Introduction to Data Management 101
The Convergence of Technology,
Data Standards & Analytical Tools
Arthur R. Cadorine - ISO
Insurance Industry Standards
 Standards
for policy and claim
transactions are being developed
 ACORD
 IAIABC
 IDMA
 These
standards will change the industry
Impact of Standards
 If
everyone speaks the same language,
communication is possible
 Information
improves
quality and timeliness
Data Standards
Who Needs’Em and Why?
 Trading
partners such as insureds,
insurers, TPAs, vendors, and brokers
 Various
 Need
sources use different definitions
data that is clean and consistent
 Reduce
duplication and cost
 Numerous
 Some
indirect benefits
obstacles remain
Data Standards
Don’t They Exist Already?
 Financial
services and some retailers
use data standards
 Some
insurance standards developed
for specific applications
 Standards
are not identical
Data Standards
Current Working Groups
 IDMA
TPA Data Standards Work Group
 ACORD
 ANSI
 RIMS
 ISO
 WC
Insurance Organizations (WCIO)
Data Standards
Current Tools
 PDRP
- GL database for public entities
 IDMA
Claims Data Exchange Standard
 IDMA
Policy Data Element Dictionary
 IDMA
TPA Data Standards White Paper
 www.idma.org/DS-announce.html
Value of Knowing Sooner
 Delays
in claims reporting cost money
 Real-time
 Early
fraud detection could save $$
claim-trend detection means
corrective premium action
Integrating EDI Reporting
 Straight-through
processing
becomes possible
 Data
quality improves
 Information
 ASP
can be aggregated
model has many advantages
Integration of Data
 ASP
can have policy and claim databases
 Systems
 One
can talk to one another
source/multiple outputs
Analytical Tools

