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Vision Data Technology 3 Data Management


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									 Data/Technology 3 - Data
Management Panel Discussion

CAS Ratemaking Seminar March 2005

 Jason L. Russ, Consulting Actuary, Milliman, Inc.
 Michael L. Toothman, Consultant Actuarial &
  Risk Consulting Services
 Peter Marotta, Principal, ISO
 Gary Knoble, Vice President, The Hartford
Data Management and the

   An ABCD Perspective
     Michael L. Toothman
The Role of the ABCD

 Consider complaints
 Counsel Actuaries
 Recommend disciplinary action
 Respond to requests for guidance
 Mediate issues
The Role of the ABCD

Consider Complaints

  – Conduct Investigations

  – Hold Hearings
   The Role of the ABCD
Counsel Actuaries

A  primary role for the ABCD
 Possible result at several points in the
  ABCD process
        – In lieu of an investigation
        – After the investigation
        – After a hearing
  The Role of the ABCD

Recommend Disciplinary Action

 Only the participating organizations
  have authority to discipline their
 Occurs in well under 5% of ABCD
  The Role of the ABCD

Respond to Requests for Guidance

  – Over 50% of ABCD cases

  – Key function of the ABCD
The Actuary’s Responsibility

  Comply   with Code of Conduct

  Comply  with Qualification
  Standards (both general and

  Comply   with Standards of Practice
 The Actuary’s Responsibility

Precept 1:

  An Actuary shall act honestly, with integrity
  and competence, and in a manner to fulfill the
  profession’s responsibility to the public and to
  uphold the reputation of the actuarial
         Real Life Issues
 ABCD  classifies cases as


 Majority   of cases are conduct issues

 Very   few cases have involved data quality
                                                               Code of Professional Conduct

The Code of Professional Conduct identifies the professional and ethical standards
required of actuaries who belong to the Academy. The SOA, ASPA, the CAS, and the
CCA have adopted identical codes.

                               Code of Professional Conduct
 Professional  Integrity - Precept 1          Courtesy  and Cooperation – Precept 10
 Qualification Standards - Precept 2          Advertising – Precept 11
 Standards of Practice - Precept 3            Confidentiality – Precept 9
 Communications and Disclosure - Precepts     Titles and Designations – Precept 12
  4, 5, and 6                                  Violations of the Code of Professional
 Conflict of Interest - Precept 7              Conduct – Precepts 13 and 14
 Control of Work Product – Precept 8
                                                                           ABCD Case Resolution

ABCD cases considered during 2003:

               Type of Case   Pending from 2002 and Earlier   Received in 2003     Total
    Conduct                                12                        3              15
    Practice                                5                        5              10
    Conduct & Practice                      3                        1              4
    Requests for Guidance                   1                        31             32
    Total                                  21                        40             61

    Cases by Practice Area    Pending from 2002 and Earlier   Received in 2003    Total
    Casualty                               2                         8             10
    Health                                 2                         6              8
    Life                                   5                         7             12
    Pension                                12                       19             31
    Total                                  21                       40             61
                                                       ABCD Case Resolution

ABCD cases considered during 2003:


   Action by Individual ABCD members
               Replied to requests for guidance             30
               Mediated                                      1
   Disposition by Chairperson and Vice Chairpersons
               Dismissed                                    4
               (Referred to Investigators in 2003—4)
   Disposition by Whole ABCD after investigation
               Dismissed                                     3
               Dismissed with guidance                       2
               Counseled                                     2
               Counseled after hearing                       2
               Recommended suspension                        1
   Total                                                    45

   CASES IN PROGRESS (as of 12/31/03)

               Pending investigation                         7
               Pending hearing                               1
               Pending receipt of more information           6
               Request for Guidance pending                  2
   Total                                                    16
                                                                                         ABCD Case Resolution

 Since its inception in 1992, the ABCD completed its cases as follows:

        Dispositions      1992   1993   1994   1995   1996   1997   1998   1999   2000   2001   2002   2003   Total

