Chapter Summaries
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CHAPTER ONE - The History of Data Management
In the History of Insurance Data Management, the student
explores both the history and basic terms and fundamentals of Data
Management. Here you will discover how the insurance industry has
changed its perception of the value, the function, and the ownership
of corporate information. The chapter covers fundamentals of insurance
information processing, and describes how data collection was shaped
by the limitations of early computer systems. You'll learn the key
distinction between data and information, and how Data Management
has emerged as a distinct profession to maximize the informational
value of data. The chapter closes with a detailed discussion of
the IDMA organization - its activities, its goals, and need for
the participation of motivated Insurance Data Management professionals
like you.
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CHAPTER TWO - The Role of the Insurance Data Manager
While Chapter One emphasized the importance of data, you'll begin
to understand the responsibilities of the people who are entrusted
with the collection and oversight of insurance information in Role
of the Insurance Data Manager. The student will see the reasons
why the actuary, the underwriter, and senior management decision-makers
all rely on the work of the Data Manager. You will be introduced
to the concept of data stewardship, and gain an appreciation for
how the Data Manager's role differs in Property/Casualty insurers,
Life/Health insurers, and Regulatory Agencies.
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CHAPTER THREE - Key Data Elements of
Insurance
In Key Data Elements of Insurance, you will learn the fundamentals
of insurance ratemaking, and understand how credible rates rely
upon quality data. Since one of the primary purposes of insurance
data is to provide an historical basis for future rates, it is vital
for any Data Management professional to understand how actuaries
use this information. You'll learn the components of a rate, the
definition of an 'adequate' rate, and the distinction between accident
year and policy year ratemaking data. Beyond the work of insurance
actuaries, you'll discover the goals of insurance regulators as
they try to fulfill their obligation to the industry and to the
public. When you've completed this chapter, you will be prepared
to better understand data collection requirements, both in published
Statistical Plans and in new requirements that are asked by actuaries
and regulators.
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CHAPTER FOUR - Insurance Companies'
Use of Data
Insurance Companies' Use of Data continues the theme of Chapter
Three, but moves beyond ratemaking. Here you will see how insurers
rely upon quality data for internal departmental and corporate needs.
You'll study the importance of data in establishing underwriting
guidelines. Insurers and regulators have developed ratios used for
assessing a company's profitability and financial health; you will
learn the definition and uses of loss ratio, expense ratio, and
combined ratio. The chapter demonstrates why insurers need a distinct
Data Management section or department, and how its activities benefit
the company by assuring access to a solid and reliable knowledge
base of data. The elements of good enterprise data strategy are
discussed. The chapter includes a discussion of the impact of Data
Management on the insurance customer. The difference between ratemaking
and statistical needs for data is explained.
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CHAPTER FIVE - The External Insurance
Environment
In The External Insurance Environment, you'll learn about the variety
of stakeholders who influence insurers and the need for information.
Key organizations covered include government agencies, insurance
advisory/rating services, Departments of Motor Vehicles, statistical
agents, the NAIC, the IAIABC, MGAs, and TPAs. You'll see that there
are many factors that influence the insurance contract beyond the
insurer and the insured. Covered topics include the relationship
between internal and external uses of data, an overview of the statutory
environment (State Insurance Departments, State Worker's Compensation
Commissions, The International Association of Industrial Accident
Boards and Commissions, and the National Association of Insurance
Commissioners), and some details on the major rating advisory organizations
and data collection agencies (AAIS, ISO, NAII, NCCI, NCIS, NISS,
AIPSO, SAA). You'll also discover how the role of statistical agents
may dramatically change in response to industry consolidation, the
Internet, deregulation, the threat of federal intervention, and
social/legal pressure.
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CHAPTER SIX - Data Quality
You'll begin to understand the tools, methodologies,
and fundamental tenets embraced by Data Management professionals
in this chapter, Data Quality. The basic components of data quality
are listed and defined, the concept of systems testing is introduced,
and the process of error evaluation is covered. To establish and
promote the quality of information in your own company, you'll benefit
by learning these proven techniques that have become the standards
of the profession. You will understand the difference between financial
and statistical data, in terms of means of collection, customers,
uses, and standards. Data standards, especially key in electronic
communication, are introduced and discussed. Quality assurance tools
are covered in an overview of statistical sampling measures, data
audits, and data monitoring systems. No architect of data quality
is equipped for the job without a command of these toolsets.
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CHAPTER SEVEN - Data Repositories
The nature of data storage and retrieval has changed along with
available technology. From ledgers and filing cabinets, early information
processing was advanced by the use of computers, tabulation machines,
and the 80-column keypunch cards. There has been a metamorphosis
from the legacy computer environment in which millions of electronic
records (still largely analogous to the 80-column keypunch card)
are stored and manipulated in their 'flat file' format, to relational
databases of information stored in a hierarchical but flexible series
of data tables. In Data Repositories, you'll study the latest advances
in technology for the storage of key insurance data, such as Data
Warehouse and Data Mining. You'll discover the advantages inherent
in the new technology, including the ease of query by members of
business units. The importance of metadata is explained. Data backup
and recovery are introduced and discussed as key elements in ensuring
data integrity.
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CHAPTER EIGHT - Future Data Management
Issues
The final chapter, Future Data Management Issues, examines the critical
concerns in technology, financial services, and regulation that
face data managers. You'll understand the key concept of convergence
and how the necessity for change is constant. Historical perspectives
on convergence precede a discussion on the digital nature of the
New Economy and convergence in financial services and in regulation.
The course and chapter conclude with an emphasis on the increasing
need for professionalism within data management, and how data managers
must recognize that what they do is both a discipline and a profession.
