Ratemaking Seminar 2002

Ratemaking Seminar 2002

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

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

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

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

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

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

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

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

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

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

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

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

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

THINK ABOUT IT! Cheaper information More timely information Better information

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

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

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

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

Ratemaking Seminar 2002