Dismissed                   12     24      9     11      8     11     13     10      5     20     16      7     146

Dismissed with guidance      6     10      3     __      5      1      5      2      8      5      4      2      51

Counseled                   __      2      8      1      6      2      5     __      2      3      2      4      35

Mediated                     3      1      1     __     __     __     __      1     __      4     __      1      11

Recommended private         __     __     __     __     __     __     __     __      1      1     __     __       2

Recommended public          __      1      2     __      3     __      1     __      3     __     __      1      11

Replied to requests for      8      8      8     10     28     31     22     31     36     21     47     30     280

Total                       29     46     31     22     50     45     46     44     55     54     69     45     536

        Peter Marotta
        Who Are We?

IDMA is a non-profit professional
   association advancing data
 management through education
 Established March 14, 1984
 First annual meeting December 10, 1985
 April 1990 – first graduates received
  professional designations
 January 2005:
  • CIDMs: 119
  • AIDMs: 121
        Mission and Purpose
 Promote  professionalism in the Data
  Management discipline, principally
  through education
 Create and maintain a curriculum for
  developing data management
  professionals, test professional proficiency,
  and provide professional certification
         Mission and Purpose
 Provide a forum for the discussion of insurance
  data management issues
 The focus of such discussions is on the
  satisfaction of insurance data needs in a manner
  that takes advantage of current technology and is
  efficient and consistent with data quality
   Statistical Agents
   Regulators
   Third Party Administrators
   Consultants
   Property & Casualty Insurers
   Life Insurers
   Trade Associations
   Technology Vendors
   Associations
   Societies
Functions Represented
      Accounting/finance
      Data administration
      Actuarial
      Operations/administration
      Claims
      Statistical
      Data processing
      Data quality
      Underwriting
      Product development
            Products and Papers
   Data Management Value Propositions
   Monthly data management bulletin (EDMIS)
   Data Quality Certification Model
   White Paper on Data Quality
   Recommended Steps for Legislators and Regulators to
    Follow in Issuing Data Requests
   White Paper on Recommended Standards for Injury
   Inventory of Carrier Reports
   Co-sponsor, with the Casualty Actuarial Society (CAS),
    an academic paper competition
 The AIDM designation requires passage of
  four IDMA examinations
 The CIDM designation also requires the
  passage of coursework from one of four
  organizations - CPCU, LOMA, SOFE or
   IDMA Courses: Insurance Data
  Collection and Reporting (IDMA I)

The course addresses the core of
most data managers' responsibilities,
the collection and reporting of
statistical and financial insurance data.
   Insurance Data Quality (IDMA 2)

The course update focuses on very specific
topics concerning data quality and how to
maintain quality. The syllabus includes texts
from two leaders in the field – Thomas C.
Redman and Larry P. English, and materials
from the CAS and IDMA.
 Systems Development and Project
      Management (IDMA 3)
The course presents and analyzes in
detail the many aspects of successful
project management: staffing,
implementation, leadership and other roles,
“Project Authority”, time management,
scheduling techniques, dealing with
problems cultural and otherwise, and
effective strategic planning.
   Data Management, Administration, and
         Warehousing (IDMA 4)
This course explores data flexibility and
shareability concepts which are aimed at
increasing the availability and usefulness of
Data, as well as, an introduction to basic
concepts and principal tools for maximizing
the usability and value of data. The Bill
Inmon concept of the Corporate Information
Factory is explored. In this 2003 update, new
focus and attention are given to data standards.
  Data Management for Insurance
This overview course is highly recommended for a
broad audience including new hires, IT personnel
who want to deepen their knowledge of the
business side of data management, anyone who
manages data in the industry, and anyone who
needs to use or communicate data – from
actuaries to underwriters. It is clear, well organized,
well written, illuminating, and structured for easy
Student proficiency is tested via a 100-question,
multiple-choice exam, and the successful
student will earn a diploma.
  Data Management Value
         (see Appendix for details)

