” Rating and UW 82 66 58 62 70 74 78 90 120 Overall L.R. 75% 50 Joe’s Flower Shop Score = 821 Linda’s Flower Shop Score = 324 Predicted Loss Ratio Internal / External Data Predicted Loss Ratio

10. 10 Deloitte Consulting LLP Less uniform and less homogeneous for exposures Diverse lines of business Diverse “industry” classes/groups A wide range of policy size Market driven pricing Class driven pricing Rating bureaus driven pricing Challenges for Commercial Lines PM

11. 11 Deloitte Consulting LLP Large loss impact Longer tail loss development Data challenges –Less cleaner (more changes, more missing, etc) –Less data available –Less standardized –Not detailed enough –Some information not captured –Information not on exposure level IT support challenges: lacking experience Challenges for Commercial Line PM

12. 12 Deloitte Consulting LLP Implementation challenges: –IT challenges –Business implementation challenges How to use model results? How to monitor the results? –Management buy-in Just a modeling project or a strategic initiative? Challenges for Commercial Line PM

13. 13 Deloitte Consulting LLP Less regulation Low hanging fruits –Significant pricing and UW inadequacy for segmentation Significant expense saving Significant operation improvement First movers’ advantages still exist! “Upsides” for Commercial Line PM

14. 14 Deloitte Consulting LLP Model design critical: –Less likely for pure premium (freq/severity) modeling; more likely for loss ratio modeling –Less likely on exposure level; more likely on policy level –Actuarial design issues: premium on-leveling, loss development, large loss impact, etc. –Implementation considerations: data availability, model design vs. implementation design, etc. Keys for Successful Commercial Lines PM

15. 15 Deloitte Consulting LLP Keys for Successful Commercial Line PM Search for powerful predictive variables: –Fully utilize internal and external variables: policy, agent, billing, drivers, vehicles, location, building, company financial and operation information, demographic information, etc. –Be creative Garbage in – garbage out, comprehensive diagnostics on model results: –Size –Industry –Geography –Programs –etc.

16. 16 Deloitte Consulting LLP Keys for Successful Commercial Lines PM Strong project management Company management buy-in Well designed implementation plan –IT implementation –Business implementation, significant impact on operations: UW process Business flow Agency management etc

17. 17 Deloitte Consulting LLP Our Experience for Commercial Lines PM It can be done for all the major commercial lines: WC, Auto, GL, Property, and BOP If carefully designed and executed, lifts curves comparable to personal lines can be achieved Some insights by line of business: –BOP typically has the cleanest data –WC results is most sensitive to size of risks –Auto’s results are most stable and can be extrapolated to mid and large size market –GL results very experienced driven –Subjective/market driven pricing typically random –External financial data useful, but may have low hit rates –Personal lines experience can be equally applied to small commercial risks, driver, credit, MVR, etc –Significantly inadequate experienced rating and UW across all lines

18. 18 Deloitte Consulting LLP Conclusions PM can work for commercial lines: –Similar segmentation power as personal lines –Significant “paradigm shift” from traditional class based UW mind set Keys for successful commercial line PM: –Strong project management skill –IT cooperation –Careful model design –Creative for predictive variables –Implementation plan First movers’ advantages still exist!