You'll find a deeper appreciation of the history, the current efforts,
and the continuing need to educate and promote the value of certified,
professional data managers in organizations like IDMA. You will
see a newly focused discussion with emphases on public trust, the
post 9/11 world, and the post-Enron world.
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Look over these sample objectives from the course — what would
your responses be like?
The History of Insurance Data Management
- Explain why insurers produce and use data, and summarize how
it is important to the company's competitive advantage.
- List the responsibilities of Data Administration and explain
how it relates to the database environment.
- Differentiate Data Management and Database Administration.
- Trace the improvements that set one generation of computers
apart from the preceding generation beginning in the 1960s and
onward.
- Explain the difference between data and information.
- Identify the founding purpose of the Insurance Data Management
Association (IDMA) and list eight activities and explain how they
relate to IDMA's stated purpose.
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Role of the Insurance Data Manager
- Describe some impediments to efficient communication.
- List important questions to ask when investigating meta-data.
Propose more that assure clarity.
- Define data stewardship and explain its purpose.
- Explain how property and casualty data managers support actuaries,
underwriters, and senior management decision-makers.
- List the characteristics of Statistical Plans and explain their
purpose.
- Name the similarities and differences between the property and
liability industry and the life and health industry, vis-à-vis
the role of the data manager.
- Trace the logic that holds that with increasing consolidation
of the industry, the data manager's role will become more critical.
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Key Data Elements of Insurance
- Quote the phrase that regulators use to judge insurance rates
(hint: it includes three conditions).
- Define an adequate rate, and go into some detail concerning
how that is determined; discuss what might complicate judging
whether or not a rate is adequate.
- Explain the "fair rate of return" approach and then
state the insurers' contrary argument.
- Distinguish between fair discrimination and unfair discrimination.
- List the seven goals regulators address in order to fulfill
their obligation to the industry and the public.
- Name the types of insurance regulation.
- List the five types of laws used in rate regulation.
- Define key ratemaking terms.
- Explain why accident year data and policy year data are more
useful for ratemaking than calendar year data.
- Differentiate policyholder, insured, and beneficiary in the
data elements required for life and health insurance.
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Insurance Companies' Use of Data
- Name at least three types of data which statistical organizations
provide that staff underwriters likely to evaluate before they
consider writing a new line of business or expanding an existing
line of business.
- Contrast the data collected by LOMA, LIMRA, and HIAA with the
data collected by property and casualty statistical bureaus, in
terms of regulatory demands, its completeness in representing
its side of the industry (life and health or property and casualty),
and its uses.
- Compare class rating with individual rating.
- List six ways data may be used to satisfy internal department
or company needs.
- Data are used to create three ratios important to determining
profitability. Define loss ratio, expense ratio, and combined
ratio.
- Advocate for sharing loss data - all forms of loss data - with
Underwriting.
- Give reasons life and health companies report to various organizations
when they are not required to by law.
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The External Insurance Environment
- Name the various departments and organizations that make up the statutory environment and list the activities that these departments engage in as they regulate the insurance industry.
- List the seven major types of external organizations that collect insurance data and explain how and why they collect and use the data.
- Contrast the role of a statistical agent with that of an advisory/rating organization.
- Define the role of an advisory organization and describe the functions of each of the eight rating advisory organizations named in this chapter.
- Enumerate the various types and roles of vendors and be able to compare and contrast the two types of vendors used for policy and claims processing.
- Identify the services provided with claims review and explain how these services save the industry money.
- Explain how submitting data to external users may benefit the insurer.
- Name and briefly explain each of the forces behind change in the statistical agents’ role.
- Explain how it can be that vendors who report on behalf of carriers and who process data find their tasks both more complex and increasingly easy.
- List the major changes of interest to the statistical community during the 1990s. Also, name three events that have occurred in the 2000s that impacted the insurance industry, and explain what changes they prompted.
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Data Quality
- Explain the difference between financial and statistical data
in terms of means of collection, customers, uses and standards.
- List several examples of the impact of using inaccurate or inconsistent
data within the industry and among its customers.
- Promote the concept of systems testing.
- Name and define the standard components of data quality.
- Characterize unit testing, system testing and acceptance testing
(user acceptance testing or field-testing).
- Define a Test Plan by referring to its five essentials.
- Name and explain seven steps in the process of error evaluation.
- Describe three error evaluation tools
- Enumerate the elements of a successful data audit.
- State the purpose of data monitoring systems, and specify what
insurers and statistical agents are responsible for under a data-monitoring
program.
- Define standards. List and explain the industry challenges —
both those that demand standards and those that stand in the way
of acceptance of standards.
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Data Repositories
- Define the data warehouse, citing the key components and explaining
what each term means specifically in relation to this definition.
- List six functions and decision-making activities which data
contained in a data warehouse can support.
- As you read the "Historical Perspective - Where We Were"
portion of this chapter, realizing that the period covered is
only a few years, name the problems inherent in the early data
warehouses and tools developed to use them.
- Define naturally evolving architecture.
- Legacy systems, as their faults and uses are recounted here,
are still with the industry; name three reasons mainframe computers
are still in use today.
- Discuss the advantages and disadvantages of enterprise data
warehouses.
- Discuss and explain data backup and recovery reasons and methods.
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Future Data Management Issues
- Use convergence as a model for evaluating the changes taking
place in the insurance marketplace.
- Identify critical issues in technology, financial services and
regulation facing data managers.
- Discuss various strategies and techniques for managing in times
of convergence.
- Identify the key aspects of a professional, and apply them to
data managers.
- Explain how professionalism is integral to successful data management.
- Data managers routinely collaborate with other functions and
activities. Explain how this collaboration will broaden and intensify
as a result of the passage of the U.S. Terrorism Risk Insurance
Act.
- Discuss the impact of the tragedies of 9/11/2001 upon data management.
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