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

Data Management and the
Actuary
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
members
 Occurs in well under 5% of ABCD
case
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
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.
Real Life Issues
 ABCD
classifies cases as
Practice
Conduct
 Majority
 Very
of cases are conduct issues
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
 Qualification Standards - Precept 2
 Standards of Practice - Precept 3
 Communications and Disclosure - Precepts
4, 5, and 6
 Conflict of Interest - Precept 7
 Control of Work Product – Precept 8
and Cooperation – Precept 10
 Advertising – Precept 11
 Confidentiality – Precept 9
 Titles and Designations – Precept 12
 Violations of the Code of Professional
Conduct – Precepts 13 and 14
 Courtesy
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
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
Cases by Practice Area
ABCD Case Resolution
ABCD cases considered during 2003:
CASES CLOSED
Action by Individual ABCD members
Replied to requests for guidance
Mediated
Disposition by Chairperson and Vice Chairpersons
Dismissed
(Referred to Investigators in 2003—4)
Disposition by Whole ABCD after investigation
Dismissed
Dismissed with guidance
Counseled
Counseled after hearing
Recommended suspension
Total
30
1
4
3
2
2
2
1
45
CASES IN PROGRESS (as of 12/31/03)
Pending investigation
Pending hearing
Pending receipt of more information
Request for Guidance pending
Total
7
1
6
2
16
ABCD Case Resolution
Since its inception in 1992, the ABCD completed its cases as follows:
Dispositions
Dismissed
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
Total
12
24
9
11
8
11
13
10
5
20
16
7
146
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
reprimand
__
__
__
__
__
__
__
__
1
1
__
__
2
Recommended public
discipline
__
1
2
__
3
__
1
__
3
__
__
1
11
Replied to requests for
guidance
8
8
8
10
28
31
22
31
36
21
47
30
280
29
46
31
22
50
45
46
44
55
54
69
45
536
Dismissed with guidance
Total
INSURANCE DATA
MANAGEMENT ASSOCIATION
(IDMA)
Peter Marotta
Who Are We?
IDMA is
a non-profit professional
association advancing data
management through education
Timeline
 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

Membership










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
Coding
Inventory of Carrier Reports
Co-sponsor, with the Casualty Actuarial Society (CAS),
an academic paper competition
Curriculum
 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)
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
Professionals
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
study.
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)
Reduces cost of collecting, storing
and dispersing data
Improves data quality, establishes
standards
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
INSURANCE DATA
MANAGEMENT ASSOCIATION
(IDMA)
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
development.
Data Management and the
Actuary
The Value of the Data Manager to
the Company Actuary
Gary Knoble
IDMA Data Management Value
Proposition
 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
delivery.
– To insure data integrity and availability
in actuarial work products and business
requirements.
Vision
Today
 Lack of enterprise
vision
 Lack of
communication
between divisions
 Independent
resourcing for
initiatives
Tomorrow
 Actuarial vision to
influence enterprise
vision
 Communication
across divisions
 Shared resources
Vision (cont.)
Independent budgets
 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.)
Redundant sources
 Lack of standards
 Lack of meta data
 Lack of business rules
 Lack of knowledge
transfer

Authoritative source
 Standards
 Meta data repository
 Documented rules
 Knowledge transfer
through
documentation and
rules

Vision (cont.)
Disparate processes
for managing data
 Uncoordinated
vendor relationships
 Inconsistent
technologies
 Different tools in silos
 Lack of reconciliation


Core processes
Standard vendor
management
 Consistent
technologies
 Coordinated tools
 Authoritative
reconciled sources

An Approach
Framework
for Governance
Rules/Operational Policies
Change data process
Technology infrastructure
Measure results