Reduces cost of collecting, storing
 and dispersing data
Improves data quality, establishes
Provides quality controls
Protects privacy and confidentiality
       Contact Information
 Headquarters:
  545 Washington Boulevard, 22-16
  Jersey City, NY 07310-1686
 Website: www.idma.org
 Executive Director: Richard Penberthy
  – Email: rpenberthy@idma.org
  – Phone: 201-469-3069
  – Fax: 201-748-1690
     IDMA: Data Management Value Proposition

                          Value: Data Quality

 Good data management improves data:

    • Validity—Are data represented by acceptable values?
    • Accuracy—Does the data describe the true underlying situation?
    • Reasonability—Does the data make sense? How does it compare with
      similar data from a prior period?
    • Completeness—Do you have all the data you need?
    • Timeliness—Are the data current?

 Allowing the data user to have more confidence in, and a better
   understanding of, the data being used.
     IDMA: Data Management Value Proposition

                         Value: Better Decisions

   Better decisions result from better data.
   Better priced risks—rates, increased limits, etc.—means improved
    bottom line, greater customer satisfaction, improved customer
    retention, increase in number of customers
   Improved ability to explain, defend (and testify as necessary)
    decisions with better data behind the decision, documented controlled
    data management processes in place helps to prove the value of data
    being used
   Improved data integrity, data utility
   As data is and can be sliced ever more finely, attention to quality,
    privacy and confidentiality is critical. Data management skills can
    ensure that.
    IDMA: Data Management Value Proposition

                  Value: Better Decisions (continued)

   The user’s time is freed up for more focus on core professional
    responsibilities, decisions and analysis when data quality is assured
    under the guidance of the data manager.
   Putting data management under the responsibility of a data
    management professional allows both disciplines to do what they do
    best and are best trained to do.
   In many cases, skilled data managers can assume handle functions
    such as responding to special calls.
   Predictive modeling is improved when better data are available,
    allowing for better existing products and better new product
Data Management and the
 The Value of the Data Manager to
      the Company Actuary

           Gary Knoble
IDMA Data Management Value
 Value   to Actuaries
  –   Better Decisions
  –   Data Quality
  –   Internal Data Coordination
  –   Compliance
   Internal Data Coordination
 Reduces  cost and time of data collection,
  storage, and dispersal
 Promotes interoperability of data and
  databases – data integration
 Manages data content and definitions
 Advocates data standards
 Ensures quality and communication
  between sources
    Enterprise Data Initiative
 Mission:
  – To provide direction and oversight to the
    Actuarial and business communities
    concerning data, data management
    (including quality), data analytics,
    including sourcing, manufacturing, and
  – To insure data integrity and availability
    in actuarial work products and business
          Today                  Tomorrow
 Lack of enterprise       Actuarial vision to
  vision                    influence enterprise
 Lack of                   vision
                           Communication
  between divisions
                            across divisions
 Independent
  resourcing for           Shared resources
              Vision (cont.)
 Independent budgets       Budget coordination
 Data planning in          Actuarial presence in
  business units without     all business data
  Actuarial                  planning
 Data sources built for    Data sources built
  individual needs           from common plan
 Redundant data            Minimize redundancy
              Vision (cont.)
 Redundant sources         Authoritative source
 Lack of standards         Standards
 Lack of meta data         Meta data repository
 Lack of business rules    Documented rules
 Lack of knowledge         Knowledge transfer
  transfer                   through
                             documentation and
                Vision (cont.)
 Disparate processes           Core processes
  for managing data
 Uncoordinated               Standard vendor
  vendor relationships         management
 Inconsistent                Consistent

  technologies                 technologies
                              Coordinated tools
 Different tools in silos
                              Authoritative
 Lack of reconciliation       reconciled sources
         An Approach

Framework  for Governance
Rules/Operational Policies
Change data process
Technology infrastructure
Measure results

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