Data/Tech 4: WORKERS’
COMPENSATION DATA
QUALITY ISSUES
CAS Ratemaking Seminar
March 10-11, 2005
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Discussion Topics
The importance of data quality
 The impact of poor quality on the WC
system
 The need for all parties involved to
understand the importance of good data
quality and the issues impacting the quality
of data
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Discussion Topics (cont.)
 The state of data quality in the industry
 Data quality successes and challenges
 Underlying processes and procedures used
by insurers and their trading partners that can
negatively or positively impact data quality
 Industry best practices around the collection
and reporting of data
 Potential improvements and next steps
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Panelists
Art Cadorine, Principal WC Services, ISO
 Pete Marotta, Principal Data Management
Consulting, ISO
 Ia Hauck, Director & Actuary, Actuarial &
Economic Services, NCCI
 Bruce Tollefson, President MN WCIA
 Tim Wisecarver, President, PA & DE CRB

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Data Quality Best Practices
Guiding Principles:
Data is a corporate asset
 Data should be fit for the use intended
 Data should flow from underlying
business processes
 Data quality should be managed as close
to the source as possible

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Key Characteristics of Data
Quality
 Accuracy
 Reasonableness
 Validity
 Avoid Redundancy
 Timeliness
 Accessibility &
& Timing
 Completeness/
Entirety
Availability
 Privacy
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Workers Compensation Insurance
Organizations (WCIO)
 A voluntary association of statutorily
authorized or licensed rating, advisory, or
data service organizations that collect
workers compensation insurance information
 Provides a forum for exchange of information
about workers compensation insurance
 Develops standards for the electronic
transmission of information between insurers
and rating/advisory organizations
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Setting the Stage
 2003 direct premiums written $50 billion (A.M. Best)
 Over 4 million policies a year
 Statutory coverage
 Auditable line
 Long tail line
 Data reporting unique to WC
 Aggregate financial data
 Unit Statistical Reports (USR)
 Detailed claim data
 Injury (FROI/SROI) and proof of coverage
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Types of Workers’
Compensation Data Collected
 Financial Data
 Annual Cycle, Little or No Classification, Policy or
Claim Detail
 Policy Information
 Coverage, Exposure & Pricing Analysis, Triggers Unit
Statistical Reports
 Unit Statistical Reports
 Policy and Claim Level Detail, Experience Rating,
Classification Pricing
 Individual Case Reports
 Quality Edits on Large Losses
 Special Calls
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State of Data Quality
Checks and Balances
Workers Compensation “Check and Balances”—All
stakeholders have an interest in the completeness,
accuracy, and timely reporting of data:
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Insurance Companies—Loss Costs/Rate Filings
Employers—Affordable and Available Coverage
Workers—Safe Workplace, Benefits and Medical Coverage
Data Collection Organizations—Credible and Reliable Estimates,
Forecasts and Analyses
Agents—Timely/Accurate Experience Ratings
State Regulators—Rate Adequacy, Employer Coverage
These individual interests contribute to the overall
health and quality of the data that fuels the WC
system
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State of Data Quality
Control Measures
The Workers Compensation data reporting system
provides an extensive complement of control
measures that contribute to the overall level of quality
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Data Reporting Standards, Rules and Training
Timeliness Control Programs
Online Reporting Tools
Editing Processes
Follow-Up Programs for Timeliness and Quality Issues
Data Quality Monitoring and Validation Tests
Incentive Programs
Test Audit Programs
NAIC Model Regulations
State Regulatory Audits of DCOs and Carriers
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State of Data Quality
Industry Standards, Tools and Training
Workers Compensation Organizations promote Data Standards,
Tools and Training that lead to Data Quality
Standards
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WCIO Data Specifications Manual
Statistical Plans
User’s Guides
Rating Plans
Provide…
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Business Rules
Common Data Definitions
Standardized Reporting Formats
Common Codes
Editing Processes
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State of Data Quality
Industry Standards, Tools and Training
Reporting Tools
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Web-based Reporting Applications
Editing Packages
Provide…
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Streamlined Reporting Processes
Pre-edit Capabilities
Training
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IDMA Data Management Courses
WCIO Data Reporting Handbook
DCO Sponsored Training and Workshops
Industry Communications (Bulletins/Circulars)
Provide…
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Professionalism and Certifications
Continuing Education
Tailored Curriculums—New Staff, New Tools, Industry Developments, etc.
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State of Data Quality
Results
State examinations of DCO’s confirm the overall accuracy of
Workers Compensation data, the effectiveness of data quality
programs, and:
 All stakeholders involved in the “checks and balances” positively influence
the timeliness and quality of our data
 Established control measures contribute to the overall level of quality
 Industry Standards, Tools and Training must continue to promote and
reinforce the importance of data quality
The Future—We need to continue to build on this data quality
commitment, always looking to raise our collective expectations
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Many Data Hand Offs
 Employers
 Other 3rd party vendors
 Agents/brokers
Policy admin. vendors
 Auditors
 Medical service providers
 Case mgmt. services
 Law firms
 Medical bill reviewers
 Others
 Mergers and acquisitions
 Transfers of books of
business
 Transfers of books of claims
 TPAs
 Insurers
 State Funds
 Reinsurers
 Data Collection
Organizations (DCOs)
 Accident Boards
 Federal regulators
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Areas of Concern for Data
Quality
 The Vast Majority of Required Data is Reported
Timely and Without Consequential Data Quality
Issues
 Where Problems Do Occur, They Reside in the
Following General Areas:
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Unreported Data
Late Reported Data
Invalid Data
Incorrect Data
Questionable Data
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Unreported Data
 Carrier Insolvencies
 Unrecoverable Loss of Carrier Records
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Late Reported Data
 Carrier System Issues
 Merger/Acquisition
 Other
 Risk or Unit Specific Issues
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Invalid Data
 Codes (Classification, Injury
Description, etc.)
 Exposure Reported for Code Not
Allowing Exposure
 Invalid Classification Combination(s)
 Unaudited or estimated payrolls
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Incorrect Data
 Rating Value Errors
 Incorrect Premium Calculations for
Statistical Codes
 Anniversary Rating Date Errors
 Accident Date Outside Policy Term
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Questionable Data
 Allocations of Exposures and/or Losses
by Classification
 Large Units with Zero Reported Losses
 Claims with High Medical Losses, but
No Indemnity
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DISCUSSIONS,
CONCLUSIONS &
QUESTIONS
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