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Importance of Data Quality

Importance of Data Quality. April 21, 2004. Agenda. Uses & Benefits of Data Elements of Quality IBC Data Quality Safeguards Metrics Data Quality Improvement Tools Incorporating Quality into Design Questions. Uses and Benefits of Data. Provide Industry Analysis

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Importance of Data Quality

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  1. Importance of Data Quality April 21, 2004

  2. Agenda • Uses & Benefits of Data • Elements of Quality • IBC Data Quality Safeguards • Metrics • Data Quality Improvement Tools • Incorporating Quality into Design • Questions

  3. Uses and Benefits of Data • Provide Industry Analysis • Identify Emerging Industry Issues • Support Lobbying Efforts • Fraud Investigation • Government Rate Filing • Company - Business Decisions • Product, Pricing, Market

  4. Elements of Quality • Validity/Consistency • Completeness • Timeliness • Accuracy Meets the needs of the business!

  5. IBC Data Quality Safeguards • Business Logic / Editing • Testing Facility • Trending Analysis • Tools & Reports • Deficiency Fees • Dedicated IBC Resources • Data Quality Management

  6. IBC Data Quality Safeguards • Accountability • Visibility • CEO Data Quality Report • Data Accuracy Profiles • Compare to Related Data Reporting • Compare to External Sources

  7. IBC Data Quality Safeguards • Compare to Financial Statements • CFO Sign-Off • Internal Actuarial Review • External Actuarial Review • Regulator Review • Compare to Rate Filing

  8. DataSubmission Submission Management Error Management Data Accuracy SNA FTP Errors EDIT Valid Data AccuracyAnalysis Products & Services

  9. Data Quality Management Team Vice President Manager Data Collection & Quality Data Quality Specialist – 1 Data Quality Analysts – 5 Data Entry Staff – 2 Manager Data Accuracy Data Accuracy Analysts – 3

  10. Metrics • 200+ Active Reporting Companies • 6 Statistical Plans • 3 Reporting Types per Plan • 1,400 Data Submissions per Week • 150 Million Data Records per Year • 1.6% of Records have Errors • 2+ Million Records Corrected per Year

  11. All Submitted Data Personal Lines Commercial Liability Commercial Property OSABSP Automobile Facility Automobile 98.38% 99.87% 98.40% 99.71% 91.91% 98.58% 91.76% 2003 Data Metrics

  12. Metrics • 3,200 Pages - Stat Plan Documentation • 1,500 Pages for Automobile • 10 User or Reference Manuals • 5 Web Applications • 1,330 Active User ID’s • 2,000 Client Interactions per Week

  13. D. Q. Improvement Tools • Documentation: • Statistical Plan Manuals • Edit Rules Documentation • Application User Manuals • Reference Manuals • Communication: • Data Quality Bulletins • Tips Emails

  14. D. Q. Improvement Tools • Meetings: • Error Correction Training • Statistical Plan Coding Seminars • Status Meetings • Annual Data Quality Forum • Deficiency Fees: • Monthly Invoice • Detail Reports (showing counts, aging, etc.)

  15. D. Q. Improvement Tools • Reports: • Submission Confirmation Email • Greensheets & Error Listings • Monthly Status Reports • UV Accuracy Reports • OSAB Database • Ad-hoc Reports • CEO Data Quality Report

  16. CEO Data Quality Report

  17. D. Q. Improvement Tools • Analysis: • Submission Process • Data Trending • Data Accuracy • Completeness Checking: • Annual Balance Reconciliation • OSABSP to ASP Balancing

  18. D. Q. Improvement Tools • Website: • Library of Communications/Bulletins • Application Description Information • Frequently Asked Questions • Links to Data Quality Applications • All User & Reference Manuals

  19. D. Q. Improvement Tools • 5 Web Applications: • Prime > Pre-Edit Testing • SMART > Submission Management • Expert > Error Management • EEC > Error Correction • EVC > VIN Correction

  20. DataSubmission Submission Management Error Management Data Quality • EXPERT • PRIME • SMART • EEC • EVC SNA FTP Errors EDIT Valid Data AccuracyAnalysis Products & Services

  21. PRIME • Streamline Testing Process • Automate Detection of Data & Mapping Errors • Identify Required Changes to Company Programs or Translation Tables • Information provided: • Batch Structure Errors • Error Volume • Error Code Frequency • Detail Record Download

  22. SMART • Coordinate Submission Management • On-Line Reconciliation to Confirm Balances • Provides Summary & Detail Submission Information • Allows users to: • Ensure Completeness • Identify Submission Abnormalities

  23. EXPERT • Coordinate Error Management Process • Flexible Search Criteria • Enables User to Identify Trends • Information provided: • Most Frequent Errors • First Time Errors • Repeat Errors • Error Correction Volume • Number of Outstanding Errors

  24. EEC • Streamline Error Correction Process • On-Line Access to Correct Errors • Refreshed Daily • Allows users to: • Improve Timeliness of Error Correction • Improve Productivity Through Bulk Correction • Reduce Paper and Courier Fees • Reduce Deficiency Fees

  25. Questions?

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