1. Predictive Data Modeling A CASE STUDY FOR DATA MODELING

2. Ken Reed, Loss Control Services Manager Barbara Rhoades, Chief Executive Officer

3. Towers Watson Content re-printed with permission from Towers Watson © 2013 all rights reserved

4. Data Analysis Why capturing your data is important… What you do with it – how to react to it…

5. How We Have Used Our Data OTRP manages the process through the Loss Control Summit Majority of our risk is Auto Liability All of our data is based on what we know…

6. Annual OTRP Loss Control Summit Loss Control Summit 2013 Working Together to Reduce Transit Losses Standing Strong Provide annually updated analysis of loss trends. Use data to drive loss control efforts and employment of resources Create awareness of emerging risk/exposures and develop responses Create opportunities to share ideas and resources

7.  Loss data from 1/1/2003 to 11/30/2011  Event based  Only looked at events with incurred values  Total of 1910 Events  Total Incurred of $14,152,647  Average Loss per Event of $7,410 Examples of How we have presented our Loss Data

8. All Events by Year

9. All Incurred by Year

10. Average per Event by Year

11. Events by Type

12. Incurred by Type

13. Average per Event by Type

14. Collisions  Total of 1485 Collision Events  Total Incurred of $7,101,609  Average Loss per Collision of $4,782  Collision breakdown 1.Fixed Object 2.Rear End Collision 3.Backing 4.All Other

15. Collision Events by Year

16. Collision Incurred by Year

17. Collisions by Type

18. Incurred by Collision Type

19. Average per Collision by Type

20. What is Predictive Modeling?

21. Historical Actuarial Perspective Historically, actuaries evaluated rates to set pricing and reserves. In a traditional approach they look at characteristic separately Univariate Analysis Describes the tradition approach of estimating the impact of one factor without considering others This is often called a “one-way” analysis Content re-printed with permission from Towers Watson © 2013 all rights reserved

22. Univariate Analysis Collision Age of Vehicle Number of Miles Content re-printed with permission from Towers Watson © 2013 all rights reserved

23. With the advanced in computing technology, actuaries are able to use complex mathematical equations to estimate the impact of all variables simultaneously. This is called.. Multivariate Analysis Collision Miles Age of Vehicle Content re-printed with permission from Towers Watson © 2013 all rights reserved

24. Actuarial Term for the computations underlying a multivariate analysis is: GLM or Generalized Linear Modeling Content re-printed with permission from Towers Watson © 2013 all rights reserved

25. Benefits of Predictive Modeling Explore impact of multiple variable simultaneously while taking into account their relationships or correlations This allows for more effective pricing in a competitive market Better claims handling though identification of claims drivers Reduction of risk though probability analysis Content re-printed with permission from Towers Watson © 2013 all rights reserved

26. Benefits of Predictive Modeling Explore impact of multiple variable simultaneously while taking into account their relationships or correlations This allows for more effective pricing in a competitive market Better claims handling though identification of claims drivers Reduction of risk though probability analysis Content re-printed with permission from Towers Watson © 2013 all rights reserved

27. How is Predictive Modeling Being Used?

28. Can Integrate all aspects of your operations and identifies the value of all customers Develop Rules Credit Analysis Eval Agents Target Inspections Underwritin g Set Base Rates Identify Predictors Quantify relationships Pricing Set Reserves Predict Fraud Predict lawsuits Identify likely outcomes Claims Predict response rates Perform conversion analysis Determine retention Marketing Content re-printed with permission from Towers Watson © 2013 all rights reserved

29. Competitive Advantage Price Improve Retention & Satisfaction

30. Claims Advantages Reduce Claim costs Improve efficiency in claim handling process – shorten cycle More Accurate reserving practices Better claim Experience leads to higher customer satisfaction Content re-printed with permission from Towers Watson © 2013 all rights reserved

31. Perform a Claims Triage Use Predictive Modeling to identify complicated claims based on multivariate analysis Routed to specialists Correct Experience for Adjuster Medial Provider? Attorney involvement Return to work Case management Content re-printed with permission from Towers Watson © 2013 all rights reserved

35. OTRP Utilized to the study to identify patterns of potential future losses Predictive Data Analysis allowed us to look at our losses differently. We normally analyze what HAS happened. This allowed us to see what is likely TO happen.

37.  Predictive Data Analysis

41. OTRP’s Experience Re-confirmed what we already knew to be true We were able to identify areas of concerns for specific members (not just the pool as a whole) Let us think about claim indicators that we might not have otherwise. FOR OTHERS: Great management tool for a “hands-off” organization. Claims management tool for claims intensive organizations. Creates the possibility to see things in a new and different way

42. Standing Strong OHIO TRANSIT RISK POOL Service ● Stability ● Security Serving Public Transit since 1994