1. Ratemaking Seminar 2002

2. The Convergence of Technology, Data Standards & Analytical Tools Actuarial Standards - 23 Arthur R. Cadorine - ISO

3. Forewarned Is Forearmed  Current economic slowdown could be a lot worse  Electronic linkages identify problems sooner  Insurers ride their roller coaster

4. Insurance Industry Standards  Standards for policy and claim transactions are being developed ACORD ACORD IAIABC IAIABC IDMA IDMA  These standards will change the industry

5. Impact of Standards  If everyone speaks the same language, communication is possible  Information quality and timeliness improves

6. Data Standards Who Needs’Em and Why?  Trading partners such as insureds, insurers, TPAs, vendors, and brokers  Various sources use different definitions  Need data that is clean and consistent  Reduce duplication and cost  Numerous indirect benefits  Some obstacles remain

7. Data Standards Don’t They Exist Already?  Financial services and some retailers use data standards  Some insurance standards developed for specific applications  Standards are not identical

8. Data Standards Current Working Groups  IDMA TPA Data Standards Work Group  ACORD  ANSI  RIMS  ISO  WC Insurance Organizations (WCIO)

9. Data Standards Current Tools  PDRP - GL database for public entities  IDMA Claims Data Exchange Standard  IDMA Policy Data Element Dictionary  IDMA TPA Data Standards White Paper  www.idma.org/DS-announce.html

10. Value of Knowing Sooner  Delays in claims reporting cost money  Real-time fraud detection could save $$  Early claim-trend detection means corrective premium action

11. Insurers: Historically Slow Adopters  Insurance has historically been slow to adopt new technology  Why is it going to change?  More timely business intelligence means a competitive advantage

12. Integrating EDI Reporting  Straight-through processing becomes possible  Data quality improves  Information can be aggregated  ASP model has many advantages

13. Integration of Data  ASP can have policy and claim databases  Systems can talk to one another  One source/multiple outputs

14. Analytical Tools  Predictive models  Web access  User-friendly report writers  User-friendly analysis software

15. THINK ABOUT IT!  Cheaper information  More timely information  Better information

16. ASOP #23: Data Quality  Purpose is to give guidance in: Selecting data Selecting data Reviewing data for appropriateness, reasonableness, and comprehensiveness Reviewing data for appropriateness, reasonableness, and comprehensiveness Making appropriate disclosures Making appropriate disclosures  Does not recommend that actuaries audit data

17. ASAP #23: Data Quality Considerations in Selection of Data  Appropriateness for intended purpose  Reasonableness, comprehensiveness, and consistency  Limitations of or modifications to data  Cost and feasibility of alternatives  Sampling methods

18. ASOP #23: Data Quality Definition of Data  Numerical, census, or class information  Not actuarial assumptions  Not computer software  Definition of comprehensive  Definition of appropriate

19. ASAP #23: Data Quality Other Considerations  Imperfect Data  Reliance on Others  Documentation/Disclosure

20. Ratemaking Seminar 2002