Data technology 3 data management panel discussion cas ratemaking seminar march 2005
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Data/Technology 3 - Data Management Panel Discussion CAS Ratemaking Seminar March 2005. Panelists. 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.

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Data technology 3 data management panel discussion cas ratemaking seminar march 2005

Data/Technology 3 - Data ManagementPanel 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 actuary

Data Management and the Actuary

An ABCD Perspective

Michael L. Toothman

The role of the abcd
The Role of the ABCD

  • Consider complaints

  • Counsel Actuaries

  • Recommend disciplinary action

  • Respond to requests for guidance

  • Mediate issues

The role of the abcd1
The Role of the ABCD

Consider Complaints

  • Conduct Investigations

  • Hold Hearings

The role of the abcd2
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 abcd3
The Role of the ABCD

Recommend Disciplinary Action

  • Only the participating organizations have authority to discipline their members

  • Occurs in well under 5% of ABCD case

The role of the abcd4
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 specific)

Comply with Standards of Practice

The Actuary’s Responsibility

The actuary s responsibility1

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 profession.

The Actuary’s Responsibility

Real life issues
Real Life Issues

  • ABCD classifies cases as

    • Practice

    • Conduct

  • 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.

    Abcd case resolution
    ABCD Case Resolution

    ABCD cases considered during 2003:

    Abcd case resolution1
    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 ABCDafter 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 resolution2
    ABCD Case Resolution

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

    Who are we
    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
    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 purpose1
    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
    Functions Represented

    • Accounting/finance

    • Data administration

    • Actuarial

    • Operations/administration

    • Claims

    • Statistical

    • Data processing

    • Data quality

    • Underwriting

    • Product development

    Products and papers
    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 Coding

    • 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 CAS

    Idma courses insurance data collection and reporting idma i
    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
    Insurance Data Quality (IDMA 2) I)

    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
    Systems Development and Project Management (IDMA 3) I)

    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
    Data Management, Administration, and Warehousing (IDMA 4) I)

    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 professionals
    Data Management for Insurance Professionals I)

    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 proposition see appendix for details
    Data Management Value Proposition I)(see Appendix for details)

    • Reduces cost of collecting, storing and dispersing data

    • Improves data quality, establishes standards

    • Provides quality controls

    • Protects privacy and confidentiality

    Contact information
    Contact Information I)

    • Headquarters:

      545 Washington Boulevard, 22-16

      Jersey City, NY 07310-1686

    • Website:

    • Executive Director: Richard Penberthy

    Idma data management value proposition
    IDMA: Data Management Value Proposition I)

    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 proposition1
    IDMA: Data Management Value Proposition I)

    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 proposition2
    IDMA: Data Management Value Proposition I)

    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 development.

    Data management and the actuary1

    Data Management and the Actuary I)

    The Value of the Data Manager to the Company Actuary

    Gary Knoble

    Idma data management value proposition3
    IDMA Data Management Value Proposition I)

    • Value to Actuaries

      • Better Decisions

      • Data Quality

      • Internal Data Coordination

      • Compliance

    Internal data coordination
    Internal Data Coordination I)

    • 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
    Enterprise Data Initiative I)

    • Mission:

      • To provide direction and oversight to the Actuarial and business communities concerning data, data management (including quality), data analytics, including sourcing, manufacturing, and delivery.

      • To insure data integrity and availability in actuarial work products and business requirements.


    Today I)

    Lack of enterprise vision

    Lack of communication between divisions

    Independent resourcing for initiatives


    Actuarial vision to influence enterprise vision

    Communication across divisions

    Shared resources


    Vision cont

    Independent budgets I)

    Data planning in business units without Actuarial representation

    Data sources built for individual needs

    Redundant data

    Budget coordination

    Actuarial presence in all business data planning

    Data sources built from common plan

    Minimize redundancy

    Vision (cont.)

    Vision cont1

    Redundant sources I)

    Lack of standards

    Lack of meta data

    Lack of business rules

    Lack of knowledge transfer

    Authoritative source


    Meta data repository

    Documented rules

    Knowledge transfer through documentation and rules

    Vision (cont.)

    Vision cont2

    Disparate processes for managing data I)

    Uncoordinated vendor relationships

    Inconsistent technologies

    Different tools in silos

    Lack of reconciliation

    Core processes

    Standard vendor management

    Consistent technologies

    Coordinated tools

    Authoritative reconciled sources

    Vision (cont.)

    An approach
    An Approach I)

    • Framework for Governance

    • Rules/Operational Policies

    • Change data process

    • Technology infrastructure

    • Measure results