Predictive models

Web access

User-friendly report writers

User-friendly analysis software
ASOP #23: Data Quality
 Purpose
is to give guidance in:
 Selecting data
 Reviewing data for appropriateness,
reasonableness, and
comprehensiveness
 Making appropriate disclosures
 Does
not recommend that actuaries
audit data
ASAP #23: Data Quality
Considerations in Selection of Data
 Appropriateness
for intended purpose
 Reasonableness,
comprehensiveness,
and consistency
 Limitations
 Cost
of or modifications to data
and feasibility of alternatives
 Sampling
methods
ASOP #23: Data Quality
Definition of Data
 Numerical,
census, or class information
 Not
actuarial assumptions
 Not
computer software
 Definition
of comprehensive
 Definition
of appropriate
ASAP #23: Data Quality
Other Considerations
 Imperfect
 Reliance
Data
on Others
 Documentation/Disclosure
IDMA
Data Management for Insurance Professionals
Chapters at a Glance
I. The History of Insurance Data Management
II. Role of Insurance Data Manager
III. Key Data Elements of Insurance
IV. Insurance Company’s Use of Data
V. The External Insurance Environment
VI. Data Quality
VII. Data Repositories
VIII. Future Data Management Issues
C.A.S.
RATEMAKING SEMINAR
Philadelphia 2004
INT-1
Introduction to Insurance Data
Management 101
Nathan Root
CNA
Data Managers, Who-What-Where
A group of people within insurance organizations
whose primary day-to-day function is to provide
business managers with the information they need to
accomplish the goals and objectives of the
organization.
– Core data managers are involved in:
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Internal data coordination
External data reporting
Information systems development
Data administration
What is a Data Manager?
• A Data Manager:
– Provides data
• To internal customers
• To external customers
– Is concerned that the data provided
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•
•
•
Is accurate & consistently derived & defined
Is readily available and timely
Is comparable/reconcilable
Secure
Who are the customers?
• Internal customers include:
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ACTUARIES
Underwriters
Accountants
Claims
Marketing and Distribution Network
Management
Who are the customers?
• External customers include:
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Statistical organization
Rate making organization
Insurance research organizations
Investors
– State & Federal regulators
The data manger’s job?
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To interpret requests for data
Determine how to obtain data
Determine where to obtain data
Control the cost of development and
maintenance
• Provide data to customers in appropriate
format
Data Management’s Task
The data manager’s task is to assure that the same data
in different systems can be reconciled, that the data
is consistent, and that derived data is defined and
calculated consistently.
Partnerships
Data users are, and should be, involved in a partnership
with insurance data managers.
-A partner in
= defining systems
= building systems
= testing systems
= and final acceptance of a system.
Knowledge and Other Users
Just as Data Managers need and must have knowledge
of the customer’s they serve, so must other insurance
professional understand the Data Manager’s function.
EACH TIME AN INDIVIDUAL WANTS INFORMATION,
DATA MANAGEMENT SKILLS COME INTO PLAY.
It must be determined where the data is, how it is identified,
how it is defined
AND HOW IT CAN BE VARIFIED.
What do you need to know about
Data Management
• Data definitions and how they differ.
• Coding conventions.
• Data redundancy.
• Level of data available/needed.
• Where did the data come from and how is it maintained.
• Schedule for updating.
• Reasonability and reliability of the data.
Who are Insurance Data Managers?
• Managers of data which can be anyone
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Professional insurance data managers
Actuaries
Underwriters and Agents
Claims personnel and SIU’s
Marketing personnel and Researchers
Accountants and Economists
Who Owns the Data?
Data use - implies data ownership - which mandates control.
An individual companies data is one of its most valuable
assets, if not its most valuable asset.
With control comes definite responsibilities.
- You also become responsible for your data’s
- VALIDITY
- ACCURACY
- REASONABILITY
- COMPLETENESS
Confidentiality and Privacy
All users and managers of data MUST be constantly
aware of the issues surrounding Confidentiality and
Privacy. Confidential data is very different from data
that is controlled by privacy laws.
-Confidential data: given with the understanding that the
information will be treated as confidential
- Privacy of data: usually governed by law, either State or
Federal or both.
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- GRAMM-LEACH-BLILEY(GLB)
HEALTH INSURANCE PORTABILITY
and ACCOUNTABILITY ACT(HIPAA)
DATA for the REGULATOR
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•
Solvency Data
Accounting
Actuarial
Ratemaking Data
Rate Filings
Special Calls
The Data Management
Environment
Micro-Computers have changed the data management
environment. Literally every user of a micro-computer
has had to become a data manager.
The Insurance Data Management Association(IDMA)
provides education and a forum for knowledge in this field
Insurance Data Management
Association(IDMA)
IDMA has partnered with the CAS and is prepared to share
its knowledge of data with CAS members.
The IDMA’s “Data Management for Insurance Professionals”
is available today. It is designed as a primer and is intended
for both the professional and those yet to become
professional within the insurance industry.
For further information on this course contact the IDMA at 1201-469-3069.
IDMA
Data Management for Insurance Professionals
Chapters at a Glance
I. The History of Insurance Data Management
II. Role of Insurance Data Manager
III. Key Data Elements of Insurance
IV. Insurance Company’s Use of Data
V. The External Insurance Environment
VI. Data Quality
VII. Data Repositories
VIII. Future Data Management Issues
Casualty Actuarial Society
Ratemaking Seminar
Philadelphia 2004
INT-1
Introductory Data Management 101
Al Hapke
Meadowbrook Insurance Group
Your Role in Data Management
• Demanding User
• Lack of defined needs
• Lack of knowledge about information
technology
• Lack of business knowledge in the IT staff
Therefore, you must communicate your goals
effectively and clearly.
Objective of Data Management:
To store and organize data in a way that
allows the analyst to answer questions about
the business.
These questions should help direct and guide
the management of the business.
Processing Systems are not adequate to satisfy
the analytical needs of the company.
They’re designed to do work, not answer
questions.
Steps That Help Communication:
• Formulate many specific questions
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Brainstorm yourself
Talk to your customers/clients/boss
Read actuarial papers
Review competitive rate filings
• Write them down
• Design your spreadsheet or model to answer
the question
• Determine what you need to populate the
Example of Questions:
What do we expect to pay for claims in this
class vs. other classes?
1.
2.
3.
4.
5.
Age/experience of driver
WC class code
Property construction
State/territory/location
Other characteristics such as credit rating,
new/renewal, etc.
Issues with this Question:
• Volume in each class or characteristic
• How much history?
• Can premium be appropriately matched
with losses?
• Can earned exposures be captured?
• Can class definitions be multidimensional?
Other Questions:
• What is our exposure to maximum loss?
– Answer can be found in limit/location studies
• How much development can we expect on
reported losses?
– Considerations:
• Report date
• Historical claim distributions
Other Questions (continued)
• Has our underlying book of business
changed?
– What types of losses are we seeing?
• This is only meaningful if we have been
profiling our mix of claims so that we can
see what’s different.
• e.g
– Size of loss at consistent points in time
– Minor coverage detail
– Cause of loss
Other Questions (continued)
• Who, how much, and what is your producer
selling?
What are the characteristics of the business
being brought in the front door?
Or…. Leaving through the back door?
Issues to Consider in Your
Management Information System
• Ease of Access - level of independence from
programmers
• Flexibility - new classes, new
characteristics, new products
• Quality of data